440 results on '"Herraiz, I."'
Search Results
2. Mortality and severe neurological morbidity in extremely preterm growth‐restricted fetuses
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Mazarico, E., primary, Meler, E., additional, Mendoza, M., additional, Herraiz, I., additional, Llurba, E., additional, De Diego, R., additional, Comas, M., additional, Boada, D., additional, González, A., additional, Bonacina, E., additional, Armengol‐Alsina, M., additional, Moline, E., additional, Hurtado, I., additional, Torre, N., additional, Gomez‐Roig, M. D., additional, Galindo, A., additional, and Figueras, F., additional
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- 2023
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3. Clinical implementation of the sFlt-1/PlGF ratio to identify preeclampsia and fetal growth restriction: A prospective cohort study
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Herraiz, I., Simón, E., Gómez-Arriaga, P.I., Quezada, M.S., García-Burguillo, A., López-Jiménez, E.A., and Galindo, A.
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- 2018
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4. The role of angiogenic biomarkers and uterine artery Doppler in pregnant women with systemic lupus erythematosus or antiphospholipid syndrome
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Rodríguez-Almaraz, M.E., Herraiz, I., Gómez-Arriaga, P.I., Vallejo, P., Gonzalo-Gil, E., Usategui, A., López-Jiménez, E.A., Galindo, A., and Galindo, M.
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- 2018
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- View/download PDF
5. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis
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Allotey, J, Whittle, R, Snell, K, Smuk, M, Townsend, R, von Dadelszen, P, Heazell, A, Magee, L, Smith, G, Sandall, J, Thilaganathan, B, Zamora, J, Riley, R, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, A, Salvesen, K, Bhattacharya, S, Uiterwaal, C, Staff, A, Andersen, L, Olive, E, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramirez, J, Masse, J, Audibert, F, Magnus, P, Jenum, A, Baschat, A, Ohkuchi, A, Mcauliffe, F, West, J, Askie, L, Mone, F, Farrar, D, Zimmerman, P, Smits, L, Riddell, C, Kingdom, J, van de Post, J, Illanes, S, Holzman, C, van Kuijk, S, Carbillon, L, Villa, P, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, van Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, C, Nagata, C, Brown, M, Vollebregt, K, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, J, Figueiro, E, Lapaire, O, Laivuori, H, Lykke, J, Conde-Agudelo, A, Galindo, A, Mbah, A, Betran, A, Herraiz, I, Trogstad, L, Steegers, E, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, W, Browne, J, Allen, R, Costa, F, Klipstein-Grobusch Browne, K, Crowther, C, Jorgensen, J, Forest, J, Rumbold, A, Mol, B, Giguere, Y, Kenny, L, Ganzevoort, W, Odibo, A, Myers, J, Yeo, S, Goffinet, F, Mccowan, L, Pajkrt, E, Teede, H, Haddad, B, Dekker, G, Kleinrouweler, E, Lecarpentier, E, Roberts, C, Groen, H, Skrastad, R, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, J, Monterio, I, Pillalis, A, Souza, R, Hawkins, L, Gabbay-Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, Khan, K, Allotey J., Whittle R., Snell K. I. E., Smuk M., Townsend R., von Dadelszen P., Heazell A. E. P., Magee L., Smith G. C. S., Sandall J., Thilaganathan B., Zamora J., Riley R. D., Khalil A., Thangaratinam S., Coomarasamy A., Kwong A., Savitri A. I., Salvesen K. A., Bhattacharya S., Uiterwaal C. S. P. M., Staff A. C., Andersen L. B., Olive E. L., Redman C., Sletner L., Daskalakis G., Macleod M., Abdollahain M., Ramirez J. A., Masse J., Audibert F., Magnus P. M., Jenum A. K., Baschat A., Ohkuchi A., McAuliffe F. M., West J., Askie L. M., Mone F., Farrar D., Zimmerman P. A., Smits L. J. M., Riddell C., Kingdom J. C., van de Post J., Illanes S. E., Holzman C., van Kuijk S. M. J., Carbillon L., Villa P. M., Eskild A., Chappell L., Prefumo F., Velauthar L., Seed P., van Oostwaard M., Verlohren S., Poston L., Ferrazzi E., Vinter C. A., Nagata C., Brown M., Vollebregt K. C., Takeda S., Langenveld J., Widmer M., Saito S., Haavaldsen C., Carroli G., Olsen J., Wolf H., Zavaleta N., Eisensee I., Vergani P., Lumbiganon P., Makrides M., Facchinetti F., Sequeira E., Gibson R., Ferrazzani S., Frusca T., Norman J. E., Figueiro E. A., Lapaire O., Laivuori H., Lykke J. A., Conde-Agudelo A., Galindo A., Mbah A., Betran A. P., Herraiz I., Trogstad L., Smith G. G. S., Steegers E. A. P., Salim R., Huang T., Adank A., Zhang J., Meschino W. S., Browne J. L., Allen R. E., Costa F. D. S., Klipstein-Grobusch Browne K., Crowther C. A., Jorgensen J. S., Forest J. -C., Rumbold A. R., Mol B. W., Giguere Y., Kenny L. C., Ganzevoort W., Odibo A. O., Myers J., Yeo S. A., Goffinet F., McCowan L., Pajkrt E., Teede H. J., Haddad B. G., Dekker G., Kleinrouweler E. C., LeCarpentier E., Roberts C. T., Groen H., Skrastad R. B., Heinonen S., Eero K., Anggraini D., Souka A., Cecatti J. G., Monterio I., Pillalis A., Souza R., Hawkins L. A., Gabbay-Benziv R., Crovetto F., Figuera F., Jorgensen L., Dodds J., Patel M., Aviram A., Papageorghiou A., Khan K., Allotey, J, Whittle, R, Snell, K, Smuk, M, Townsend, R, von Dadelszen, P, Heazell, A, Magee, L, Smith, G, Sandall, J, Thilaganathan, B, Zamora, J, Riley, R, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, A, Salvesen, K, Bhattacharya, S, Uiterwaal, C, Staff, A, Andersen, L, Olive, E, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramirez, J, Masse, J, Audibert, F, Magnus, P, Jenum, A, Baschat, A, Ohkuchi, A, Mcauliffe, F, West, J, Askie, L, Mone, F, Farrar, D, Zimmerman, P, Smits, L, Riddell, C, Kingdom, J, van de Post, J, Illanes, S, Holzman, C, van Kuijk, S, Carbillon, L, Villa, P, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, van Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, C, Nagata, C, Brown, M, Vollebregt, K, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, J, Figueiro, E, Lapaire, O, Laivuori, H, Lykke, J, Conde-Agudelo, A, Galindo, A, Mbah, A, Betran, A, Herraiz, I, Trogstad, L, Steegers, E, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, W, Browne, J, Allen, R, Costa, F, Klipstein-Grobusch Browne, K, Crowther, C, Jorgensen, J, Forest, J, Rumbold, A, Mol, B, Giguere, Y, Kenny, L, Ganzevoort, W, Odibo, A, Myers, J, Yeo, S, Goffinet, F, Mccowan, L, Pajkrt, E, Teede, H, Haddad, B, Dekker, G, Kleinrouweler, E, Lecarpentier, E, Roberts, C, Groen, H, Skrastad, R, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, J, Monterio, I, Pillalis, A, Souza, R, Hawkins, L, Gabbay-Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, Khan, K, Allotey J., Whittle R., Snell K. I. E., Smuk M., Townsend R., von Dadelszen P., Heazell A. E. P., Magee L., Smith G. C. S., Sandall J., Thilaganathan B., Zamora J., Riley R. D., Khalil A., Thangaratinam S., Coomarasamy A., Kwong A., Savitri A. I., Salvesen K. A., Bhattacharya S., Uiterwaal C. S. P. M., Staff A. C., Andersen L. B., Olive E. L., Redman C., Sletner L., Daskalakis G., Macleod M., Abdollahain M., Ramirez J. A., Masse J., Audibert F., Magnus P. M., Jenum A. K., Baschat A., Ohkuchi A., McAuliffe F. M., West J., Askie L. M., Mone F., Farrar D., Zimmerman P. A., Smits L. J. M., Riddell C., Kingdom J. C., van de Post J., Illanes S. E., Holzman C., van Kuijk S. M. J., Carbillon L., Villa P. M., Eskild A., Chappell L., Prefumo F., Velauthar L., Seed P., van Oostwaard M., Verlohren S., Poston L., Ferrazzi E., Vinter C. A., Nagata C., Brown M., Vollebregt K. C., Takeda S., Langenveld J., Widmer M., Saito S., Haavaldsen C., Carroli G., Olsen J., Wolf H., Zavaleta N., Eisensee I., Vergani P., Lumbiganon P., Makrides M., Facchinetti F., Sequeira E., Gibson R., Ferrazzani S., Frusca T., Norman J. E., Figueiro E. A., Lapaire O., Laivuori H., Lykke J. A., Conde-Agudelo A., Galindo A., Mbah A., Betran A. P., Herraiz I., Trogstad L., Smith G. G. S., Steegers E. A. P., Salim R., Huang T., Adank A., Zhang J., Meschino W. S., Browne J. L., Allen R. E., Costa F. D. S., Klipstein-Grobusch Browne K., Crowther C. A., Jorgensen J. S., Forest J. -C., Rumbold A. R., Mol B. W., Giguere Y., Kenny L. C., Ganzevoort W., Odibo A. O., Myers J., Yeo S. A., Goffinet F., McCowan L., Pajkrt E., Teede H. J., Haddad B. G., Dekker G., Kleinrouweler E. C., LeCarpentier E., Roberts C. T., Groen H., Skrastad R. B., Heinonen S., Eero K., Anggraini D., Souka A., Cecatti J. G., Monterio I., Pillalis A., Souza R., Hawkins L. A., Gabbay-Benziv R., Crovetto F., Figuera F., Jorgensen L., Dodds J., Patel M., Aviram A., Papageorghiou A., and Khan K.
- Abstract
Objective: Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods: MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results: Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overa
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- 2022
6. Prediction of perinatal survival in early‐onset fetal growth restriction: role of placental growth factor
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Rodríguez Calvo, Juan, Villalaín González, Cecilia, Gómez Arriaga, Paula Isabel, Quezada, M. S., Herraiz, I., Galindo, A., Rodríguez Calvo, Juan, Villalaín González, Cecilia, Gómez Arriaga, Paula Isabel, Quezada, M. S., Herraiz, I., and Galindo, A.
- Abstract
CRUE-CSIC (Acuerdos Transformativos 2022), Objective To analyze the ability to predict perinatal survival and severe neonatal morbidity of cases with early-onset fetal growth restriction (eoFGR) using maternal variables, ultrasound parameters and angiogenic markers at the time of diagnosis. Methods This was a prospective observational study in a cohort of singleton pregnancies with a diagnosis of eoFGR (< 32 weeks of gestation). At diagnosis of eoFGR, complete assessment was performed, including ultrasound examination (anatomy, biometry and Doppler assessment) and maternal serum measurement of the angiogenic biomarkers, soluble fms-like tyrosine kinase-1 (sFlt-1) and placental growth factor (PlGF). Logistic regression models for the prediction of perinatal survival (in cases diagnosed at < 28 weeks) and severe neonatal morbidity (in all liveborn cases) were calculated. Results In total, 210 eoFGR cases were included, of which 185 (88.1%) survived perinatally. The median gestational age at diagnosis was 27 + 0 weeks. All cases diagnosed at ≥ 28 weeks survived. In cases diagnosed < 28 weeks, survivors (vs non-survivors) had a higher gestational age (26.1 vs 24.4 weeks), estimated fetal weight (EFW; 626 vs 384 g), cerebroplacental ratio (1.1 vs 0.9), PlGF (41 vs 18 pg/mL) and PlGF multiples of the median (MoM; 0.10 vs 0.06) and lower sFlt-1/PlGF ratio (129 vs 479) at the time of diagnosis (all P < 0.001). The best combination of two variables for predicting perinatal survival was provided by EFW and PlGF MoM (area under the receiver-operating-characteristics curve (AUC), 0.84 (95% CI, 0.75–0.92)). These were also the best variables for predicting severe neonatal morbidity (AUC, 0.73 (95% CI, 0.66–0.80)). Conclusions A model combining EFW and maternal serum PlGF predicts accurately perinatal survival in eoFGR cases diagnosed before 28 weeks of gestation. Prenatal prediction of severe neonatal morbidity in eoFGR cases is modest regardless of the model used. © 2022 The Authors. Ultrasound in Obstetrics & Gynecolog, Instituto de Salud Carlos III (ISCIII), European Regional Development Fund (FEDER), Depto. de Salud Pública y Materno - Infantil, Fac. de Medicina, TRUE, pub
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- 2023
7. Prediction of postnatal circulation in pulmonary atresia/critical stenosis with intact ventricular septum: systematic review and external validation of models
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Villalaín, C., primary, Moon‐Grady, A. J., additional, Ulrike, H., additional, Strainic, J., additional, Cohen, J. L., additional, Shah, A., additional, Levi, D. S., additional, Gómez‐Montes, E., additional, Herraiz, I., additional, and Galindo, A., additional
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- 2023
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8. Prediction of perinatal survival in early‐onset fetal growth restriction: role of placental growth factor
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Rodríguez‐Calvo, J., primary, Villalaín, C., additional, Gómez‐Arriaga, P. I., additional, Quezada, M. S., additional, Herraiz, I., additional, and Galindo, A., additional
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- 2023
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- View/download PDF
9. Working Group on Nephrops Surveys (WGNEPS; outputs from 2022 meeting)
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Aguzzi J., Aristegui-Ezquibela M., Burgos C., Chatzievangelou D., Doyle J., Fallon N., Fifas S., González-Herraiz I., Jonsson P., Lundy M., Martinelli M., Medve?ek D., Naseer A., Nava E., Nawri N., Jónasson J. P., Pereira B., Pieri G., Silva C., Tibone M., Valeiras J., Vila Y., Weetman A., and Wieland K.
- Subjects
Fisheries and aquaculture ,Technologies and data ,Adriatic Sea (ICES adjacent region) ,UWTV ,Nephrops ,Ecosystem observation, processes and dynamics ,Survey ,All ICES Ecoregions - Abstract
The Working Group on Nephrops Surveys (WGNEPS) is the international coordination group for Nephrops underwater television and trawl surveys within ICES. This report summarizes the national contributions on the results of the surveys conducted in 2022 together with time series covering all survey years, problems encountered, data quality checks and technological improvements as well as the planning for survey activities for 2023. In total, 21 surveys covering 26 functional units (FU’s) in the ICES area and 1 geographical subarea (GSA) in the Adriatic Sea were discussed and further improvements in respect to survey design and data analysis standardization and the use of most recent technology were reviewed. The first exploratory UWTV survey on the FU 25 Nephrops grounds was also presented to the group. The results of the evaluation of reference sets for FU3&4 Skagerrak/Kattegat were accepted following the process set down by the 2018 workshop (WKNEPS). An alternative method estimate Nephrops abundance was shown to the group using the recently published R package sdmTMB. The group agreed to hold a workshop in 2025 to address burrow size estimations to update correction factors and terms of reference for this to be agreed at next meeting. Automatic burrow detection based on deep learning methods continues to show promising results where datasets from multiple institutes were used. Plans are being progressed for an international Nephrops UWTV database to be established at the ICES data centre with a sub-group.
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- 2023
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10. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis
- Author
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Allotey, J., Whittle, R., Snell, K. I. E., Smuk, M., Townsend, R., von Dadelszen, P., Heazell, A. E. P., Magee, L., Smith, G. C. S., Sandall, J., Thilaganathan, B., Zamora, J., Riley, R. D., Khalil, A., Thangaratinam, S., Coomarasamy, A., Kwong, A., Savitri, A. I., Salvesen, K. A., Bhattacharya, S., Uiterwaal, C. S. P. M., Staff, A. C., Andersen, L. B., Olive, E. L., Redman, C., Sletner, L., Daskalakis, G., Macleod, M., Abdollahain, M., Ramirez, J. A., Masse, J., Audibert, F., Magnus, P. M., Jenum, A. K., Baschat, A., Ohkuchi, A., Mcauliffe, F. M., West, J., Askie, L. M., Mone, F., Farrar, D., Zimmerman, P. A., Smits, L. J. M., Riddell, C., Kingdom, J. C., van de Post, J., Illanes, S. E., Holzman, C., van Kuijk, S. M. J., Carbillon, L., Villa, P. M., Eskild, A., Chappell, L., Prefumo, F., Velauthar, L., Seed, P., van Oostwaard, M., Verlohren, S., Poston, L., Ferrazzi, E., Vinter, C. A., Nagata, C., Brown, M., Vollebregt, K. C., Takeda, S., Langenveld, J., Widmer, M., Saito, S., Haavaldsen, C., Carroli, G., Olsen, J., Wolf, H., Zavaleta, N., Eisensee, I., Vergani, P., Lumbiganon, P., Makrides, M., Facchinetti, F., Sequeira, E., Gibson, R., Ferrazzani, S., Frusca, T., Norman, J. E., Figueiro, E. A., Lapaire, O., Laivuori, H., Lykke, J. A., Conde-Agudelo, A., Galindo, A., Mbah, A., Betran, A. P., Herraiz, I., Trogstad, L., Smith, G. G. S., Steegers, E. A. P., Salim, R., Huang, T., Adank, A., Zhang, J., Meschino, W. S., Browne, J. L., Allen, R. E., Costa, F. D. S., Klipstein-Grobusch Browne, K., Crowther, C. A., Jorgensen, J. S., Forest, J. -C., Rumbold, A. R., Mol, B. W., Giguere, Y., Kenny, L. C., Ganzevoort, W., Odibo, A. O., Myers, J., Yeo, S. A., Goffinet, F., Mccowan, L., Pajkrt, E., Teede, H. J., Haddad, B. G., Dekker, G., Kleinrouweler, E. C., Lecarpentier, E., Roberts, C. T., Groen, H., Skrastad, R. B., Heinonen, S., Eero, K., Anggraini, D., Souka, A., Cecatti, J. G., Monterio, I., Pillalis, A., Souza, R., Hawkins, L. A., Gabbay-Benziv, R., Crovetto, F., Figuera, F., Jorgensen, L., Dodds, J., Patel, M., Aviram, A., Papageorghiou, A., Khan, K., Clinicum, HUS Gynecology and Obstetrics, Department of Obstetrics and Gynecology, HUS Children and Adolescents, Lastentautien yksikkö, Children's Hospital, Allotey, J, Whittle, R, Snell, K, Smuk, M, Townsend, R, von Dadelszen, P, Heazell, A, Magee, L, Smith, G, Sandall, J, Thilaganathan, B, Zamora, J, Riley, R, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, A, Salvesen, K, Bhattacharya, S, Uiterwaal, C, Staff, A, Andersen, L, Olive, E, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramirez, J, Masse, J, Audibert, F, Magnus, P, Jenum, A, Baschat, A, Ohkuchi, A, Mcauliffe, F, West, J, Askie, L, Mone, F, Farrar, D, Zimmerman, P, Smits, L, Riddell, C, Kingdom, J, van de Post, J, Illanes, S, Holzman, C, van Kuijk, S, Carbillon, L, Villa, P, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, van Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, C, Nagata, C, Brown, M, Vollebregt, K, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, J, Figueiro, E, Lapaire, O, Laivuori, H, Lykke, J, Conde-Agudelo, A, Galindo, A, Mbah, A, Betran, A, Herraiz, I, Trogstad, L, Steegers, E, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, W, Browne, J, Allen, R, Costa, F, Klipstein-Grobusch Browne, K, Crowther, C, Jorgensen, J, Forest, J, Rumbold, A, Mol, B, Giguere, Y, Kenny, L, Ganzevoort, W, Odibo, A, Myers, J, Yeo, S, Goffinet, F, Mccowan, L, Pajkrt, E, Teede, H, Haddad, B, Dekker, G, Kleinrouweler, E, Lecarpentier, E, Roberts, C, Groen, H, Skrastad, R, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, J, Monterio, I, Pillalis, A, Souza, R, Hawkins, L, Gabbay-Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, Khan, K, Tampere University, Obstetrics and Gynaecology, APH - Quality of Care, Amsterdam Reproduction & Development (AR&D), APH - Personalized Medicine, APH - Digital Health, and Obstetrics and gynaecology
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Calibration (statistics) ,Perinatal Death ,Overfitting ,Cohort Studies ,Fetal Development ,0302 clinical medicine ,Discriminative model ,3123 Gynaecology and paediatrics ,Models ,Pregnancy ,GROWTH RESTRICTION ,Statistics ,Medicine ,Prenatal ,030212 general & internal medicine ,Ultrasonography ,RISK ,030219 obstetrics & reproductive medicine ,PRETERM ,Radiological and Ultrasound Technology ,LOW-DOSE ASPIRIN ,DIAGNOSIS TRIPOD ,Obstetrics and Gynecology ,General Medicine ,Statistical ,Stillbirth ,Prognosis ,Pregnancy Complication ,external validation ,individual participant data ,intrauterine death ,prediction model ,stillbirth ,Female ,Humans ,Infant, Newborn ,Models, Statistical ,Pregnancy Complications ,Regression Analysis ,Risk Assessment ,Ultrasonography, Prenatal ,3. Good health ,PREECLAMPSIA ,Meta-analysis ,Human ,Cohort study ,Prognosi ,MEDLINE ,Regression Analysi ,WEEKS GESTATION ,03 medical and health sciences ,VELOCIMETRY ,Radiology, Nuclear Medicine and imaging ,RECURRENCE ,business.industry ,Infant ,Newborn ,R1 ,HYPERTENSIVE DISORDERS ,Reproductive Medicine ,Sample size determination ,Cohort Studie ,RG ,business ,RA ,Predictive modelling - Abstract
Objective Stillbirth is a potentially preventable complication of pregnancy. Identifying women at high risk of stillbirth can guide decisions on the need for closer surveillance and timing of delivery in order to prevent fetal death. Prognostic models have been developed to predict the risk of stillbirth, but none has yet been validated externally. In this study, we externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods MEDLINE, EMBASE, DH-DATA and AMED databases were searched from inception to December 2020 to identify studies reporting stillbirth prediction models. Studies that developed or updated prediction models for stillbirth for use at any time during pregnancy were included. IPD from cohorts within the International Prediction of Pregnancy Complications (IPPIC) Network were used to validate externally the identified prediction models whose individual variables were available in the IPD. The risk of bias of the models and cohorts was assessed using the Prediction study Risk Of Bias ASsessment Tool (PROBAST). The discriminative performance of the models was evaluated using the C-statistic, and calibration was assessed using calibration plots, calibration slope and calibration-in-the-large. Performance measures were estimated separately in each cohort, as well as summarized across cohorts using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results Seventeen studies reporting the development of 40 prognostic models for stillbirth were identified. None of the models had been previously validated externally, and the full model equation was reported for only one-fifth (20%, 8/40) of the models. External validation was possible for three of these models, using IPD from 19 cohorts (491 201 pregnant women) within the IPPIC Network database. Based on evaluation of the model development studies, all three models had an overall high risk of bias, according to PROBAST. In the IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65 and summary calibration slopes ranging from 0.40 to 0.88, with risk predictions that were generally too extreme compared with the observed risks. The models had little to no clinical utility, as assessed by net benefit. However, there remained uncertainty in the performance of some models due to small available sample sizes. Conclusions The three validated stillbirth prediction models showed generally poor and uncertain predictive performance in new data, with limited evidence to support their clinical application. The findings suggest methodological shortcomings in their development, including overfitting. Further research is needed to further validate these and other models, identify stronger prognostic factors and develop more robust prediction models. (c) 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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- 2022
11. Erratum: Risk factors associated with adverse fetal outcomes in pregnancies affected by Coronavirus disease 2019 (COVID-19): A secondary analysis of the WAPM study on COVID-19 (Journal of Perinatal Medicine (2020) 48:9 (950-958) DOI: 10.1515/jpm-2020-0355)
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Di Mascio D., Sen C., Saccone G., Galindo A., Grunebaum A., Yoshimatsu J., Stanojevic M., Kurjak A., Chervenak F., Vena F., Giancotti A., Brunelli R., Muzii L., Panici P. B., Mollo A., Berghella V., Flacco M. E., Manzoli L., Esposito R., Coviello A., Cerbone M., Maruotti G. M., Nazzaro G., Locci M., Guida M., Di Spiezio Sardo A., Bifulco G., Zullo F., Herraiz I., Villalain C., Suarez M. J. R., Gambacorti-Passerini Z. M., De Los Angeles Anaya Baz M., Galan E. V. A., Carbone I. F., Lopez Y. C., De Leon Luis J. A., Hernandez I. C., Venturella R., Rizzo G., Mappa I., Gerosolima G., Hellmeyer L., Frusca T., Volpe N., Schera G. B. L., Fieni S., Esposito E., Simonazzi G., Di Donna G., Youssef A., Gatta A. N. D., Di Donna M. C., Chiantera V., Buono N., Sozzi G., Greco P., Morano D., Bianchi B., Marino M. G. L., Laraud F., Ramone A., Cagnacci A., Barra F., Gustavino C., Ferrero S., Ghezzi F., Cromi A., Lagana A. S., Longo V. L., Stollagli F., Puri L., Sirico A., Scambia G., Lanzone A., Driul L., Fabiana Cecchini D., Xodo S., Rodriguez B., Mercado-Olivares F., Elkafrawi D., Sisti G., Morlando M., Schiattarella A., Colacurci N., De Franciscis P., Valori E., Cataneo I., Lenzi M., Sandri F., Buscemi R., Gattei G., Della Sala F., Rovellotti M. C., Done E., Faron G., Gucciardo L., Luigi N., Sorrentino F., Vasciaveo L., Liberati M., Buca D., Leombroni M., Di Sebastiano F., Di Tizio L., D'Antonio F., Gazzolo D., Franchi M., Ianniciello Q. C., Garzon S., Petriglia G., Borrello L., Nieto-Calvache A. J., Burgos-Luna J. M., Kadji C., Carlin A., Bevilacqua E., Moucho M., Pinto P. V., Figueiredo R., Rosello J. M., Loscalzo G., Martinez-Varea A., Diago V., Lopez J. S. J., Aykanat A. Y., Cosma S., Carosso A., Benedetto C., Bermejo A., Feuerschuette O. H. M., Uyaniklar O., Ocakouglu S. R., Atak Z., Gunduz R., Haberal E. T., Froessler B., Parange A., Palm P., Samardjiski I., Okuyan E., Daskalakis G., Antsaklis P., De Sa R. A. M., Pittaro A., Gonzalez-Duran M. L., Guisan A. C., Genc S. O., Zlatohlavkova B., Piqueras A. L., Oliva D. E., Cil A. P., Api O., Ples L., Kyvernitakis I., Lila A., Granese R., Ercoli A., Zoccali G., Villasco A., Biglia N., Madalina C., Costa E., Daelemans C., Pintiaux A., Cueto E., Hadar E., Dollinger S., Sinai N. A. B., Huertas E., Arango P., Sanchez A., Schvartzman J. A., Cojocaru L., Turan S., Turan O., Di Dedda M. C., Molpeceres R. G., Zdjelar S., Premru-Srsen T., Cerar L. K., Druskovic M., De Robertis V., Stefanovic V., Nupponen I., Nelskyla K., Khodjaeva Z., Gorina K. A., Sukhikh G. T., Visentin S., Cosmi E., Ferrari J., Gatti A., Luvero D., Angioli R., Palumbo M., D'Urso G., Colaleo F., Rapisarda A. M. C., Di Mascio D., Sen C., Saccone G., Galindo A., Grunebaum A., Yoshimatsu J., Stanojevic M., Kurjak A., Chervenak F., Vena F., Giancotti A., Brunelli R., Muzii L., Panici P.B., Mollo A., Berghella V., Flacco M.E., Manzoli L., Esposito R., Coviello A., Cerbone M., Maruotti G.M., Nazzaro G., Locci M., Guida M., Di Spiezio Sardo A., Bifulco G., Zullo F., Herraiz I., Villalain C., Suarez M.J.R., Gambacorti-Passerini Z.M., De Los Angeles Anaya Baz M., Galan E.V.A., Carbone I.F., Lopez Y.C., De Leon Luis J.A., Hernandez I.C., Venturella R., Rizzo G., Mappa I., Gerosolima G., Hellmeyer L., Frusca T., Volpe N., Schera G.B.L., Fieni S., Esposito E., Simonazzi G., Di Donna G., Youssef A., Gatta A.N.D., Di Donna M.C., Chiantera V., Buono N., Sozzi G., Greco P., Morano D., Bianchi B., Marino M.G.L., Laraud F., Ramone A., Cagnacci A., Barra F., Gustavino C., Ferrero S., Ghezzi F., Cromi A., Lagana A.S., Longo V.L., Stollagli F., Puri L., Sirico A., Scambia G., Lanzone A., Driul L., Fabiana Cecchini D., Xodo S., Rodriguez B., Mercado-Olivares F., Elkafrawi D., Sisti G., Morlando M., Schiattarella A., Colacurci N., De Franciscis P., Valori E., Cataneo I., Lenzi M., Sandri F., Buscemi R., Gattei G., Della Sala F., Rovellotti M.C., Done E., Faron G., Gucciardo L., Luigi N., Sorrentino F., Vasciaveo L., Liberati M., Buca D., Leombroni M., Di Sebastiano F., Di Tizio L., D'Antonio F., Gazzolo D., Franchi M., Ianniciello Q.C., Garzon S., Petriglia G., Borrello L., Nieto-Calvache A.J., Burgos-Luna J.M., Kadji C., Carlin A., Bevilacqua E., Moucho M., Pinto P.V., Figueiredo R., Rosello J.M., Loscalzo G., Martinez-Varea A., Diago V., Lopez J.S.J., Aykanat A.Y., Cosma S., Carosso A., Benedetto C., Bermejo A., Feuerschuette O.H.M., Uyaniklar O., Ocakouglu S.R., Atak Z., Gunduz R., Haberal E.T., Froessler B., Parange A., Palm P., Samardjiski I., Okuyan E., Daskalakis G., Antsaklis P., De Sa R.A.M., Pittaro A., Gonzalez-Duran M.L., Guisan A.C., Genc S.O., Zlatohlavkova B., Piqueras A.L., Oliva D.E., Cil A.P., Api O., Ples L., Kyvernitakis I., Lila A., Granese R., Ercoli A., Zoccali G., Villasco A., Biglia N., Madalina C., Costa E., Daelemans C., Pintiaux A., Cueto E., Hadar E., Dollinger S., Sinai N.A.B., Huertas E., Arango P., Sanchez A., Schvartzman J.A., Cojocaru L., Turan S., Turan O., Di Dedda M.C., Molpeceres R.G., Zdjelar S., Premru-Srsen T., Cerar L.K., Druskovic M., De Robertis V., Stefanovic V., Nupponen I., Nelskyla K., Khodjaeva Z., Gorina K.A., Sukhikh G.T., Visentin S., Cosmi E., Ferrari J., Gatti A., Luvero D., Angioli R., Palumbo M., D'Urso G., Colaleo F., Rapisarda A.M.C., Di Mascio, D., Sen, C., Saccone, G., Galindo, A., Grunebaum, A., Yoshimatsu, J., Stanojevic, M., Kurjak, A., Chervenak, F., Vena, F., Giancotti, A., Brunelli, R., Muzii, L., Panici, P. B., Mollo, A., Berghella, V., Flacco, M. E., Manzoli, L., Esposito, R., Coviello, A., Cerbone, M., Maruotti, G. M., Nazzaro, G., Locci, M., Guida, M., Di Spiezio Sardo, A., Bifulco, G., Zullo, F., Herraiz, I., Villalain, C., Suarez, M. J. R., Gambacorti-Passerini, Z. M., De Los Angeles Anaya Baz, M., Galan, E. V. A., Carbone, I. F., Lopez, Y. C., De Leon Luis, J. A., Hernandez, I. C., Venturella, R., Rizzo, G., Mappa, I., Gerosolima, G., Hellmeyer, L., Frusca, T., Volpe, N., Schera, G. B. L., Fieni, S., Esposito, E., Simonazzi, G., Di Donna, G., Youssef, A., Gatta, A. N. D., Di Donna, M. C., Chiantera, V., Buono, N., Sozzi, G., Greco, P., Morano, D., Bianchi, B., Marino, M. G. L., Laraud, F., Ramone, A., Cagnacci, A., Barra, F., Gustavino, C., Ferrero, S., Ghezzi, F., Cromi, A., Lagana, A. S., Longo, V. L., Stollagli, F., Puri, L., Sirico, A., Scambia, G., Lanzone, A., Driul, L., Fabiana Cecchini, D., Xodo, S., Rodriguez, B., Mercado-Olivares, F., Elkafrawi, D., Sisti, G., Morlando, M., Schiattarella, A., Colacurci, N., De Franciscis, P., Valori, E., Cataneo, I., Lenzi, M., Sandri, F., Buscemi, R., Gattei, G., Della Sala, F., Rovellotti, M. C., Done, E., Faron, G., Gucciardo, L., Luigi, N., Sorrentino, F., Vasciaveo, L., Liberati, M., Buca, D., Leombroni, M., Di Sebastiano, F., Di Tizio, L., D'Antonio, F., Gazzolo, D., Franchi, M., Ianniciello, Q. C., Garzon, S., Petriglia, G., Borrello, L., Nieto-Calvache, A. J., Burgos-Luna, J. M., Kadji, C., Carlin, A., Bevilacqua, E., Moucho, M., Pinto, P. V., Figueiredo, R., Rosello, J. M., Loscalzo, G., Martinez-Varea, A., Diago, V., Lopez, J. S. J., Aykanat, A. Y., Cosma, S., Carosso, A., Benedetto, C., Bermejo, A., Feuerschuette, O. H. M., Uyaniklar, O., Ocakouglu, S. R., Atak, Z., Gunduz, R., Haberal, E. T., Froessler, B., Parange, A., Palm, P., Samardjiski, I., Okuyan, E., Daskalakis, G., Antsaklis, P., De Sa, R. A. M., Pittaro, A., Gonzalez-Duran, M. L., Guisan, A. C., Genc, S. O., Zlatohlavkova, B., Piqueras, A. L., Oliva, D. E., Cil, A. P., Api, O., Ples, L., Kyvernitakis, I., Lila, A., Granese, R., Ercoli, A., Zoccali, G., Villasco, A., Biglia, N., Madalina, C., Costa, E., Daelemans, C., Pintiaux, A., Cueto, E., Hadar, E., Dollinger, S., Sinai, N. A. B., Huertas, E., Arango, P., Sanchez, A., Schvartzman, J. A., Cojocaru, L., Turan, S., Turan, O., Di Dedda, M. C., Molpeceres, R. G., Zdjelar, S., Premru-Srsen, T., Cerar, L. K., Druskovic, M., De Robertis, V., Stefanovic, V., Nupponen, I., Nelskyla, K., Khodjaeva, Z., Gorina, K. A., Sukhikh, G. T., Visentin, S., Cosmi, E., Ferrari, J., Gatti, A., Luvero, D., Angioli, R., Palumbo, M., D'Urso, G., Colaleo, F., and Rapisarda, A. M. C.
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N.A - Abstract
Due to a technical error, the author list at the end of this article is unfortunately incorrect. Elif Gül Yapar Eyi is not a co-author, and therefore, his name and affiliation should not appear in the list. The correct author list and affiliations read as follows: Daniele Di Mascio, Cihat Sen, Gabriele Saccone, Alberto Galindo, Amos Grünebaum, Jun Yoshimatsu, Milan Stanojevic, AsimKurjak, Frank Chervenak, María Jos´e Rodríguez Suárez, Zita Maria Gambacorti-Passerini, María de los Angeles Anaya Baz, Esther Vanessa Aguilar Galán, Yolanda Cuñarro López, Juan Antonio De León Luis, Ignacio Cueto Hernández, Ignacio Herraiz, Cecilia Villalain, Roberta Venturella, Giuseppe Rizzo, Ilenia Mappa, Giovanni Gerosolima, Lars Hellmeyer, Josefine Königbauer, Giada Ameli, Tiziana Frusca, Nicola Volpe, Giovanni Battista Luca Schera, Stefania Fieni, Eutalia Esposito, Giuliana Simonazzi, Gaetana Di Donna, Aly Youssef, Anna Nunzia Della Gatta, Mariano Catello Di Donna, Vito Chiantera, Natalina Buono, Giulio Sozzi, Pantaleo Greco, Danila Morano, Beatrice Bianchi, Maria Giulia Lombana Marino, Federica Laraud, Arianna Ramone, Angelo Cagnacci, Fabio Barra, Claudio Gustavino, Simone Ferrero, Fabio Ghezzi, Antonella Cromi, Antonio Simone Laganá, Valentina Laurita Longo, Francesca Stollagli, Angelo Sirico, Antonio Lanzone, Lorenza Driul, Fabiana Cecchini D, Serena Xodo, Brian Rodriguez, Felipe Mercado-Olivares, Deena Elkafrawi, Giovanni Sisti, Rosanna Esposito, Antonio Coviello, Marco Cerbone, Maddalena Morlando, Antonio Schiattarella, Nicola Colacurci, Pasquale De Franciscis, Ilaria Cataneo, Marinella Lenzi, Fabrizio Sandri, Riccardo Buscemi, Giorgia Gattei, Francesca della Sala, Eleonora Valori, Maria Cristina Rovellotti, Elisa Done, Gilles Faron, Leonardo Gucciardo, Valentina Esposito, Flaminia Vena, Antonella Giancotti, Roberto Brunelli, Ludovico Muzii, Luigi Nappi, Felice Sorrentino, Lorenzo Vasciaveo, Marco Liberati, Danilo Buca, Martina Leombroni, Francesca Di Sebastiano, Luciano Di Tizio, Diego Gazzolo, Massimo Franchi, Quintino Cesare Ianniciello, Simone Garzon, Giuliano Petriglia, Leonardo Borrello, Albaro Jos´e Nieto-Calvache, Juan Manuel Burgos-Luna, Caroline Kadji, Andrew Carlin, Elisa Bevilacqua, Marina Moucho, Pedro Viana Pinto, Rita Figueiredo, Jos´e Morales Roselló, Gabriela Loscalzo, Alicia Martinez-Varea, Vincente Diago, Jesús S Jimenez Lopez, Alicia Yeliz Aykanat, Stefano Cosma, Andrea Carosso, Chiara Benedetto, Amanda Bermejo, Otto Henrique May Feuerschuette, Ozlem Uyaniklar, Sakine Rahimli Ocakouglu, Zeliha Atak, Reyhan Gündüz, Esra Tustas Haberal, Bernd Froessler, Anupam Parange, Peter Palm, Igor Samardjiski, Chiara Taccaliti, Erhan Okuyan, George Daskalakis, Renato Augusto Moreira de Sa, Alejandro Pittaro, Maria Luisa Gonzalez-Duran, Ana Concheiro Guisan, Serife Özlem Genç, Blanka Zlatohlávková, Anna Luengo Piqueras, Dolores Esteban Oliva, Aylin Pelin Cil, Olus Api, Panos Antsaklis, Liana Ples, Ioannis Kyvernitakis, Holger Maul, Marcel Malan, Albert Lila, Roberta Granese, Alfredo Ercoli, Giuseppe Zoccali, Andrea Villasco, Nicoletta Biglia, Ciuhodaru Madalina, Elena Costa, Caroline Daelemans, Axelle Pintiaux, Elisa Cueto, Eran Hadar, Sarah Dollinger, Noa A. Brzezinski Sinai, Erasmo Huertas, Pedro Arango, Amadeo Sanchez, Javier Alfonso Schvartzman, Liviu Cojocaru, Sifa Turan, Ozhan Turan, Maria Carmela Di Dedda, Rebeca Garrote Molpeceres, Snezana Zdjelar, Tanja Premru-Srsen, Lilijana Kornhauser Cerar, Mirjam Druškovic, Valentina De Robertis, Vedran Stefanovic, Irmeli Nupponen, Kaisa Nelskylä, Zulfiya Khodjaeva, Ksenia A. Gorina, Gennady T. Sukhikh, Giuseppe Maria Maruotti, Silvia Visentin, Erich Cosmi, Jacopo Ferrari, Alessandra Gatti, Daniela Luvero, Roberto Angioli, Ludovica Puri, Marco Palumbo, Giusella D’Urso, Francesco Colaleo, Agnese Maria Chiara Rapisarda, Ilma Floriana Carbone, Antonio Mollo, Giovanni Nazzaro, Mariavittoria Locci, Maurizio Guida, Attilio Di Spiezio Sardo, Pierluigi Benedetti Panici, Vincenzo Berghella, Maria Elena Flacco, Lamberto Manzoli, Giuseppe Bifulco, Giovanni Scambia, Fulvio Zullo and Francesco D’Antonio Flaminia Vena, Antonella Giancotti, Roberto Brunelli, Ludovico Muzii and Pierluigi Benedetti Panici, Department of Maternal and Child Health and Urological Sciences, Sapienza University of Rome, Rome, Italy Rosanna Esposito, Antonio Coviello, Marco Cerbone, Giuseppe Maria Maruotti, Giovanni Nazzaro, Mariavittoria Locci, Maurizio Guida, Attilio Di Spiezio Sardo, Giuseppe Bifulco and Fulvio Zullo, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy Ignacio Herraiz and Cecilia Villalain, Department of Obstetrics and Gynaecology, Fetal Medicine Unit, Maternal and Child Health and Development Network, University Hospital 12 de Octubre, Complutense University of Madrid, Madrid, Spain María Jos´e Rodríguez Suárez, Hospital Universitario Central de Asturias, Asturias, Spain Zita Maria Gambacorti-Passerini, Department of Obstetrics and Gynaecology, Ciudad Real University General Hospital, Ciudad Real, Spain María de los Angeles Anaya Baz and Esther Vanessa Aguilar Galán, Department of Obstetrics and Gynaecology, Ciudad Real University General Hospital, Ciudad Real, Spain; University of Castilla-La Mancha, Ciudad Real, Spain Yolanda Cuñarro López, Juan Antonio De León Luis and Ignacio Cueto Hernández, Department of Obstetrics and Gynaecology, Fetal Medicine Unit, Maternal and Child Health and Development Network, Gregorio Marañón Hospital, Complutense University of Madrid, Madrid, Spain Roberta Venturella, Department of Obstetrics and Gynaecology, School of Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy Giuseppe Rizzo, University of Roma Tor Vergata, Division of Maternal Fetal Medicine, Ospedale Cristo Re Roma, Rome, Italy; Department of Obstetrics and Gynaecology, The First I.M. Sechenov Moscow State Medical University, Moscow, Russia Ilenia Mappa, University of Roma Tor Vergata, Division of Maternal Fetal Medicine, Ospedale Cristo Re Roma, Rome, Italy Giovanni Gerosolima, Department of Obstetrics and Gynaecology, Ospedale AOSG Moscati, Avellino, Italy Lars Hellmeyer, Josefine Königbauer and Giada Ameli, Department of Gynaecology and Obstetrics, Vivantes Klinikum im Friedrichshain, Berlin, Germany Tiziana Frusca, Nicola Volpe, Giovanni Battista Luca Schera and Stefania Fieni, Department of Obstetrics and Gynaecology, University of Parma, Parma, Italy Eutalia Esposito, Department of Obstetrics and Gynaecology, Ospedale di San Leonardo, Castellammare di Stabia, Italy Giuliana Simonazzi, Gaetana Di Donna, Aly Youssef and Anna Nunzia Della Gatta, Department of Obstetrics and Gynaecology, University of Bologna, Sant’Orsola- Malpighi University Hospital, Bologna, Italy Mariano Catello Di Donna, Vito Chiantera, Natalina Buono and Giulio Sozzi, Department of Gynaecologic Oncology, University of Palermo, Palermo, Sicilia, Italy Pantaleo Greco, Danila Morano, Beatrice Bianchi and Maria Giulia Lombana Marino, Department ofMedical Sciences, Section of Obstetrics and Gynaecology, Azienda Ospedaliera-Universitaria Sant’Anna, University of Ferrara, Ferrara, Italy Federica Laraud, Arianna Ramone, Angelo Cagnacci, Fabio Barra, Claudio Gustavino and Simone Ferrero, Academic Unit of Obstetrics and Gynaecology, IRCCS Ospedale Policlinico, San Martino, Genova, Italy Fabio Ghezzi, Antonella Cromi and Antonio Simone Laganà, Department of Obstetrics and Gynaecology, “Filippo Del Ponte” Hospita University of Insubria, Varese, Italy Valentina Laurita Longo, Department of Obstetrics and Gynaecology, Fondazione Policlinico Universitario A Gemelli IRCCS – Università Cattolica del Sacro Cuore, Rome, Italy; Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Rome, Italy; and Queen Margaret University, Institute for Global Health and Development, Edinburgh, UK Francesca Stollagli and Ludovica Puri, Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Rome, Italy Angelo Sirico and Giovanni Scambia, Department of Obstetrics and Gynaecology, Fondazione Policlinico Universitario A Gemelli IRCCS – Università Cattolica del Sacro Cuore, Rome, Italy Antonio Lanzone, Department of Obstetrics and Gynaecology, Fondazione Policlinico Universitario A Gemelli IRCCS – Università Cattolica del Sacro Cuore, Rome, Italy; Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Rome, Italy Lorenza Driul, Fabiana Cecchini D and Serena Xodo, Clinic of Obstetrics and Gynaecology, University of Udine, Udine, Italy Brian Rodriguez, Felipe Mercado-Olivares, Deena Elkafrawi and Giovanni Sisti, Department of Obstetrics and Gynaecology, New York Health and Hospitals/Lincoln Bronx, The Bronx, NY, USA Maddalena Morlando, Antonio Schiattarella, Nicola Colacurci and Pasquale De Franciscis, Department of Woman, Child and General and Specialized Surgery, University of Campania Luigi Vanvitelli, Naples, Italy Ilaria Cataneo, Marinella Lenzi and Fabrizio Sandri, Unit of Obstetrics and Gynaecology, Ospedale Maggiore, Bologna, Italy Riccardo Buscemi, Giorgia Gattei, Francesca della Sala and Maria Cristina Rovellotti, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy Eleonora Valori, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy; Hospital Castelli, Verbania, Italy Elisa Done, Gilles Faron and Leonardo Gucciardo, UZ Brussel, Universitair Ziekenhuis, Brussel, Belgium Valentina Esposito, University of Milan, Milan, Italy Luigi Nappi, Felice Sorrentino and Lorenzo Vasciaveo, Department of Obstetrics and Gynaecology, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy.
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- 2021
12. External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis
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Snell, K, Allotey, J, Smuk, M, Hooper, R, Chan, C, Ahmed, A, Chappell, L, Von Dadelszen, P, Green, M, Kenny, L, Khalil, A, Khan, K, Mol, B, Myers, J, Poston, L, Thilaganathan, B, Staff, A, Smith, G, Ganzevoort, W, Laivuori, H, Odibo, A, Arenas Ramirez, J, Kingdom, J, Daskalakis, G, Farrar, D, Baschat, A, Seed, P, Prefumo, F, da Silva Costa, F, Groen, H, Audibert, F, Masse, J, Skrastad, R, Salvesen, K, Haavaldsen, C, Nagata, C, Rumbold, A, Heinonen, S, Askie, L, Smits, L, Vinter, C, Magnus, P, Eero, K, Villa, P, Jenum, A, Andersen, L, Norman, J, Ohkuchi, A, Eskild, A, Bhattacharya, S, Mcauliffe, F, Galindo, A, Herraiz, I, Carbillon, L, Klipstein-Grobusch, K, Yeo, S, Browne, J, Moons, K, Riley, R, Thangaratinam, S, Vergani, P, Snell K. I. E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L. C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K. S., Mol B. W., Myers J., Poston L., Thilaganathan B., Staff A. C., Smith G. C. S., Ganzevoort W., Laivuori H., Odibo A. O., Arenas Ramirez J., Kingdom J., Daskalakis G., Farrar D., Baschat A. A., Seed P. T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R. B., Salvesen K. A., Haavaldsen C., Nagata C., Rumbold A. R., Heinonen S., Askie L. M., Smits L. J. M., Vinter C. A., Magnus P., Eero K., Villa P. M., Jenum A. K., Andersen L. B., Norman J. E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F. M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S. A., Browne J. L., Moons K. G. M., Riley R. D., Thangaratinam S., Vergani P., Snell, K, Allotey, J, Smuk, M, Hooper, R, Chan, C, Ahmed, A, Chappell, L, Von Dadelszen, P, Green, M, Kenny, L, Khalil, A, Khan, K, Mol, B, Myers, J, Poston, L, Thilaganathan, B, Staff, A, Smith, G, Ganzevoort, W, Laivuori, H, Odibo, A, Arenas Ramirez, J, Kingdom, J, Daskalakis, G, Farrar, D, Baschat, A, Seed, P, Prefumo, F, da Silva Costa, F, Groen, H, Audibert, F, Masse, J, Skrastad, R, Salvesen, K, Haavaldsen, C, Nagata, C, Rumbold, A, Heinonen, S, Askie, L, Smits, L, Vinter, C, Magnus, P, Eero, K, Villa, P, Jenum, A, Andersen, L, Norman, J, Ohkuchi, A, Eskild, A, Bhattacharya, S, Mcauliffe, F, Galindo, A, Herraiz, I, Carbillon, L, Klipstein-Grobusch, K, Yeo, S, Browne, J, Moons, K, Riley, R, Thangaratinam, S, Vergani, P, Snell K. I. E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L. C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K. S., Mol B. W., Myers J., Poston L., Thilaganathan B., Staff A. C., Smith G. C. S., Ganzevoort W., Laivuori H., Odibo A. O., Arenas Ramirez J., Kingdom J., Daskalakis G., Farrar D., Baschat A. A., Seed P. T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R. B., Salvesen K. A., Haavaldsen C., Nagata C., Rumbold A. R., Heinonen S., Askie L. M., Smits L. J. M., Vinter C. A., Magnus P., Eero K., Villa P. M., Jenum A. K., Andersen L. B., Norman J. E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F. M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S. A., Browne J. L., Moons K. G. M., Riley R. D., Thangaratinam S., and Vergani P.
- Abstract
BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHODS: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULTS: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions
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- 2020
13. Predictors of adverse perinatal outcome up to 34 weeks, a multivariable analysis study
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Morales-Roselló J, Galindo A, Scarinci E, Herraiz I, Buongiorno S, Loscalzo G, Gómez Arriaga PI, Cañada Martínez AJ, Rosati P, Lanzone A, and Perales Marín A
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middle cerebral artery Doppler ,umbilical artery Doppler ,uterine artery Doppler ,adverse perinatal outcome ,Cerebroplacental ratio - Abstract
The objective was to evaluate the best predictors of adverse perinatal outcome (APO) in foetuses examined up to 34 weeks and delivered by spontaneous or induced labour. This was a retrospective study of 129 pregnancies that underwent an ultrasound Doppler examination at 23-34 weeks and entered into labour within 30 days. Cerebroplacental ratio (CPR) and mean uterine artery pulsatility index (mUtA PI) were converted into multiples of the median (MoM) and estimated foetal weight (EFW) into centiles to adjust for gestational age (GA). Sonographic and clinical parameters were evaluated using logistic regression analysis.The multivariable model for the prediction of APO presented a notable accuracy: Detection rate (DR) was 39.5% for a false positive rate (FPR) of 5% and 56.8% for a FPR of 10%, AUC 0.82, p < .0001. Significant predictors were GA, EFW centile, and CPR MoM, but not mUtA PI MoM. Moreover, the type of labour onset did not exert any influence on APO. In conclusion, up to 34 weeks, prediction of APO after spontaneous or induced labour may be done measuring CPR and EFW.IMPACT STATEMENTWhat is already known on this subject? Earlier in pregnancy, foetal growth restriction is caused by placental disease causing progressive hemodynamic changes. These changes have been exhaustively described. Conversely, information about the best predictors of adverse outcome is scarce.What do the results of this study add? The findings of this study show that prior to 34 weeks and up to 1 month before labour, labour outcome might be predicted by gestational age, foetal cerebroplacental ratio (CPR) and estimated foetal weight (EFW).What are the implications of these findings for clinical practice and/or further research? If CPR behaves as a good marker of outcome not only at the end of pregnancy but also earlier in gestation, it might be interrogated along with EFW in foetuses attempting vaginal delivery to determine the risk of adverse outcome.
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- 2022
14. Nephrops in 8c in 2021
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Vázquez-Vilamea, A. (Armando), and Morlán-Díaz, R. (Roberto)
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trawlers ,surveys ,North Galicia ,Cantabrian Sea ,geographical distribution ,Nephrops ,logbooks - Published
- 2022
15. Estimación área de la Unidad Funcional de Cigala 25 (Galicia Norte) para el diseño de la campaña ISUNEP25_062022
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Lourido-Soto, A. (Antía), and Vila, Y. (Yolanda)
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cigala ,Norway lobster ,FU 25 ,North Galicia ,Nephrops ,Assessment area - Published
- 2022
16. Maternal and neonatal outcomes of pregnancies complicated by late fetal growth restriction undergoing induction of labor with dinoprostone compared with cervical balloon: A retrospective, international study
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Di Mascio, D., Villalain, C., Rizzo, G., Morales-Rossello, J., Sileo, F. G., Maruotti, G. M., Prefumo, F., Galindo, A., D'Antonio, F., Buca, D., Herraiz, I., Loscalzo, G., Finarelli, A., Bertucci, E., Facchinetti, F., Brunelli, R., Giancotti, A., Muzii, L., Carbone, L., Saccone, G., D'Amico, A., Tinari, S., Cerra, C., Nappi, L., Greco, P., Monaci, R., Fichera, A., Fratelli, N., Liberati, M., Di Mascio, D., Villalain, C., Rizzo, G., Morales-Rossello, J., Sileo, F. G., Maruotti, G. M., Prefumo, F., Galindo, A., D'Antonio, F., Buca, D., Herraiz, I., Loscalzo, G., Finarelli, A., Bertucci, E., Facchinetti, F., Brunelli, R., Giancotti, A., Muzii, L., Carbone, L., Saccone, G., D'Amico, A., Tinari, S., Cerra, C., Nappi, L., Greco, P., Monaci, R., Fichera, A., Fratelli, N., and Liberati, M.
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induction of labor ,Neonatal intensive care unit ,Cohort Studies ,fetal growth restriction ,prostaglandins ,0302 clinical medicine ,Pregnancy ,Oxytocics ,Medicine ,Cook balloon catheter ,dinoprostone ,Foley balloon catheter ,late fetal growth restriction ,mechanical induction ,030212 general & internal medicine ,030219 obstetrics & reproductive medicine ,Fetal Growth Retardation ,Vaginal delivery ,Obstetrics ,Incidence (epidemiology) ,Pregnancy Outcome ,Obstetrics and Gynecology ,General Medicine ,Italy ,Settore MED/40 ,Administration ,Administration, Intravaginal ,Adult ,Catheterization ,Cesarean Section ,Dinoprostone ,Female ,Humans ,Infant, Newborn ,Labor, Induced ,Spain ,Urinary Catheterization ,prostaglandin ,Human ,Cohort study ,Uterine tachysystole ,medicine.medical_specialty ,Lower risk ,NO ,03 medical and health sciences ,Intravaginal ,business.industry ,Induced ,Infant ,Odds ratio ,medicine.disease ,Newborn ,Labor ,Oxytocic ,Cohort Studie ,business - Abstract
Introduction: The aim of this study was to compare vaginal dinoprostone and mechanical methods for induction of labor (IOL) in pregnancies complicated by late fetal growth restriction. Material and methods: Multicenter, retrospective, cohort study involving six referral centers in Italy and Spain. Inclusion criteria were pregnancies complicated by late fetal growth restriction as defined by Delphi consensus criteria. The primary outcome was the occurrence of uterine tachysystole; secondary outcomes were either cesarean delivery or operative vaginal delivery for non-reassuring fetal status, a composite score of adverse neonatal outcome and admission to neonatal intensive care unit (NICU). Univariate and multivariate logistic regression analysis was used to analyze the data. Results: A total of 571 pregnancies complicated by late fetal growth restriction undergoing IOL (391 with dinoprostone and 180 with mechanical methods) were included in the analysis. The incidence of uterine tachysystole (19.2% vs. 5.6%; p = 0.001) was higher in women undergoing IOL with dinoprostone than in those undergoing IOL with mechanical methods. Similarly, the incidence of cesarean delivery or operative delivery for non-reassuring fetal status (25.6% vs. 17.2%; p = 0.027), composite adverse neonatal outcome (26.1% vs. 16.7%; p = 0.013) and NICU admission (16.9% vs. 5.6%; p
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- 2021
17. Perinatal survival counseling of early-onset fetal growth restriction with placental growth factor.
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Rodríguez‐Calvo, J., Villalaín, C., Gómez‐Arriaga, P. I., Quezada, M. S., Herraiz, I., Galindo, A., Rodríguez-Calvo, J, and Gómez-Arriaga, P I
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PLACENTAL growth factor ,FETAL growth retardation ,HYDROPS fetalis ,GESTATIONAL age ,REGRESSION analysis ,FORECASTING - Abstract
Objective: To analyze the capability to predict perinatal survival and severe neonatal morbidity at diagnosis of early-onset fetal growth restriction (eoFGR) using maternal variables, ultrasound parameters and angiogenic markers.Methods: Prospective observational study in a cohort of singleton pregnancies with a diagnosis of eoFGR (< 32+0 weeks). At diagnosis of eoFGR, complete assessment was performed, including ultrasound examination (anatomy, biometry and Doppler study) and maternal serum measurement of the angiogenic biomarkers sFlt-1 and PlGF. Logistic regression models for the prediction of perinatal survival (in cases diagnosed < 28+0 weeks) and severe neonatal morbidity (in all cases) were calculated.Results: We included 210 eoFGR cases, with 185 (88%) perinatal survivors. Median gestational age at diagnosis was 27+0 weeks. All cases diagnosed at ≥ 28+0 weeks survived. In cases diagnosed < 28+0 weeks, survivors (vs. non-survivors) showed at diagnosis: higher gestational age (26.1 vs. 24.4 weeks), estimated fetal weight (626 vs. 384 g), cerebroplacental ratio (1.1 vs. 0.9) and PlGF (41 vs. 18 pg/ml), and lower sFlt-1/PlGF ratio (129 vs. 479), all p < 0.001. The best combination of two variables for predicting perinatal survival was provided by EFW and PlGF (AUC 0.83; 95% CI, 0.74 - 0.92). These were also the best variables for predicting severe neonatal morbidity (AUC 0.73; 95% CI, 0.65 - 0.80).Conclusions: EFW and maternal serum determination of PlGF accurately predict perinatal survival in eoFGR cases diagnosed before 28 weeks. Prenatal prediction of severe neonatal morbidity in eoFGR performs modestly. This article is protected by copyright. All rights reserved. [ABSTRACT FROM AUTHOR]- Published
- 2023
- Full Text
- View/download PDF
18. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications ( <scp>IPPIC</scp> ) Network database: individual participant data meta‐analysis
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Allotey, J, Whittle, R, Snell, KIE, Smuk, M, Townsend, R, Dadelszen, P, Heazell, AEP, Magee, L, Smith, GCS, Sandall, J, Thilaganathan, B, Zamora, J, Riley, RD, Khalil, A, Thangaratinam, S, Coomarasamy, A, Kwong, A, Savitri, AI, Salvesen, KÅ, Bhattacharya, S, Uiterwaal, CSPM, Staff, AC, Andersen, LB, Olive, EL, Redman, C, Sletner, L, Daskalakis, G, Macleod, M, Abdollahain, M, Ramírez, JA, Massé, J, Audibert, F, Magnus, PM, Jenum, AK, Baschat, A, Ohkuchi, A, McAuliffe, FM, West, J, Askie, LM, Mone, F, Farrar, D, Zimmerman, PA, Smits, LJM, Riddell, C, Kingdom, JC, Post, J, Illanes, SE, Holzman, C, Kuijk, SMJ, Carbillon, L, Villa, PM, Eskild, A, Chappell, L, Prefumo, F, Velauthar, L, Seed, P, Oostwaard, M, Verlohren, S, Poston, L, Ferrazzi, E, Vinter, CA, Nagata, C, Brown, M, Vollebregt, KC, Takeda, S, Langenveld, J, Widmer, M, Saito, S, Haavaldsen, C, Carroli, G, Olsen, J, Wolf, H, Zavaleta, N, Eisensee, I, Vergani, P, Lumbiganon, P, Makrides, M, Facchinetti, F, Sequeira, E, Gibson, R, Ferrazzani, S, Frusca, T, Norman, JE, Figueiró‐Filho, EA, Lapaire, O, Laivuori, H, Lykke, JA, Conde‐Agudelo, A, Galindo, A, Mbah, A, Betran, AP, Herraiz, I, Trogstad, L, Smith, GGS, Steegers, EAP, Salim, R, Huang, T, Adank, A, Zhang, J, Meschino, WS, Browne, JL, Allen, RE, Costa, F Da Silva, Klipstein‐Grobusch, K, Crowther, CA, Jørgensen, JS, Forest, J‐C, Rumbold, AR, Mol, BW, Giguère, Y, Kenny, LC, Ganzevoort, W, Odibo, AO, Myers, J, Yeo, SA, Goffinet, F, McCowan, L, Pajkrt, E, Teede, HJ, Haddad, BG, Dekker, G, Kleinrouweler, EC, LeCarpentier, É, Roberts, CT, Groen, H, Skråstad, RB, Heinonen, S, Eero, K, Anggraini, D, Souka, A, Cecatti, JG, Monterio, I, Pillalis, A, Souza, R, Hawkins, LA, Gabbay‐Benziv, R, Crovetto, F, Figuera, F, Jorgensen, L, Dodds, J, Patel, M, Aviram, A, Papageorghiou, A, and Khan, K
- Abstract
Objective: Stillbirth is a potentially preventable complication of pregnancy. Identifying women at risk can guide decisions on closer surveillance or timing of birth to prevent fetal death.Prognostic models have been developed to predict the risk of stillbirth, but none have yet been externally validated. We externally validated published prediction models for stillbirth using individual participant data (IPD) meta-analysis to assess their predictive performance. Methods: We searched Medline, EMBASE, DH-DATA and AMED databases from inception to December 2020 to identify stillbirth prediction models. We included studies that developed or updated prediction models for stillbirth for use at any time during pregnancy. IPD from cohorts within the International Prediction of Pregnancy Complication (IPPIC) Network were used to externally validate the identified prediction models whose individual variables were available in the IPD. We assessed the risk of bias of the models and IPD using PROBAST, and reported discriminative performance using the C-statistic, and calibration performance using calibration plots, calibration slopeand calibration-in-the-large. We estimated performance measures separately in each study, and then summarised across studies using random-effects meta-analysis. Clinical utility was assessed using net benefit. Results: We identified 17 studies reporting the development of 40 prognostic models for stillbirth. None of the models were previously externally validated, and only a fifth (20%, 8/40) reported the full model equation. We were able to validate three of these models using the IPD from 19 cohort studies (491,201 pregnant women) within the IPPIC Network database. Based on evaluating their development studies, all three models had an overall high risk of bias according to PROBAST. In our IPD meta-analysis, the models had summary C-statistics ranging from 0.53 to 0.65; summary calibration slopes of 0.40to 0.88, and generally with observed risks predictions that were too extreme compared to observed risks; and little to no clinical utility as assessed by net benefit. However, there remained uncertainty in performance for some models due to small available sample sizes. Conclusion: The three validated models generally showed poor and uncertain predictive performancein new data, with limited evidence to support their clinical application. Findings suggest methodological shortcomings in their development including overfitting of models. Further research is needed to further validate these and other models, identify stronger prognostic factors, and to develop more robust prediction models
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- 2021
19. Implementation of the sFlt-1/PlGF ratio for prediction and diagnosis of pre-eclampsia in singleton pregnancy: implications for clinical practice
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Stepan, H., Herraiz, I., Schlembach, D., Verlohren, S., Brennecke, S., Chantraine, F., Klein, E., Lapaire, O., Llurba, E., Ramoni, A., Vatish, M., Wertaschnigg, D., and Galindo, A.
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- 2015
- Full Text
- View/download PDF
20. Nephrops in 8c - Functional Unit 25 (North Galicia) (ICES WGBIE)
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González-Herraiz, I. (Isabel), Velasco, F. (Francisco), Gómez-Suárez, F.J. (Francisco Javier), Vázquez-Vilamea, A. (Armando), Morlán-Díaz, R. (Roberto), Salinas-Aguilera, M.I. (Miren Itxaso), and Rodríguez-Gutiérrez, J. (José)
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SPiCT ,Sentinel Fishery ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) - Published
- 2021
21. ICES WKMSYSPiCT Final SPICT model for Nephrops Functional Unit 31 (Cantabrian Sea)
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González-Herraiz, I. (Isabel)
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SPiCT ,Stock assessment ,Nephrops Functional Unit 31 (Cantabrian Sea) ,Surplus Production Model In Continuous Time - Published
- 2021
22. Final SPiCT model for Nephrops Functional Unit 25
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González-Herraiz, I. (Isabel)
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SPiCT ,depleted stocks ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) ,Surplus Production Model In Continuous Time - Published
- 2021
23. Application of SPiCT to produce MSY advice for Nephrops Functional Unit 31
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Velasco, F. (Francisco), Vázquez-Vilamea, A. (Armando), Morlán-Díaz, R. (Roberto), and Rincón-Hidalgo, M. (Margarita)
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SPiCT ,Stock assessment ,Pesquerías ,Centro Oceanográfico de A Coruña ,Nephrops Functional Unit 31 (Cantabrian Sea) ,Surplus Production Model In Continuous Time - Abstract
Improving scientific advice to fishery managenent for resources of interest for Spain in Atlantic waters, IMPRESS
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- 2021
24. Placental growth factor testing in the management of late preterm preeclampsia without severe features: a multicenter, randomized, controlled trial
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Peguero A, Herraiz I, Perales A, Melchor JC, Melchor I, Marcos B, Villalain C, Martinez-Portilla R, Mazarico-Gallego E, Meler E, Hernández-Bou S, JAUME AGUILAR MATAS, Del Rio M, Galindo A, and Figueras-Retuerta F
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biomarkers ,prediction ,preeclampsia ,blood pressure ,infant ,morbidity ,therapy ,newborn - Abstract
BACKGROUND: In women with late preterm preeclampsia, the optimal time for delivery remains a controversial topic, because of the fine balance between the maternal benefits from early delivery and the risks for prematurity. It remains challenging to define prognostic markers to identify women at highest risk for complications, in which case a selective, planned delivery may reduce the adverse maternal and perinatal outcomes. OBJECTIVE: This trial aimed to determine whether using an algorithm based on the maternal levels of placental growth factor in women with late preterm preeclampsia to evaluate the best time for delivery reduced the progression to preeclampsia with severe features without increasing the adverse perinatal outcomes. STUDY DESIGN: This parallel-group, open-label, multicenter, randomized controlled trial was conducted at 7 maternity units across Spain. We compared selective planned deliveries based on maternal levels of placental growth factor at admission (revealed group) and expectant management under usual care (concealed group) with individual randomization in singleton pregnancies with late preterm preeclampsia from 34 to 36+6 weeks' gestation. The coprimary maternal outcome was the progression to preeclampsia with severe features. The coprimary neonatal outcome was morbidity at infant hospital discharge with a noninferiority hypothesis (noninferiority margin of 10% difference in incidence). Analyses were conducted according to intention-to-treat. RESULTS: Between January 1, 2016, and December 31, 2019, 178 women were recruited. Of those women, 88 were assigned to the revealed group and 90 were assigned to the concealed group. The data analysis was performed before the completion of the required sample size. The proportion of women with progression to preeclampsia with severe features was significantly lower in the revealed group than in the concealed group (adjusted relative risk, 0.5; 95% confidence interval, 0.33-0.76; P=.001). The proportion of infants with neonatal morbidity was not significantly different between groups (adjusted relative risk, 0.77; 95% confidence interval, 0.39-1.53; P=.45). CONCLUSION: There is evidence to suggest that the use of an algorithm based on placental growth factor levels in women with late preterm preeclampsia leads to a lower rate of progression to preeclampsia with severe features and reduces maternal complications without worsening the neonatal outcomes. This trade-off should be discussed with women with late preterm preeclampsia to allow shared decision making about the timing of delivery.
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- 2021
25. Applying length-based assessment methods to fisheries resources of the Bay of Biscay and Atlantic Iberian Waters: stock status and parameters sensitivity
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Cousido-Rocha, M. (Marta), Cerviño, S. (Santiago), Gil, J. (Juan), González-Herraiz, I. (Isabel), Rincón-Hidalgo, M. (Margarita), Ramos, F. (Fernando), Rodríguez-Cabello, C. (Cristina), Sampedro-Pastor, P. (Paz), Vila, Y. (Yolanda), Pennino, M.G. (María Gracia), Alonso-Fernández, A., and Ministerio de Ciencia, Innovación y Universidades (España)
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Atlantic Iberian Waters ,Data Limited Methods (DLM) ,Length Based Indicators (LBI) ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) ,Bay of Biscay ,fishery resources ,Lenght Based Spawning Potential Ratio (LBSPR) - Abstract
ASLO 2021 Aquatic Sciences Virtual Meeting, 22–27 June 2021, Length-based methods have been widely applied to estimate biological parameters and to understand the dynamics of marine resource populations within the category of data-limited stocks, Project IMPRESS (RTI2018-099868-B-I00), ERDF, Ministry of Science, Innovation and Universities - State Research Agency, and also of GAIN (Xunta de Galicia), GRC MERVEX (nº IN607-A 2018-4)
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- 2021
26. Maternal and perinatal outcomes of pregnant women with SARS-CoV-2 infection
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Saccone, G. Sen, C. Di Mascio, D. Galindo, A. Grünebaum, A. Yoshimatsu, J. Stanojevic, M. Kurjak, A. Chervenak, F. Suárez, M.J.R. Gambacorti-Passerini, Z.M. de los Angeles Anaya Baz, M. Galán, E.V.A. López, Y.C. Luis, J.A.D.L. Hernández, I.C. Herraiz, I. Villalain, C. Venturella, R. Rizzo, G. Mappa, I. Gerosolima, G. Hellmeyer, L. Königbauer, J. Ameli, G. Frusca, T. Volpe, N. Schera, G.B.L. Fieni, S. Esposito, E. Simonazzi, G. Di Donna, G. Youssef, A. Gatta, A.N.D. Di Donna, M.C. Chiantera, V. Buono, N. Sozzi, G. Greco, P. Morano, D. Bianchi, B. Marino, M.G.L. Laraud, F. Ramone, A. Cagnacci, A. Barra, F. Gustavino, C. Ferrero, S. Ghezzi, F. Cromi, A. Laganà, A.S. Longo, V.L. Stollagli, F. Sirico, A. Lanzone, A. Driul, L. Cecchini, F. Xodo, S. Rodriguez, B. Mercado-Olivares, F. Elkafrawi, D. Sisti, G. Esposito, R. Coviello, A. Cerbone, M. Morlando, M. Schiattarella, A. Colacurci, N. De Franciscis, P. Cataneo, I. Lenzi, M. Sandri, F. Buscemi, R. Gattei, G. Sala, F.D. Valori, E. Rovellotti, M.C. Done, E. Faron, G. Gucciardo, L. Esposito, V. Vena, F. Giancotti, A. Brunelli, R. Muzii, L. Nappi, L. Sorrentino, F. Liberati, M. Buca, D. Leombroni, M. Di Sebastiano, F. Franchi, M. Ianniciello, Q.C. Garzon, S. Petriglia, G. Borrello, L. Nieto-Calvache, A.J. Burgos-Luna, J.M. Kadji, C. Carlin, A. Bevilacqua, E. Moucho, M. Viana Pinto, P. Figueiredo, R. Morales Roselló, J. Loscalzo, G. Martinez-Varea, A. Diago, V. Jimenez Lopez, J.S. Aykanat, A.Y. Cosma, S. Carosso, A. Benedetto, C. Bermejo, A. Feuerschuette, O.H.M. Uyaniklar, O. Ocakouglu, S.R. Atak, Z. Gündüz, R. Haberal, E.T. Froessler, B. Parange, A. Palm, P. Samardjiski, I. Taccaliti, C. Okuyan, E. Daskalakis, G. de Sa, R.A.M. Pittaro, A. Gonzalez-Duran, M.L. Guisan, A.C. Genç, S.Ö. Zlatohlávková, B. Piqueras, A.L. Oliva, D.E. Cil, A.P. Api, O. Antsaklis, P. Ples, L. Kyvernitakis, I. Maul, H. Malan, M. Lila, A. Granese, R. Ercoli, A. Zoccali, G. Villasco, A. Biglia, N. Madalina, C. Costa, E. Daelemans, C. Pintiaux, A. Cueto, E. Hadar, E. Dollinger, S. Brzezinski-Sinai, N.A. Huertas, E. Arango, P. Sanchez, A. Schvartzman, J.A. Cojocaru, L. Turan, S. Turan, O. Di Dedda, M.C. Molpeceres, R.G. Zdjelar, S. Premru-Srsen, T. Kornhauser-Cerar, L. Druškovic, M. De Robertis, V. Stefanovic, V. Nupponen, I. Nelskylä, K. Khodjaeva, Z. Gorina, K.A. Sukhikh, G.T. Maruotti, G.M. Visentin, S. Cosmi, E. Ferrari, J. Gatti, A. Luvero, D. Angioli, R. Puri, L. Palumbo, M. D'Urso, G. Colaleo, F. Rapisarda, A.M.C. Carbone, I.F. Manzoli, L. Flacco, M.E. Nazzaro, G. Locci, M. Guida, M. Sardo, A.D.S. Panici, P.B. Khalil, A. Berghella, V. Bifulco, G. Scambia, G. Zullo, F. D'Antonio, F. The WAPM (World Association of Perinatal Medicine) Working Group on COVID-19
- Abstract
Objectives: To evaluate the maternal and perinatal outcomes of pregnancies affected by SARS-CoV-2 infection. Methods: This was a multinational retrospective cohort study including women with a singleton pregnancy and laboratory-confirmed SARS-CoV-2 infection, conducted in 72 centers in 22 different countries in Europe, the USA, South America, Asia and Australia, between 1 February 2020 and 30 April 2020. Confirmed SARS-CoV-2 infection was defined as a positive result on real-time reverse-transcription polymerase chain reaction (RT-PCR) assay of nasopharyngeal swab specimens. The primary outcome was a composite measure of maternal mortality and morbidity, including admission to the intensive care unit (ICU), use of mechanical ventilation and death. Results: In total, 388 women with a singleton pregnancy tested positive for SARS-CoV-2 on RT-PCR of a nasopharyngeal swab and were included in the study. Composite adverse maternal outcome was observed in 47/388 (12.1%) women; 43 (11.1%) women were admitted to the ICU, 36 (9.3%) required mechanical ventilation and three (0.8%) died. Of the 388 women included in the study, 122 (31.4%) were still pregnant at the time of data analysis. Among the other 266 women, six (19.4% of the 31 women with first-trimester infection) had miscarriage, three (1.1%) had termination of pregnancy, six (2.3%) had stillbirth and 251 (94.4%) delivered a liveborn infant. The rate of preterm birth before 37 weeks' gestation was 26.3% (70/266). Of the 251 liveborn infants, 69/251 (27.5%) were admitted to the neonatal ICU, and there were five (2.0%) neonatal deaths. The overall rate of perinatal death was 4.1% (11/266). Only one (1/251, 0.4%) infant, born to a mother who tested positive during the third trimester, was found to be positive for SARS-CoV-2 on RT-PCR. Conclusions: SARS-CoV-2 infection in pregnant women is associated with a 0.8% rate of maternal mortality, but an 11.1% rate of admission to the ICU. The risk of vertical transmission seems to be negligible. © 2020 International Society of Ultrasound in Obstetrics and Gynecology. © 2020 International Society of Ultrasound in Obstetrics and Gynecology
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- 2021
27. Erratum: Risk factors associated with adverse fetal outcomes in pregnancies affected by Coronavirus disease 2019 (COVID-19): A secondary analysis of the WAPM study on COVID-19 (Journal of Perinatal Medicine (2020) 48:9 (950-958) DOI: 10.1515/jpm-2020-0355)
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Di Mascio, D. Sen, C. Saccone, G. Galindo, A. Grünebaum, A. Yoshimatsu, J. Stanojevic, M. Kurjak, A. Chervenak, F. Vena, F. Giancotti, A. Brunelli, R. Muzii, L. Panici, P.B. Mollo, A. Berghella, V. Flacco, M.E. Manzoli, L. Esposito, R. Coviello, A. Cerbone, M. Maruotti, G.M. Nazzaro, G. Locci, M. Guida, M. Di Spiezio Sardo, A. Bifulco, G. Zullo, F. Herraiz, I. Villalain, C. Suárez, M.J.R. Gambacorti-Passerini, Z.M. De Los Angeles Anaya Baz, M. Galán, E.V.A. Carbone, I.F. López, Y.C. De León Luis, J.A. Hernández, I.C. Venturella, R. Rizzo, G. Mappa, I. Gerosolima, G. Hellmeyer, L. Frusca, T. Volpe, N. Schera, G.B.L. Fieni, S. Esposito, E. Simonazzi, G. Di Donna, G. Youssef, A. Gatta, A.N.D. Di Donna, M.C. Chiantera, V. Buono, N. Sozzi, G. Greco, P. Morano, D. Bianchi, B. Marino, M.G.L. Laraud, F. Ramone, A. Cagnacci, A. Barra, F. Gustavino, C. Ferrero, S. Ghezzi, F. Cromi, A. Laganà, A.S. Longo, V.L. Stollagli, F. Puri, L. Sirico, A. Scambia, G. Lanzone, A. Driul, L. Fabiana Cecchini, D. Xodo, S. Rodriguez, B. Mercado-Olivares, F. Elkafrawi, D. Sisti, G. Morlando, M. Schiattarella, A. Colacurci, N. De Franciscis, P. Valori, E. Cataneo, I. Lenzi, M. Sandri, F. Buscemi, R. Gattei, G. Della Sala, F. Rovellotti, M.C. Done, E. Faron, G. Gucciardo, L. Luigi, N. Sorrentino, F. Vasciaveo, L. Liberati, M. Buca, D. Leombroni, M. Di Sebastiano, F. Di Tizio, L. D'Antonio, F. Gazzolo, D. Franchi, M. Ianniciello, Q.C. Garzon, S. Petriglia, G. Borrello, L. Nieto-Calvache, A.J. Burgos-Luna, J.M. Kadji, C. Carlin, A. Bevilacqua, E. Moucho, M. Pinto, P.V. Figueiredo, R. Roselló, J.M. Loscalzo, G. Martinez-Varea, A. Diago, V. Lopez, J.S.J. Aykanat, A.Y. Cosma, S. Carosso, A. Benedetto, C. Bermejo, A. Feuerschuette, O.H.M. Uyaniklar, O. Ocakouglu, S.R. Atak, Z. Gündüz, R. Haberal, E.T. Froessler, B. Parange, A. Palm, P. Samardjiski, I. Okuyan, E. Daskalakis, G. Antsaklis, P. De Sa, R.A.M. Pittaro, A. Gonzalez-Duran, M.L. Guisan, A.C. Genç, S.Ö. Zlatohlávková, B. Piqueras, A.L. Oliva, D.E. Cil, A.P. Api, O. Ples, L. Kyvernitakis, I. Lila, A. Granese, R. Ercoli, A. Zoccali, G. Villasco, A. Biglia, N. Madalina, C. Costa, E. Daelemans, C. Pintiaux, A. Cueto, E. Hadar, E. Dollinger, S. Sinai, N.A.B. Huertas, E. Arango, P. Sanchez, A. Schvartzman, J.A. Cojocaru, L. Turan, S. Turan, O. Di Dedda, M.C. Molpeceres, R.G. Zdjelar, S. Premru-Srsen, T. Cerar, L.K. Druškovic, M. De Robertis, V. Stefanovic, V. Nupponen, I. Nelskylä, K. Khodjaeva, Z. Gorina, K.A. Sukhikh, G.T. Visentin, S. Cosmi, E. Ferrari, J. Gatti, A. Luvero, D. Angioli, R. Palumbo, M. D'Urso, G. Colaleo, F. Rapisarda, A.M.C.
- Abstract
Due to a technical error, the author list at the end of this article is unfortunately incorrect. Elif Gül Yapar Eyi is not a co-author, and therefore, his name and affiliation should not appear in the list. The correct author list and affiliations read as follows: Daniele Di Mascio, Cihat Sen, Gabriele Saccone, Alberto Galindo, Amos Grünebaum, Jun Yoshimatsu, Milan Stanojevic, AsimKurjak, Frank Chervenak, María Jos´e Rodríguez Suárez, Zita Maria Gambacorti-Passerini, María de los Angeles Anaya Baz, Esther Vanessa Aguilar Galán, Yolanda Cuñarro López, Juan Antonio De León Luis, Ignacio Cueto Hernández, Ignacio Herraiz, Cecilia Villalain, Roberta Venturella, Giuseppe Rizzo, Ilenia Mappa, Giovanni Gerosolima, Lars Hellmeyer, Josefine Königbauer, Giada Ameli, Tiziana Frusca, Nicola Volpe, Giovanni Battista Luca Schera, Stefania Fieni, Eutalia Esposito, Giuliana Simonazzi, Gaetana Di Donna, Aly Youssef, Anna Nunzia Della Gatta, Mariano Catello Di Donna, Vito Chiantera, Natalina Buono, Giulio Sozzi, Pantaleo Greco, Danila Morano, Beatrice Bianchi, Maria Giulia Lombana Marino, Federica Laraud, Arianna Ramone, Angelo Cagnacci, Fabio Barra, Claudio Gustavino, Simone Ferrero, Fabio Ghezzi, Antonella Cromi, Antonio Simone Laganá, Valentina Laurita Longo, Francesca Stollagli, Angelo Sirico, Antonio Lanzone, Lorenza Driul, Fabiana Cecchini D, Serena Xodo, Brian Rodriguez, Felipe Mercado-Olivares, Deena Elkafrawi, Giovanni Sisti, Rosanna Esposito, Antonio Coviello, Marco Cerbone, Maddalena Morlando, Antonio Schiattarella, Nicola Colacurci, Pasquale De Franciscis, Ilaria Cataneo, Marinella Lenzi, Fabrizio Sandri, Riccardo Buscemi, Giorgia Gattei, Francesca della Sala, Eleonora Valori, Maria Cristina Rovellotti, Elisa Done, Gilles Faron, Leonardo Gucciardo, Valentina Esposito, Flaminia Vena, Antonella Giancotti, Roberto Brunelli, Ludovico Muzii, Luigi Nappi, Felice Sorrentino, Lorenzo Vasciaveo, Marco Liberati, Danilo Buca, Martina Leombroni, Francesca Di Sebastiano, Luciano Di Tizio, Diego Gazzolo, Massimo Franchi, Quintino Cesare Ianniciello, Simone Garzon, Giuliano Petriglia, Leonardo Borrello, Albaro Jos´e Nieto-Calvache, Juan Manuel Burgos-Luna, Caroline Kadji, Andrew Carlin, Elisa Bevilacqua, Marina Moucho, Pedro Viana Pinto, Rita Figueiredo, Jos´e Morales Roselló, Gabriela Loscalzo, Alicia Martinez-Varea, Vincente Diago, Jesús S Jimenez Lopez, Alicia Yeliz Aykanat, Stefano Cosma, Andrea Carosso, Chiara Benedetto, Amanda Bermejo, Otto Henrique May Feuerschuette, Ozlem Uyaniklar, Sakine Rahimli Ocakouglu, Zeliha Atak, Reyhan Gündüz, Esra Tustas Haberal, Bernd Froessler, Anupam Parange, Peter Palm, Igor Samardjiski, Chiara Taccaliti, Erhan Okuyan, George Daskalakis, Renato Augusto Moreira de Sa, Alejandro Pittaro, Maria Luisa Gonzalez-Duran, Ana Concheiro Guisan, Serife Özlem Genç, Blanka Zlatohlávková, Anna Luengo Piqueras, Dolores Esteban Oliva, Aylin Pelin Cil, Olus Api, Panos Antsaklis, Liana Ples, Ioannis Kyvernitakis, Holger Maul, Marcel Malan, Albert Lila, Roberta Granese, Alfredo Ercoli, Giuseppe Zoccali, Andrea Villasco, Nicoletta Biglia, Ciuhodaru Madalina, Elena Costa, Caroline Daelemans, Axelle Pintiaux, Elisa Cueto, Eran Hadar, Sarah Dollinger, Noa A. Brzezinski Sinai, Erasmo Huertas, Pedro Arango, Amadeo Sanchez, Javier Alfonso Schvartzman, Liviu Cojocaru, Sifa Turan, Ozhan Turan, Maria Carmela Di Dedda, Rebeca Garrote Molpeceres, Snezana Zdjelar, Tanja Premru-Srsen, Lilijana Kornhauser Cerar, Mirjam Druškovic, Valentina De Robertis, Vedran Stefanovic, Irmeli Nupponen, Kaisa Nelskylä, Zulfiya Khodjaeva, Ksenia A. Gorina, Gennady T. Sukhikh, Giuseppe Maria Maruotti, Silvia Visentin, Erich Cosmi, Jacopo Ferrari, Alessandra Gatti, Daniela Luvero, Roberto Angioli, Ludovica Puri, Marco Palumbo, Giusella D’Urso, Francesco Colaleo, Agnese Maria Chiara Rapisarda, Ilma Floriana Carbone, Antonio Mollo, Giovanni Nazzaro, Mariavittoria Locci, Maurizio Guida, Attilio Di Spiezio Sardo, Pierluigi Benedetti Panici, Vincenzo Berghella, Maria Elena Flacco, Lamberto Manzoli, Giuseppe Bifulco, Giovanni Scambia, Fulvio Zullo and Francesco D’Antonio Flaminia Vena, Antonella Giancotti, Roberto Brunelli, Ludovico Muzii and Pierluigi Benedetti Panici, Department of Maternal and Child Health and Urological Sciences, Sapienza University of Rome, Rome, Italy Rosanna Esposito, Antonio Coviello, Marco Cerbone, Giuseppe Maria Maruotti, Giovanni Nazzaro, Mariavittoria Locci, Maurizio Guida, Attilio Di Spiezio Sardo, Giuseppe Bifulco and Fulvio Zullo, Department of Neuroscience, Reproductive Sciences and Dentistry, School of Medicine, University of Naples Federico II, Naples, Italy Ignacio Herraiz and Cecilia Villalain, Department of Obstetrics and Gynaecology, Fetal Medicine Unit, Maternal and Child Health and Development Network, University Hospital 12 de Octubre, Complutense University of Madrid, Madrid, Spain María Jos´e Rodríguez Suárez, Hospital Universitario Central de Asturias, Asturias, Spain Zita Maria Gambacorti-Passerini, Department of Obstetrics and Gynaecology, Ciudad Real University General Hospital, Ciudad Real, Spain María de los Angeles Anaya Baz and Esther Vanessa Aguilar Galán, Department of Obstetrics and Gynaecology, Ciudad Real University General Hospital, Ciudad Real, Spain; University of Castilla-La Mancha, Ciudad Real, Spain Yolanda Cuñarro López, Juan Antonio De León Luis and Ignacio Cueto Hernández, Department of Obstetrics and Gynaecology, Fetal Medicine Unit, Maternal and Child Health and Development Network, Gregorio Marañón Hospital, Complutense University of Madrid, Madrid, Spain Roberta Venturella, Department of Obstetrics and Gynaecology, School of Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy Giuseppe Rizzo, University of Roma Tor Vergata, Division of Maternal Fetal Medicine, Ospedale Cristo Re Roma, Rome, Italy; Department of Obstetrics and Gynaecology, The First I.M. Sechenov Moscow State Medical University, Moscow, Russia Ilenia Mappa, University of Roma Tor Vergata, Division of Maternal Fetal Medicine, Ospedale Cristo Re Roma, Rome, Italy Giovanni Gerosolima, Department of Obstetrics and Gynaecology, Ospedale AOSG Moscati, Avellino, Italy Lars Hellmeyer, Josefine Königbauer and Giada Ameli, Department of Gynaecology and Obstetrics, Vivantes Klinikum im Friedrichshain, Berlin, Germany Tiziana Frusca, Nicola Volpe, Giovanni Battista Luca Schera and Stefania Fieni, Department of Obstetrics and Gynaecology, University of Parma, Parma, Italy Eutalia Esposito, Department of Obstetrics and Gynaecology, Ospedale di San Leonardo, Castellammare di Stabia, Italy Giuliana Simonazzi, Gaetana Di Donna, Aly Youssef and Anna Nunzia Della Gatta, Department of Obstetrics and Gynaecology, University of Bologna, Sant’Orsola- Malpighi University Hospital, Bologna, Italy Mariano Catello Di Donna, Vito Chiantera, Natalina Buono and Giulio Sozzi, Department of Gynaecologic Oncology, University of Palermo, Palermo, Sicilia, Italy Pantaleo Greco, Danila Morano, Beatrice Bianchi and Maria Giulia Lombana Marino, Department ofMedical Sciences, Section of Obstetrics and Gynaecology, Azienda Ospedaliera-Universitaria Sant’Anna, University of Ferrara, Ferrara, Italy Federica Laraud, Arianna Ramone, Angelo Cagnacci, Fabio Barra, Claudio Gustavino and Simone Ferrero, Academic Unit of Obstetrics and Gynaecology, IRCCS Ospedale Policlinico, San Martino, Genova, Italy Fabio Ghezzi, Antonella Cromi and Antonio Simone Laganà, Department of Obstetrics and Gynaecology, “Filippo Del Ponte” Hospita University of Insubria, Varese, Italy Valentina Laurita Longo, Department of Obstetrics and Gynaecology, Fondazione Policlinico Universitario A Gemelli IRCCS – Università Cattolica del Sacro Cuore, Rome, Italy; Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Rome, Italy; and Queen Margaret University, Institute for Global Health and Development, Edinburgh, UK Francesca Stollagli and Ludovica Puri, Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Rome, Italy Angelo Sirico and Giovanni Scambia, Department of Obstetrics and Gynaecology, Fondazione Policlinico Universitario A Gemelli IRCCS – Università Cattolica del Sacro Cuore, Rome, Italy Antonio Lanzone, Department of Obstetrics and Gynaecology, Fondazione Policlinico Universitario A Gemelli IRCCS – Università Cattolica del Sacro Cuore, Rome, Italy; Istituto di Clinica Ostetrica e Ginecologica, Università Cattolica del Sacro Cuore, Rome, Italy Lorenza Driul, Fabiana Cecchini D and Serena Xodo, Clinic of Obstetrics and Gynaecology, University of Udine, Udine, Italy Brian Rodriguez, Felipe Mercado-Olivares, Deena Elkafrawi and Giovanni Sisti, Department of Obstetrics and Gynaecology, New York Health and Hospitals/Lincoln Bronx, The Bronx, NY, USA Maddalena Morlando, Antonio Schiattarella, Nicola Colacurci and Pasquale De Franciscis, Department of Woman, Child and General and Specialized Surgery, University of Campania Luigi Vanvitelli, Naples, Italy Ilaria Cataneo, Marinella Lenzi and Fabrizio Sandri, Unit of Obstetrics and Gynaecology, Ospedale Maggiore, Bologna, Italy Riccardo Buscemi, Giorgia Gattei, Francesca della Sala and Maria Cristina Rovellotti, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy Eleonora Valori, Department of Translational Medicine, University of Eastern Piedmont, Novara, Italy; Hospital Castelli, Verbania, Italy Elisa Done, Gilles Faron and Leonardo Gucciardo, UZ Brussel, Universitair Ziekenhuis, Brussel, Belgium Valentina Esposito, University of Milan, Milan, Italy Luigi Nappi, Felice Sorrentino and Lorenzo Vasciaveo, Department of Obstetrics and Gynaecology, Department of Medical and Surgical Sciences, University of Foggia, Foggia, Italy. © 2021 De Gruyter. All rights reserved.
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- 2021
28. Assessment of an intervention to optimise antenatal management of women admitted with preterm labour and intact membranes using amniocentesis-based predictive risk models: study protocol for a randomised controlled trial (OPTIM-PTL Study)
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Cobo, T, Aldecoa, V, Bartha, JL, Bugatto, F, Carrillo-Badillo, MP, Comas, C, Diago-Almeda, V, Ferrero, S, Goya, M, Herraiz, I, Marti-Malgosa, L, Olivella, A, Paules, C, Vives, A, Figueras, F, Palacio, M, Gratacos, E, Garrido-Gimenez, C, and Medina, C
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maternal medicine ,fetal medicine ,ultrasonography - Abstract
Introduction The majority of women admitted with threatened preterm labour (PTL) do not delivery prematurely. While those with microbial invasion of the amniotic cavity (MIAC) represent the highest risk group, this is a condition that is not routinely ruled out since it requires amniocentesis. Identification of low-risk or high-risk cases might allow individualisation of care, that is, reducing overtreatment with corticosteroids and shorten hospital stay in low-risk women, while allowing early antibiotic therapy in those with MIAC. Benefits versus risks of amniocentesis-based predictor models of spontaneous delivery within 7 days and/or MIAC have not been evaluated. Methods and analysis This will be a Spanish randomised, multicentre clinical trial in singleton pregnancies (23.0-34.6 weeks) with PTL, conducted in 13 tertiary centres. The intervention arm will consist in the use of amniocentesis-based predictor models: if low risk, hospital discharge within 24 hours of results with no further medication will be recommended. If high risk, antibiotics will be added to standard management. The control group will be managed according to standard institutional protocols, without performing amniocentesis for this indication. The primary outcome will be total antenatal doses of corticosteroids, and secondary outcomes will be days of maternal stay and the occurrence of clinical chorioamnionitis. A cost analysis will be undertaken. To observe a reduction from 90% to 70% in corticosteroid doses, a reduction in 1 day of hospital stay (SD of 2) and a reduction from 24% to 12% of clinical chorioamnionitis, a total of 340 eligible patients randomised 1 to 1 to each study arm is required (power of 80%, with type I error alpha=0.05 and two-sided test, considering a dropout rate of 20%). Randomisation will be stratified by gestational age and centre. Ethics and dissemination Prior to receiving approval from the Ethics Committee (HCB/2020/1356) and the Spanish Agency of Medicines and Medical Devices (AEMPS) (identification number: 2020-005-202-26), the trial was registered in the European Union Drug Regulating Authorities Clinical Trials database (2020-005202-26). AEMPS approved the trial as a low-intervention trial. All participants will be required to provide written informed consent. Findings will be disseminated through workshops, peer-reviewed publications and national/international conferences. Protocol version V.4 10 May 2021.
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- 2021
29. Gestational Age-Specific Reference Ranges for the sFlt-1/PlGF Immunoassay Ratio in Twin Pregnancies
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De La Calle, M, Delgado, JL, Verlohren, S, Escudero, AI, Bartha, JL, Campillos, JM, De La Cruz, AA, Chantraine, F, Hernandez, JAG, Herraiz, I, Llurba, E, Kurka, H, Guo, G, Sillman, J, Hund, M, and Marin, AP
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Soluble fms-like tyrosine kinase-1 ,Placental growth factor ,embryonic structures ,Reference ranges ,sFlt-1 ,Twin pregnancies ,Biomarker ,PlGF ratio ,Preeclampsia ,Prediction - Abstract
Objective: Establish reference ranges for the Elecsys (R) soluble fms-like tyrosine kinase-1 (sFlt-1)/placental growth factor (PlGF) immunoassay ratio in twin pregnancies. Methods: Data analyzed were from 3 prospective studies: Prediction of Short-Term Outcome in Pregnant Women with Suspected Preeclampsia (PE) (PROGNOSIS), Study of Early-onset PE in Spain (STEPS), and a multicenter case-control study. Median, 5th, and 95th percentiles for sFlt-1, PlGF, and the sFlt-1/PlGF ratios were determined for normal twin pregnancies for 7 gestational windows and compared with the previous data for singleton pregnancies. Results: The reference range analysis included 269 women with normal twin pregnancies. Before 29 weeks' gestation, median, 5th, and 95th percentiles for sFlt-1/PlGF ratios did not differ between twin and singleton pregnancies. From 29 weeks' gestation to delivery, median, 5th, and 95th percentiles for sFlt-1/PlGF ratios were substantially higher in twin versus singleton pregnancies. sFlt-1 values were higher in women with twin pregnancies across all gestational windows. PlGF values were similar or higher in twin versus singleton pregnancies; PlGF concentrations increased from 10 weeks + 0 days to 28 weeks + 6 days' gestation. Conclusions: Reference ranges for the sFlt-1/PlGF ratio are similar in women with twin and singleton pregnancies until 29 weeks' gestation but appear higher in twin pregnancies thereafter.
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- 2021
30. Benchmark Workshop on the development of MSY advice for category 3 stocks using Sur-plus Production Model in Continuous Time; SPiCT (WKMSYSPiCT)
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Berg, C., Coleman, P., Cooper, A. (Anne), Hansen, H.O. (Hege Overbo), Haslob, H. (Holger), Helle, K. (Kristin), González-Herraiz, I. (Isabel), Kokkalis, Alex, Mildenberger, T. (Tobias), Moura, T., Pennino, M.G. (María Gracia), Serra Pereira, B., Ramírez, J. (John), Sampedro-Pastor, P. (Paz), Schuchert, P. (Pia), Silva, C., Vila, Y. (Yolanda), White, J., Winker, H., Azevedo, M. (Manuela), and Cardinale, M.
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SPiCT ,Category 3 stocks ,ICES ,Stock assessment ,14. Life underwater ,Pesquerías ,Advice ,Centro Oceanográfico de A Coruña ,MSY ,Surplus Production Model In Continuous Time - Abstract
The Benchmark Workshop on the application of SPiCT to produce MSY advice for selected stocks (WKMSYSPiCT) is a unique benchmark in that it is ICES first effort to provide MSY advice for category 3 stocks and it incorporated model learning sessions, with model developers and stock assessors, carried out prior to the data evaluation meeting. Thirteen stocks, including nine de-mersal fish stocks and four Functional Units of Nephrops (Nephrops norvegicus), pertaining to four ICES Assessment Working Groups (WGNSSK, WGDEEP, WGCSE and WGBIE), were selected based on the availability of appropriate data and network capacity. Stock assessments using the Surplus Production in Continuous Time (SPiCT) were successful for two demersal stocks, Me-grim (Lepidorhombus spp.) in Division 6.b (lez.27.6b) and Black-bellied anglerfish (Lophius bude-gassa) in divisions 8.c and 9.a (ank.27.8c9a) and for three Functional Units of Nephrops, Norway lobster FU 25 (nep.fu.25), Norway lobster FU 26–27 (nep.fu.2627) and Norway lobster FU 31 (nep.fu.31). WKMSYSPiCT considered that the stocks´ current category could be upgraded since the methodology is appropriate to determine stock status and a short-term catch forecast. Several model configurations were applied for the two Tusk (Brosme brosme) stocks, Tusk in subareas 1 and 2 (usk.27.1-2) and Tusk in subareas 4 and 7-9, and in divisions 3.a, 5.b, 6.a, and 12.b (usk.27.3a45b6a7-912b) and for Norway lobster FU 28–29 (nep.fu.2829), but the available data did not allow to distinguish between two very different stock status. For Pollock (Pollachius pol-lachius) in Subarea 8 and Division 9.a (pol.27.89a), no model configuration passed diagnostics tests. The extensive exploration of input data and model configurations carried out during the workshop resulted in several recommendations regarding the use of historical catches, the stand-ardization of CPUE, including approaches accounting for spatial, target and technological creep effects and, SPiCT model diagnostics.
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- 2021
31. Maternal and perinatal outcomes in high compared to low risk pregnancies complicated by severe acute respiratory syndrome coronavirus 2 infection (phase 2): the World Association of Perinatal Medicine working group on coronavirus disease 2019
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D'Antonio, F. Sen, C. Mascio, D.D. Galindo, A. Villalain, C. Herraiz, I. Arisoy, R. Ovayolu, A. Eroğlu, H. Canales, M.G. Ladella, S. Cojocaru, L. Turan, O. Turan, S. Hadar, E. Brzezinski-Sinai, N.A. Dollinger, S. Uyaniklar, O. Ocakouglu, S.R. Atak, Z. Premru-Srsen, T. Kornhauser-Cerar, L. Druškovič, M. Ples, L. Gündüz, R. Ağaçayak, E. Schvartzman, J.A. Malbran, M.N. Liberati, M. Sebastiano, F.D. Oronzi, L. Cerra, C. Buca, D. Cagnacci, A. Ramone, A. Barra, F. Carosso, A. Benedetto, C. Cosma, S. Pintiaux, A. Daelemans, C. Costa, E. Özel, A. Muhçu, M. Lopez, J.S.J. Alvarado, C. Piqueras, A.L. Oliva, D.E. Schera, G.B.L. Volpe, N. Frusca, T. Samardjiski, I. Simeonova, S. Papestiev, I.A. Hojman, J. Turkcuoglu, I. Cromi, A. Laganà, A.S. Ghezzi, F. Sirico, A. Familiari, A. Scambia, G. Sukhikh, Z.K.G.T. Gorina, K.A. de Sa, R.A.M. Vaz, M. Feuerschuette, O.H.M. Gatta, A.N.D. Youssef, A. Donna, G.D. Martinez-Varea, A. Loscalzo, G. Roselló, J.M. Stefanovic, V. Nupponen, I. Nelskylä, K. Ayala, R. Molpeceres, R.G. Vázquez, A.P. Sandri, F. Cataneo, I. Lenzi, M. Haberal, E.T. Huertas, E. Sanchez, A. Arango, P. Bermejo, A. Alcantara, M.M.G. Göynümer, G. Okuyan, E. Madalina, C. Guisan, A.C. Schulte, A.M. Esposito, V. De Robertis, V. Zdjelar, S. Lackovic, M. Mihajlovic, S. Jekova, N. Saccone, G. Aslan, M.M. Dedda, M.C.D. Chalid, M. Canache, J.E.M. Daskalakis, G. Antsaklis, P. Vega, E.C. Cueto, E. Taccaliti, C. Aykanat, Y. Özlem Genç, Ş. Froessler, B. Radulova, P.A. Morano, D. Bianchi, B. Marino, M.G.L. Meccariello, G. Rohatgi, B. Schiattarella, A. Morlando, M. Colacurci, N. Villasco, A. Biglia, N. Marques, A.L.S. Gatti, A. Luvero, D. Angioli, R. Pittaro, A. Lila, A. Zlatohlávková, B. On the behalf of the World Association of Perinatal Medicine working group on coronavirus disease 2019
- Abstract
BACKGROUND: It has still to be ascertained whether severe acute respiratory syndrome coronavirus 2 infection in pregnancy is associated with worse maternal and fetal outcomes compared to low risk gestations. OBJECTIVE: This study aimed to evaluate maternal and perinatal outcomes in high- and low-risk pregnancies complicated by severe acute respiratory syndrome coronavirus 2 infection. STUDY DESIGN: This was a multinational retrospective cohort study involving women with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection from 76 centers from 25 countries in Europe, the United States, South America, Asia, and Australia from April 4, 2020, to October 28, 2020. The primary outcome was a composite measure of maternal mortality and morbidity, including admission to the intensive care unit, use of mechanical ventilation, or death. The secondary outcome was a composite measure of adverse perinatal outcome, including miscarriage, fetal loss, neonatal and perinatal death, and admission to the neonatal intensive care unit. All outcomes were assessed in high- and low-risk pregnancies. Pregnancies were considered high risk in case of either preexisting chronic medical conditions in pregnancy or obstetrical disorders occurring in pregnancy. The Fisher exact test and logistic regression analysis were used to analyze the data. RESULTS: A total of 887 singleton pregnancies who tested positive for severe acute respiratory syndrome coronavirus 2 infection using reverse transcription-polymerase chain reaction of nasal and pharyngeal swab specimens were included in the study. The risk of composite adverse maternal outcomes was higher in high-risk pregnancies than in low-risk pregnancies (odds ratio, 1.52; 95% confidence interval, 1.03–2.24; P=.035). In addition, women carrying high-risk pregnancies were at higher risk of hospital admission (odds ratio, 1.48; 95% confidence interval, 1.07–2.04; P=.002), presence of severe respiratory symptoms (odds ratio, 2.13; 95% confidence interval, 0.41–3.21; P=.001), admission to the intensive care unit (odds ratio, 2.63; 95% confidence interval, 1.42–4.88), and invasive mechanical ventilation (odds ratio, 2.65; 95% confidence interval, 1.19–5.94; P=.002). When exploring perinatal outcomes, high-risk pregnancies were at high risk of adverse perinatal outcomes (odds ratio, 1.78; 95% confidence interval, 0.15–2.72; P=.009). However, such association was mainly because of the higher incidence of miscarriage in high-risk pregnancies compared with that in low-risk pregnancies (5.3% vs 1.6%, P=.008); furthermore, there was no difference in other explored outcomes between the 2 study groups. At logistic regression analysis, maternal age (odds ratio, 1.12; 95% confidence interval, 1.02–1.22; P=.023) and high-risk pregnancy (odds ratio, 4.21; 95% confidence interval, 3.90–5.11; P
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- 2021
32. External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis.
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Kingdom J., Poston L., Thilaganathan B., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Arenas Ramirez J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S.A., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L.C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., Myers J., Kingdom J., Poston L., Thilaganathan B., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Arenas Ramirez J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., Ohkuchi A., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S.A., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Allotey J., Smuk M., Hooper R., Chan C., Ahmed A., Chappell L.C., Von Dadelszen P., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., and Myers J.
- Abstract
BACKGROUND: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. METHOD(S): IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. RESULT(S): Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decis
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- 2021
33. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: An individual participant data meta-analysis.
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Allotey J., Smuk M., Hooper R., Chan C.L., Ahmed A., Chappell L.C., von Dadelszen P., Dodds J., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., Myers J., Poston L., Thilaganathan B., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S., Teede H.J., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Ramirez J.A., Kingdom J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P.M., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., Ohkuchi A., Allotey J., Smuk M., Hooper R., Chan C.L., Ahmed A., Chappell L.C., von Dadelszen P., Dodds J., Green M., Kenny L., Khalil A., Khan K.S., Mol B.W., Myers J., Poston L., Thilaganathan B., Eskild A., Bhattacharya S., McAuliffe F.M., Galindo A., Herraiz I., Carbillon L., Klipstein-Grobusch K., Yeo S., Teede H.J., Browne J.L., Moons K.G.M., Riley R.D., Thangaratinam S., Snell K.I.E., Staff A.C., Smith G.C.S., Ganzevoort W., Laivuori H., Odibo A.O., Ramirez J.A., Kingdom J., Daskalakis G., Farrar D., Baschat A.A., Seed P.T., Prefumo F., da Silva Costa F., Groen H., Audibert F., Masse J., Skrastad R.B., Salvesen K.A., Haavaldsen C., Nagata C., Rumbold A.R., Heinonen S., Askie L.M., Smits L.J.M., Vinter C.A., Magnus P.M., Eero K., Villa P.M., Jenum A.K., Andersen L.B., Norman J.E., and Ohkuchi A.
- Abstract
Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objective(s): To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design(s): This was an individual participant data meta-analysis of cohort studies. Setting(s): Source data from secondary and tertiary care. Predictors: We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes: Early-onset (delivery at < 34 weeks' gestation), late-onset (delivery at >= 34 weeks' gestation) and any-onset pre-eclampsia. Analysis: We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration.We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of >= 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I2 and 2. A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Result(s): The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models c
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- 2021
34. Cerebroplacental ratio in predicting adverse perinatal outcome: a meta-analysis of individual participant data
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Charlotte A, V, Ivy R, V, Martijn W, H, Wessel, G, Linda J, S, Caroline J, B, Ben Willem J, M, Christianne Jm, D, Patrick Mm, B, Marjon A, D, Khalil, A, Thilaganathan, B, M Turan, O, Crimmins, S, Harman, C, M Shannon, A, Kumar, S, Dicker, P, Malone, F, C Tully, E, Unterscheider, J, Crippa, I, Ghidini, A, Roncaglia, N, Vergani, P, Bhide, A, D'Antonio, F, Pilu, G, Galindo, A, Herraiz, I, Vázquez-Sarandeses, A, Ebbing, C, L Johnsen, S, O Karlsen, H, Vollgraff Heidweiller-Schreurs, Charlotte A, van Osch, Ivy R, Heymans, Martijn W, Ganzevoort, Wessel, Schoonmade, Linda J, Bax, Caroline J, Mol, Ben Willem J, de Groot, Christianne Jm, Bossuyt, Patrick Mm, de Boer, Marjon A, Asma Khalil, Basky Thilaganathan, Ozhan M Turan, Sarah Crimmins, Chris Harman, Alisson M Shannon, Sailesh Kumar, Patrick Dicker, Fergal Malone, Elizabeth C Tully, Julia Unterscheider, Isabella Crippa, Alessandro Ghidini, Nadia Roncaglia, Patrizia Vergani, Amarnath Bhide, Francesco D'Antonio, Gianluigi Pilu, Alberto Galindo, Ignacio Herraiz, Alicia Vázquez-Sarandeses, Cathrine Ebbing, Synnøve L Johnsen, Henriette O Karlsen, Charlotte A, V, Ivy R, V, Martijn W, H, Wessel, G, Linda J, S, Caroline J, B, Ben Willem J, M, Christianne Jm, D, Patrick Mm, B, Marjon A, D, Khalil, A, Thilaganathan, B, M Turan, O, Crimmins, S, Harman, C, M Shannon, A, Kumar, S, Dicker, P, Malone, F, C Tully, E, Unterscheider, J, Crippa, I, Ghidini, A, Roncaglia, N, Vergani, P, Bhide, A, D'Antonio, F, Pilu, G, Galindo, A, Herraiz, I, Vázquez-Sarandeses, A, Ebbing, C, L Johnsen, S, O Karlsen, H, Vollgraff Heidweiller-Schreurs, Charlotte A, van Osch, Ivy R, Heymans, Martijn W, Ganzevoort, Wessel, Schoonmade, Linda J, Bax, Caroline J, Mol, Ben Willem J, de Groot, Christianne Jm, Bossuyt, Patrick Mm, de Boer, Marjon A, Asma Khalil, Basky Thilaganathan, Ozhan M Turan, Sarah Crimmins, Chris Harman, Alisson M Shannon, Sailesh Kumar, Patrick Dicker, Fergal Malone, Elizabeth C Tully, Julia Unterscheider, Isabella Crippa, Alessandro Ghidini, Nadia Roncaglia, Patrizia Vergani, Amarnath Bhide, Francesco D'Antonio, Gianluigi Pilu, Alberto Galindo, Ignacio Herraiz, Alicia Vázquez-Sarandeses, Cathrine Ebbing, Synnøve L Johnsen, and Henriette O Karlsen
- Abstract
Objective: To investigate if cerebroplacental ratio (CPR) adds to the predictive value of umbilical artery pulsatility index (UA PI) alone – standard of practice – for adverse perinatal outcome in singleton pregnancies. Design and setting: Meta-analysis based on individual participant data (IPD). Population or sample: Ten centres provided 17 data sets for 21 661 participants, 18 731 of which could be included. Sample sizes per data set ranged from 207 to 9215 individuals. Patient populations varied from uncomplicated to complicated pregnancies. Methods: In a collaborative, pooled analysis, we compared the prognostic value of combining CPR with UA PI, versus UA PI only and CPR only, with a one-stage IPD approach. After multiple imputation of missing values, we used multilevel multivariable logistic regression to develop prediction models. We evaluated the classification performance of all models with receiver operating characteristics analysis. We performed subgroup analyses according to gestational age, birthweight centile and estimated fetal weight centile. Main outcome measures: Composite adverse perinatal outcome, defined as perinatal death, caesarean section for fetal distress or neonatal unit admission. Results: Adverse outcomes occurred in 3423 (18%) participants. The model with UA PI alone resulted in an area under the curve (AUC) of 0.775 (95% CI 0.709–0.828) and with CPR alone in an AUC of 0.778 (95% CI 0.715–0.831). Addition of CPR to the UA PI model resulted in an increase in the AUC of 0.003 points (0.778, 95% CI 0.714–0.831). These results were consistent across all subgroups. Conclusions: Cerebroplacental ratio added no predictive value for adverse perinatal outcome beyond UA PI, when assessing singleton pregnancies, irrespective of gestational age or fetal size. Tweetable abstract: Doppler measurement of cerebroplacental ratio in clinical practice has limited added predictive value to umbilical artery alone.
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- 2021
35. Uterine artery Doppler and sFlt-1/PlGF ratio: prognostic value in early-onset pre-eclampsia
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Gómez-Arriaga, P. I., Herraiz, I., López-Jiménez, E. A., Escribano, D., Denk, B., and Galindo, A.
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- 2014
- Full Text
- View/download PDF
36. Application of SPiCT to produce MSY advice for Nephrops Funcional Unit 25 (North Galicia)
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González-Herraiz, I. (Isabel), Morlán-Díaz, R. (Roberto), Vázquez-Vilamea, A. (Armando), Gómez-Suárez, F.J. (Francisco Javier), and Fariña-Pérez, C. (Celso)
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SPiCT ,Production Models ,Stock assessment ,Pesquerías ,Nephrops Functional Unit 25 (North Galicia) ,Centro Oceanográfico de A Coruña - Published
- 2020
37. Use of SPiCT in the stock of Nephrops of North Galicia (ICES Functional Unit no 25) - ICES WKMSYSPiCT Data Evaluation
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González-Herraiz, I. (Isabel), Morlán-Díaz, R. (Roberto), Vázquez-Vilamea, A. (Armando), Gómez-Suárez, F.J. (Francisco Javier), and Fariña-Pérez, C. (Celso)
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Production Models ,SPiCT ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) - Published
- 2020
38. First approach to SPiCT in Nephrops Div. 8c: FU 25 and FU 31
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González-Herraiz, I. (Isabel)
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SPiCT ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) ,Nephrops Functional Unit 31 (Cantabrian Sea) - Published
- 2020
39. Searching FU 25 Nephrops stock reference points with SPiCT
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González-Herraiz, I. (Isabel)
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Production Models ,SPiCT ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) - Abstract
IMPRESS project
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- 2020
40. Use of SPiCT in the stock of Nephrops of North Galicia (ICES Functional Unit no 25)
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González-Herraiz, I. (Isabel)
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Production Models ,SPiCT ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) - Abstract
IMPRESS project
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- 2020
41. FU 25 Nephrops Sentinel Fishery (2017-2019)
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Fariña-Pérez, C. (Celso), Rodríguez-Gutiérrez, J. (José), and Salinas-Aguilera, M.I. (Miren Itxaso)
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Sentinel Fishery ,Stock assessment ,Nephrops Functional Unit 25 (North Galicia) - Published
- 2020
42. FU 31 Nephrops Sentinel Fishery in 2019
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Fariña-Pérez, C. (Celso), Rodríguez-Gutiérrez, J. (José), and Salinas-Aguilera, M.I. (Miren Itxaso)
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Nephrops Functional Unit 31 (Cantabrian Sea) - Published
- 2020
43. Nephrops Sentinel Fishery in Functional Unit 31 (Cantabrian Sea) 2019
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Fariña-Pérez, C. (Celso), Rodríguez-Gutiérrez, J. (José), and Salinas-Aguilera, M.I. (Miren Itxaso)
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Sentinel Fishery ,Stock assessment ,Pesquerías ,Centro Oceanográfico de A Coruña ,Nephrops Functional Unit 31 (Cantabrian Sea) - Published
- 2020
44. Is it possible to predict late antepartum stillbirth by means of cerebroplacental ratio and maternal characteristics?
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Morales-Roselló J, Galindo A, Herraiz I, Gil MM, Brik M, De Paco-Matallana C, Ciammela R, Sanchez Ajenjo C, Cañada Martinez AJ, Delgado JL, and Perales-Marín A
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congenital, hereditary, and neonatal diseases and abnormalities ,embryonic structures ,population characteristics ,female genital diseases and pregnancy complications ,reproductive and urinary physiology ,Cerebroplacental ratio, fetal growth restriction, fetal hemodynamics, fetal middle cerebral artery Doppler, stillbirth, umbilical artery Doppler - Abstract
To examine the potential value of fetal ultrasound and maternal characteristics in the prediction of antepartum stillbirth after 32 weeks' gestation.
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- 2020
45. Nephrops Sentinel Fishery in Functional Unit 25 (North Galicia) 2017-2019
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González-Herraiz, I. (Isabel), Gómez-Suárez, F.J. (Francisco Javier), Fariña-Pérez, C. (Celso), Rodríguez-Gutiérrez, J. (José), and Salinas-Aguilera, M.I. (Miren Itxaso)
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Sentinel Fishery ,Stock assessment ,Pesquerías ,Nephrops Functional Unit 25 (North Galicia) ,Centro Oceanográfico de A Coruña - Published
- 2020
46. Prediction of Perinatal Mortality in Ebstein's Anomaly Diagnosed in the Second Trimester of Pregnancy
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Masoller-Casas N, Gómez Del Rincón O, Herraiz I, Gómez-Montes E, Soveral I, Pérez-Cruz M, Martínez-Biosques C, Granados MA, Bennasar M, Escobar-Diaz MC, Martínez JM, and Galindo A
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Congenital heart defects ,Fetal echocardiography ,Ebstein’s anomaly ,Prenatal diagnosis ,Tricuspid valve anomaly - Abstract
OBJECTIVES: Firstly, to describe the outcome of a series of fetuses with Ebstein's anomaly (EA) and, secondly, to study the utility of different second-trimester echocardiographic parameters to predict fetal and neonatal mortality. METHODS: 39 fetuses with EA diagnosed between 18 and 28 weeks of gestation were included. Fetal echocardiography included the cardiothoracic ratio (CTR); right atrial (RA) area index; displacement of the tricuspid valve (TV); tricuspid regurgitation; pulmonary artery; and ductus arteriosus flow characteristics. Additionally, 2 novel parameters were obtained: the relative RA area ratio (RA area/cardiac area) and the TV displacement index (TVDI, TV displacement distance/longi-tudinal diameter of the left ventricle). Correlation between the echocardiographic variables and the primary outcome of perinatal mortality or survival at 1 year of life was evaluated. RESULTS: From the initial cohort, 8 cases were excluded due to complex congenital heart defects. Termination of pregnancy (TOP) was performed in 15 cases, and fetal death was diagnosed in 3 cases. In the live-born cohort of 13 patients, 4 died in the neonatal period, yielding a perinatal survival rate of 29 and 56%, respectively, after excluding TOP cases. Compared with survivors, nonsurvivors showed a significantly higher CTR (56.7 ± 16.2 vs. 42.6 ± 8.6; p = 0.04), relative RA area ratio (0.39 ± 0.13 vs. 0.25 ± 0.05; p = 0.01), and TVDI (0.62 ± 0.17 vs. 0.44 ± 0.12; p = 0.03) at diagnosis. The best model to predict perinatal mortality was obtained by using a scoring system which included the relative RA area ratio and TVDI (AUC 0.905 [95% CI 0.732-1.000]). CONCLUSIONS: Fetuses with a relative RA area ratio =0.29 and TVDI =0.65 at the second trimester have the highest risk of dying in the perinatal stage.
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- 2020
47. Stock indentification - Nephrops 8c - Functional Units 25 (North Galicia) and 31 (Cantabrian Sea)
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González-Herraiz, I. (Isabel)
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stock identification ,Nephrops Functional Unit 25 (North Galicia) ,Nephrops Functional Unit 31 (Cantabrian Sea) - Published
- 2020
48. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: An individual participant data meta-analysis
- Author
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Allotey, J. Snell, K.I.E. Smuk, M. Hooper, R. Chan, C.L. Ahmed, A. Chappell, L.C. von Dadelszen, P. Dodds, J. Green, M. Kenny, L. Khalil, A. Khan, K.S. Mol, B.W. Myers, J. Poston, L. Thilaganathan, B. Staff, A.C. Smith, G.C.S. Ganzevoort, W. Laivuori, H. Odibo, A.O. Ramírez, J.A. Kingdom, J. Daskalakis, G. Farrar, D. Baschat, A.A. Seed, P.T. Prefumo, F. da Silva Costa, F. Groen, H. Audibert, F. Massé, J. Skråstad, R.B. Salvesen, K.A. Haavaldsen, C. Nagata, C. Rumbold, A.R. Heinonen, S. Askie, L.M. Smits, L.J.M. Vinter, C.A. Magnus, P.M. Eero, K. Villa, P.M. Jenum, A.K. Andersen, L.B. Norman, J.E. Ohkuchi, A. Eskild, A. Bhattacharya, S. McAuliffe, F.M. Galindo, A. Herraiz, I. Carbillon, L. Klipstein-Grobusch, K. Yeo, S. Teede, H.J. Browne, J.L. Moons, K.G.M. Riley, R.D. Thangaratinam, S. The IPPIC Collaborative Network
- Abstract
Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk is needed to plan management. Objectives: To assess the performance of existing pre-eclampsia prediction models and to develop and validate models for pre-eclampsia using individual participant data meta-analysis. We also estimated the prognostic value of individual markers. Design: This was an individual participant data meta-analysis of cohort studies. Setting: Source data from secondary and tertiary care. Predictors: We identified predictors from systematic reviews, and prioritised for importance in an international survey. Primary outcomes: Early-onset (delivery at < 34 weeks’ gestation), late-onset (delivery at ≥ 34 weeks’ gestation) and any-onset pre-eclampsia. Analysis: We externally validated existing prediction models in UK cohorts and reported their performance in terms of discrimination and calibration.We developed and validated 12 new models based on clinical characteristics, clinical characteristics and biochemical markers, and clinical characteristics and ultrasound markers in the first and second trimesters. We summarised the data set-specific performance of each model using a random-effects meta-analysis. Discrimination was considered promising for C-statistics of ≥ 0.7, and calibration was considered good if the slope was near 1 and calibration-in-the-large was near 0. Heterogeneity was quantified using I2 and 2. A decision curve analysis was undertaken to determine the clinical utility (net benefit) of the models. We reported the unadjusted prognostic value of individual predictors for pre-eclampsia as odds ratios with 95% confidence and prediction intervals. Results: The International Prediction of Pregnancy Complications network comprised 78 studies (3,570,993 singleton pregnancies) identified from systematic reviews of tests to predict pre-eclampsia. Twenty-four of the 131 published prediction models could be validated in 11 UK cohorts. Summary C-statistics were between 0.6 and 0.7 for most models, and calibration was generally poor owing to large between-study heterogeneity, suggesting model overfitting. The clinical utility of the models varied between showing net harm to showing minimal or no net benefit. The average discrimination for IPPIC models ranged between 0.68 and 0.83. This was highest for the second-trimester clinical characteristics and biochemical markers model to predict early-onset pre-eclampsia, and lowest for the first-trimester clinical characteristics models to predict any pre-eclampsia. Calibration performance was heterogeneous across studies. Net benefit was observed for International Prediction of Pregnancy Complications first and second-trimester clinical characteristics and clinical characteristics and biochemical markers models predicting any pre-eclampsia, when validated in singleton nulliparous women managed in the UK NHS. History of hypertension, parity, smoking, mode of conception, placental growth factor and uterine artery pulsatility index had the strongest unadjusted associations with pre-eclampsia. Limitations: Variations in study population characteristics, type of predictors reported, too few events in some validation cohorts and the type of measurements contributed to heterogeneity in performance of the International Prediction of Pregnancy Complications models. Some published models were not validated because model predictors were unavailable in the individual participant data. Conclusion: For models that could be validated, predictive performance was generally poor across data sets. Although the International Prediction of Pregnancy Complications models show good predictive performance on average, and in the singleton nulliparous population, heterogeneity in calibration performance is likely across settings. © 2020, NIHR Journals Library. All rights reserved.
- Published
- 2020
49. Resumen del consejo científico de ICES para los recursos pesqueros de interés para la flota española en aguas Atlántico ibéricas - I Stocks demersales - Programa de Pesca ICES
- Author
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Velasco, F. (Francisco), Cerviño, S. (Santiago), Abad, E. (Esther), Sampedro-Pastor, P. (Paz), and González-Herraiz, I. (Isabel)
- Subjects
Consejo científico ,Demersales ,ICES ,Stock assessment - Published
- 2020
50. Scientific, Technical and Economic Committee for Fisheries (STECF) - Fisheries Dependent Information – FDI (STECF-20-10)
- Author
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González-Herraiz, I. (Isabel) and Gómez-Suárez, F.J. (Francisco Javier)
- Subjects
fish ,marine resources ,Fishery data ,EU fleet ,Spatial effort ,Pesquerías ,Discard Plans ,Centro Oceanográfico de A Coruña ,fishery biology - Abstract
Commission Decision of 25 February 2016 setting up a Scientific, Technical and Economic Committee for Fisheries, C(2016) 1084, OJ C 74, 26.2.2016, p. 4–10. The Commission may consult the group on any matter relating to marine and fisheries biology, fishing gear technology, fisheries economics, fisheries governance, ecosystem effects of fisheries, aquaculture or similar disciplines. The STECF reviewed the report of the EWG on Fisheries-dependent Information during its winter 2020 virtual plenary meeting., EU
- Published
- 2020
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