An Assessment of Surgical Thromboprophylaxis in a Tertiary Care Center
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE) is a frequent surgical complication. The American College of Chest Physicians (ACCP) recommends implementation of pharmacologic thromboprophylaxis according to surgery type and VTE risk factors. We conducted a retrospective cohort study of surgical admissions to determine the rate and predictors of use and appropriate use of thromboprophylaxis as defined by the 2004 ACCP guidelines and to determine the risk of postoperative VTE. METHODS: Using data from an administrative health care database of the Centre Hospitalier Universitaire de Sherbrooke in the province of Quebec, we assembled a cohort of all consecutive surgical admissions in 2006 that met ACCP criteria for pharmacologic thromboprophylaxis and assessed rates of thromboprophylaxis presence and appropriateness. Multiple logistic regression was used to determine characteristics associated with thromboprophylaxis prescription. The incidence of postoperative VTE was assessed at 3 months. RESULTS: Of 2286 surgical admissions that met criteria for pharmacologic thromboprophylaxis, 81% received thromboprophylaxis and, of these, 31% received appropriate thromboprophylaxis as per ACCP guidelines. Male sex, age below 40 years, and short-duration hospitalization were significantly associated with absent and inappropriate thromboprophylaxis. Cancer diagnosis and heart failure within 3 months preceding surgery were protective against inappropriate thromboprophylaxis (OR 0.43, 95% CI [0.33-0.57] and 0.43 [0.26-0.70], respectively). At 3 months following surgery, 27 patients (1.2%) developed VTE. Patients who developed VTE were more likely to have had a previous VTE than patients who did not develop a VTE (P < .0001). CONCLUSIONS: Targeted recommendations, in particular concerning male patients with short duration hospitalization, may improve thromboprophylaxis compliance and appropriateness rates.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".