P3967Influence of peri-operative stroke on 5-year mortality following open heart surgery
Bibliographic record
Abstract
Introduction: Predictors of stroke following cardiac surgery are well documented. However, the influence of stroke on mortality, as well as predictors of mortality following stroke, have not been well explored. Purpose: To assess the influence of non-fatal peri-operative stroke on long-term mortality following cardiac surgery. Additionally, for those surviving a peri-operative stroke, predictors associated with long-term mortality were explored. Methods: A provincial registry which prospectively captures all coronary interventions, was accessed to identify all residents, ≥20 years of age, undergoing primary isolated CABG, valve, or combined CABG/valve surgery between April 2007 and December 2012. Rates of peri-operative stroke (fatal and non-fatal) were estimated for each surgery type. Logistic models were used to explore factors associated with peri-operative stroke. For long-term survival, stroke included only non-fatal, peri-operative stroke. Kaplan-Meier survival curves estimated mortality up to 5 years stratified by stroke, and by surgery type. Cox proportional hazards models were used to estimate the effect of stroke on risk of mortality, by surgery type. Among stroke patients undergoing CABG, factors associated with 5-year mortality were also explored.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".