Journal Article
Multicenter Study
Add like
Add dislike
Add to saved papers

An internally validated prediction model for critical COVID-19 infection and intensive care unit admission in symptomatic pregnant women.

BACKGROUND: Pregnant women are at an increased risk of mortality and morbidity owing to COVID-19. Many studies have reported on the association of COVID-19 with pregnancy-specific adverse outcomes, but prediction models utilizing large cohorts of pregnant women are still lacking for estimating the risk of maternal morbidity and other adverse events.

OBJECTIVE: The main aim of this study was to develop a prediction model to quantify the risk of progression to critical COVID-19 and intensive care unit admission in pregnant women with symptomatic infection.

STUDY DESIGN: This was a multicenter retrospective cohort study including 8 hospitals from 4 countries (the United Kingdom, Austria, Greece, and Turkey). The data extraction was from February 2020 until May 2021. Included were consecutive pregnant and early postpartum women (within 10 days of birth); reverse transcriptase polymerase chain reaction confirmed SARS-CoV-2 infection. The primary outcome was progression to critical illness requiring intensive care. The secondary outcomes included maternal death, preeclampsia, and stillbirth. The association between the primary outcome and 12 candidate predictors having a known association with severe COVID-19 in pregnancy was analyzed with log-binomial mixed-effects regression and reported as adjusted risk ratios. All the potential predictors were evaluated in 1 model and only the baseline factors in another. The predictive accuracy was assessed by the area under the receiver operating characteristic curves.

RESULTS: Of the 793 pregnant women who were positive for SARS-CoV-2 and were symptomatic, 44 (5.5%) were admitted to intensive care, of whom 10 died (1.3%). The 'mini-COvid Maternal Intensive Therapy' model included the following demographic and clinical variables available at disease onset: maternal age (adjusted risk ratio, 1.45; 95% confidence interval, 1.07-1.95; P=.015); body mass index (adjusted risk ratio, 1.34; 95% confidence interval, 1.06-1.66; P=.010); and diagnosis in the third trimester of pregnancy (adjusted risk ratio, 3.64; 95% confidence interval, 1.78-8.46; P=.001). The optimism-adjusted area under the receiver operating characteristic curve was 0.73. The 'full-COvid Maternal Intensive Therapy' model included body mass index (adjusted risk ratio, 1.39; 95% confidence interval, 1.07-1.95; P=.015), lower respiratory symptoms (adjusted risk ratio, 5.11; 95% confidence interval, 1.81-21.4; P=.007), neutrophil to lymphocyte ratio (adjusted risk ratio, 1.62; 95% confidence interval, 1.36-1.89; P<.001); and serum C-reactive protein (adjusted risk ratio, 1.30; 95% confidence interval, 1.15-1.44; P<.001), with an optimism-adjusted area under the receiver operating characteristic curve of 0.85. Neither model showed signs of a poor fit. Categorization as high-risk by either model was associated with a shorter diagnosis to intensive care unit admission interval (log-rank test P<.001, both), higher maternal death (5.2% vs 0.2%; P<.001), and preeclampsia (5.7% vs 1.0%; P<.001). A spreadsheet calculator is available for risk estimation.

CONCLUSION: At presentation with symptomatic COVID-19, pregnant and recently postpartum women can be stratified into high- and low-risk for progression to critical disease, even where resources are limited. This can support the nature and place of care. These models also highlight the independent risk for severe disease associated with obesity and should further emphasize that even in the absence of other comorbidities, vaccination is particularly important for these women. Finally, the model also provides useful information for policy makers when prioritizing national vaccination programs to quickly protect those at the highest risk of critical and fatal COVID-19.

Full text links

We have located links that may give you full text access.
Can't access the paper?
Try logging in through your university/institutional subscription. For a smoother one-click institutional access experience, please use our mobile app.

Related Resources

For the best experience, use the Read mobile app

Mobile app image

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app

All material on this website is protected by copyright, Copyright © 1994-2024 by WebMD LLC.
This website also contains material copyrighted by 3rd parties.

By using this service, you agree to our terms of use and privacy policy.

Your Privacy Choices Toggle icon

You can now claim free CME credits for this literature searchClaim now

Get seemless 1-tap access through your institution/university

For the best experience, use the Read mobile app