Estimation of Values below the Limit of Detection of a Contemporary Sensitive Troponin I Assay Improves Diagnosis of Acute Myocardial Infarction

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Erscheinungsjahr:
2015
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Beschreibung:
  • BACKGROUND: The limit of detection (LoD) is the minimal amount of a substance that can be consistently detected. In the diagnosis of acute myocardial infarction (AMI) many patients present with troponin concentrations below the LoD of contemporary sensitive cardiac troponin I (cs-cTnI) assays. These censored values below the LoD influence the diagnostic performance of these assays compared to highly sensitive cTnI (hs-cTnI) assays. Therefore we assessed the impact of a new approach for interpolation of the left-censored data of a cs-cTnI assay in the evaluation of patients with suspected AMI.

    METHODS: Our posthoc analysis used a real world cohort of 1818 patients with suspected MI. Data on cs-cTnI was available in 1786 patients. As a comparator the hs-cTnI version of the assay was used. To reconstruct quantities below the LoD of the cs-cTnI assay, a gamma regression approach incorporating the GRACE (Global Registry of Acute Coronary Events) score variables was used.

    RESULTS: Censoring of cs-cTnI data below the LoD yielded weaker diagnostic information [area under the curve (AUC), 0.781; 95% CI, 0.731-0.831] regarding AMI compared to the hs-cTnI assay (AUC, 0.949; CI, 0.936-0.961). Use of our model to estimate cs-cTnI values below the LoD showed an AUC improvement to 0.921 (CI, 0.902-0.940). The cs-cTnI LoD concentration had a negative predictive value (NPV) of 0.950. An estimated concentration that was to be undercut by 25% of patients presenting with suspected AMI was associated with an improvement of the NPV to 0.979.

    CONCLUSIONS: Estimation of values below the LoD of a cs-cTnI assay with this new approach improves the diagnostic performance in evaluation of patients with suspected AMI.

Lizenz:
  • info:eu-repo/semantics/restrictedAccess
Quellsystem:
Forschungsinformationssystem des UKE

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oai:pure.atira.dk:publications/78bf2d17-3053-49d4-a63c-a4a834728dfa