ArticleEuropean heart journal. Acute cardiovascular care2025
Clinical derivation and data simulated validation of rule-out and rule-in algorithms for the Siemens Atellica IM high-sensitivity cardiac troponin I assay.
Article in European heart journal. Acute cardiovascular care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Article
- Analytical Error of Cardiac Troponin and Impact on the Performance of Accelerated Diagnostic Protocols in Patients with Acute Chest Pain.Clinical chemistry · 2025Observational
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15 authors.
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Abstract
aimsThis prospective, two-centre study derived and validated predictive algorithms for the Siemens Atellica IM high-sensitivity cardiac troponin I (hs-cTnI) assay in the emergency department (ED). METHODS AND
resultsAlgorithms for predicting 30-day myocardial infarction (MI) Types 1 and 2 and death or non-ST-elevation MI (NSTEMI, Types 1 and 2) at index admission were developed from a derivation cohort of 1896 patients and validated using a synthetic data set with nearly 1 million patient cases. Performance was compared with the European Society of Cardiology algorithms for hs-cTnT (Roche Diagnostics) and hs-cTnI (Abbott Diagnostics). An admission hs-cTnI concentration < 5 ng/L had a negative predictive value (NPV) and sensitivity for 30-day MI or death of 99.5-99.7% and 98.1-98.8%, respectively, in the derivation cohort and validation data set. The NPV and sensitivity were ≥99.7% and ≥98.8% for ruling out index NSTEMI. A 0- to 1-h algorithm with baseline hs-cTnI concentration < 10 ng/L and Δ change < 3 ng/L had NPV of ≥99.5% and sensitivity ≥ 97.3% for predicting 30-day MI or death and a ≥99.5% sensitivity and NPV for index NSTEMI. Rule-in algorithms of either 0-h hs-cTnI ≥ 120 ng/L or 0- to 1-h Δ change ≥ 12 ng/L had positive predictive value ≥ 73% and specificity > 96% for 30-day MI or death and index NSTEMI. The results were comparable with established hs-cTn algorithms.
conclusionThis study presents Siemens Atellica hs-cTnI algorithms for diagnosis and risk prediction in the ED with performance comparable with established hs-cTnT (Roche) and hs-cTnI (Abbott) algorithms.
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