Long-term incidence of venous thromboembolic events following cystectomy: A population-based analysis.
Bibliographic record
Abstract
288 Background: Cancer and immobility both contribute to the development of venous thromboembolic events (VTE), including pulmonary embolism and deep vein thrombosis. As such, patients undergoing radical cystectomy for bladder cancer are at elevated risk. We sought to assess the long-term incidence of VTE among all patients undergoing radical cystectomy in the province of Ontario. Methods: We conducted a population-based cohort study to examine the incidence of VTE, a composite of pulmonary embolism and deep vein thrombosis, among all patients treated with radical cystectomy for bladder cancer between 2002 and 2014 in Ontario, Canada. We estimated the cumulative incidence of VTE and used Fine and Grey competing risk survival analysis to assess risk factors for VTE while accounting for the risk of any cause mortality. Results: Among 3623 eligible patients, the 10 year cumulative incidence of VTE was 6.68% (Table 1). Among those who experienced VTE, the median time from surgery was 216 days (interquartile range 52-677 days; mean 527 days). However, VTE rates peaked much earlier with a mode of 20 days. Neither preoperative (HR 0.68, 95% CI 0.39-1.18) nor postoperative chemotherapy (HR 1.32, 95% CI 0.95-1.84) were significantly associated with VTE incidence. While patients with a prior history of VTE had increased risk of VTE after cystectomy (HR 5.1, 95% CI 2.2-12.0), age, gender, comorbidity score, rurality, diversion type (continent vs ileal conduit), treatment at an academic institution, or year of treatment were not significantly associated with the risk of VTE. Conclusions: Among patients undergoing cystectomy for bladder cancer, the cumulative incidence of VTE continues to rise long after the date of surgery indicating that previous studies may have underestimated these rates, but the highest rates occur at 20 days after surgery. Chemotherapy does not appear to increase the risk of VTE. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".