Troponin Testing After Noncardiac Surgery in Ontario: An Observational Study
Bibliographic record
Abstract
BACKGROUND: In 2017, the Canadian Cardiovascular Society (CCS) published guidelines recommending postoperative troponin surveillance in higher-risk patients having major noncardiac surgery. The objective of this study was to evaluate the proportion of major noncardiac surgery patients that would meet recommendations for troponin testing and to assess the rates of troponin testing before guideline adoption. METHODS: We conducted a retrospective observational study of patients age 40 to 105 undergoing a subset of major noncardiac surgeries that included orthopedics, gynecology, general, urology, vascular, and thoracic surgeries in Ontario, Canada from January 1, 2010 to December 31, 2017. The primary outcomes were the proportion of patients recommended for testing based on the guidelines and rates of troponin testing within 2 days of surgery. RESULTS: We identified 257,704 patients who underwent noncardiac surgery. Mean age was 66.4 ± 11.9 years, and 12.4% underwent urgent surgery. Applying the CCS guidelines, 71.2% of elective surgery patients and 81.0% of urgent surgery patients would have met recommendations for postoperative troponin screening, whereas 10.8% and 27.1% received postoperative troponin testing, respectively. Most elective surgery patients met recommendations for testing based on the age criterion (54.9%), followed by diabetes (24.6%) and high-risk surgery (22.7%) criteria. Troponin testing varied substantially by types of surgery: highest for open abdominal aortic aneurisms and lowest for hysterectomies. CONCLUSIONS: Based on the CCS guidelines, most patients undergoing the subset of surgeries assessed would have met recommendations for routine troponin testing. In contrast, routine troponin testing before guideline adoption was done infrequently in Ontario, with substantial variations based on the surgery type.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".