The association of pregnancy with outcomes among critically ill reproductive-aged women: A propensity score-matched retrospective cohort analysis

BACKGROUND: The maternal mortality rate in the United States is unacceptably high. However, the relative contribution of pregnancy to these outcomes is unknown. Studies comparing outcomes among pregnant vs nonpregnant critically ill patients show mixed results and are limited by small sample sizes.

RESEARCH QUESTION: What is the association of pregnancy with critical illness outcomes?

STUDY DESIGN AND METHODS: We performed a retrospective cohort study of women 18 to 55 years of age who received invasive mechanical ventilation (MV) on hospital day 0 or 1 or who demonstrated sepsis on admission (infection with organ failure) discharged from Premier Healthcare Database hospitals from 2008 through 2021. The exposure was pregnancy. The primary outcome was in-hospital mortality. We created propensity scores for pregnancy (using patient and hospital characteristics) and performed 1:1 propensity score matching without replacement within age strata (to ensure exact age matching). We performed multilevel multivariable mixed-effects logistic regression for propensity-matched pairs with pair as a random effect.

RESULTS: Three thousand ninety-three pairs were included in the matched MV cohort, and 13,002 pairs were included in the sepsis cohort. The characteristics of both cohorts were well balanced (all standard mean differences, < 0.1). Among matched pairs, unadjusted mortality was 8.0% vs 13.8% for MV and 1.4% vs 2.3% for sepsis among pregnant and nonpregnant patients, respectively. In adjusted regression, pregnancy was associated with lower odds of in-hospital mortality (MV: OR, 0.50; 95% CI, 0.41-0.60; P < .001; sepsis: OR, 0.52; 95% CI, 0.40-0.67; P < .001).

INTERPRETATION: In this large US cohort, critically ill pregnant women receiving MV or with sepsis showed better survival than propensity score-matched nonpregnant women. These findings must be interpreted in the context of likely residual confounding.

Rachel Kohn, Deepshikha C Ashana, Kelly C Vranas, Elizabeth M Viglianti, Katrina Hauschildt, Catherine Chen, Emily A Vail, Leslie Moroz, Hayley B Gershengorn