Outcome Reporting in Cardiac Surgery Trials: Systematic Review and Critical Appraisal
Bibliographic record
Abstract
BACKGROUND: There is currently no accepted standard for reporting outcomes following cardiac surgery. The objective of this paper was to systematically review the literature to evaluate the current use and definition of perioperative outcomes reported in cardiac surgery trials. METHODS AND RESULTS: We reviewed 5 prominent medical and surgical journals on Medline from January 1, 2010, to June 30, 2014, for randomized controlled trials involving coronary artery bypass grafting and/or valve surgery. We identified 34 trials meeting inclusion criteria. Sample sizes ranged from 57 to 4752 participants (median 351). Composite end points were used as a primary outcome in 56% (n=19) of the randomized controlled trials and as a secondary outcome in 12% (n=4). There were 14 different composite end points. Mortality at any time (all-cause and/or cardiovascular) was reported as an individual end point or as part of a combined end point in 82% (n=28), myocardial infarction was reported in 68% (n=23), and bleeding was reported in 24% (n=8). Patient-centered outcomes, such as quality of life and functional classification, were reported in 29% (n=10). Definition of clinical events such as myocardial infarction, stroke, renal failure, and bleeding varied considerably among trials, particularly for postoperative myocardial infarction and bleeding, for which 8 different definitions were used for each. CONCLUSIONS: Outcome reporting in the cardiac surgery literature is heterogeneous, and efforts should be made to standardize the outcomes reported and the definitions used to ascertain them. The development of standardizing outcome reporting is an essential step toward strengthening the process of evidence-based care in cardiac surgery.
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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 | 0.258 | 0.597 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.021 | 0.014 |
| Bibliometrics | 0.022 | 0.020 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".