Comorbidities and Pregnancy-Related Risk Factors in Patients with Severe Maternal Morbidity: Application of a Validated Obstetrical Comorbidity Scoring System to a Surveillance-Identified Population.

Abstract

Background/Objectives: Patient characteristics-especially comorbidities-influence the risk of severe maternal morbidity (SMM). Recent efforts have sought to derive an obstetric comorbidity score to be used for case-mix adjustment. We assess the use of a validated obstetric comorbidity index among patients with SMM and identify additional conditions that could be included in the index. Methods: We applied a validated obstetrical comorbidity scoring system to patients identified through Maryland's SMM Surveillance and Review program, using chi-square analyses to compare prevalence of comorbidities by primary causes of SMM. We compared mean and median comorbidity score by hospital level of care and adverse outcomes (length of stay, volume of blood product transfusion, intensive care unit (ICU) admission, transfer to a higher level of care, and neonatal intensive care unit (NICU) admission). Through the review of case data, we identified additional risk factors for SMM. Using tetrachoric correlation, we examined the degree of correlation between comorbidities from the validated index and the additional risk factors in our sample. Results: A total of 978 SMM events were identified and reviewed between 2020 and 2024. Mean comorbidity score was highest among patients with SMM from hypertensive disorders of pregnancy, and prevalence of index comorbidities varied by primary cause of SMM. Patients that delivered at level IV hospitals had the highest mean comorbidity scores. Scores were also higher with a length of stay ≥4 days, larger volumes of blood product transfusion, and patients whose newborns were admitted to the NICU. We identified 13 additional risk factors for consideration in future indices, finding minimal correlation between the 27 indicators in the validated index and the additional 13. Conclusions: Accurately identifying patient risk for SMM has important applications in both clinical settings and population-level perinatal health research.