Cargando…
Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models
BACKGROUND: Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. METHOD: Women with confirmed early onset pre-eclampsia were recruited from 53...
Autores principales: | , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372261/ https://www.ncbi.nlm.nih.gov/pubmed/28356148 http://dx.doi.org/10.1186/s12916-017-0827-3 |
_version_ | 1782518580058783744 |
---|---|
author | Thangaratinam, Shakila Allotey, John Marlin, Nadine Dodds, Julie Cheong-See, Fiona von Dadelszen, Peter Ganzevoort, Wessel Akkermans, Joost Kerry, Sally Mol, Ben W. Moons, Karl G. M. Riley, Richard D. Khan, Khalid S. |
author_facet | Thangaratinam, Shakila Allotey, John Marlin, Nadine Dodds, Julie Cheong-See, Fiona von Dadelszen, Peter Ganzevoort, Wessel Akkermans, Joost Kerry, Sally Mol, Ben W. Moons, Karl G. M. Riley, Richard D. Khan, Khalid S. |
author_sort | Thangaratinam, Shakila |
collection | PubMed |
description | BACKGROUND: Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. METHOD: Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. RESULTS: A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81–0.87; PREP-S) and 0.82 (0.80–0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. CONCLUSIONS: PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care. TRIAL REGISTRATION: ISRCTN40384046, retrospectively registered. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-017-0827-3) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5372261 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-53722612017-03-30 Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models Thangaratinam, Shakila Allotey, John Marlin, Nadine Dodds, Julie Cheong-See, Fiona von Dadelszen, Peter Ganzevoort, Wessel Akkermans, Joost Kerry, Sally Mol, Ben W. Moons, Karl G. M. Riley, Richard D. Khan, Khalid S. BMC Med Research Article BACKGROUND: Unexpected clinical deterioration before 34 weeks gestation is an undesired course in early-onset pre-eclampsia. To safely prolong preterm gestation, accurate and timely prediction of complications is required. METHOD: Women with confirmed early onset pre-eclampsia were recruited from 53 maternity units in the UK to a large prospective cohort study (PREP-946) for development of prognostic models for the overall risk of experiencing a complication using logistic regression (PREP-L), and for predicting the time to adverse maternal outcome using a survival model (PREP-S). External validation of the models were carried out in a multinational cohort (PIERS-634) and another cohort from the Netherlands (PETRA-216). Main outcome measures were C-statistics to summarise discrimination of the models and calibration plots and calibration slopes. RESULTS: A total of 169 mothers (18%) in the PREP dataset had adverse outcomes by 48 hours, and 633 (67%) by discharge. The C-statistics of the models for predicting complications by 48 hours and by discharge were 0.84 (95% CI, 0.81–0.87; PREP-S) and 0.82 (0.80–0.84; PREP-L), respectively. The PREP-S model included maternal age, gestation, medical history, systolic blood pressure, deep tendon reflexes, urine protein creatinine ratio, platelets, serum alanine amino transaminase, urea, creatinine, oxygen saturation and treatment with antihypertensives or magnesium sulfate. The PREP-L model included the above except deep tendon reflexes, serum alanine amino transaminase and creatinine. On validation in the external PIERS dataset, the reduced PREP-S model showed reasonable calibration (slope 0.80) and discrimination (C-statistic 0.75) for predicting adverse outcome by 48 hours. Reduced PREP-L model showed excellent calibration (slope: 0.93 PIERS, 0.90 PETRA) and discrimination (0.81 PIERS, 0.75 PETRA) for predicting risk by discharge in the two external datasets. CONCLUSIONS: PREP models can be used to obtain predictions of adverse maternal outcome risk, including early preterm delivery, by 48 hours (PREP-S) and by discharge (PREP-L), in women with early onset pre-eclampsia in the context of current care. They have a potential role in triaging high-risk mothers who may need transfer to tertiary units for intensive maternal and neonatal care. TRIAL REGISTRATION: ISRCTN40384046, retrospectively registered. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12916-017-0827-3) contains supplementary material, which is available to authorized users. BioMed Central 2017-03-30 /pmc/articles/PMC5372261/ /pubmed/28356148 http://dx.doi.org/10.1186/s12916-017-0827-3 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Thangaratinam, Shakila Allotey, John Marlin, Nadine Dodds, Julie Cheong-See, Fiona von Dadelszen, Peter Ganzevoort, Wessel Akkermans, Joost Kerry, Sally Mol, Ben W. Moons, Karl G. M. Riley, Richard D. Khan, Khalid S. Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models |
title | Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models |
title_full | Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models |
title_fullStr | Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models |
title_full_unstemmed | Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models |
title_short | Prediction of complications in early-onset pre-eclampsia (PREP): development and external multinational validation of prognostic models |
title_sort | prediction of complications in early-onset pre-eclampsia (prep): development and external multinational validation of prognostic models |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5372261/ https://www.ncbi.nlm.nih.gov/pubmed/28356148 http://dx.doi.org/10.1186/s12916-017-0827-3 |
work_keys_str_mv | AT thangaratinamshakila predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT alloteyjohn predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT marlinnadine predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT doddsjulie predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT cheongseefiona predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT vondadelszenpeter predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT ganzevoortwessel predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT akkermansjoost predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT kerrysally predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT molbenw predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT moonskarlgm predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT rileyrichardd predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT khankhalids predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels AT predictionofcomplicationsinearlyonsetpreeclampsiaprepdevelopmentandexternalmultinationalvalidationofprognosticmodels |