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Multicenter Study
. 2021 Jul 20;78(3):216-229.
doi: 10.1016/j.jacc.2021.04.067. Epub 2021 May 3.

Predicting In-Hospital Mortality in Patients Undergoing Percutaneous Coronary Intervention

Yulanka S Castro-Dominguez  1 , Yongfei Wang  1 , Karl E Minges  1 , Robert L McNamara  2 , John A Spertus  3 , Gregory J Dehmer  4 , John C Messenger  5 , Kimberly Lavin  6 , Cornelia Anderson  6 , Kristina Blankinship  6 , Nestor Mercado  7 , Julie M Clary  8 , Anwar D Osborne  9 , Jeptha P Curtis  1 , Matthew A Cavender  10
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Free article
Multicenter Study

Predicting In-Hospital Mortality in Patients Undergoing Percutaneous Coronary Intervention

Yulanka S Castro-Dominguez et al. J Am Coll Cardiol. .
Free article

Abstract

Background: Standardization of risk is critical in benchmarking and quality improvement efforts for percutaneous coronary interventions (PCIs). In 2018, the CathPCI Registry was updated to include additional variables to better classify higher-risk patients.

Objectives: This study sought to develop a model for predicting in-hospital mortality risk following PCI incorporating these additional variables.

Methods: Data from 706,263 PCIs performed between July 2018 and June 2019 at 1,608 sites were used to develop and validate a new full and pre-catheterization model to predict in-hospital mortality, and a simplified bedside risk score. The sample was randomly split into a development cohort (70%, n = 495,005) and a validation cohort (30%, n = 211,258). The authors created 1,000 bootstrapped samples of the development cohort and used stepwise selection logistic regression on each sample. The final model included variables that were selected in at least 70% of the bootstrapped samples and those identified a priori due to clinical relevance.

Results: In-hospital mortality following PCI varied based on clinical presentation. Procedural urgency, cardiovascular instability, and level of consciousness after cardiac arrest were most predictive of in-hospital mortality. The full model performed well, with excellent discrimination (C-index: 0.943) in the validation cohort and good calibration across different clinical and procedural risk cohorts. The median hospital risk-standardized mortality rate was 1.9% and ranged from 1.1% to 3.3% (interquartile range: 1.7% to 2.1%).

Conclusions: The risk of mortality following PCI can be predicted in contemporary practice by incorporating variables that reflect clinical acuity. This model, which includes data previously not captured, is a valid instrument for risk stratification and for quality improvement efforts.

Keywords: hierarchical logistic regression model; percutaneous coronary intervention; risk-standardized mortality rates.

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Conflict of interest statement

Funding Support and Author Disclosures This research was supported by the American College of Cardiology Foundation’s National Cardiovascular Data Registry. The views expressed represent those of the author(s) and do not necessarily represent the official views of the National Cardiovascular Data Registry or its associated professional societies. Mr. Wang and Dr. Minges have received salary support for analytic services provided to the American College of Cardiology. Dr. Spertus has served as the principal investigator of a Data Analytic Center for the American College of Cardiology Foundation National Cardiovascular Data Registry, related to this work; has served as a consultant on PROs to Novartis, Amgen, Janssen, Lilly, Merck, and Myokardia, unrelated to this work; has served on the scientific advisory board for United Healthcare; owns the copyright to the Seattle Angina Questionnaire, Kansas City Cardiomyopathy Questionnaire, and Peripheral Artery Questionnaire; and has served on the Board of Directors for Blue Cross and Blue Shield of Kansas City. Dr. Messenger has received research support to his institution from Philips Medical Systems. Dr. Clary has received research support to her institution from Novartis and Boehringer Ingelheim; and has received consulting fees from Allergan. Dr. Curtis has a contract with the American College of Cardiology for his role as Senior Medical Officer, National Cardiovascular Data Registry; has received salary support from the American College of Cardiology, National Cardiovascular Data Registry; and holds equity interest in Medtronic. Dr. Cavender has received research support to his institution from Amgen, AstraZeneca, CSL Behring, and Novartis; and has received consulting fees from Amgen, Bayer, Boehringer Ingelheim, Edwards Lifesciences, Merck, and Novo Nordisk.

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