Performance of the high-sensitivity troponin assay in diagnosing acute myocardial infarction: systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: High-sensitivity cardiac troponin assays have been adopted by many clinical centres worldwide; however, clinicians are uncertain how to interpret the results. We sought to assess the utility of these assays in diagnosing acute myocardial infarction (MI). METHODS: We carried out a systematic review and meta-analysis of studies comparing high-sensitivity with conventional assays of cardiac troponin levels among adults with suspected acute MI in the emergency department. We searched MEDLINE, EMBASE and Cochrane databases up to April 2013 and used bivariable random-effects modelling to obtain summary parameters for diagnostic accuracy. RESULTS: We identified 9 studies that assessed the use of high-sensitivity troponin T assays (n = 9186 patients). The summary sensitivity of these tests in diagnosing acute MI at presentation to the emergency department was estimated to be 0.94 (95% confidence interval [CI] 0.89-0.97); for conventional tests, it was 0.72 (95% CI 0.63-0.79). The summary specificity was 0.73 (95% CI 0.64-0.81) for the high-sensitivity assay compared with 0.95 (95% CI 0.93-0.97) for the conventional assay. The differences in estimates of the summary sensitivity and specificity between the high-sensitivity and conventional assays were statistically significant (p < 0.01). The area under the curve was similar for both tests carried out 3-6 hours after presentation. Three studies assessed the use of high-sensitivity troponin I assays and showed similar results. INTERPRETATION: Used at presentation to the emergency department, the high-sensitivity cardiac troponin assay has improved sensitivity, but reduced specificity, compared with the conventional troponin assay. With repeated measurements over 6 hours, the area under the curve is similar for both tests, indicating that the major advantage of the high-sensitivity test is early diagnosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".