Multifaceted Intervention to Prevent Venous Thromboembolism in Patients Hospitalized for Acute Medical Illness: A Multicenter Cluster-Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Misuse of thromboprophylaxis may increase preventable complications for hospitalized medical patients. OBJECTIVES: To assess the net clinical benefit of a multifaceted intervention in emergency wards (educational lectures, posters, pocket cards, computerized clinical decision support systems and, where feasible, electronic reminders) for the prevention of venous thromboembolism. PATIENTS/METHODS: Prospective cluster-randomized trial in 27 hospitals. After a pre-intervention period, centers were randomized as either intervention (n = 13) or control (n = 14). All patients over 40 years old, admitted to the emergency room, and hospitalized in a medical ward were included, totaling 1,402 (712 intervention and 690 control) and 15,351 (8,359 intervention and 6,992 control) in the pre-intervention and intervention periods, respectively. RESULTS: Symptomatic venous thromboembolism or major bleeding (primary outcome) occurred at 3 months in 3.1% and 3.2% of patients in the intervention and control groups, respectively (adjusted odds ratio: 1.02 [95% confidence interval: 0.78-1.34]). The rates of thromboembolism (1.9% vs. 1.9%), major bleedings (1.2% vs. 1.3%), and mortality (11.3% vs. 11.1%) did not differ between the groups. Between the pre-intervention and intervention periods, the proportion of patients who received prophylactic anticoagulant treatment more steeply increased in the intervention group (from 35.0% to 48.2%: +13.2%) than the control (40.7% to 44.1%: +3.4%), while the rate of adequate thromboprophylaxis remained stable in both groups (52.4% to 50.9%: -1.5%; 49.1% to 48.8%: -0.3%). CONCLUSIONS: Our intervention neither improved adequate prophylaxis nor reduced the rates of clinical events. New strategies are required to improve thromboembolism prevention for hospitalized medical patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT01212393.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".