Abstract 4138427: Frailty Measured by The Risk Analysis Index as a Predictor of In-hospital Outcomes After PCI: A Retrospective Nationwide Analysis of 449,857 Patients
Background: Frailty emerges as an independent predictor of adverse outcomes post-cardiac procedures including percutaneous coronary intervention (PCI). Various indices have been developed to assess frailty, but no gold standard exists. The Risk Analysis Index (RAI) is a promising frailty index that enables better preoperative evaluation for personalized care. Objective: To assess RAI as a preoperative assessment tool for predicting post-PCI in-hospital outcomes. Methods: In this retrospective cohort analysis, The National Inpatient Sample was queried from 2016 to 2020 for patients who underwent PCI. Our cohort was stratified depending on RAI score into Robust, Prefrail, Frail, and Very Frail ( Figure 1.A ). Primary outcomes were non-home discharge (NHD), mortality, and extended length of stay (defined as length of stay exceeding 75% of the cohort) (eLOS). The statistical significance of difference in the primary outcomes was assessed amongst the four frailty groups using The Chi-square test ( x 2 ). In addition, RAI was tested for its ability to predict the primary outcomes using the area under the curve (AUC). Results: The study sample included 449,857 unweighted admissions, of which 67.09% were males, the median age was 50 (IQR: 46-54), 22.6% were Robust, 54.9% were Prefrail, 19% were Frail, and 3.5% were Very Frail ( Figure 1.A ). Increasing RAI frailty scores (robust versus very frail) correlated with significantly higher NHD (7.64% vs. 61.54%; p<0.0001 ), eLOS (11.42% vs. 54.33%; p<0.0001 ), and mortality (1.25% vs. 7.06%; p<0.0001 ) ( Figure 1.B ). RAI effectively predicted NHD (C-statistic 0.73; 95% CI 0.72-0.73), eLOS (C-statistic 0.68; 95% CI 0.67-0.68), and mortality (C-statistic 0.66; 95% CI 0.65-0.66) ( Figure 1.C ). Conclusion: Frailty, measured by RAI, is a significant predictor of post-PCI in-hospital outcomes, including eLOS, NHD, and mortality. RAI facilitates better patient stratification and personalized care strategies in clinical practice.
Authors
- Mohamed Riad Fouad (ORCID: https://orcid.org/0000-0002-4102-5111)
- Kirellos Said Abbas (ORCID: https://orcid.org/0000-0003-0339-9339)
- Abdul Rahman Akkawi (ORCID: https://orcid.org/0000-0002-3247-7618)
- Basel Abdelazeem (ORCID: https://orcid.org/0000-0002-2919-6196)
- Hassan Alshaker (ORCID: https://orcid.org/0000-0003-4937-4460)
- Yazan Almohtasib
- Mohammad Akram Kawsara
- Kerollos Abdelsayed (ORCID: https://orcid.org/0009-0001-2499-5570)
- Ahmad Nawlo
Institutions
- West Virginia University (US)
- Brigham and Women's Hospital (US)
- University of Kansas (US)
- Wichita State University (US)
- Magdi Yacoub Heart Foundation (EG)
- University of Missouri–Kansas City (US)
- Alexandria University (EG)
Publication Details
- Journal
- Circulation
- Published
- 2024-11-12
- DOI
- https://doi.org/10.1161/circ.150.suppl_1.4138427
- Primary Topic
- Cardiac, Anesthesia and Surgical Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00