Troponin I after Cardiac Surgery and 30-Day Mortality
Bibliographic record
Abstract
Devereaux et al. corroborate the independent negative prognostic effect of increased levels of cardiac troponin I after cardiac surgery,1 reinforcing the notion derived from a meta-analysis of earlier studies2 that the predictive thresholds of 5670 ng per liter after coronary-artery bypass grafting (CABG) and aortic-valve replacement or repair and of 12,981 ng per liter after other cardiac surgery are much higher than the cut-off points endorsed in guidelines3 and provide sufficient prognostic information for identifying those patients with levels below these thresholds for whom there is a low likelihood of a complicated course. Although the authors were unable to differentiate ischemic myocardial damage from procedural injury, it is well recognized that levels of cardiac troponin I increase almost universally after cardiac surgery, and the magnitude of this increase varies depending on the surgical procedure performed and the anesthesia and cardioplegia used.1,4 We believe that their data beg the question of what is now the truly abnormal value of cardiac troponin I after cardiac surgery, because they have moved the threshold bar to particularly high values, thereby suggesting that caution has to be paid as to the clinical judgment used when integrating the variable elevated cardiac troponin I levels into the complex puzzle of other known powerful independent predictors of worse postoperative outcome.1
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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 | 0.003 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.011 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".