Impact of Charlson Comorbidity Index on clinical outcomes of patients with non-ST segment elevation acute coronary syndrome: a propensity score matching method.

Objective: Patients with non-ST segment elevation acute coronary syndrome (NSTEACS) admitted into emergency department are usually combined with a high number of comorbidities. Charlson Comorbidity Index (CCI) is the most commonly used measure to assess comorbidity in clinical practice. However, the impact of CCI on the clinical outcomes of patients with NSTEACS are still unclear.

Design: A multicenter retrospective cohort study.

Setting: We used data from the Chongqing Medical University Medical Data Science Academy in Chongqing, China, which contains data from seven tertiary hospitals.

Participants: Data from 3308 consecutive patients aged over 18 diagnosed with NSTEACS admitted to emergency departments of seven hospitals from August 2012 to March 2023 were retrospectively analysed.

Methods: Patients were divided into two groups based on CCI: CCI <3 as low CCI, and CCI ≥3 as high CCI. A propensity score matching (PSM) analysis using the 1:1 nearest neighbour matching method with a calliper value of 0.02 was adopted to control for differences between the comparison cohorts. Univariate and multivariate logistic regression analyses were carried out to produce ORs with 95% CIs to identify whether the CCI is a potential independent predictor of in-hospital outcomes in the matched cohort.

Primary And Secondary Outcome Measures: In-hospital mortality rate, major adverse cardiovascular events (MACEs), length of stay and readmission rate.

Results: 876 and 2432 patients belonged to the high CCI group (CCI ≥3) and the low CCI group (CCI <3). After PSM, 618 pairs were matched. There were significant differences in sociodemographic, clinical characteristics and laboratory tests between the two groups before PSM. The results were balanced and comparable after PSM (p>0.05). In patients with high CCI, in-hospital mortality, the incidence of MACEs, length of stay (LOS) and readmission rate were significantly higher compared with those with low CCI. Univariate analysis revealed that a higher CCI was associated with an increased incidence of MACEs, prolonged LOS and a higher readmission rate. Multivariate analysis demonstrated that even after adjusting for various confounding factors, a higher CCI remained an independent risk factor for an increased incidence of MACEs, prolonged LOS and higher readmission rate.

Conclusion: A high CCI not only increases the risk of in-hospital MACEs but also prolongs the length of stay and increases the readmission rate. We recommend that the CCI be used as a crucial risk indicator for clinical practitioners to identify and manage patients with a poor prognosis.