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

Maged M. Costantine; Grecio Sandoval; William A. Grobman; Jennifer L. Bailit; Uma M. Reddy; Ronald J. Wapner; Michael W. Varner; John M. Thorp; Steve N. Caritis; Mona Prasad; Alan T.N. Tita; Yoram Sorokin; Dwight J. Rouse; Sean C. Blackwell; Jorge E. Tolosa

doi:10.1055/s-0040-1718704

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

Maged M. Costantine^*, Grecio Sandoval, William A. Grobman, Jennifer L. Bailit, Uma M. Reddy, Ronald J. Wapner, Michael W. Varner, John M. Thorp, Steve N. Caritis, Mona Prasad, Alan T.N. Tita, Yoram Sorokin, Dwight J. Rouse, Sean C. Blackwell, Jorge E. Tolosa

^*Corresponding author for this work

Obstetrics and Gynecology

Research output: Contribution to journal › Article › peer-review

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.

Original language	English (US)
Pages (from-to)	786-796
Number of pages	11
Journal	American journal of perinatology
Volume	39
Issue number	7
DOIs	https://doi.org/10.1055/s-0040-1718704
State	Published - May 1 2022

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.

Keywords

calculator
maternal and neonatal morbidity
vaginal delivery

ASJC Scopus subject areas

Pediatrics, Perinatology, and Child Health
Obstetrics and Gynecology

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10.1055/s-0040-1718704

Cite this

Costantine, M. M., Sandoval, G., Grobman, W. A., Bailit, J. L., Reddy, U. M., Wapner, R. J., Varner, M. W., Thorp, J. M., Caritis, S. N., Prasad, M., Tita, A. T. N., Sorokin, Y., Rouse, D. J., Blackwell, S. C., & Tolosa, J. E. (2022). A Model to Predict Vaginal Delivery and Maternal and Neonatal Morbidity in Low-Risk Nulliparous Patients at Term. American journal of perinatology, 39(7), 786-796. https://doi.org/10.1055/s-0040-1718704

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

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.",

keywords = "calculator, maternal and neonatal morbidity, vaginal delivery",

author = "Costantine, {Maged M.} and Grecio Sandoval and Grobman, {William A.} and Bailit, {Jennifer L.} and Reddy, {Uma M.} and Wapner, {Ronald J.} and Varner, {Michael W.} and Thorp, {John M.} and Caritis, {Steve N.} and Mona Prasad and Tita, {Alan T.N.} and Yoram Sorokin and Rouse, {Dwight J.} and Blackwell, {Sean C.} and Tolosa, {Jorge E.}",

note = "Publisher Copyright: {\textcopyright} 2020. Thieme.",

year = "2022",

month = may,

day = "1",

doi = "10.1055/s-0040-1718704",

language = "English (US)",

volume = "39",

pages = "786--796",

journal = "American journal of perinatology",

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Costantine, MM, Sandoval, G, Grobman, WA, Bailit, JL, Reddy, UM, Wapner, RJ, Varner, MW, Thorp, JM, Caritis, SN, Prasad, M, Tita, ATN, Sorokin, Y, Rouse, DJ, Blackwell, SC & Tolosa, JE 2022, 'A Model to Predict Vaginal Delivery and Maternal and Neonatal Morbidity in Low-Risk Nulliparous Patients at Term', American journal of perinatology, vol. 39, no. 7, pp. 786-796. https://doi.org/10.1055/s-0040-1718704

TY - JOUR

T1 - A Model to Predict Vaginal Delivery and Maternal and Neonatal Morbidity in Low-Risk Nulliparous Patients at Term

AU - Costantine, Maged M.

AU - Sandoval, Grecio

AU - Grobman, William A.

AU - Bailit, Jennifer L.

AU - Reddy, Uma M.

AU - Wapner, Ronald J.

AU - Varner, Michael W.

AU - Thorp, John M.

AU - Caritis, Steve N.

AU - Prasad, Mona

AU - Tita, Alan T.N.

AU - Sorokin, Yoram

AU - Rouse, Dwight J.

AU - Blackwell, Sean C.

AU - Tolosa, Jorge E.

PY - 2022/5/1

Y1 - 2022/5/1

N2 - 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.

AB - 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.

KW - calculator

KW - maternal and neonatal morbidity

KW - vaginal delivery

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

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