Prediction of COVID-19 Severity at Delivery after Asymptomatic or Mild COVID-19 during Pregnancy

Authors

Grecio J. Sandoval, Biostatistics Center, George Washington University, Washington, District of Columbia.
Torri D. Metz, Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah.
William A. Grobman, Department of Obstetrics and Gynecology, Northwestern University, Chicago, Illinois.
Tracy A. Manuck, Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, North Carolina.
Brenna L. Hughes, Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, North Carolina.
George R. Saade, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, Texas.
Monica Longo, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland.
Hyagriv N. Simhan, Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, Pennsylvania.
Dwight J. Rouse, Department of Obstetrics and Gynecology, Brown University, Providence, Rhode Island.
Hector Mendez-Figueroa, Department of Obstetrics and Gynecology, Children's Memorial Hermann Hospital, University of Texas Health Science Center at Houston, Houston, Texas.
Cynthia Gyamfi-Bannerman, Department of Obstetrics and Gynecology, Columbia University, New York, New York.
Angela C. Ranzini, Department of Obstetrics and Gynecology, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio.
Maged M. Costantine, Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio.
Harish M. Sehdev, Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania.
Alan T. Tita, Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, Alabama.

Document Type

Journal Article

Publication Date

5-10-2024

Journal

American journal of perinatology

DOI

10.1055/s-0044-1786868

Abstract

OBJECTIVE: This study aimed to develop a prediction model that estimates the probability that a pregnant person who has had asymptomatic or mild coronavirus disease 2019 (COVID-19) prior to delivery admission will progress in severity to moderate, severe, or critical COVID-19. STUDY DESIGN: This was a secondary analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patients who delivered from March through December 2020 at hospitals across the United States. Those eligible for this analysis presented for delivery with a current or previous asymptomatic or mild SARS-CoV-2 infection. The primary outcome was moderate, severe, or critical COVID-19 during the delivery admission through 42 days postpartum. The prediction model was developed and internally validated using stratified cross-validation with stepwise backward elimination, incorporating only variables that were known on the day of hospital admission. RESULTS: Of the 2,818 patients included, 26 (0.9%; 95% confidence interval [CI], 0.6-1.3%) developed moderate-severe-critical COVID-19 during the study period. Variables in the prediction model were gestational age at delivery admission (adjusted odds ratio [aOR], 1.15; 95% CI, 1.08-1.22 per 1-week decrease), a hypertensive disorder in a prior pregnancy (aOR 3.05; 95% CI, 1.25-7.46), and systolic blood pressure at admission (aOR, 1.04; 95% CI, 1.02-1.05 per mm Hg increase). This model yielded an area under the receiver operating characteristic curve of 0.82 (95% CI, 0.72-0.91). CONCLUSION: Among individuals presenting for delivery who had asymptomatic-mild COVID-19, gestational age at delivery admission, a hypertensive disorder in a prior pregnancy, and systolic blood pressure at admission were predictive of delivering with moderate, severe, or critical COVID-19. This prediction model may be a useful tool to optimize resources for SARS-CoV-2-infected pregnant individuals admitted for delivery. KEY POINTS: · Three factors were associated with delivery with more severe COVID-19.. · The developed model yielded an area under the receiver operating characteristic curve of 0.82 and model fit was good.. · The model may be useful tool for SARS-CoV-2 infected pregnancies admitted for delivery..

Department

Biostatistics and Bioinformatics

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