Key result
GRACE 2.0 score strongly predicts in-hospital mortality in Kenyan ACS patients but shows modest 6-month accuracy.
Why the study?
Despite the high burden of coronary heart disease in Africa, little is known about appropriate risk stratification systems to predict outcomes in patients with ACS in this region.
Does the GRACE 2.0 risk score accurately predict in-hospital and 6-month mortality in patients with ACS in a Kenyan tertiary hospital?
Cohort (n=378)
No
Does the GRACE 2.0 risk score accurately predict in-hospital and 6-month mortality in patients with ACS in a Kenyan tertiary hospital?
Effect estimate: AUROC 0.87 for in-hospital mortality; AUROC 0.66 for 6-month mortality
Absolute Event Rate: 2.11% vs 12.7%
p-value: p=<0.001 for in-hospital mortality risk group differences and 0.028-<0.001 for 6-month mortality differences in risk groups
The GRACE 2.0 score accurately predicts in-hospital mortality for ACS patients in a Kenyan tertiary center but has limited discriminatory power for predicting 6-month post-discharge mortality.
GRACE 2.0 may aid in-hospital risk stratification in Kenyan ACS; leaves open its utility for 6-month prediction and external validation.
Introduction: The incidence of coronary heart disease (CHD) is rising globally. Despite the high burden of CHD in Africa, little is known about appropriate risk stratification systems that can be used to predict outcomes in patients with acute coronary syndromes (ACS) in this region. Methodology: This was a single-center retrospective cohort study conducted at the Aga Khan University hospital. Data was explored descriptively by summarizing categorical variables using frequencies/percentages and continuous variables using medians and interquartile ranges. Risk groups and mortality were compared using Fisher’s exact test or the chi-square test. The area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity were obtained from a binary logistic regression model with mortality as the outcome of interest. The model fit was assessed using Hosmer-Lemeshow statistics. Analysis was performed using R version 4.3.2 (2023– 10-31 ucrt) and p-value < 0.05 set as statistical significance. Results: 378 participants were enrolled. NSTEMI was diagnosed in 48.4% of participants and STEMI in 51.6%. ACS in-hospital mortality was 2.11% and 6-months mortality was 12.70%. NSTEMI in-hospital mortality was 0.55% (p = 0.45) and 15.92% (p = 0.028) at 6-months. STEMI in-hospital mortality was 3.72% (p < 0.001) and 18.23% (p < 0.001) at 6-months. The AUROC curve for in-hospital mortality was 0.87 and 0.66 for 6-month mortality, demonstrating acceptable discriminatory capacity. Calibration of the score using the Hosmer-Lemeshow model fit was appropriate (p = 0.999). Conclusion: The GRACE 2 score demonstrated good discriminative power and an acceptable goodness-of-fit for in-hospital outcomes in our setting, but was insufficiently accurate for reliably predicting 6-month post-discharge mortality.
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Nyanga et al. (2026) conducted a cohort in Adults with acute coronary syndromes (ACS) including NSTEMI and STEMI presenting to a private referral hospital in Kenya (n=378). GRACE 2.0 risk score assessment vs. Observed mortality outcomes without intervention was evaluated on In-hospital and 6-month post discharge mortality (AUROC 0.87 for in-hospital mortality; AUROC 0.66 for 6-month mortality, p=<0.001 for in-hospital mortality risk group differences and 0.028-<0.001 for 6-month mortality differences in risk groups). The GRACE 2.0 risk score demonstrated good discrimination for in-hospital mortality prediction with AUROC 0.87 but only modest discrimination for 6-month post discharge mortality with AUROC 0.66 in Kenyan ACS patients.
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