THE EFFECT OF THROMBOPROPHYLAXIS ON THE INCIDENCE OF POSTOPERATIVE VENOUS THROMBOEMBOLISM FOLLOWING HIGH-ENERGY FRACTURES OF THE LOWER LEG: A RETROSPECTIVE COHORT STUDY
Bibliographic record
Abstract
Venous thromboembolisms (VTE) (deep vein thrombosis [DVT] or pulmonary embolism [PE]) are frequent complications following high-energy fractures. In this context, VTEs are most often due to vascular injury and/or to immobilization. Post-operative thromboprophylaxis is recommended for patients presenting with a high-energy pelvic or hip fracture whereas patients with ankle and foot fractures do not need chemoprophylaxis. Guidelines are not as clear when it comes to patients presenting with high-energy fractures around then knee. The objective of this study was to describe the incidence of post-operative VTEs in patients admitted for high-energy fractures around the knee. We included in this retrospective cohort study all adult patients who underwent surgery for a high-energy fracture around the knee between 2011 and 2020 at (hospital name). Included fractures were of the femoral diaphysis; the distal femur; the proximal tibia; the tibial shaft; as well as knee dislocations. Patients presenting with fractures that required thromboprophylaxis or with a pathological fracture as well as patients under anticoagulation for a pre-existing condition were excluded from this study. Collected data concerned demographics, hospitalization and surgery dates, presence of VTE risk factors, thromboprophylaxis, and the occurrence of VTE following surgery were collected. We analyzed 985 patient files out of the 2217 identified. Seventy-three patients (7.4%) suffered a VTE (63 DVT, 17 PE), of which 59 (80%) had received some form of thromboprophylaxis. Patients who suffered a VTE were significantly older (52.3 vs 43.7 years old; p < 0 .0001) or had a previous history of either DVT or PE (p=0.0009). Twenty-nine had to have an external fixator prior to definitive fracture fixation (p < 0 .0001) and half were polytraumatized (p=0.04). Distal femur fractures were at higher risk of VTE (OR 2.19; 95% CI 1.18–4.09) In our cohort, patients more at risk of suffering from a VTE following surgery for high-energy lower leg fractures were significantly older; had a previous history of VTE; were polytraumatized; had to have an external fixator; or presented with a distal femur fracture. Most patients who suffered a VTE were under thromboprophylaxis. More aggressive thromboprophylaxis should be administered to high-risk patients.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 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".