What is the clinical evidence from this study?

Study design: Cohort. Population: Acute Coronary Syndrome (n=19237). Intervention: ACTION risk model vs. GRACE risk model. Primary outcome: In-hospital mortality prediction (c-index) (c-index 0.945, 95% CI 0.922-0.955, p=0.0004).

December 19, 2023Open Access

Performance of the Risk Scores for Predicting In-Hospital Mortality in Patients with Acute Coronary Syndrome in a Chinese Cohort

Key Result

The ACTION risk model demonstrated the highest accuracy in predicting in-hospital mortality with a c-index of 0.945, outperforming the GRACE model, though its calibration was unsatisfactory.

Study Design

Type

Cohort (n=19,237)

Multicenter

Structured PICO

Do the ACTION, CPACS, TIMI, or GRACE 2.0 risk models improve prediction of in-hospital mortality compared to the standard GRACE model in Chinese patients with acute coronary syndrome?

Population

19,237 Chinese patients with acute coronary syndrome who underwent coronary angiography or percutaneous coronary intervention, evaluated for in-hospital mortality.

Exposure

Risk assessment using the ACTION, CPACS, TIMI, and GRACE 2.0 scoring models

Comparator

Risk assessment using the standard GRACE model

Outcome

In-hospital mortality (defined as any postprocedural death within the same hospital admission)hard clinical

The standard GRACE score remains the most robust and well-calibrated model for predicting in-hospital mortality in Chinese ACS patients, outperforming newer or region-specific models like ACTION and CPACS in calibration.

Main Result

Effect estimate: c-index 0.945 (95% CI 0.922-0.955)

Absolute Event Rate: 0.945% vs 0.926%

p-value: p=0.0004

Limitations

Missing data points (e.g., 2925 missing values for weight) required imputation using the random forest algorithm.
High c-index values may have been influenced by the lower incidence of death events and the large number of low-risk individuals in the cohort.
The lower mortality observed may be attributed to an overestimated proportion of unstable angina diagnoses in China.

Abstract

Background: The prognosis of patients with acute coronary syndrome (ACS) varies greatly, and risk assessment models can help clinicians to identify and manage high-risk patients. While the Global Registry of Acute Coronary Events (GRACE) model is widely used, the clinical pathways for acute coronary syndromes (CPACS), which was constructed based on the Chinese population, and acute coronary treatment and intervention outcomes network (ACTION) have not yet been validated in the Chinese population. Methods: Patients with ACS who underwent coronary angiography or percutaneous coronary intervention from 2011 to 2020, were retrospectively recruited and the appropriate corresponding clinical indicators was obtained. The primary endpoint was in-hospital mortality. The performance of the GRACE, GRACE 2.0, ACTION, thrombolysis in myocardial infarction (TIMI) and CPACS risk models was evaluated and compared. Results: A total of 19,237 patients with ACS were included. Overall, in-hospital mortality was 2.2%. ACTION showed the highest accuracy in predicting discriminated risk (c-index 0.945, 95% confidence interval CI 0.922–0.955), but the calibration was not satisfactory. GRACE and GRACE 2.0 did not significantly differ in discrimination (p = 0.1480). GRACE showed the most accurate calibration in all patients and in the subgroup analysis of all models. CPACS (c-index 0.841, 95% CI 0.821–0.861) and TIMI (c-index 0.811, 95% CI 0.787–0.835) did not outperform (c-index 0.926, 95% CI 0.911–0.940). Conclusions: In contemporary Chinese ACS patients, the ACTION risk model’s calibration is not satisfactory, although outperformed the gold standard GRACE model in predicting hospital mortality. The CPACS model developed for Chinese patients did not show better predictive performance than the GRACE model.

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