Isabelle Malhamé1, Niharika Mehta1,2, Christina A Raker2, Erica J Hardy1,2, Hannah Spalding1, Benjamin A Bouvier1, David A Savitz2,3, Valery A Danilack2,3. 1. Department of Medicine of the Warren Alpert Medical School of Brown University, Women & Infants Hospital, Providence, Rhode Island, USA. 2. Department of Obstetrics and Gynecology of the Warren Medical Alpert School of Brown University, Women & Infants Hospital, Providence, Rhode Island, USA. 3. Department of Epidemiology, Brown University School of Public Health, Providence, Rhode Island, USA.
Abstract
BACKGROUND: Cardiovascular severe maternal morbidity (CSMM) is rising and has become the leading cause of maternal mortality. Research using administrative data sets may allow for better understanding of this critical group of diseases. OBJECTIVE: To validate a composite variable of CSMM for use in epidemiologic studies. METHODS: We analysed delivery hospitalisations at an obstetric teaching hospital from 2007 to 2017. We utilised a subset of indicators developed by the Centers for Disease Control and Prevention based on ICD codes to form the composite variable for CSMM. Two expert clinicians manually reviewed all qualifying events using a standardised tool to determine whether these represented true CSMM events. Additionally, we estimated the number of CSMM cases among delivery hospitalisations without qualifying ICD codes by manually reviewing all hospitalisations with severe preeclampsia, a population at high risk of CSMM, and a random sample of 1000 hospitalisations without severe preeclampsia. We estimated validity of the composite variable. RESULTS: Among 91 355 admissions for delivery, we captured 113 potential CSMM cases using qualifying ICD codes. Of these, 65 (57.5%) were true CSMM cases. Indicators for acute myocardial infarction, cardiac arrest, and cardioversion had the highest true-positive rates (100% for all). We found an additional 70 CSMM cases in the 2102 admissions with severe preeclampsia and a single CSMM case in the random sample. Assuming a rate of 1 CSMM case per 1000 deliveries in the remaining cohort, the composite variable had a positive predictive value of 57.5% (95% CI 47,9, 66.8), a negative predictive value of 99.8% (95% CI 99.8, 99.9), a sensitivity of 29.0% (95% CI 23.2, 35.4), and a specificity of 100% (95% CI 99.9, 100.0). CONCLUSION: A novel composite variable for CSMM had reasonable PPV but limited sensitivity. This composite variable may enable epidemiologic studies geared towards reducing maternal morbidity and mortality.
BACKGROUND: Cardiovascular severe maternal morbidity (CSMM) is rising and has become the leading cause of maternal mortality. Research using administrative data sets may allow for better understanding of this critical group of diseases. OBJECTIVE: To validate a composite variable of CSMM for use in epidemiologic studies. METHODS: We analysed delivery hospitalisations at an obstetric teaching hospital from 2007 to 2017. We utilised a subset of indicators developed by the Centers for Disease Control and Prevention based on ICD codes to form the composite variable for CSMM. Two expert clinicians manually reviewed all qualifying events using a standardised tool to determine whether these represented true CSMM events. Additionally, we estimated the number of CSMM cases among delivery hospitalisations without qualifying ICD codes by manually reviewing all hospitalisations with severe preeclampsia, a population at high risk of CSMM, and a random sample of 1000 hospitalisations without severe preeclampsia. We estimated validity of the composite variable. RESULTS: Among 91 355 admissions for delivery, we captured 113 potential CSMM cases using qualifying ICD codes. Of these, 65 (57.5%) were true CSMM cases. Indicators for acute myocardial infarction, cardiac arrest, and cardioversion had the highest true-positive rates (100% for all). We found an additional 70 CSMM cases in the 2102 admissions with severe preeclampsia and a single CSMM case in the random sample. Assuming a rate of 1 CSMM case per 1000 deliveries in the remaining cohort, the composite variable had a positive predictive value of 57.5% (95% CI 47,9, 66.8), a negative predictive value of 99.8% (95% CI 99.8, 99.9), a sensitivity of 29.0% (95% CI 23.2, 35.4), and a specificity of 100% (95% CI 99.9, 100.0). CONCLUSION: A novel composite variable for CSMM had reasonable PPV but limited sensitivity. This composite variable may enable epidemiologic studies geared towards reducing maternal morbidity and mortality.