Identification of patients with suspected NSTE-ACS in the observe zone: evaluating GRACE 1.0 score and a biomarker panel for risk stratification and management optimization

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Abstract Background Current guidelines recommend additional diagnostic work-up for patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) triaged in the observe zone using accelerated diagnostic protocols. This study assessed the effectiveness of combining the Global Registry of Acute Coronary Events (GRACE) 1.0 score with additional non-cardiospecific biomarkers for risk stratification in the observe zone. Methods A total of 6,789 patients with suspected NSTE-ACS were enrolled over 24 months, with 961 (21.8%) assigned to the observe zone. A classification and regression tree (CART) analysis dichotomized risk using the GRACE score and additional biomarkers beyond high-sensitivity cardiac troponin including C-reactive protein <10mg/dL, N-terminal pro-B-type natriuretic peptide <300ng/L, D-dimers <5mg/L, estimated glomerular filtration rate >30ml/min/1.73m², Copeptin <10pmol/L, and haemoglobin >10g/dL. The primary endpoint was 1-year all-cause mortality, validated using the Biomarkers in Acute Cardiac Care (BACC) cohort. Results A low GRACE 1.0 score <109 points was found in 37.6% of observe zone patients, showing a negative predictive value of 98.6% and sensitivity of 89.8% for death. Adding biomarker information reduced predicted 1-year-mortality from 1.38% with the GRACE score alone to 0.46% when none of the biomarkers were above cutoff (prevalent in 22.7%). The proportion of protocol-eligible patients increased from 22.7% to 37.6%, with no events within 30 days. Findings were confirmed in the BACC cohort. Conclusions A low GRACE 1.0 score combined with ≤1 elevated biomarker significantly improves mortality prediction in the observe zone, helping identify low-risk patients for further out-of-hospital diagnostic work-up, potentially decongesting crowded emergency departments.Comparison of algorithm performancesTime to event analysis.

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