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Predictive modeling of emergency cesarean delivery
- Source :
- PLoS ONE, PLoS ONE, Vol 13, Iss 1, p e0191248 (2018)
- Publication Year :
- 2018
- Publisher :
- Public Library of Science (PLoS), 2018.
-
Abstract
- Objective & para;& para;To increase discriminatory accuracy (DA) for emergency cesarean sections (ECSs).& para;& para;Study design & para;& para;We prospectively collected data on and studied all 6,157 births occurring in 2014 at four public hospitals located in three different autonomous communities of Spain. To identify risk factors (RFs) for ECS, we used likelihood ratios and logistic regression, fitted a classification tree (CTREE), and analyzed a random forest model (RFM). We used the areas under the receiver-operating-characteristic (ROC) curves (AUCs) to assess their DA.& para;& para;Results & para;& para;The magnitude of the LR+ for all putative individual RFs and ORs in the logistic regression models was low to moderate. Except for parity, all putative RFs were positively associated with ECS, including hospital fixed-effects and night-shift delivery. The DA of all logistic models ranged from 0.74 to 0.81. The most relevant RFs (pH, induction, and previous C-section) in the CTREEs showed the highest ORs in the logistic models. The DA of the RFM and its most relevant interaction terms was even higher (AUC = 0.94; 95% CI: 0.93-0.95).& para;& para;Conclusion & para;& para;Putative fetal, maternal, and contextual RFs alone fail to achieve reasonable DA for ECS. It is the combination of these RFs and the interactions between them at each hospital that make it possible to improve the DA for the type of delivery and tailor interventions through prediction to improve the appropriateness of ECS indications.<br />The Spanish Ministry of Health approved and financed this study under the Strategy for Assistance at Normal Childbirth in the National Health System (PI/01445).
- Subjects :
- Maternal Health
lcsh:Medicine
Blood Pressure
Logistic regression
Vascular Medicine
Labor and Delivery
0302 clinical medicine
Pregnancy
Risk Factors
Area under curve
Medicine and Health Sciences
Medicine
Prospective Studies
030212 general & internal medicine
Termination of Pregnancy
lcsh:Science
Prospective cohort study
Emergency Cesarean Delivery
Likelihood Functions
030219 obstetrics & reproductive medicine
Multidisciplinary
Obstetrics
Obstetrics and Gynecology
Hospitals
Random forest
Obstetric Procedures
Area Under Curve
Hypertension
Female
Anatomy
Research Article
Adult
medicine.medical_specialty
Decision Making
Surgical and Invasive Medical Procedures
03 medical and health sciences
Hypertensive Disorders in Pregnancy
Humans
Scalp
Cesarean Section
Hospitals, Public
business.industry
lcsh:R
Infant, Newborn
Biology and Life Sciences
Health Care
Logistic Models
Multicenter study
Spain
Health Care Facilities
Birth
Women's Health
lcsh:Q
Emergencies
business
Head
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- PLOS ONE
- Accession number :
- edsair.doi.dedup.....1a478b25e924334eb496ccdc939401d7