Výsledky vyhledávání - "Thangaratinam, S."

Epidemiology of pre-existing multimorbidity in pregnant women in the UK in 2018: a population-based cross-sectional study

Publikováno v: BMC Pregnancy and Childbirth, Vol 22, Iss 1, Pp 1-15 (2022)
MuM-PreDiCT Group 2022, ' Epidemiology of pre-existing multimorbidity in pregnant women in the UK in 2018 : a population-based cross-sectional study ', BMC Pregnancy and Childbirth, vol. 22, no. 1, 120 . https://doi.org/10.1186/s12884-022-04442-3
MuM-PreDiCT Group 2022, ' Epidemiology of pre-existing multimorbidity in pregnant women in the UK in 2018: a population-based cross-sectional study ', BMC Pregnancy and Childbirth, vol. 22, no. 1, 120 . https://doi.org/10.1186/s12884-022-04442-3
BMC Pregnancy and Childbirth
BMC Pregnancy and Childbirth, 2022, 22 (1), pp.120. ⟨10.1186/s12884-022-04442-3⟩

Background Although maternal death is rare in the United Kingdom, 90% of these women had multiple health/social problems. This study aims to estimate the prevalence of pre-existing multimorbidity (two or more long-term physical or mental health condi

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6ab5048ad92dea03c44f01e9dc40f44d
https://doaj.org/article/25f231e5d3254eb2a3d71bca5da07e43

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

Autor: 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.

Publikováno v: IPPIC Collaborative Network & Mone, F 2021, ' External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database: an individual participant data meta-analysis ', Ultrasound in Obstetrics and Gynecology . https://doi.org/10.1002/uog.23757
Ultrasound in obstetrics & gynecology, 59(2), 209-219. John Wiley and Sons Ltd
the IPPIC Collaborative Network 2022, ' External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database : individual participant data meta-analysis ', Ultrasound in Obstetrics and Gynecology, vol. 59, no. 2, pp. 209-219 . https://doi.org/10.1002/uog.23757
Ultrasound in Obstetrics and Gynecology, 59(2), 209-219. John Wiley and Sons Ltd
IPPIC Collaborative Network 2021, ' External validation of prognostic models to predict stillbirth using the International Prediction of Pregnancy Complications (IPPIC) Network database : an individual participant data meta-analysis ', Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology . https://doi.org/10.1002/uog.23757
2022, ' External validation of prognostic models to predict stillbirth using International Prediction of Pregnancy Complications (IPPIC) Network database : individual participant data meta-analysis ', Ultrasound in Obstetrics and Gynecology, vol. 59, no. 2, pp. 209-219 . https://doi.org/10.1002/uog.23757

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 model

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7afa3ce05a1ae96f7fce48ed60d2e6e3
https://hdl.handle.net/11380/1279718

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