Cardiovascular instability, consciousness level tied to in-hospital mortality after PCI

Combining variables that reflect clinical acuity can predict mortality risk following percutaneous coronary intervention (PCI) in contemporary practice, suggests a study.

“This model, which includes data previously not captured, is a valid instrument for risk stratification and for quality improvement efforts,” the authors said.

In this study, the authors used data from 706,263 PCIs performed between July 2018 and June 2019 at 1,608 sites to develop and validate a new full and precatheterization model to predict in-hospital mortality and a simplified bedside risk score. They randomly split the sample into a development cohort (n=495,005, 70 percent) and a validation cohort (n=211,258, 30 percent).

Overall, 1,000 bootstrapped samples of the development cohort were created; stepwise selection logistic regression was used on each sample. The final model included variables selected in at least 70 percent of the bootstrapped samples and those identified a priori due to clinical relevance.

In-hospital mortality after PCI differed according to the clinical presentation. The most dominant predictors of in-hospital mortality were procedural urgency, cardiovascular instability, and level of consciousness.

The full model had a good performance, demonstrating excellent discrimination (C-index, 0.943) in the validation cohort and good calibration across different clinical and procedural risk cohorts. The median rate of hospital risk-standardization mortality was 1.9 percent and ranged from 1.1 percent to 3.3 percent (interquartile range, 1.7–2.1 percent).

“Standardization of risk is critical in benchmarking and quality improvement efforts for PCIs,” the authors said. “In 2018, the CathPCI Registry was updated to include additional variables to better classify higher-risk patients.”