Qualitative troponin I estimation in the diagnosis of acute coronary syndromes in three rural hospitals.
Bibliographic record
Abstract
OBJECTIVE: To examine the utility of point-of-care qualitative troponin I (TnI) testing in patients with possible acute coronary syndromes (ACS). METHODS: A retrospective chart review of all patients undergoing qualitative TnI testing between September 2001 and February 2002 was conducted at the emergency departments of 3 rural hospitals in Alberta. We looked at the incidence of ACS, the comparison between TnI and creatine kinase (CK) testing and the timing of testing. RESULTS: Of the 235 patients tested, 8 had ST-elevation myocardial infarctions and 11 non ST-elevation infarctions. One patient had unstable angina with minimal myocardial damage. Qualitative TnI testing was positive in all 14 cases of infarction tested more than 6 hours after symptom onset, and CK elevation occurred in 15/17 cases (TnI sensitivity 1.0 [95% confidence interval (CI) 0.78-1.0], CK sensitivity 0.882 [95% CI 0.66-0.97]). There were 3 positive TnI tests and 33 raised CK levels in patients without evidence for ACS (TnI specificity 0.986 [95% CI 0.96-0.99], likelihood ratio [LR] 72.0 [95% CI 23.4-221.5]); CK specificity 0.847 [95% CI 0.79-0.89], LR 5.8 [95% CI 4.0-8.3]). In 44 patients (20.8%) TnI testing was inappropriately not repeated more than 6 hours after symptom onset. CONCLUSION: Qualitative TnI testing appears highly sensitive and more specific than CK estimation in detecting myocardial infarction. Diagnostic algorithms must emphasize the importance of testing 6 or more hours after symptom onset.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".