Recent evolution in demographic and clinical characteristics and in-hospital morbidity in patients undergoing coronary surgery.
Bibliographic record
Abstract
BACKGROUND: Over the last 12 years, the demographic and clinical characteristics of patients undergoing myocardial revascularization surgery have evolved rapidly. The goal of our study was to analyze the evolution of these trends and the results of these surgical interventions. METHODS: We identified patients who underwent a first or second myocardial revascularization between 1993 and 2004, and we arbitrarily divided them into 2 groups: 1 cohort of patients who underwent surgery between 1993 and 1998 and 1 cohort of patients who underwent surgery between 1999 and 2004. We compared demographic and clinical characteristics between the 2 cohorts and determined which variables were significant predictors of morbidity and mortality. RESULTS: From 1993 to 2004, 12 202 patients underwent a first (95.5%) or second (4.5%) myocardial revascularization. Patients in the later cohort presented with a high-risk profile. They were older and had metabolic syndrome or diabetes and peripheral vascular disease. On the other hand, there were fewer active smokers in this group. Whereas the rate of postoperative infarction and renal insufficiency was higher in the second cohort, this group had a lower incidence of stroke and prolonged mechanical ventilation and shorter hospital stays. Overall, observed mortality decreased in spite of a steady increase in predicted mortality. Identified predictors of mortality were age, stroke, female sex, nonelective surgery, renal insufficiency, peripheral vascular disease, chronic obstructive pulmonary disease, ventricular dysfunction and stenosis of the left main trunk. CONCLUSION: Our study confirmed current trends that show an increase in the at-risk population with dysmetabolic syndrome in cardiac surgery, as well as constant improvements in tertiary care in anesthesia and coronary 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 | 0.001 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".