Venous thromboembolism in orthopaedic oncology
Bibliographic record
Abstract
Aims Malignancy and surgery are risk factors for venous thromboembolism (VTE). We undertook a systematic review of the literature concerning the prophylactic management of VTE in orthopaedic oncology patients. Methods MEDLINE (PubMed), EMBASE (Ovid), Cochrane, and CINAHL databases were searched focusing on VTE, deep vein thrombosis (DVT), pulmonary embolism (PE), bleeding, or wound complication rates. Results In all, 17 studies published from 1998 to 2018 met the inclusion criteria for the systematic review. The mean incidence of all VTE events in orthopaedic oncology patients was 10.7% (1.1% to 27.7%). The rate of PE was 2.4% (0.1% to 10.6%) while the rate of lethal PE was 0.6% (0.0% to 4.3%). The overall rate of DVT was 8.8% (1.1% to 22.3%) and the rate of symptomatic DVT was 2.9% (0.0% to 6.2%). From the studies that screened all patients prior to hospital discharge, the rate of asymptomatic DVT was 10.9% (2.0% to 20.2%). The most common risk factors identified for VTE were endoprosthetic replacements, hip and pelvic resections, presence of metastases, surgical procedures taking longer than three hours, and patients having chemotherapy. Mean incidence of VTE with and without chemical prophylaxis was 7.9% (1.1% to 21.8%) and 8.7% (2.0% to 23.4%; p = 0.11), respectively. No difference in the incidence of bleeding or wound complications between prophylaxis groups was reported. Conclusion Current evidence is limited to guide clinicians. It is our consensus opinion, based upon logic and deduction, that all patients be considered for both mechanical and chemical VTE prophylaxis, particularly in high-risk patients (pelvic or hip resections, prosthetic reconstruction, malignant diagnosis, presence of metastases, or surgical procedures longer than three hours). Additionally, the surgeon must determine, in each patient, if the risk of haemorrhage outweighs the risk of VTE. No individual pharmacological agent has been identified as being superior in the prevention of VTE events. Cite this article: Bone Joint J 2020;102-B(12)1743:–1751.
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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 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".