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5. Millimeter-wave emission during the 2003 low excitation phase of eta Carinae

Author

Abraham, Z., Falceta-Goncalves, D., Dominici, T. P., Nyman, L. -A., Durouchoux, P., McAuliffe, F., Caproni, A., and Jatenco-Pereira, V.

Subjects
Astrophysics
Abstract

In this paper we present observations of eta Carinae in the 1.3 mm and 7 mm radio continuum, during the 2003.5 low excitation phase. The expected minimum in the light curves was confirmed at both wavelengths and was probably due to a decrease in the number of UV photons available to ionize the gas surrounding the binary system. At 7 mm a very well defined peak was superimposed on the declining flux density. It presented maximum amplitude in 29 June 2003 and lasted for about 10 days. We show that its origin can be free-free emission from the gas at the shock formed by wind-wind collision, which is also responsible for the observed X-ray emission. Even though the shock strength is strongly enhanced as the two stars in the binary system approach each other, during periastron passage the X-ray emission is strongly absorbed and the 7 mm observations represent the only direct evidence of this event.

Published
2005
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9. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis

Author

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

Published
2022

10. Direct current cardioversion in pregnancy: a multicentre study

Author

Cauldwell, M., primary, Adamson, D., additional, Bhatia, K., additional, Bhagra, C., additional, Bolger, A., additional, Everett, T., additional, Fox, C., additional, Girling, J., additional, Head, C., additional, English, K., additional, Hudsmith, L., additional, James, R., additional, Johnson, M., additional, MacKiliop, L., additional, McAuliffe, F. M., additional, Mariappa, G., additional, Orchard, E., additional, O’Brien, M., additional, Siddiqui, F., additional, Simpson, L., additional, Simpson, M., additional, Timmons, P., additional, Vause, S., additional, Wander, G., additional, Walker, N., additional, and Steer, P. J., additional

Published
2023
Full Text
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13. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database: individual participant data meta-analysis

Author

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

Subjects
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.

Published
2022

17. External validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysis

Author

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

Published
2020

24. Pregnancies in women with Turner syndrome: a retrospective multicentre UK study

Author

Cauldwell, M, primary, Steer, PJ, additional, Adamson, D, additional, Alexander, C, additional, Allen, L, additional, Bhagra, C, additional, Bolger, A, additional, Bonner, S, additional, Calanchini, M, additional, Carroll, A, additional, Casey, R, additional, Curtis, S, additional, Head, C, additional, English, K, additional, Hudsmith, L, additional, James, R, additional, Joy, E, additional, Keating, N, additional, MacKiliop, L, additional, McAuliffe, F, additional, Morris, RK, additional, Mohan, A, additional, Von Klemperer, K, additional, Kaler, M, additional, Rees, DA, additional, Shetty, A, additional, Siddiqui, F, additional, Simpson, L, additional, Stocker, L, additional, Timmons, P, additional, Vause, S, additional, and Turner, HE, additional

Published
2022
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32. Placental growth factor in assessment of women with suspected pre-eclampsia to reduce maternal morbidity: a stepped wedge cluster randomised control trial (PARROT Ireland)

Author

Hayes-Ryan, D, primary, Khashan, A S, additional, Hemming, K, additional, Easter, C, additional, Devane, D, additional, Murphy, D J, additional, Hunter, A, additional, Cotter, A, additional, McAuliffe, F M, additional, Morrison, J J, additional, Breathnach, F M, additional, Dempsey, E, additional, Kenny, L C, additional, and O’Donoghue, K, additional

Published
2021
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37. FIGO (international Federation of Gynecology and obstetrics) initiative on fetal growth: best practice advice for screening, diagnosis, and management of fetal growth restriction.

Author

Melamed, N, Baschat, A, Yinon, Y, Athanasiadis, A, Mecacci, F, Figueras, F, Berghella, V, Nazareth, A, Tahlak, M, McIntyre, HD, Da Silva Costa, F, Kihara, AB, Hadar, E, McAuliffe, F, Hanson, M, Ma, RC, Gooden, R, Sheiner, E, Kapur, A, Divakar, H, Ayres-de-Campos, D, Hiersch, L, Poon, LC, Kingdom, J, Romero, R, Hod, M, Melamed, N, Baschat, A, Yinon, Y, Athanasiadis, A, Mecacci, F, Figueras, F, Berghella, V, Nazareth, A, Tahlak, M, McIntyre, HD, Da Silva Costa, F, Kihara, AB, Hadar, E, McAuliffe, F, Hanson, M, Ma, RC, Gooden, R, Sheiner, E, Kapur, A, Divakar, H, Ayres-de-Campos, D, Hiersch, L, Poon, LC, Kingdom, J, Romero, R, and Hod, M

Abstract

Fetal growth restriction (FGR) is defined as the failure of the fetus to meet its growth potential due to a pathological factor, most commonly placental dysfunction. Worldwide, FGR is a leading cause of stillbirth, neonatal mortality, and short- and long-term morbidity. Ongoing advances in clinical care, especially in definitions, diagnosis, and management of FGR, require efforts to effectively translate these changes to the wide range of obstetric care providers. This article highlights agreements based on current research in the diagnosis and management of FGR, and the areas that need more research to provide further clarification of recommendations. The purpose of this article is to provide a comprehensive summary of available evidence along with practical recommendations concerning the care of pregnancies at risk of or complicated by FGR, with the overall goal to decrease the risk of stillbirth and neonatal mortality and morbidity associated with this condition. To achieve these goals, FIGO (the International Federation of Gynecology and Obstetrics) brought together international experts to review and summarize current knowledge of FGR. This summary is directed at multiple stakeholders, including healthcare providers, healthcare delivery organizations and providers, FIGO member societies, and professional organizations. Recognizing the variation in the resources and expertise available for the management of FGR in different countries or regions, this article attempts to take into consideration the unique aspects of antenatal care in low-resource settings (labelled “LRS” in the recommendations). This was achieved by collaboration with authors and FIGO member societies from low-resource settings such as India, Sub-Saharan Africa, the Middle East, and Latin America.

Published
2021

38. A literature review and best practice advice for second and third trimester risk stratification, monitoring, and management of pre-eclampsia: Compiled by the Pregnancy and Non-Communicable Diseases Committee of FIGO (the International Federation of Gynecology and Obstetrics).

Author

Poon, LC, Magee, LA, Verlohren, S, Shennan, A, von Dadelszen, P, Sheiner, E, Hadar, E, Visser, G, Da Silva Costa, F, Kapur, A, McAuliffe, F, Nazareth, A, Tahlak, M, Kihara, AB, Divakar, H, McIntyre, HD, Berghella, V, Yang, H, Romero, R, Nicolaides, KH, Melamed, N, Hod, M, Poon, LC, Magee, LA, Verlohren, S, Shennan, A, von Dadelszen, P, Sheiner, E, Hadar, E, Visser, G, Da Silva Costa, F, Kapur, A, McAuliffe, F, Nazareth, A, Tahlak, M, Kihara, AB, Divakar, H, McIntyre, HD, Berghella, V, Yang, H, Romero, R, Nicolaides, KH, Melamed, N, and Hod, M

Published
2021

48. Diagnosis and management of gestational diabetes mellitus.

Author

Benhalima K., Thangaratinam S., Cooray S.D., Sukumar N., Huda M.S.B., Devlieger R., McAuliffe F., Saravanan P., Teede H.J., Benhalima K., Thangaratinam S., Cooray S.D., Sukumar N., Huda M.S.B., Devlieger R., McAuliffe F., Saravanan P., and Teede H.J.

Abstract

The COVID-19 pandemic has required rapid transformation and ada ptation of healthcare services. Women with gestational diabetes mellitus (GDM) are one of the largest high-risk groups accessing antenatal care. In reformulating the care offered to those with GDM, there is a need to balance t he sometimes competing requirement of lowering the risk of direct viral transmission against the potential adv erse impact of service changes. We suggest pragmatic options for screening of GDM in a pandemic setting based on blo od tests, and risk calculators applied to underlying risk factors. Alternative models for antenatal care provision f or women with GDM, including targeting high-risk groups, early lifestyle interventions and remote monitoring are provide d. Testing options and their timing for postpartum screening in women who had GDM are also considered. Our suggest ions are only applicable in a pandemic scenario, and usual guidelines and care pathways should be re-implemented as soon as possible and appropriate.Copyright © 2020 European Society of Endocrinology.

Published
2020

49. 'The boob answers a lot of problems': Exploring barriers and enablers to successful extended breastfeeding in women with high BMIs

Author

O'Reilly, Sharleen, O'Brien, E, Walker, H, O'Carroll, E, Courtney, J, McAuliffe, F, O'Reilly, Sharleen, O'Brien, E, Walker, H, O'Carroll, E, Courtney, J, and McAuliffe, F

Abstract

AbstractIntroduction:Breastfeeding provides optimal nutrition for infants yet breastfeeding rates worldwide do not meet WHO targets for 50% exclusive breastfeeding at 6 months. Ireland's breastfeeding rate is one of the lowest in the world (only 58% initiation) and maternal obesity and overweight is prevalent (> 50% pregnancies). Women with obesity and overweight are particularly at risk of having lower breastfeeding rates but little is known about the factors that supported this sub-group to successfully breastfeed. Our aim was to explore barriers and enablers present in: women with high body mass index (BMI) who successfully breastfed for > 6 months, partners of women with > 6 months breastfeeding, and healthcare professionals (HPs) who support women to breastfeed.Materials and Methods:Women with high BMIs (n = 20) were recruited via an extended breastfeeding Facebook group and snowballing. Partners (n = 20) were recruited via social media and word of mouth. HPs (n = 19) were recruited via posters and direct invitation. Semi-structured interviews were conducted either in-person or on telephone and digitally recorded. Interviews were verbatim transcribed and thematically analysed. Two research students independently coded each interview and consensus decided any discrepancies.Results:Barriers to breastfeeding identified aligned with previous research but the challenges appear to be increased for either the frequency or intensity of occurrence in women with high BMIs. Common barriers are: a lack of breastfeeding culture; limited access within health services to high quality and consistent breastfeeding advice; large breast

Published
2020

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