Abstract

Objectives: This study aimed to develop a mortality risk model for percutaneous coronary intervention (PCI) specific to the Out of Hospital Cardiac Arrest (OHCA) population and assess the influence of these patients on currently publicly reported PCI metrics in Washington state. Methods: Our study analyzed 331 out of hospital cardiac arrest patients who underwent PCI in Washington state over a 1-year period. Data was obtained over a 2-year period from the Clinical Outcomes Assessment Program (COAP), a PCI public reporting program for Washington hospitals and Cardiac Arrest Registry to Enhance Survival (CARES), a disease-based OHCA registry. Stepwise multivariate logistic regression was used for model development and bootstrapping was performed. Model performance was analyzed using c statistic and the Hosmer Lemeshow goodness of fit tests. Results: The OHCA model contains seven predictors of mortality: age, GFR, cardiogenic shock, emergency-salvage priority, witnessed arrest, arrest after 911 arrival, and initial shockable rhythm. The C statistics for mortality prediction of the new OHCA, CathPCI ® and COAP PCI models were c=.85 (95% CI .81-.90), c=.82 (95% CI .77-.87) and c=.79 (95% CI .74-.84), respectively. Prediction of mortality in OHCA patients undergoing PCI had an overall difference of .029. No hospitals were reclassified in quality performance based on reversal of observed-to-expected mortality ratios when applying the new model to OHCA patients undergoing PCI. Conclusions: The new OHCA model predicting PCI mortality in the OHCA population demonstrated excellent discrimination using a combination of pre-hospital and baseline features. This improved on the currently utilized model’s sensitivity and specificity for predicted mortality in the OCHA cohort, but the impact of this population on hospitals’ overall performance for PCI mortality was minimal. Even small changes in metric performance have important implications for hospitals and patients in the era of public reporting.

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