Literature DB >> 24575790

Prediction of postpartum hemorrhage in women with gestational hypertension or mild preeclampsia at term.

Corine M Koopmans1, Karin van der Tuuk, Henk Groen, Johannes P R Doornbos, Irene M de Graaf, Pauline C M van der Salm, Martina M Porath, Simone M I Kuppens, Ella J Wijnen, Robert Aardenburg, Aren J van Loon, Bettina M C Akerboom, Peggy J A van der Lans, Ben W J Mol, Maria G van Pampus.   

Abstract

OBJECTIVE: To assess whether postpartum hemorrhage can be predicted in women with gestational hypertension or mild preeclampsia at term.
DESIGN: A cohort study in which we used data from our multicentre randomized controlled trial (HYPITAT trial).
SETTING: The study was conducted in 38 hospitals in the Netherlands between 2005 and 2008. POPULATION: Women with gestational hypertension or mild preeclampsia at term (n = 1132).
METHODS: An antepartum model (model A) and an antepartum/intrapartum model (model B) were created using logistic regression. The predictive capacity of the models was assessed with receiver operating characteristic analysis and calibration. MAIN OUTCOME MEASURE: Postpartum hemorrhage, defined as blood loss >1000 mL within 24 h after delivery.
RESULTS: Postpartum hemorrhage occurred in 118 (10.4%) women. Maternal age (odds ratio 1.03), prepregnancy body mass index (odds ratio 0.96), and women with preeclampsia (odds ratio 1.5) were independent antepartum prognostic variables of postpartum hemorrhage. Intrapartum variables incorporated in the model were gestational age at delivery (odds ratio 1.2), duration of dilatation stage (odds ratio 1.1), and episiotomy (odds ratio 1.5). Model A and model B showed moderate discrimination, with areas under the receiver operating characteristic curve of 0.59 (95% confidence interval 0.53-0.64) and 0.64 (95% confidence interval 0.59-0.70), respectively. Calibration was moderate for model A (Hosmer-Lemeshow p = 0.26) but better for model B (Hosmer-Lemeshow p = 0.36). The rates of postpartum hemorrhage ranged from 4% (lowest 10%) to 22% (highest 10%).
CONCLUSION: In the assessment of performance of a prediction model, calibration is more important than discriminative capacity. Our prediction model shows that for women with gestational hypertension or mild preeclampsia at term, distinction between low and high risk of developing postpartum hemorrhage is possible when antepartum and intrapartum variables are combined.
© 2014 Nordic Federation of Societies of Obstetrics and Gynecology.

Entities:  

Keywords:  Preeclampsia; calibration; gestational hypertension; predictive value; prognostic model; receiver-operating characteristic curve analysis

Mesh:

Year:  2014        PMID: 24575790     DOI: 10.1111/aogs.12352

Source DB:  PubMed          Journal:  Acta Obstet Gynecol Scand        ISSN: 0001-6349            Impact factor:   3.636


  9 in total

1.  A novel oppositional binary crow search algorithm with optimal machine learning based postpartum hemorrhage prediction model.

Authors:  Sujatha Krishnamoorthy; Yihang Liu; Kun Liu
Journal:  BMC Pregnancy Childbirth       Date:  2022-07-13       Impact factor: 3.105

2.  Cost-effectiveness Analysis of Intraoperative Cell Salvage for Obstetric Hemorrhage.

Authors:  Grace Lim; Vladyslav Melnyk; Francesca L Facco; Jonathan H Waters; Kenneth J Smith
Journal:  Anesthesiology       Date:  2018-02       Impact factor: 7.892

3.  Machine Learning and Statistical Models to Predict Postpartum Hemorrhage.

Authors:  Kartik K Venkatesh; Robert A Strauss; Chad A Grotegut; R Philip Heine; Nancy C Chescheir; Jeffrey S A Stringer; David M Stamilio; Katherine M Menard; J Eric Jelovsek
Journal:  Obstet Gynecol       Date:  2020-04       Impact factor: 7.623

4.  Predictive value of a bleeding score for postpartum hemorrhage.

Authors:  Ada Gillissen; Thomas van den Akker; Camila Caram-Deelder; Dacia D C A Henriquez; Sebastiaan W A Nij Bijvank; Kitty W M Bloemenkamp; Jeroen Eikenboom; Johanna G van der Bom
Journal:  Res Pract Thromb Haemost       Date:  2019-04-04

5.  Predicting peripartum blood transfusion: focusing on pre-pregnancy characteristics.

Authors:  Yung-Taek Ouh; Kyu-Min Lee; Ki Hoon Ahn; Soon-Cheol Hong; Min-Jeong Oh; Hai-Joong Kim; Sung Won Han; Geum Joon Cho
Journal:  BMC Pregnancy Childbirth       Date:  2019-12-05       Impact factor: 3.007

6.  The association of antenatal D-dimer and fibrinogen with postpartum hemorrhage and intrauterine growth restriction in preeclampsia.

Authors:  Hailing Shao; Shichu Gao; Dongru Dai; Xiaomin Zhao; Ying Hua; Huijun Yu
Journal:  BMC Pregnancy Childbirth       Date:  2021-09-05       Impact factor: 3.007

7.  A risk prediction model of perinatal blood transfusion for patients who underwent cesarean section: a case control study.

Authors:  Yao Wang; Juan Xiao; Fanzhen Hong
Journal:  BMC Pregnancy Childbirth       Date:  2022-04-30       Impact factor: 3.007

8.  Prediction of Maternal Hemorrhage Using Machine Learning: Retrospective Cohort Study.

Authors:  Jill M Westcott; Francine Hughes; Wenke Liu; Mark Grivainis; Iffath Hoskins; David Fenyo
Journal:  J Med Internet Res       Date:  2022-07-18       Impact factor: 7.076

9.  Obstetric hemorrhage risk assessment tool predicts composite maternal morbidity.

Authors:  Emer L Colalillo; Andrew D Sparks; Jaclyn M Phillips; Chinelo L Onyilofor; Homa K Ahmadzia
Journal:  Sci Rep       Date:  2021-07-19       Impact factor: 4.379

  9 in total

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