The CLUE postsurgery VTE risk instrument for abdominal and pelvic surgery: validation of patient risk factor component
Bibliographic record
Abstract
ABSTRACT: Venous thromboembolism (VTE) remains a major postoperative risk. Systematic reviews have established procedure-specific VTE risk estimates, which form 1 component of the CLUE postsurgery VTE risk instrument. The instrument also incorporates patient-level factors, including age (≥75 years), body mass index (≥35 kg/m2), and prior VTE, to stratify overall risk. However, the patient risk factor component has not been formally validated. Therefore, we conducted the validation using data from the VISION study, a prospective, international cohort of 11 636 patients undergoing major general abdominal, urologic, or gynecologic surgery. Thirty-day postoperative VTE incidence was analyzed using modified Poisson regression. The instrument classified patients into low- (72%), medium- (25%), and high-risk (4%) categories. VTE occurred in 97 patients (0.8%). Compared to the low-risk group, the relative risk of VTE was 1.56 (95% confidence interval [CI], 1.01-2.43) for medium-risk patients and 3.60 (95% CI, 1.90-6.83) for high-risk patients. Among patients who did not receive antithrombotic medication, relative risks increased to 1.91 for medium-risk patients and 5.41 for high-risk patients. The CLUE postsurgery VTE risk instrument, using 3 widely available patient-level factors, accurately classifies patients into substantially different categories of relative VTE risk. This validated patient component complements procedure-specific absolute risk estimates derived from prior systematic reviews. To support evidence-based thromboprophylaxis decisions, the instrument is now available through an interactive online platform (www.cluevte.org).
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".