Literature DB >> 29911829

Risk Score for Prediction of Postpartum Hemorrhages in Normal Labor at Chonburi Hospital.

Wanicha Sittiparn, Teera Siwadune.   

Abstract

Background: Postpartum hemorrhage (PPH) is major cause of morbidity and mortality globally. Although the majority of PPH could be avoided through the use of pharmacologic prevention during the third stage of labor, the maternal mortality rate from PPH is unchanged and the blood transfusion rate is increasing. In rural hospital or primary care unit, most health care workers are general practitioners and intern doctors, they are inexperienced in managing PPH case and lack of medication, blood component, medical instrument, and surgical team. Most deaths are from delay and incorrect treatment in the primary hospital. Thus, early detection of PPH could decrease maternal morbidity and mortality. Objective: To develop a risk score based on maternal clinical characteristics and medical history for prediction of postpartum hemorrhage (PPH) in normal labor in the antepartum period. The present study was a part of risk management developing system that conform to service plan of the Public Health Ministry. Material and Method: A retrospective cohort study reviewed the medical charts for normal labor between September 1, 2012 and October 31, 2015, at Chonburi Hospital, Thailand. Risk factors were identified and analyzed by multivariable logistic regression. Risk score was conducted according to adjusted odds ratio of each significant variable in regression model.
Results: Among 650 women, advanced maternal age, body mass index before pregnancy, pregnancy induced hypertension and diabetes mellitus types 2 were significantly associated with PPH in normal labor. These factors were incorporated into a risk score that could be predicted PPH in normal labor with sensitivity 81.3% and specificity 50.8% at optimal cut-off score equal or greater than 4.
Conclusion: Applying developed PPH risk score is a practical way to identify patients who are at high-risk for developing PPH for an early detection, treatment, and transfer.

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Year:  2017        PMID: 29911829

Source DB:  PubMed          Journal:  J Med Assoc Thai        ISSN: 0125-2208


  4 in total

1.  Machine learning-based prediction of postpartum hemorrhage after vaginal delivery: combining bleeding high risk factors and uterine contraction curve.

Authors:  Jia Liu; Chuan Wang; Ruiling Yan; Yaosheng Lu; Jieyun Bai; Huijin Wang; Ruiman Li
Journal:  Arch Gynecol Obstet       Date:  2022-02-16       Impact factor: 2.493

2.  Risk Factors for Postpartum Hemorrhage in a Thai-Myanmar Border Community Hospital: A Nested Case-Control Study.

Authors:  Waraporn Thepampan; Nuchsara Eungapithum; Krittai Tanasombatkul; Phichayut Phinyo
Journal:  Int J Environ Res Public Health       Date:  2021-04-27       Impact factor: 3.390

3.  Risk factors for postpartum haemorrhage in the Northern Province of Rwanda: A case control study.

Authors:  Oliva Bazirete; Manassé Nzayirambaho; Aline Umubyeyi; Innocent Karangwa; Marilyn Evans
Journal:  PLoS One       Date:  2022-02-15       Impact factor: 3.240

4.  A Fuzzy Expert System to Predict the Risk of Postpartum Hemorrhage.

Authors:  Yussriya Hanaa Doomah; Song-Yuan Xu; Li-Xia Cao; Sheng-Lian Liang; Gloria Francisca Nuer-Allornuvor; Xiao-Yan Ying
Journal:  Acta Inform Med       Date:  2019-12
  4 in total

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