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2. 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

3. Nicotinamide riboside improves muscle mitochondrial biogenesis, satellite cell differentiation, and gut microbiota in a twin study

Author

Lapatto, H. A. (Helena A. K.), Kuusela, M. (Minna), Heikkinen, A. (Aino), Muniandy, M. (Maheswary), van der Kolk, B. W. (Birgitta W.), Gopalakrishnan, S. (Swetha), Pöllänen, N. (Noora), Sandvik, M. (Martin), Schmidt, M. S. (Mark S.), Heinonen, S. (Sini), Saari, S. (Sina), Kuula, J. (Juho), Hakkarainen, A. (Antti), Tampio, J. (Janne), Saarinen, T. (Tuure), Taskinen, M.-R. (Marja-Riitta), Lundbom, N. (Nina), Groop, P.-H. (Per-Henrik), Tiirola, M. (Marja), Katajisto, P. (Pekka), Lehtonen, M. (Marko), Brenner, C. (Charles), Kaprio, J. (Jaakko), Pekkala, S. (Satu), Ollikainen, M. (Miina), Pietiläinen, K. H. (Kirsi H.), Pirinen, E. (Eija), Lapatto, H. A. (Helena A. K.), Kuusela, M. (Minna), Heikkinen, A. (Aino), Muniandy, M. (Maheswary), van der Kolk, B. W. (Birgitta W.), Gopalakrishnan, S. (Swetha), Pöllänen, N. (Noora), Sandvik, M. (Martin), Schmidt, M. S. (Mark S.), Heinonen, S. (Sini), Saari, S. (Sina), Kuula, J. (Juho), Hakkarainen, A. (Antti), Tampio, J. (Janne), Saarinen, T. (Tuure), Taskinen, M.-R. (Marja-Riitta), Lundbom, N. (Nina), Groop, P.-H. (Per-Henrik), Tiirola, M. (Marja), Katajisto, P. (Pekka), Lehtonen, M. (Marko), Brenner, C. (Charles), Kaprio, J. (Jaakko), Pekkala, S. (Satu), Ollikainen, M. (Miina), Pietiläinen, K. H. (Kirsi H.), and Pirinen, E. (Eija)

Abstract

Nicotinamide adenine dinucleotide (NAD⁺) precursor nicotinamide riboside (NR) has emerged as a promising compound to improve obesity-associated mitochondrial dysfunction and metabolic syndrome in mice. However, most short-term clinical trials conducted so far have not reported positive outcomes. Therefore, we aimed to determine whether long-term NR supplementation boosts mitochondrial biogenesis and metabolic health in humans. Twenty body mass index (BMI)–discordant monozygotic twin pairs were supplemented with an escalating dose of NR (250 to 1000 mg/day) for 5 months. NR improved systemic NAD⁺ metabolism, muscle mitochondrial number, myoblast differentiation, and gut microbiota composition in both cotwins. NR also showed a capacity to modulate epigenetic control of gene expression in muscle and adipose tissue in both cotwins. However, NR did not ameliorate adiposity or metabolic health. Overall, our results suggest that NR acts as a potent modifier of NAD⁺ metabolism, muscle mitochondrial biogenesis and stem cell function, gut microbiota, and DNA methylation in humans irrespective of BMI.

Published
2023

4. Supplementary material and dataset from: Impaired adipocyte SLC7A10 promotes lipid storage in association with insulin resistance and altered BCAA metabolism

Author

Jersin RÅ, Tallapragada DSP, Skartveit L, Bjune MS, Muniandy M, Lee-Ødegård S, Heinonen S, Alvarez M, Birkeland KI, Drevon CA, Pajukanta P, McCann A, Pietiläinen KH, Claussnitzer M, Mellgren G, Dankel SN

Abstract

The files contain supplementary material to the articleImpaired adipocyte SLC7A10 promotes lipid storage in association with insulin resistance and altered BCAA metabolism by Jersin et al. published in the Journal of ClinicalEndocrinology &Metabolism.

Published
2023
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7. 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

13. 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

14. Monipaikkaisuus, etätyö ja digitalisaatio Pohjois-Pohjanmaan yrityksissä:MOPPI-hankkeen yritysselvitys

Author

Simunaniemi, A.-M. (Anna-Mari) and Heinonen, S. (Samu)

Subjects
mikroyritykset, Pohjois-Pohjanmaa, maaseutu, etätyö, Northern Ostrobothnia, rural, monipaikkaisuus, digitalisaatio, digitalization, micro-enterprises, distributed work
Abstract

Tiivistelmä Koronakriisin myötä suurin osa yrityksistä siirtyi nopeasti ainakin osittaiseen etätyöskentelyyn. Työelämä muuttui hyvin merkittävästi nopealla aikataululla. Etätyö on ansiotyötä, jota tehdään satunnaisesti tai jatkuvasti joissain muissa paikoissa kuin varsinaisessa työpaikassa. Monipaikkaista työtä voidaan tehdä varsinaisen työntekopaikan ohella esimerkiksi kotona, työnantajan eri toimipaikoissa, asiakkaan tiloissa tai esimerkiksi julkisissa tiloissa. Monipaikkaisuuden vaikutuksia alueiden elinvoimaisuuteen ei tunneta kovin hyvin. Tämä selvitys perustuu tarpeeseen saada lisää ymmärrystä etätyöskentelyn, monipaikkaisuuden ja digitalisaation luomista mahdollisuuksista sekä niihin liittyvistä kehittämisen esteistä Pohjois-Pohjanmaalla toimivissa mikro- ja pienyrityksissä sekä maaseutumaisilla alueilla. Selvitys on osa Euroopan maaseuturahaston rahoittamaa ”Maaseudun monipaikkaisen asumisen, yrittämisen ja etätyöskentelyn edistämisen keinot Pohjois-Pohjanmaalla” (MOPPI) -hanketta. Tämän yritysten näkökulmasta tehdyn selvityksen kohderyhmät olivat Pohjois-Pohjanmaalla toimivat mikro- ja pk-yritykset. Hankkeen tuottamaa tietoa voidaan hyödyntää, kun kehitetään maaseudulla toimivien (mikro)yritysten toimintaedellytyksiä ja uusiutumista. Verkkokysely toteutettiin marraskuussa 2021. Kyselyyn vastasi 58 Pohjois-Pohjanmaalla toimivaa yrittäjää, joista 16 oli yksinyritäjiä. Yritysten henkilöstömäärä vaihteli yhden ja 110 henkilön välillä. Verkkokyselyn lisäksi haastateltiin kymmentä yrittäjää syvemmin selvityksen teemoista. Tärkein syy toimia maaseudulla lähtee yrittäjän omasta asuinpaikasta sekä mieltymyksestä asua ja toimia maaseudulla. Maaseutu voi olla myös osalle työvoimasta houkutteleva asuinpaikka. Yrityksille voikin olla hyötyä siitä, että he tuovat työnantajaviestinnässään esille etätyömahdollisuuden maaseudulla. Etätyöskentelyn vaikutukset yrityksissä ovat hyvin vaihtelevia. Tutkimuksen perusteella merkittävintä näyttää olevan työn luonne ja sen kytkeytyminen fyysiseen ympäristöön tai tiettyyn toimi- tai tuotantotilaan. Kuntien julkiset yrityspalvelut ovat tutkimukseen osallistuneiden mukaan melko huonosti tunnettuja tai ainakin vähän käytettyjä. Yrittäjillä on kiinnostusta yhteiskäyttöisten toimitilojen vuokraamiseen sekä säännöllistä työskentelyä että lyhytkestoisia liiketapaamisia varten. Selvityksen pohjalta tunnistettuja toimenpide-ehdotuksia ovat muun muassa yhteiskäyttöisten toimistotilojen ja niihin liittyvien oheispalveluiden kehittäminen sekä julkisten yrityspalveluiden ja koulutusten monipuolisempi ja kohdennetumpi viestintä. Osaavan työvoiman houkuttelemiseksi ja maaseutualueiden yrittäjyyden lisäämiseksi tärkeintä on asuinympäristön viihtyisyys ja palveluiden tarjonta. Abstract During the COVID-19 pandemic, most companies adopted quickly at least partial distance working practices. Ways of working changed dramatically. Distance work means paid salary work that regularly or occasionally in other locations that the specified workplace. Working is possible in multiple locations, for instance at home, public locations, cafes et cetera. Present practices and impacts of multi-locality working are not thoroughly investigated yet. This report aims to provide new understanding on this theme particularly in micro- and small-sized companies in the countryside of Northern Ostrobothnia region. This report is part of the MOPPI Project funded by European Agricultural Fund for Rural Development through Centre for Economic Development, Transport and the Environment. The investigation focuses on micro- and small-sized companies in Northern Ostrobothia. The findings help region and business development stakeholders promote business renewal and prerequisites for entrepreneurial operations. A total of 58 entrepreneurs participated in online survey in November 2021. Sixteen of them were solo entrepreneurs, and number of employees among participating companies varied between one and 110. After the survey, ten entrepreneurs were selected for thematic interviews. The most important background motivator to run a business in rural location is the place of residence. Recruiting companies could benefit if they could promote opportunity for distance working and living in rural environment when searching for employers. On the other hand, some companies are potentially willing to spread out and start business operations in regions where they can find skilled professionals. Impacts of distance working are miscellaneous. The survey shows that distance working is adopted in practically all companies where it is practically possibly. Particularly solo entrepreneurs with knowledge work are highly motivated to continue working even without permanent physical offices. One of the suggested development actions is accessibility to short- and long-term co-working offices. Entrepreneurs need every now and then meeting rooms for business and customer meetings, but office hubs could also provide social entrepreneurship networks. Lunch restaurant and catering services in accordance to working offices are appreciated. Other widely recognized needs are adequate broadband connections in all regions, and easy access to public transport.

Published
2022

15. Treatment of Multisystem Inflammatory Syndrome in Children

Author

McArdle A. J., Vito O., Patel H., Seaby E. G., Shah P., Wilson C., Broderick C., Nijman R., Tremoulet A. H., Munblit D., Ulloa-Gutierrez R., Carter M. J., De T., Hoggart C., Whittaker E., Herberg J. A., Kaforou M., Cunnington A. J., Levin M., Vazquez J. A., Carmona R., Perez L., Rubinos M., Veliz N., Yori S., Haerynck F., Hoste L., Leal I. A., Da Silva A. R. A., Silva A. E. A., Barchik A., Barreiro S. T. A., Cochrane N., Teixeira C. H., Arauj J. M., Ossa R. A. P. -D. L., Vieira C. S., Dimitrova A., Ganeva M., Stefanov S., Telcharova-Mihaylovska A., Biggs C. M., Scuccimarri R., Withington D., Raul B. B., Ampuero C., Aravena J., Casanova D., Cruces P., Diaz F., Garcia-Salum T., Godoy L., Medina R. A., Galaz G. V., Avila-Aguero M. L., Brenes-Chacon H., Ivankovich-Escoto G., Yock-Corrales A., Badib A., Badreldin K., Elkhashab Y., Heshmat H., Heinonen S., Angoulvant F., Belot A., Ouldali N., Beske F., Heep A., Masjosthusmann K., Reiter K., Heuvel I. V. D., Both U. V., Agrafiotou A., Antachopoulos C., Eleftheriou I., Farmaki E., Fotis L., Kafetzis D., Lampidi S., Liakopoulou T., Maritsi D., Michailidou E., Milioudi M., Mparmpounaki I., Papadimitriou E., Papaevangelou V., Roilides E., Tsiatsiou O., Tsolas G., Tsolia M., Vantsi P., Pineda L. Y. B., Aguilar K. L. B., Quintero E. M. C., Ip P., Kwan M. Y. W., Kwok J., Lau Y. L., To K., Wong J. S. C., David M., Farkas D., Kalcakosz S., Szekeres K., Zsigmond B., Aslam N., Andreozzi L., Bianco F., Bucciarelli V., Buonsenso D., Cimaz R., D'Argenio P., Dellepiane R. M., Fabi M., Mastrolia M. V., Mauro A., Mazza A., Romani L., Simonini G., Tipo V., Valentini P., Verdoni L., Reel B., Pace D., Torpiano P., Flores M. F., Dominguez M. G., Vargas A. L. G., Hernandez L. L., Figueroa R. P. M., Gaxiola G. P., Valadez J., Klevberg S., Knudsen P. K., Maseide P. H., Carrera J. M., Castano E. G., Timana C. A. D., Leon T. D., Estripeaut D., Levy J., Norero X., Record J., Rojas-Bonilla M., Iramain R., Hernandez R., Huaman G., Munaico M., Peralta C., Seminario D., Yarleque E. H. Z., Gadzinska J., Mandziuk J., Okarska-Napierala M., Alacheva Z. A., Alexeeva E., Ananin P. V., Antsupova M., Bakradze M. D., Bobkova P., Borzakova S., Chashchina I. L., Fisenko A. P., Gautier M. S., Glazyrina A., Kondrikova E., Korobyants E., Korsunskiy A. A., Kovygina K., Krasnaya E., Kurbanova S., Kurdup M. K., Mamutova A. V., Mazankova L., Mitushin I. L., Nargizyan A., Orlova Y. O., Osmanov I. M., Polyakova A. S., Romanova O., Samitova E., Sologub A., Spiridonova E., Tepaev R. F., Tkacheva A. A., Yusupova V., Zholobova E., Grasa C. D., Segura N. L., Martinon-Torres F., Melendo S., Echevarria A. M., Guzman J. M. M., Argueta J. R. P., Rivero-Calle I., Riviere J., Rodriguez-Gonzalez M., Rojo P., Manubens J. S., Soler-Palacin P., Soriano-Arandes A., Tagarro A., Villaverde S., Altman M., Brodin P., Horne A., Palmblad K., Brotschi B., Sauteur P. M., Schmid J. P., Prader S., Relly C., Schlapbach L. J., Seiler M., Truck J., Wutz D., Ketharanathan N., Vermont C., Ozkan E. A., Erdeniz E. H., Borisova G., Boychenko L., Diudenko N., Kasiyan O., Katerynych K., Melnyk K., Miagka N., Teslenko M., Trykosh M., Volokha A., Akomolafe T., Al-Abadi E., Alders N., Avram P., Bamford A., Bank M., Roy R. B., Beattie T., Boleti O., Broad J., Carrol E. D., Chandran A., Cooper H., Davies P., Emonts M., Evans C., Fidler K., Foster C., Gong C., Gongrun B., Gonzalez C., Grandjean L., Grant K., Hacohen Y., Hall J., Hassell J., Hesketh C., Hewlett J., Hnieno A., Holt-Davis H., Hossain A., Hudson L. D., Johnson M., Johnson S., Jyothish D., Kampmann B., Kavirayani A., Kelly D., Kucera F., Langer D., Lillie J., Longbottom K., Lyall H., MacKdermott N., Maltby S., McLelland T., McMahon A. -M., Miller D., Morrison Z., Mosha K., Muller J., Myttaraki E., Nadel S., Osaghae D., Osman F., Ostrzewska A., Panthula M., Papachatzi E., Papadopoulou C., Penner J., Polandi S., Prendergast A. J., Ramnarayan P., Rhys-Evans S., Riordan A., Rodrigues C. M. C., Romaine S., Seddon J., Shingadia D., Srivastava A., Struik S., Taylor A., Tran S., Tudor-Williams G., Van Der Velden F., Ventilacion L., Wellman P. A., Yanney M. P., Yeung S., Badheka A., Badran S., Bailey D. M., Burch A. K., Burns J. C., Cichon C., Cirks B., Dallman M. D., Delany D. R., Fairchok M., Friedman S., Geracht J., Langs-Barlow A., Mann K., Padhye A., Quade A., Ramirez K. A., Rockett J., Sayed I. A., Shahin A. A., Umaru S., Widener R., Angela M. H., Kandawasvika G., McArdle A.J., Vito O., Patel H., Seaby E.G., Shah P., Wilson C., Broderick C., Nijman R., Tremoulet A.H., Munblit D., Ulloa-Gutierrez R., Carter M.J., De T., Hoggart C., Whittaker E., Herberg J.A., Kaforou M., Cunnington A.J., Levin M., Vazquez J.A., Carmona R., Perez L., Rubinos M., Veliz N., Yori S., Haerynck F., Hoste L., Leal I.A., Da Silva A.R.A., Silva A.E.A., Barchik A., Barreiro S.T.A., Cochrane N., Teixeira C.H., Arauj J.M., Ossa R.A.P.-D.L., Vieira C.S., Dimitrova A., Ganeva M., Stefanov S., Telcharova-Mihaylovska A., Biggs C.M., Scuccimarri R., Withington D., Raul B.B., Ampuero C., Aravena J., Casanova D., Cruces P., Diaz F., Garcia-Salum T., Godoy L., Medina R.A., Galaz G.V., Avila-Aguero M.L., Brenes-Chacon H., Ivankovich-Escoto G., Yock-Corrales A., Badib A., Badreldin K., Elkhashab Y., Heshmat H., Heinonen S., Angoulvant F., Belot A., Ouldali N., Beske F., Heep A., Masjosthusmann K., Reiter K., Heuvel I.V.D., Both U.V., Agrafiotou A., Antachopoulos C., Eleftheriou I., Farmaki E., Fotis L., Kafetzis D., Lampidi S., Liakopoulou T., Maritsi D., Michailidou E., Milioudi M., Mparmpounaki I., Papadimitriou E., Papaevangelou V., Roilides E., Tsiatsiou O., Tsolas G., Tsolia M., Vantsi P., Pineda L.Y.B., Aguilar K.L.B., Quintero E.M.C., Ip P., Kwan M.Y.W., Kwok J., Lau Y.L., To K., Wong J.S.C., David M., Farkas D., Kalcakosz S., Szekeres K., Zsigmond B., Aslam N., Andreozzi L., Bianco F., Bucciarelli V., Buonsenso D., Cimaz R., D'Argenio P., Dellepiane R.M., Fabi M., Mastrolia M.V., Mauro A., Mazza A., Romani L., Simonini G., Tipo V., Valentini P., Verdoni L., Reel B., Pace D., Torpiano P., Flores M.F., Dominguez M.G., Vargas A.L.G., Hernandez L.L., Figueroa R.P.M., Gaxiola G.P., Valadez J., Klevberg S., Knudsen P.K., Maseide P.H., Carrera J.M., Castano E.G., Timana C.A.D., Leon T.D., Estripeaut D., Levy J., Norero X., Record J., Rojas-Bonilla M., Iramain R., Hernandez R., Huaman G., Munaico M., Peralta C., Seminario D., Yarleque E.H.Z., Gadzinska J., Mandziuk J., Okarska-Napierala M., Alacheva Z.A., Alexeeva E., Ananin P.V., Antsupova M., Bakradze M.D., Bobkova P., Borzakova S., Chashchina I.L., Fisenko A.P., Gautier M.S., Glazyrina A., Kondrikova E., Korobyants E., Korsunskiy A.A., Kovygina K., Krasnaya E., Kurbanova S., Kurdup M.K., Mamutova A.V., Mazankova L., Mitushin I.L., Nargizyan A., Orlova Y.O., Osmanov I.M., Polyakova A.S., Romanova O., Samitova E., Sologub A., Spiridonova E., Tepaev R.F., Tkacheva A.A., Yusupova V., Zholobova E., Grasa C.D., Segura N.L., Martinon-Torres F., Melendo S., Echevarria A.M., Guzman J.M.M., Argueta J.R.P., Rivero-Calle I., Riviere J., Rodriguez-Gonzalez M., Rojo P., Manubens J.S., Soler-Palacin P., Soriano-Arandes A., Tagarro A., Villaverde S., Altman M., Brodin P., Horne A., Palmblad K., Brotschi B., Sauteur P.M., Schmid J.P., Prader S., Relly C., Schlapbach L.J., Seiler M., Truck J., Wutz D., Ketharanathan N., Vermont C., Ozkan E.A., Erdeniz E.H., Borisova G., Boychenko L., Diudenko N., Kasiyan O., Katerynych K., Melnyk K., Miagka N., Teslenko M., Trykosh M., Volokha A., Akomolafe T., Al-Abadi E., Alders N., Avram P., Bamford A., Bank M., Roy R.B., Beattie T., Boleti O., Broad J., Carrol E.D., Chandran A., Cooper H., Davies P., Emonts M., Evans C., Fidler K., Foster C., Gong C., Gongrun B., Gonzalez C., Grandjean L., Grant K., Hacohen Y., Hall J., Hassell J., Hesketh C., Hewlett J., Hnieno A., Holt-Davis H., Hossain A., Hudson L.D., Johnson M., Johnson S., Jyothish D., Kampmann B., Kavirayani A., Kelly D., Kucera F., Langer D., Lillie J., Longbottom K., Lyall H., MacKdermott N., Maltby S., McLelland T., McMahon A.-M., Miller D., Morrison Z., Mosha K., Muller J., Myttaraki E., Nadel S., Osaghae D., Osman F., Ostrzewska A., Panthula M., Papachatzi E., Papadopoulou C., Penner J., Polandi S., Prendergast A.J., Ramnarayan P., Rhys-Evans S., Riordan A., Rodrigues C.M.C., Romaine S., Seddon J., Shingadia D., Srivastava A., Struik S., Taylor A., Tran S., Tudor-Williams G., Van Der Velden F., Ventilacion L., Wellman P.A., Yanney M.P., Yeung S., Badheka A., Badran S., Bailey D.M., Burch A.K., Burns J.C., Cichon C., Cirks B., Dallman M.D., Delany D.R., Fairchok M., Friedman S., Geracht J., Langs-Barlow A., Mann K., Padhye A., Quade A., Ramirez K.A., Rockett J., Sayed I.A., Shahin A.A., Umaru S., Widener R., Angela M.H., Kandawasvika G., Pediatric Surgery, Pediatrics, University of Zurich, National Institute of Health and Medical Research, Wellcome Trust, Medical Research Foundation, Shah, Priyen [0000-0001-9164-8862], Ulloa-Gutierrez, Rolando [0000-0002-9157-9227], Herberg, Jethro A [0000-0001-6941-6491], Cunnington, Aubrey J [0000-0002-1305-3529], Levin, Michael [0000-0003-2767-6919], and Apollo - University of Cambridge Repository

Subjects
Inotrope, Male, medicine.medical_treatment, 2700 General Medicine, 030204 cardiovascular system & hematology, Antibodies, Viral, Medical and Health Sciences, Cohort Studies, 0302 clinical medicine, Glucocorticoid, hemic and lymphatic diseases, Medicine and Health Sciences, 030212 general & internal medicine, Viral, Child, 11 Medical and Health Sciences, OUTCOMES, Respiration, Immunoglobulins, Intravenous, General Medicine, Systemic Inflammatory Response Syndrome, 3. Good health, Hospitalization, Treatment Outcome, Child, Preschool, Combination, Artificial, Regression Analysis, Drug Therapy, Combination, Female, Original Article, Intravenous, Life Sciences & Biomedicine, Cohort study, Human, medicine.medical_specialty, BATS Consortium, Adolescent, Immunoglobulins, 610 Medicine & health, Regression Analysi, Antibodies, Immunomodulation, 03 medical and health sciences, Medicine, General & Internal, Pharmacotherapy, Drug Therapy, Clinical Research, Internal medicine, General & Internal Medicine, medicine, MANAGEMENT, Confidence Intervals, Humans, Preschool, Propensity Score, Glucocorticoids, Mechanical ventilation, Science & Technology, business.industry, SARS-CoV-2, Inflammatory and immune system, COVID-19, Odds ratio, medicine.disease, Respiration, Artificial, Confidence interval, KAWASAKI-LIKE DISEASE, COVID-19 Drug Treatment, Systemic inflammatory response syndrome, 10036 Medical Clinic, Immunoglobulins, Intravenou, Propensity score matching, Cohort Studie, business, ACUTE RESPIRATORY SYNDROME, Confidence Interval, TOXIC-SHOCK-SYNDROME
Abstract

BackgroundEvidence is urgently needed to support treatment decisions for children with multisystem inflammatory syndrome (MIS-C) associated with severe acute respiratory syndrome coronavirus 2.MethodsWe performed an international observational cohort study of clinical and outcome data regarding suspected MIS-C that had been uploaded by physicians onto a Web-based database. We used inverse-probability weighting and generalized linear models to evaluate intravenous immune globulin (IVIG) as a reference, as compared with IVIG plus glucocorticoids and glucocorticoids alone. There were two primary outcomes: the first was a composite of inotropic support or mechanical ventilation by day 2 or later or death; the second was a reduction in disease severity on an ordinal scale by day 2. Secondary outcomes included treatment escalation and the time until a reduction in organ failure and inflammation.ResultsData were available regarding the course of treatment for 614 children from 32 countries from June 2020 through February 2021; 490 met the World Health Organization criteria for MIS-C. Of the 614 children with suspected MIS-C, 246 received primary treatment with IVIG alone, 208 with IVIG plus glucocorticoids, and 99 with glucocorticoids alone; 22 children received other treatment combinations, including biologic agents, and 39 received no immunomodulatory therapy. Receipt of inotropic or ventilatory support or death occurred in 56 patients who received IVIG plus glucocorticoids (adjusted odds ratio for the comparison with IVIG alone, 0.77; 95% confidence interval [CI], 0.33 to 1.82) and in 17 patients who received glucocorticoids alone (adjusted odds ratio, 0.54; 95% CI, 0.22 to 1.33). The adjusted odds ratios for a reduction in disease severity were similar in the two groups, as compared with IVIG alone (0.90 for IVIG plus glucocorticoids and 0.93 for glucocorticoids alone). The time until a reduction in disease severity was similar in the three groups.ConclusionsWe found no evidence that recovery from MIS-C differed after primary treatment with IVIG alone, IVIG plus glucocorticoids, or glucocorticoids alone, although significant differences may emerge as more data accrue. (Funded by the European Union's Horizon 2020 Program and others; BATS ISRCTN number, ISRCTN69546370.).

Published
2021

16. Increased risk of preeclampsia in women with a genetic predisposition to elevated blood pressure

Author

Kivioja, A. (Anna), Toivonen, E. (Elli), Tyrmi, J. (Jaakko), Ruotsalainen, S. (Sanni), Ripatti, S. (Samuli), Huhtala, H. (Heini), Jääskeläinen, T. (Tiina), Heinonen, S. (Seppo), Kajantie, E. (Eero), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Saarela, T. (Tanja), Laivuori, H. (Hannele), Kivioja, A. (Anna), Toivonen, E. (Elli), Tyrmi, J. (Jaakko), Ruotsalainen, S. (Sanni), Ripatti, S. (Samuli), Huhtala, H. (Heini), Jääskeläinen, T. (Tiina), Heinonen, S. (Seppo), Kajantie, E. (Eero), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Saarela, T. (Tanja), and Laivuori, H. (Hannele)

Abstract

Background: Preeclampsia causes significant maternal and perinatal morbidity. Genetic factors seem to affect the onset of the disease. We aimed to investigate whether the polygenic risk score for blood pressure (BP; BP-PRS) is associated with preeclampsia, its subtypes, and BP values during pregnancy. Methods: The analyses were performed in the FINNPEC study (Finnish Genetics of Pre-Eclampsia Consortium) cohort of 1514 preeclamptic and 983 control women. In a case-control setting, the data were divided into percentiles to compare women with high BP-PRS (HBP-PRS; >95th percentile) or low BP-PRS (≤5th percentile) to others. Furthermore, to evaluate the effect of BP-PRS on BP, we studied 3 cohorts: women with preeclampsia, hypertensive controls, and normotensive controls. Results: BP values were higher in women with HBP-PRS throughout the pregnancy. Preeclampsia was more common in women with HBP-PRS compared with others (71.8% and 60.1%, respectively; P=0.009), and women with low BP-PRS presented with preeclampsia less frequently than others (44.8% and 61.5%, respectively; P<0.001). HBP-PRS was associated with an increased risk for preeclampsia (odds ratio, 1.7 [95% CI, 1.1–2.5]). Furthermore, women with HBP-PRS presented with recurrent preeclampsia and preeclampsia with severe features more often. Conclusions: Our results suggest that HBP-PRS is associated with an increased risk of preeclampsia, recurrent preeclampsia, and preeclampsia with severe features. Furthermore, women with HBP-PRS present higher BP values during pregnancy. The results strengthen the evidence pointing toward the role of genetic variants associated with BP regulation in the etiology of preeclampsia, especially its more severe forms.

Published
2022

17. Characteristics of preeclampsia in donor cell gestations

Author

Ervaala, A. (Attina), Laivuori, H. (Hannele), Gissler, M. (Mika), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Kajantie, E. (Eero), Heinonen, S. (Seppo), Wedenoja, S. (Satu), Ervaala, A. (Attina), Laivuori, H. (Hannele), Gissler, M. (Mika), Kere, J. (Juha), Kivinen, K. (Katja), Pouta, A. (Anneli), Kajantie, E. (Eero), Heinonen, S. (Seppo), and Wedenoja, S. (Satu)

Abstract

Pregnancies conceived through donor oocytes or sperm show increased risk for preeclampsia. We studied this issue in a preeclampsia case-control cohort (n = 2778), and found overrepresentation of donor cell gestations among women with preeclampsia (14/1627, 0.86%; OR 1.81; 95% CI: 1.07–3.08; P = 0.025) compared to the population data. Moreover, we observed excess of male births from donor cell pregnancies (male-to-female ratio 2.5 vs. 0.97; OR 2.57; 95% CI 1.02–6.36; P = 0.043). Maternal age (36.7 vs. 30.2; P < 0.0001) and preterm deliveries (64% vs. 38%; P = 0.046) distinguished donor cell gestations from other pregnancies with preeclampsia. These results support foreign fetal antigens as modulators of preeclampsia.

Published
2022

18. Reflection image beyond the known extent of the prospective zone provided by 3D virtual-source methodology

Author

Chamarczuk, M. (author), Draganov, D.S. (author), Malinowski, M. (author), Koivisto, E. (author), Heinonen, S. (author), Rötsä, S. (author), Chamarczuk, M. (author), Draganov, D.S. (author), Malinowski, M. (author), Koivisto, E. (author), Heinonen, S. (author), and Rötsä, S. (author)

Abstract

We apply a full-scale 3D seismic virtual-source survey (VSS) for the purpose of near-mine mineral exploration in the Kylylahti sulfide deposit, Finland. Based on the ambient-noise (AN) characterization including beamforming results, we created a 10-days subset of AN recordings that were dominated by multi-azimuth high-velocity arrivals. We use an illumination-diagnosis and location procedure to show that the AN recordings associated with the high apparent velocities are related to body-wave events. Next, we produce 994 virtual-source gathers by applying seismic-interferometry processing by crosscorrelating AN at all receivers resulting in a full 3D VSS. We apply standard 3D time-domain reflectiondata processing and imaging using the subset and the full AN data, and validate both results against a pre-existing detailed geological information and 3D active-source data processed in the same way as the passive data. The resulting post-stack migrated sections show agreement of reflections between the passive and active data and indicate that VSS provides images where the active-source data are not available. In particular, the previously unknown extent of the ore-bearing complex was captured exclusively by passive data, which added a new geological insight into the Kylylahti formation. The methodological approach developed can be used in other areas in mineral exploration context., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Applied Geophysics and Petrophysics

Published
2022
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27. External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications ( <scp>IPPIC</scp> ) Network database: individual participant data meta‐analysis

Author

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

Published
2021

29. Treatment of Multisystem Inflammatory Syndrome in Children

Author

McArdle, A.J. Vito, O. Patel, H. Seaby, E.G. Shah, P. Wilson, C. Broderick, C. Nijman, R. Tremoulet, A.H. Munblit, D. Ulloa-Gutierrez, R. Carter, M.J. De, T. Hoggart, C. Whittaker, E. Herberg, J.A. Kaforou, M. Cunnington, A.J. Levin, M. Vazquez, J.A. Carmona, R. Perez, L. Rubinos, M. Veliz, N. Yori, S. Haerynck, F. Hoste, L. Leal, I.A. Da Silva, A.R.A. Silva, A.E.A. Barchik, A. Barreiro, S.T.A. Cochrane, N. Teixeira, C.H. Arauj, J.M. Ossa, R.A.P.-D.L. Vieira, C.S. Dimitrova, A. Ganeva, M. Stefanov, S. Telcharova-Mihaylovska, A. Biggs, C.M. Scuccimarri, R. Withington, D. Raul, B.B. Ampuero, C. Aravena, J. Casanova, D. Cruces, P. Diaz, F. Garcia-Salum, T. Godoy, L. Medina, R.A. Galaz, G.V. Avila-Aguero, M.L. Brenes-Chacon, H. Ivankovich-Escoto, G. Yock-Corrales, A. Badib, A. Badreldin, K. Elkhashab, Y. Heshmat, H. Heinonen, S. Angoulvant, F. Belot, A. Ouldali, N. Beske, F. Heep, A. Masjosthusmann, K. Reiter, K. Heuvel, I.V.D. Both, U.V. Agrafiotou, A. Antachopoulos, C. Eleftheriou, I. Farmaki, E. Fotis, L. Kafetzis, D. Lampidi, S. Liakopoulou, T. Maritsi, D. Michailidou, E. Milioudi, M. Mparmpounaki, I. Papadimitriou, E. Papaevangelou, V. Roilides, E. Tsiatsiou, O. Tsolas, G. Tsolia, M. Vantsi, P. Pineda, L.Y.B. Aguilar, K.L.B. Quintero, E.M.C. Ip, P. Kwan, M.Y.W. Kwok, J. Lau, Y.L. To, K. Wong, J.S.C. David, M. Farkas, D. Kalcakosz, S. Szekeres, K. Zsigmond, B. Aslam, N. Andreozzi, L. Bianco, F. Bucciarelli, V. Buonsenso, D. Cimaz, R. D'Argenio, P. Dellepiane, R.M. Fabi, M. Mastrolia, M.V. Mauro, A. Mazza, A. Romani, L. Simonini, G. Tipo, V. Valentini, P. Verdoni, L. Reel, B. Pace, D. Torpiano, P. Flores, M.F. Domínguez, M.G. Vargas, A.L.G. Hernandez, L.L. Figueroa, R.P.M. Gaxiola, G.P. Valadez, J. Klevberg, S. Knudsen, P.K. Maseide, P.H. Carrera, J.M. Castano, E.G. Timana, C.A.D. Leon, T.D. Estripeaut, D. Levy, J. Norero, X. Record, J. Rojas-Bonilla, M. Iramain, R. Hernandez, R. Huaman, G. Munaico, M. Peralta, C. Seminario, D. Yarleque, E.H.Z. Gadzinska, J. Mandziuk, J. Okarska-Napierała, M. Alacheva, Z.A. Alexeeva, E. Ananin, P.V. Antsupova, M. Bakradze, M.D. Bobkova, P. Borzakova, S. Chashchina, I.L. Fisenko, A.P. Gautier, M.S. Glazyrina, A. Kondrikova, E. Korobyants, E. Korsunskiy, A.A. Kovygina, K. Krasnaya, E. Kurbanova, S. Kurdup, M.K. Mamutova, A.V. Mazankova, L. Mitushin, I.L. Nargizyan, A. Orlova, Y.O. Osmanov, I.M. Polyakova, A.S. Romanova, O. Samitova, E. Sologub, A. Spiridonova, E. Tepaev, R.F. Tkacheva, A.A. Yusupova, V. Zholobova, E. Grasa, C.D. Segura, N.L. Martinon-Torres, F. Melendo, S. Echevarria, A.M. Guzman, J.M.M. Argueta, J.R.P. Rivero-Calle, I. Riviere, J. Rodriguez-Gonzalez, M. Rojo, P. Manubens, J.S. Soler-Palacin, P. Soriano-Arandes, A. Tagarro, A. Villaverde, S. Altman, M. Brodin, P. Horne, A. Palmblad, K. Brotschi, B. Sauteur, P.M. Schmid, J.P. Prader, S. Relly, C. Schlapbach, L.J. Seiler, M. Truck, J. Wutz, D. Ketharanathan, N. Vermont, C. Ozkan, E.A. Erdeniz, E.H. Borisova, G. Boychenko, L. Diudenko, N. Kasiyan, O. Katerynych, K. Melnyk, K. Miagka, N. Teslenko, M. Trykosh, M. Volokha, A. Akomolafe, T. Al-Abadi, E. Alders, N. Avram, P. Bamford, A. Bank, M. Roy, R.B. Beattie, T. Boleti, O. Broad, J. Carrol, E.D. Chandran, A. Cooper, H. Davies, P. Emonts, M. Evans, C. Fidler, K. Foster, C. Gong, C. Gongrun, B. Gonzalez, C. Grandjean, L. Grant, K. Hacohen, Y. Hall, J. Hassell, J. Hesketh, C. Hewlett, J. Hnieno, A. Holt-Davis, H. Hossain, A. Hudson, L.D. Johnson, M. Johnson, S. Jyothish, D. Kampmann, B. Kavirayani, A. Kelly, D. Kucera, F. Langer, D. Lillie, J. Longbottom, K. Lyall, H. MacKdermott, N. Maltby, S. McLelland, T. McMahon, A.-M. Miller, D. Morrison, Z. Mosha, K. Muller, J. Myttaraki, E. Nadel, S. Osaghae, D. Osman, F. Ostrzewska, A. Panthula, M. Papachatzi, E. Papadopoulou, C. Penner, J. Polandi, S. Prendergast, A.J. Ramnarayan, P. Rhys-Evans, S. Riordan, A. Rodrigues, C.M.C. Romaine, S. Seddon, J. Shingadia, D. Srivastava, A. Struik, S. Taylor, A. Taylor, A. Taylor, A. Tran, S. Tudor-Williams, G. Van Der Velden, F. Ventilacion, L. Wellman, P.A. Yanney, M.P. Yeung, S. Badheka, A. Badran, S. Bailey, D.M. Burch, A.K. Burns, J.C. Cichon, C. Cirks, B. Dallman, M.D. Delany, D.R. Fairchok, M. Friedman, S. Geracht, J. Langs-Barlow, A. Mann, K. Padhye, A. Quade, A. Ramirez, K.A. Rockett, J. Sayed, I.A. Shahin, A.A. Umaru, S. Widener, R. Angela, M.H. Kandawasvika, G. BATS Consortium

Subjects
hemic and lymphatic diseases
Abstract

BACKGROUND Evidence is urgently needed to support treatment decisions for children with multisystem inflammatory syndrome (MIS-C) associated with severe acute respiratory syndrome coronavirus 2. METHODS We performed an international observational cohort study of clinical and outcome data regarding suspected MIS-C that had been uploaded by physicians onto a Web-based database. We used inverse-probability weighting and generalized linear models to evaluate intravenous immune globulin (IVIG) as a reference, as compared with IVIG plus glucocorticoids and glucocorticoids alone. There were two primary outcomes: the first was a composite of inotropic support or mechanical ventilation by day 2 or later or death; the second was a reduction in disease severity on an ordinal scale by day 2. Secondary outcomes included treatment escalation and the time until a reduction in organ failure and inflammation. RESULTS Data were available regarding the course of treatment for 614 children from 32 countries from June 2020 through February 2021; 490 met the World Health Organization criteria for MIS-C. Of the 614 children with suspected MIS-C, 246 received primary treatment with IVIG alone, 208 with IVIG plus glucocorticoids, and 99 with glucocorticoids alone; 22 children received other treatment combinations, including biologic agents, and 39 received no immunomodulatory therapy. Receipt of inotropic or ventilatory support or death occurred in 56 patients who received IVIG plus glucocorticoids (adjusted odds ratio for the comparison with IVIG alone, 0.77; 95% confidence interval [CI], 0.33 to 1.82) and in 17 patients who received glucocorticoids alone (adjusted odds ratio, 0.54; 95% CI, 0.22 to 1.33). The adjusted odds ratios for a reduction in disease severity were similar in the two groups, as compared with IVIG alone (0.90 for IVIG plus glucocorticoids and 0.93 for glucocorticoids alone). The time until a reduction in disease severity was similar in the three groups. CONCLUSIONS We found no evidence that recovery from MIS-C differed after primary treatment with IVIG alone, IVIG plus glucocorticoids, or glucocorticoids alone, although significant differences may emerge as more data accrue. Copyright © 2021 Massachusetts Medical Society.

Published
2021

30. A non-targeted LC–MS metabolic profiling of pregnancy:longitudinal evidence from healthy and pre-eclamptic pregnancies

Author

Jääskeläinen, T. (Tiina), Kärkkäinen, O. (Olli), Jokkala, J. (Jenna), Klåvus, A. (Anton), Heinonen, S. (Seppo), Auriola, S. (Seppo), Lehtonen, M. (Marko), T. F. (The FINNPEC Core Investigator Group), Hanhineva, K. (Kati), and Laivuori, H. (Hannele)

Subjects
Pregnancy, Metabolomics, Preeclampsia, LC–MS, humanities
Abstract

Introduction: Maternal metabolism changes substantially during pregnancy. However, few studies have used metabolomics technologies to characterize changes across gestation. Objectives and methods: We applied liquid chromatography–mass spectrometry (LC–MS) based non-targeted metabolomics to determine whether the metabolic profile of serum differs throughout the pregnancy between pre-eclamptic and healthy women in the FINNPEC (Finnish Genetics of Preeclampsia Consortium) Study. Serum samples were available from early and late pregnancy. Results: Progression of pregnancy had large-scale effects to the serum metabolite profile. Altogether 50 identified metabolites increased and 49 metabolites decreased when samples of early pregnancy were compared to samples of late pregnancy. The metabolic signatures of pregnancy were largely shared in pre-eclamptic and healthy women, only urea, monoacylglyceride 18:1 and glycerophosphocholine were identified to be increased in the pre-eclamptic women when compared to healthy controls. Conclusions: Our study highlights the need of large-scale longitudinal metabolomic studies in non-complicated pregnancies before more detailed understanding of metabolism in adverse outcomes could be provided. Our findings are one of the first steps for a broader metabolic understanding of the physiological changes caused by pregnancy per se. Collaborators for The FINNPEC Core Investigator Group Eero Kajantie (Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland; Children’s Hospital, Helsinki University Hospital and University of Helsinki, Helsinki, Finland; PEDEGO Research Unit, MRC Oulu, Oulu University Hospital and University of Oulu, Oulu, Finland). Juha Kere (Department of Biosciences and Nutrition, and Science for Life Laboratory, Karolinska Institutet, Stockholm, Sweden; Molecular Neurology Research Program, University of Helsinki, Helsinki, Finland; Folkhälsan Institute of Genetics, Helsinki, Finland), Katja Kivinen (Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland), Anneli Pouta (Department of Government Services, National Institute for Health and Welfare, Helsinki, Finland).

Published
2021

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

Author

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

Published
2021

32. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: An individual participant data meta-analysis.

Author

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

Published
2021

33. Near-surface structure of the Sodankylä area in Finland, obtained by passive seismic interferometry

Author

Afonin, N. (Nikita), Kozlovskaya, E. (Elena), Heinonen, S. (Suvi), Buske, S. (Stefan), Afonin, N. (Nikita), Kozlovskaya, E. (Elena), Heinonen, S. (Suvi), and Buske, S. (Stefan)

Abstract

Controlled-source seismic exploration surveys are not always possible in nature-protected areas. As an alternative, the application of passive seismic techniques in such areas can be proposed. In our study, we show results of passive seismic interferometry application for mapping the uppermost crust in the area of active mineral exploration in northern Finland. We utilize continuous seismic data acquired by the Sercel Unite wireless multichannel recording system along several profiles during XSoDEx (eXperiment of SOdankylä Deep Exploration) multidisciplinary geophysical project. The objective of XSoDEx was to obtain a structural image of the upper crust in the Sodankylä area of northern Finland in order to achieve a better understanding of the mineral system at depth. The key experiment of the project was a high-resolution seismic reflection experiment. In addition, continuous passive seismic data were acquired in parallel with reflection seismic data acquisition. Due to this, the length of passive data suitable for noise cross-correlation was limited from several hours to a couple of days. Analysis of the passive data demonstrated that dominating sources of ambient noise are non-stationary and have different origins across the XSoDEx study area. As the long data registration period and isotropic azimuthal distribution of noise sources are two major conditions for empirical Green function (EGF) extraction under the diffuse field approximation assumption, it was not possible to apply the conventional techniques of passive seismic interferometry. To find the way to obtain EGFs, we used numerical modelling in order to investigate properties of seismic noise originating from sources with different characteristics and propagating inside synthetic heterogeneous Earth models representing real geological conditions in the XSoDEx study area. The modelling demonstrated that scattering of ballistic waves on irregular shape heterogeneities, such as massive sulfides or

Published
2021

40. Genetic predisposition to hypertension is associated with preeclampsia in European and Central Asian women

Author

Steinthorsdottir, V. (Valgerdur), McGinnis, R. (Ralph), Williams, N. O. (Nicholas O.), Stefansdottir, L. (Lilja), Thorleifsson, G. (Gudmar), Shooter, S. (Scott), Fadista, J. (Joao), Sigurdsson, J. K. (Jon K.), Auro, K. M. (Kirsi M.), Berezina, G. (Galina), Borges, M.-C. (Maria-Carolina), Bumpstead, S. (Suzannah), Bybjerg-Grauholm, J. (Jonas), Colgiu, I. (Irina), Dolby, V. A. (Vivien A.), Dudbridge, F. (Frank), Engel, S. M. (Stephanie M.), Franklin, C. S. (Christopher S.), Frigge, M. L. (Michael L.), Frisbaek, Y. (Yr), Geirsson, R. T. (Reynir T.), Geller, F. (Frank), Gretarsdottir, S. (Solveig), Gudbjartsson, D. F. (Daniel F.), Harmon, Q. (Quaker), Hougaard, D. M. (David Michael), Hegay, T. (Tatyana), Helgadottir, A. (Anna), Hjartardottir, S. (Sigrun), Jaeaeskelaeinen, T. (Tiina), Johannsdottir, H. (Hrefna), Jonsdottir, I. (Ingileif), Juliusdottir, T. (Thorhildur), Kalsheker, N. (Noor), Kasimov, A. (Abdumadjit), Kemp, J. P. (John P.), Kivinen, K. (Katja), Klungsoyr, K. (Kari), Lee, W. K. (Wai K.), Melbye, M. (Mads), Miedzybrodska, Z. (Zosia), Moffett, A. (Ashley), Najmutdinova, D. (Dilbar), Nishanova, F. (Firuza), Olafsdottir, T. (Thorunn), Perola, M. (Markus), Pipkin, F. B. (Fiona Broughton), Poston, L. (Lucilla), Prescott, G. (Gordon), Saevarsdottir, S. (Saedis), Salimbayeva, D. (Damilya), Scaife, P. J. (Paula Juliet), Skotte, L. (Line), Staines-Urias, E. (Eleonora), Stefansson, O. A. (Olafur A.), Sorensen, K. M. (Karina Meden), Thomsen, L. C. (Liv Cecilie Vestrheim), Tragante, V. (Vinicius), Trogstad, L. (Lill), Simpson, N. A. (Nigel A. B.), Laivuori, H. (Hannele), Morgan, L. (Linda), Aripova, T. (Tamara), Casas, J. P. (Juan P.), Dominiczak, A. F. (Anna F.), Walker, J. J. (James J.), Thorsteinsdottir, U. (Unnur), Iversen, A.-C. (Ann-Charlotte), Feenstra, B. (Bjarke), Lawlor, D. A. (Deborah A.), Boyd, H. A. (Heather Allison), Magnus, P. (Per), Zakhidova, N. (Nodira), Svyatova, G. (Gulnara), Stefansson, K. (Kari), Heinonen, S. (Seppo), Kajantie, E. (Eero), Kere, J. (Juha), Pouta, A. (Anneli), Macphail, S. (Sheila), Kilby, M. (Mark), Habiba, M. (Marwan), Williamson, C. (Catherine), O'Shaughnessy, K. (Kevin), O'Brien, S. (Shaughn), Cameron, A. (Alan), Redman, C. W. (Christopher W. G.), Farrall, M. (Martin), and Caulfield, M. (Mark)

Subjects
embryonic structures, reproductive and urinary physiology, female genital diseases and pregnancy complications
Abstract

Preeclampsia is a serious complication of pregnancy, affecting both maternal and fetal health. In genome-wide association meta-analysis of European and Central Asian mothers, we identify sequence variants that associate with preeclampsia in the maternal genome at ZNF831/20q13 and FTO/16q12. These are previously established variants for blood pressure (BP) and the FTO variant has also been associated with body mass index (BMI). Further analysis of BP variants establishes that variants at MECOM/3q26, FGF5/4q21 and SH2B3/12q24 also associate with preeclampsia through the maternal genome. We further show that a polygenic risk score for hypertension associates with preeclampsia. However, comparison with gestational hypertension indicates that additional factors modify the risk of preeclampsia. Studies to identify maternal variants associated with preeclampsia have been limited by sample size. Here, the authors meta-analyze eight GWAS of 9,515 preeclamptic women, identifying five variants associated with preeclampsia and showing that genetic predisposition to hypertension is a major risk factor for preeclampsia.

Published
2020

41. Validation and development of models using clinical, biochemical and ultrasound markers for predicting pre-eclampsia: An individual participant data meta-analysis

Author

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

43. Fetal HLA-G mediated immune tolerance and interferon response in preeclampsia

Author

Wedenoja, S. (Satu), Yoshihara, M. (Masahito), Teder, H. (Hindrek), Sariola, H. (Hannu), Gissler, M. (Mika), Katayama, S. (Shintaro), Wedenoja, J. (Juho), Häkkinen, I. M. (Inka M.), Ezer, S. (Sini), Linder, N. (Nina), Lundin, J. (Johan), Skoog, T. (Tiina), Sahlin, E. (Ellika), Iwarsson, E. (Erik), Pettersson, K. (Karin), Kajantie, E. (Eero), Mokkonen, M. (Mikael), Heinonen, S. (Seppo), Laivuori, H. (Hannele), Krjutškov, K. (Kaarel), Kere, J. (Juha), Wedenoja, S. (Satu), Yoshihara, M. (Masahito), Teder, H. (Hindrek), Sariola, H. (Hannu), Gissler, M. (Mika), Katayama, S. (Shintaro), Wedenoja, J. (Juho), Häkkinen, I. M. (Inka M.), Ezer, S. (Sini), Linder, N. (Nina), Lundin, J. (Johan), Skoog, T. (Tiina), Sahlin, E. (Ellika), Iwarsson, E. (Erik), Pettersson, K. (Karin), Kajantie, E. (Eero), Mokkonen, M. (Mikael), Heinonen, S. (Seppo), Laivuori, H. (Hannele), Krjutškov, K. (Kaarel), and Kere, J. (Juha)

Abstract

Background: Fetal immune tolerance is crucial for pregnancy success. We studied the link between preeclampsia, a severe pregnancy disorder with uncertain pathogenesis, and fetal human leukocyte antigen G (HLA-G) and other genes regulating maternal immune responses. Methods: We assessed sex ratios and regulatory HLA-G haplotypes in population cohorts and series of preeclampsia and stillbirth. We studied placental mRNA expression of 136 genes by sequencing and HLA-G and interferon alpha (IFNα) protein expression by immunohistochemistry. Findings: We found underrepresentation of males in preeclamptic births, especially those delivered preterm or small for gestational age. Balancing selection at HLA-G associated with the sex ratio, stillbirth, and preeclampsia. We observed downregulation of HLA-G, its receptors, and many other tolerogenic genes, and marked upregulation of IFNA1 in preeclamptic placentas. Interpretation: These findings indicate that an evolutionary trade-off between immune tolerance and protection against infections at the maternal-fetal interface promotes genetic diversity in fetal HLA-G, thereby affecting survival, preeclampsia, and sex ratio. We highlight IFNA1 as a potential mediator of preeclampsia and a target for therapeutic trials.

Published
2020

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

Author

Snell, KIE, Allotey, J, Smuk, M, Hooper, R, Chan, C, Ahmed, A, Chappell, LC, Von Dadelszen, P, Green, M, Kenny, L, Khalil, A, Khan, KS, Mol, BW, Myers, J, Poston, L, Thilaganathan, B, Staff, AC, Smith, GCS, Ganzevoort, W, Laivuori, H, Odibo, AO, Arenas Ramírez, J, Kingdom, J, Daskalakis, G, Farrar, D, Baschat, AA, Seed, PT, Prefumo, F, da Silva Costa, F, Groen, H, Audibert, F, Masse, J, Skråstad, RB, Salvesen, KÅ, Haavaldsen, C, Nagata, C, Rumbold, AR, Heinonen, S, Askie, LM, Smits, LJM, Vinter, CA, Magnus, P, Eero, K, Villa, PM, Jenum, AK, Andersen, LB, Norman, JE, Ohkuchi, A, Eskild, A, Bhattacharya, S, McAuliffe, FM, Galindo, A, Herraiz, I, Carbillon, L, Klipstein-Grobusch, K, Yeo, SA, Browne, JL, Moons, KGM, Riley, RD, Thangaratinam, S, IPPIC Collaborative Network, Snell, KIE, Allotey, J, Smuk, M, Hooper, R, Chan, C, Ahmed, A, Chappell, LC, Von Dadelszen, P, Green, M, Kenny, L, Khalil, A, Khan, KS, Mol, BW, Myers, J, Poston, L, Thilaganathan, B, Staff, AC, Smith, GCS, Ganzevoort, W, Laivuori, H, Odibo, AO, Arenas Ramírez, J, Kingdom, J, Daskalakis, G, Farrar, D, Baschat, AA, Seed, PT, Prefumo, F, da Silva Costa, F, Groen, H, Audibert, F, Masse, J, Skråstad, RB, Salvesen, KÅ, Haavaldsen, C, Nagata, C, Rumbold, AR, Heinonen, S, Askie, LM, Smits, LJM, Vinter, CA, Magnus, P, Eero, K, Villa, PM, Jenum, AK, Andersen, LB, Norman, JE, Ohkuchi, A, Eskild, A, Bhattacharya, S, McAuliffe, FM, Galindo, A, Herraiz, I, Carbillon, L, Klipstein-Grobusch, K, Yeo, SA, Browne, JL, Moons, KGM, Riley, RD, Thangaratinam, S, and IPPIC Collaborative Network

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

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