Inpatient compliance with venous thromboembolism prophylaxis after orthopaedic trauma: results from a randomized controlled trial of aspirin versus low molecular weight heparin
Bibliographic record
Abstract
Abstract Objectives: To compare inpatient compliance with venous thromboembolism prophylaxis regimens. Design: A secondary analysis of patients enrolled in the ADAPT (A Different Approach to Preventing Thrombosis) randomized controlled trial. Setting: Level I trauma center. Patients/Participants: Patients with operative extremity or any pelvic or acetabular fracture requiring venous thromboembolism prophylaxis. Intervention: We compared patients randomized to receive either low molecular weight heparin (LMWH) 30 mg or aspirin 81 mg BID during their inpatient admission. Main Outcome Measurements: The primary outcome measure was the number of doses missed compared with prescribed number of doses. Results: A total of 329 patients were randomized to receive either LMWH 30 mg BID (164 patients) or aspirin 81 mg BID (165 patients). No differences observed in percentage of patients who missed a dose (aspirin: 41.2% vs LMWH: 43.3%, P = .7) or mean number of missed doses (0.6 vs 0.7 doses, P = .4). The majority of patients (57.8%, n = 190) did not miss any doses. Missed doses were often associated with an operation. Conclusions: These data should reassure clinicians that inpatient compliance is similar for low molecular weight heparin and aspirin regimens.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".