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

Abstract

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.

Keywords: SARS-CoV-2; calibration; prediction; pregnancy; risk estimation; vaccination.

Figure 1

ROC curves ROC curves of miniCOMIT (green line) and fullCOMIT (orange line). FullCOMIT, using laboratory parameters, BMI, and respiratory symptoms outperformed miniCOMIT, which includes maternal age, BMI, and gestational age. BMI, body mass index; COMIT, COvid Maternal Intensive Therapy; ROC, receiver operating curves. Kalafat et al. Prediction of critical COVID-19 in symptomatic pregnant women. Am J Obstet Gynecol 2022.

Figure 2

Diagnosis to ICU admission interval stratified by risk categories According to miniCOMIT (A) and fullCOMIT (B). Risk stratification by both models was significantly associated with the diagnosis to ICU admission interval (log-rank test P<.0001, both). COMIT, COvid Maternal Intensive Therapy; ICU, intensive care unit. Kalafat et al. Prediction of critical COVID-19 in symptomatic pregnant women. Am J Obstet Gynecol 2022.

Supplemental Figure 1

The calibration plot of miniCOMIT The smooth black line represents that the fit of the model predicted the risk of outcome to the observed rate within each decile of predicted probability. The straight red line is used as a reference for perfect fit. The bar chart at the base of the figure presents the distribution of cases with intensive care unit admission (above the line) across the spectrum of predicted probability. Kalafat et al. Prediction of critical COVID-19 in symptomatic pregnant women. Am J Obstet Gynecol 2022.

Supplemental Figure 2

Calibration plot of fullCOMIT The smooth black line represents the fit of the model predicted risk of outcome to the observed rate within each decile of predicted probability. The straight red line is used as reference for perfect fit. The bar chart at the base of the figure presents distribution of cases with intensive care unit admission (above the line) across the spectrum of predicted probability. Kalafat et al. Prediction of critical COVID-19 in symptomatic pregnant women. Am J Obstet Gynecol 2022.