• Int J Obstet Anesth · May 2022

    Comparative performance of obstetric comorbidity indices within categories of race and ethnicity: an external validation study.

    • V E Tangel, J Bryant-Huppert, S Y Jiang, C M Oxford-Horrey, S Dzotsi, K Kjaer, and R S White.
    • Weill Cornell Medicine, Department of Anesthesiology, New York, NY, USA.
    • Int J Obstet Anesth. 2022 May 1; 50: 103543.

    BackgroundExisting obstetric comorbidity adjustment indices were created without explicitly accounting for sociodemographic diversity in the development populations, which could lead to imprecise estimates if these indices are applied to populations different from the ones in which they were developed. The objective of this study was to validate two obstetric comorbidity indices (one using severe maternal morbidity [SMM] and one using end-organ injury or mortality) within categories of race/ethnicity.MethodsDelivery hospitalizations from the State Inpatient Databases for Florida, Maryland, Kentucky, Washington (2015-2018) and New York (2015-2016) were analyzed. Outcomes were modeled using logistic regression by category of race/ethnicity and overall, with each model having its respective index value as the covariate. Discrimination and calibration were assessed.ResultsThere were 1 604 203 delivery hospitalizations, among which 1.6% experienced SMM and 0.4% had SMM excluding blood transfusions. Maternal end-organ injury or mortality was identified in 0.5% of cases. For the entire patient population, the area under the receiver operating curve (AUROC) was 0.72 (95% CI 0.71 to 0.72) and 0.75 (95% CI 0.75 to 0.76) for SMM and non-transfusion SMM, respectively. The AUROC for maternal end-organ injury or death was 0.65 (95% CI 0.65 to 0.66). All scores exhibited poor calibration across racial/ethnic groups. There was no substantial variation within categories of race/ethnicity in terms of index performance.ConclusionUsers of these indices should consider performance data in totality when choosing a measure for obstetric comorbidity adjustment. There were no marked differences in model performance observed across race/ethnicity groups within each index.Copyright © 2022 Elsevier Ltd. All rights reserved.

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