Post-operative oral chemoprophylaxis in patients undergoing hip arthroscopy mitigates VTE risk with a low side-effect profile
Bibliographic record
Abstract
Hip arthroscopy (HA) has increased exponentially over the last decade. A recent systematic review found that the risk of venous thromboembolism (VTE) is 2%. This was higher than previous reports which may have underestimated the true incidence of VTE in HA. Thus, protocols to mediate VTE may be more necessary than previously thought. The aim of this article is to present a VTE prevention protocol and evaluate its subsequent efficacy. This is a prospective study of 880 consecutive HA cases. All patients were treated according to a predetermined VTE protocol which classified patients as high (≥1 risk factors) or low (no risk factors) risk for post-operative VTE. In high-risk patients, the protocol followed that of low-risk patients but additionally included rivaroxaban for 2 weeks post-operatively. The incidence of VTE was recorded and analysed in this study. A total of 880 HA cases at an average age of 35.4 years were evaluated, with 76.6% (n = 674) undergoing labral repair and concomitant cam and/or pincer resection, 17.2% (n = 151) of cases for isolated labral tear repaired, and 6.1% (n = 55) classified as other. The overall incidence of VTE was 0.45%. The incidence of VTE was 1.2% and 0.16% in high- and low-risk groups, respectively. Oral VTE prophylaxis was not associated with post-operative complications. This study demonstrated a lower rate of VTE in both risk groups. It highlights the value of a predetermined risk-adjusted protocol to VTE prophylaxis. Rivaroxaban prophylaxis is safe and efficacious in HA with a low associated morbidity.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".