Predicting in-hospital mortality using Elixhauser comorbidity in patients underwent single and multiple coronary...

Area of Science:

• Cardiology
• Public Health
• Medical Informatics

Background:

• Coronary Artery Bypass Grafting (CABG) is a complex surgical procedure associated with significant risks.
• Comorbidities are prevalent in patients undergoing CABG and are linked to adverse cardiovascular outcomes.
• Predicting in-hospital mortality is crucial for risk stratification and patient management in CABG surgery.

Purpose of the Study:

• To evaluate the predictive capability of comorbidities using the Elixhauser Comorbidity Index (ECI) for in-hospital mortality in patients undergoing CABG.
• To assess the impact of age adjustment on the predictive accuracy of the ECI for in-hospital mortality.
• To compare the predictive performance of the ECI across different numbers of CABG procedures (1, 2, 3, and 4+).

Main Methods:

• Utilized the National Inpatient Sample database to identify patients who underwent CABG between Q4 2015 and 2020.
• Employed logistic regression models to determine the best-fit model for predicting in-hospital mortality based on the ECI.
• Adjusted the ECI for age to evaluate its enhanced predictive power.

Main Results:

• The ECI demonstrated moderate predictive power for in-hospital mortality across all CABG groups (c-statistic 0.6-0.7).
• Age-adjusted ECI significantly improved prediction, especially for patients undergoing 3 (c-statistic=0.69) and 4+ (c-statistic=0.72) CABG procedures.
• Predictive accuracy for age-adjusted ECI was comparable for 1 and 2 CABG procedures (c-statistic=0.67).

Conclusions:

• The Elixhauser Comorbidity Index is a valuable tool for predicting in-hospital mortality in CABG patients.
• Incorporating age into the ECI enhances its predictive accuracy, particularly for high-risk patients undergoing multiple revascularization procedures.
• These findings support the use of ECI in clinical decision-making and risk assessment for CABG surgery.