P2748The PROTROPICS feasibility: prognostic value of elevated troponins in critical illness
Bibliographic record
Abstract
Background: Troponins are sensitive and specific markers of cardiac injury, most commonly used in clinical practice for the diagnosis of myocardial infarction (MI). Critically ill patients frequently have elevated troponins. Whether fulfilling criteria for MI or not, observational evidence to date shows that elevated troponins in critical illness are associated with an increased risk of death when adjusted for other confounding factors. Purpose: We aimed to assess the feasibility of a large study to ascertain the prognostic value of troponin elevations on hospital mortality in critically ill patients. Methods: We recruited patients in 4 academic medical and surgical intensive care units (ICUs) in Canada. All patients admitted to participating ICUs during the 1 month enrolment period were eligible. We excluded cardiac surgical patients and patients who were admitted and either died or were discharged within 12 hours. Using a deferred consent model, while the patients were in the ICU, we obtained high sensitivity troponin T and ECGs daily for 1 week, every other day for 3 weeks and then weekly for 2 months. Clinicians were blinded to the study troponins and ECGs. Data on the patients' symptoms, medications, laboratory results, and clinical events were also collected. We defined MI using the third universal definition. ECG adjudicators were blinded to the troponin measurements. Patients were followed until hospital discharge, death or for a maximum of 3 months.
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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 | 0.004 | 0.011 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".