Am J Perinatol 2022; 39(07): 786-796
DOI: 10.1055/s-0040-1718704
Original Article

A Model to Predict Vaginal Delivery and Maternal and Neonatal Morbidity in Low-Risk Nulliparous Patients at Term

Maged M. Costantine
1   Departments of Obstetrics and Gynecology of University of Texas Medical Branch, Galveston, Texas
,
Grecio Sandoval
2   The George Washington University Biostatistics Center, Washington, Dist. of Columbia
,
William A. Grobman
3   Department of Obstetrics and Gynecology, Northwestern University, Chicago, Illinois
,
Jennifer L. Bailit
4   Department of Obstetrics and Gynecology, MetroHealth Medical Center-Case Western Reserve University, Cleveland, Ohio
,
Uma M. Reddy
5   Department of Obstetrics and Gynecology, The Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
,
Ronald J. Wapner
6   Department of Obstetrics and Gynecology, Columbia University, New York, New York
,
Michael W. Varner
7   Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah
,
John M. Thorp Jr.
8   Department of Obstetrics and Gynecology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
,
Steve N. Caritis
9   Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, Pennsylvania
,
Mona Prasad
10   Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
,
Alan T.N. Tita
11   Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, Alabama
,
Yoram Sorokin
12   Department of Obstetrics and Gynecology, Wayne State University, Detroit, Michigan
,
Dwight J. Rouse
13   Department of Obstetrics and Gynecology, Brown University, Providence, Rhode Island
,
Sean C. Blackwell
14   Department of Obstetrics and Gynecology, The University of Texas Health Science Center at Houston, McGovern Medical School-Children's Memorial Hermann Hospital, Houston, Texas
,
Jorge E. Tolosa
15   Department of Obstetrics and Gynecology, Oregon Health and Science University, Portland, Oregon
,
for the Eunice Kennedy Shriver National Institute of Child Health Human Development Maternal-Fetal Medicine Units Network, Bethesda, MD› Author Affiliations

Funding The project described was supported by grants from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), grant nos.: HD21410, HD27869, HD27915, HD27917, HD34116, HD34208, HD36801, HD40500, HD40512, HD40544, HD40545, HD40560, HD40485, HD53097, HD53118; the National Center for Research Resources grant nos.: UL1 RR024989, 5UL1 RR025764. Comments and views of the authors do not necessarily represent views of the National Institute of Health.
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Abstract

Objective This study aimed to develop and validate a model to predict the probability of vaginal delivery (VD) in low-risk term nulliparous patients, and to determine whether it can predict the risk of severe maternal and neonatal morbidity.

Methods Secondary analysis of an obstetric cohort of patients and their neonates born in 25 hospitals across the United States (n = 115,502). Trained and certified research personnel abstracted the maternal and neonatal records. Nulliparous patients with singleton, nonanomalous vertex fetuses, admitted with an intent for VD ≥ 37 weeks were included in this analysis. Patients in active labor (cervical exam > 5 cm), those with prior cesarean and other comorbidities were excluded. Eligible patients were randomly divided into a training and test sets. Based on the training set, and using factors available at the time of admission for delivery, we developed and validated a logistic regression model to predict the probability of VD, and then estimated the prevalences of severe morbidity according to the predicted probability of VD.

Results A total of 19,611 patients were included. Based on the training set (n = 9,739), a logistic regression model was developed that included maternal age, body mass index (BMI), cervical dilatation, and gestational age on admission. The model was internally validated on the test set (n = 9,872 patients) and yielded a receiver operating characteristic-area under the curve (ROC-AUC) of 0.71 (95% confidence interval [CI]: 0.70–0.72). Based on a subset of 18,803 patients with calculated predicted probabilities, we demonstrated that the prevalences of severe morbidity decreased as the predicted probability of VD increased (p < 0.01).

Conclusion In a large cohort of low-risk nulliparous patients in early labor or undergoing induction of labor, at term with singleton gestations, we developed and validated a model to calculate the probability of VD, and maternal and neonatal morbidity. If externally validated, this calculator may be clinically useful in helping to direct level of care, staffing, and adjustment for case-mix among various systems.

Key Points

  • A model to predict the probability of vaginal delivery in low-risk nulliparous patients at term.

  • The model also predicts the risk of severe maternal and neonatal morbidity.

  • The prevalences of severe morbidity decrease as the probability of vaginal delivery increases.

Note

This study was presented at the 35th and 36th Annual Meeting of the Society for Maternal Fetal Medicine.


* See [Supplementary Material] (available in the online version) for a list of other members of the NICHD MFMU Network.


Supplementary Material



Publication History

Received: 17 August 2020

Accepted: 07 September 2020

Article published online:
19 October 2020

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