Incidence of Deep Vein Thrombosis and Pulmonary Embolus Following Periacetabular Osteotomy
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism, a known complication of orthopaedic procedures, is thought to be more prevalent following hip surgery. Venous thromboembolism risk assessment and appropriate prophylaxis according to the American College of Chest Physicians guidelines has become the standard of care. However, it is accepted that venous thromboembolism prophylaxis is associated with potential adverse sequelae including hematoma, wound drainage, and infection. Little is known regarding the incidence of venous thromboembolism following periacetabular osteotomy and the necessity for and method of routine prophylaxis. METHODS: A total of 1067 periacetabular osteotomies performed at six North American centers utilizing different methods of prophylaxis against venous thromboembolism were analyzed for type of prophylaxis and incidence of clinically symptomatic venous thromboembolism. RESULTS: There were four cases of pulmonary embolus and seven cases of deep vein thrombosis. There were no reported deaths. The crude incidence of clinically symptomatic venous thromboembolism was 9.4 per 1000 procedures. CONCLUSIONS: The risk from chemoprophylaxis and the development of hematoma may be greater than the risk of clinically important venous thromboembolism in patients undergoing periacetabular osteotomy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".