Abstract 8909: High Hospital-Specific Postoperative Troponin Testing Intensity Was Associated With Improved Outcomes After Major Vascular Surgery
Bibliographic record
Abstract
Background: Acute myocardial injury after non-cardiac surgery is associated with increased mortality and cardiovascular morbidity, but it is not known if systematic postoperative troponin testing will lead to improved patient outcomes. Methods: We defined a cohort of vascular surgery patients in Ontario, Canada from January 1, 2010 to December 31, 2017. Hospital-level troponin testing intensity (classified into tertiles) was determined by the proportion of patients that received postoperative troponin testing. Cox proportional hazards modeling was used to assess the association (expressed as hazard ratio [HR]) between hospital-specific testing intensity with 30-day and 1-year major adverse cardiovascular outcomes (MACE) while adjusting for patient-, surgery-, and hospital-level factors. MACE was defined as all-cause mortality, myocardial infarction, or coronary revascularization. Rates of postoperative consultations and new filled prescription medications (≥65y) were also assessed. Results: The cohort consisted of 18,467 patients. Mean age was 72y (SD9) and 74.0% were male. The proportion of patients that received postoperative troponin testing were 77.5%, 35.8%, and 21.6% in the high, medium, and low testing intensity groups, respectively. At 30-days, 5.3%, 5.3% and 6.5% of patients in high, medium, and low testing intensity group experienced MACE, respectively. Compared with low-testing intensity, high-testing intensity was associated with a lower hazard of 30-day MACE (HR 0.71; 95%CI 0.57-0.89) and at 1-year (HR 0.83; 95%CI 0.72-0.94; Figure 1). High testing intensity hospitals had higher rates of postoperative cardiology and internal medicine consults and higher rates of new prescription medications filled. Conclusion: Patients undergoing vascular surgery at hospitals with higher postoperative troponin testing intensity had better 30-day and 1-year outcomes than patients who had surgery at hospitals with lower testing intensity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".