10 Current Utilisation of High-Sensitivity Troponin; Does it Improve Our Accuracy in Diagnosing Acute Myocardial Infarction?
Bibliographic record
Abstract
Introduction High sensitivity troponin assays (Hs-Tn) are part of the diagnostic criteria for identifying myocardial infarction, in the presence of ischaemic chest pain, with or without ECG changes. However, the increased sensitivity of the new generation HS-Tn assays has come at the expense of a marked reduction in specificity, which is further confounded when sampled inappropriately in the absence of clinical features suggestive of an acute coronary syndrome (ACS). We audited the utilisation of HS-Tn in both the emergency and acute medical departments at our institution. Methods A retrospective observational audit was performed before and after formal education was delivered to the hospital regarding use of HS-TnI, between October 2013 and July 2014. The audit was assessed against current European Society of Cardiology guidelines in the use of HS-Tn in diagnosing ACS. The main parameters assessed were presence of symptoms or ECG findings in keeping with an ischaemic-episode and the concordance of the initial diagnosis with the subsequent cardiologist-guided diagnosis. Results Ninety-six consecutive patients were sampled in the two audit cycles (50 in the initial cohort and 46 in the re-audit. All patients had HS-TnI assayed on admission and initial treatment with anti-platelet and anti-thrombotic therapy commenced. 46% (n = 23/50) (Figure 1) vs. 67% (n = 31/46) sampled in the presence of chest pain +/- ECG changes. 8% (n = 4/50) vs. 11% (n = 5/46) were treated for an ACS following cardiology review, with 92% (n = 46/50) vs. 89% (n = 41/46), having no evidence of ACS. 52% (n = 26/46) (Figure 2) vs. 34% (14/41) of the cohorts had an elevated HS-TnI (>0.04 mcg/L), attributable to concurrent sepsis, renal dysfunction or tachy-arrhythmias. Conclusion HS-Tn is frequently performed in the absence of clinical features or clinical suspicion of an ACS, reducing the specificity of the test. There are important clinical and financial implications with the inappropriate use of Troponin assays outside of the context of a clinical suspicion of an ACS. Improved education and adherence to guidelines is paramount in improving clinical and diagnostic accuracy of this cardiac biomarker in identifying ACS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".