For patients with chest pain who are deemed clinically to be low risk and discharged home from the emergency department (ED), it is unclear whether further laboratory tests can improve risk stratification. Here, we investigated the utility of a clinical chemistry score (CCS), which comprises plasma glucose, the estimated glomerular filtration rate, and high-sensitivity cardiac troponin (I or T) to generate a common score for risk stratification. In a cohort of 14,676 chest pain patients in the province of Ontario, Canada and who were discharged home from the ED (November 2012–February 2013 and April 2013–September 2015) we evaluated the CCS as a risk stratification tool for all-cause mortality, plus hospitalization for myocardial infarction or unstable angina (primary outcome) at 30, 90, and 365 days post-discharge using Cox proportional hazard models. At 30 days the primary outcome occurred in 0.3% of patients with a CCS < 2 (n = 6404), 0.9% of patients with a CCS = 2 (n = 4336), and 2.3% of patients with a CCS > 2 (n = 3936) (p < 0.001). At 90 days, patients with CCS < 2 (median age = 52y (IQR = 46–60), 59.4% female) had an adjusted HR = 0.51 (95% confidence interval (CI) = 0.32–0.82) for the composite outcome and patients with a CCS > 2 (median age = 74y (IQR = 64–82), 48.0% female) had an adjusted HR = 2.80 (95%CI = 1.98–3.97). At 365 days, 1.3%, 3.4%, and 11.1% of patients with a CCS < 2, 2, or >2 respectively, had the composite outcome (p < 0.001). In conclusion, the CCS can risk stratify chest pain patients discharged home from the ED and identifies both low- and high-risk patients who may warrant different medical care.
Utilizing machine learning dimensionality reduction for risk stratification of chest pain patients in the emergency department