Predictive Biochemical Model of Frailty and Mortality After Acute Myocardial Infarction.

Frailty, characterized by reduced resistance to stressors, is associated with adverse outcomes in patients with myocardial infarction. The Fried score is commonly used to assess frailty but has several limitations. This study aimed to evaluate the relation between frailty and blood biomarkers and their predictive value for long-term mortality using a biochemical model. A total of 2 cohorts of elderly patients (>65 years old) hospitalized for acute coronary syndrome were included. Geriatric assessments and several blood biomarkers were measured. The predictive models for frailty were developed using logistic regression. The survival models were also developed using Cox regression. Among 466 patients, 9 biomarkers were significantly associated with frailty. Between these biomarkers, white blood cells count, hemoglobin, and fibrinogen showed the highest predictive power. Model 1, without growth differentiation factor 15 (GDF-15), showed a better accuracy in predicting the mortality than the Fried score. Model 2, with GDF-15, had a stronger correlation with frailty but had a lower predictive power for survival. Frailty is associated with dysregulation in the physiological systems and several biomarkers were linked to this fact in our study. However, the inclusion of GDF-15 did not significantly improve the model's predictive ability. Frailty assessment using blood biomarkers can provide valuable prognostic information in elderly patients with acute coronary syndrome.

Clinical History and Detectable Troponin Concentrations below the 99th Percentile for Risk Stratification of Patients with Chest Pain and First Normal Troponin.

Decision-making is challenging in patients with chest pain and normal high-sensitivity cardiac troponin T (hs-cTnT; <99th percentile; <14 ng/L) at hospital arrival. Most of these patients might be discharged early. We investigated clinical data and hs-cTnT concentrations for risk stratification. This is a retrospective study including 4476 consecutive patients presenting to the emergency department with chest pain and first normal hs-cTnT. The primary endpoint was one-year death or acute myocardial infarction, and the secondary endpoint added urgent revascularization. The number of primary and secondary endpoints was 173 (3.9%) and 252 (5.6%). Mean hs-cTnT concentrations were 6.9 ± 2.5 ng/L. Undetectable (<5 ng/L) hs-cTnT (n = 1847, 41%) had optimal negative predictive value (99.1%) but suboptimal sensitivity (90.2%) and discrimination accuracy (AUC = 0.664) for the primary endpoint. Multivariable analysis was used to identify the predictive clinical variables. The clinical model showed good discrimination accuracy (AUC = 0.810). The addition of undetectable hs-cTnT (≥ or <5 ng/L; HR, hazard ratio = 3.80; 95% CI, confidence interval 2.27-6.35; p = 0.00001) outperformed the clinical model alone (AUC = 0.836, p = 0.002 compared to the clinical model). Measurable hs-cTnT concentrations (between detection limit and 99th percentile; per 0.1 ng/L, HR = 1.13; CI 1.06-1.20; p = 0.0001) provided further predictive information (AUC = 0.844; p = 0.05 compared to the clinical plus undetectable hs-cTnT model). The results were reproducible for the secondary endpoint and 30-day events. Clinical assessment, undetectable hs-cTnT and measurable hs-cTnT concentrations must be considered for decision-making after a single negative hs-cTnT result in patients presenting to the emergency department with acute chest pain.