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Trends in Incidence and Outcomes of Pregnancy-Related Acute Myocardial Infarction (From a Nationwide Inpatient Sample Database)

Published:January 25, 2019DOI:https://doi.org/10.1016/j.amjcard.2019.01.030
      Acute myocardial infarction (AMI) during pregnancy is rare but fatal complication. Recent incidence of pregnancy related AMI and trends in the related outcomes are unknown. The Nationwide Inpatient Sample database was utilized from years 2005 to 2014. International Classification of Disease-Ninth Revision were used to identify pregnancy related admissions and AMI. Primary outcome was incidence and trend of AMI related to pregnancy and Secondary outcomes were trends in mortality, resource utilization, and predictors of AMI during pregnancy. Simple logistic regression model was used to calculate predictors of AMI during pregnancy. p Values for trends were generated by Cochrane-Armitage test for categorical variables and simple linear regression for continuous variables. A total of 43,437,621 pregnancy related hospitalization and 3,786 cases of AMI (86% ante-partum and 14% postpartum) were noted during study period. The incidence of AMI during the study period was 8.7 per 100,000 pregnancies with an overall increase in incidence during the study period (relative increase of 18.9%, p <0.001). There was a concomitant decrease in mortality (relative decrease of 40.05%, p <0.001), cost of care (relative decrease of 8.70%, p <0.001), and length of stay (relative decrease of 13.53%, p <0.001). Significant predictors of AMI during pregnancy were higher age of pregnancy, black race, co-morbidities such as hypertension, thrombophilia, diabetes milletus, substance abuse, smoking, hyperlipidemia, heart failure, deep venous thrombosis, transfusion, fluid and electrolyte imbalance, and postpartum complications such as hemorrhage, infection, and depression. In conclusion, the incidence of AMI 2005 to 2014 rose with a concomitant decrease in mortality and resource utilization. High-risk patient characteristics were identified which could be utilized for resource allocation to further improve outcomes.
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