Venous Thromboembolism in Cancer Patients Following Major Surgery
Bibliographic record
Abstract
Abstract Abstract 5253 Background: Venous thromboembolism (VTE), encompassing deep vein thrombosis (DVT) and pulmonary embolism (PE), is common in cancer patients and surgery is an important risk factor. The timing of post-operative VTE in cancer patients is uncertain. Objectives: We used the administrative health claims (RAMQ) and hospital discharge (MED ECHO) databases of Quebec, Canada to describe the occurrence of post-operative VTE in cancer patients and to explore anticoagulant use following hospital discharge. Methods: Using a previously defined cohort of individuals with a discharge diagnosis of VTE between January 1, 1994 and December 31, 2004 in MED ECHO which systematically records information on all hospital admissions in the province of Quebec, we identified patients with a cancer diagnosis in the 12 months preceding the VTE and who had major surgery in the 3 months prior to the VTE. Discharge diagnoses were defined according to the 9th edition International Classification of Diseases codes and surgical procedures according to the Canadian classification of diagnostic, therapeutic, and surgical procedures. Results: In all, 2706 patients with VTE had a cancer diagnosis and underwent major surgery in the 3 months preceding the VTE. The mean age was 65.9 years (SD=12.6) and 54% were female. The most common cancer was gastrointestinal (38%), and general surgery was the most frequent procedure (48%). The mean hospital stay was 29.8 days (SD=35.3). The mean time to VTE was 34.8 days (SD=68.3). In all, 34% of VTE events occurred after discharge. Among patients with post-discharge VTE (n=917), 4% had an out-patient anticoagulant prescription at discharge. Conclusions: Post-operative VTE in cancer patients often occurs after hospital discharge. This suggests that the risk of VTE extends beyond the immediate postoperative period. Prospective studies are needed to determine the effectiveness and safety of thromboprophylaxis beyond discharge in cancer patients undergoing surgery. Disclosures: Tagalakis: Sanofi Aventis: Research Funding; Pfizer: Research Funding.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".