Use of statins and reduced risk of recurrence of VTE in an older population
Bibliographic record
Abstract
We aimed to determine whether statin use is associated with a decreased risk of recurrent venous thromboembolism (VTE) in older patients. We used a pre-assembled cohort of patients at least 65 years of age diagnosed with incident VTE between January 1, 1994 and December 31, 2004 in the province of Québec, Canada and followed until December 31, 2005. Time-dependent Cox proportional hazards models were used to estimate adjusted hazard ratios (HRs) and 95 % confidence intervals (CIs) of recurrent VTE associated with current and past use of statins, compared with non-use. The cohort included 25,681 patients with incident VTE. During a mean follow-up of 3.0 years, there were 2343 recurrent VTE events (rate: 3.1 per 100 person-years). Compared with non-use, current use of statins was associated with a decreased risk of VTE recurrence (rates: 1.55 vs 3.47 per 100 per year, respectively; HR: 0.74, 95 % CI: 0.61-0.89), while no association was observed with past use (HR: 0.98, 95 % CI: 0.76-1.25). In a secondary analysis, longer durations of statin use were associated with greater risk reductions (0-6 months, HR 0.82, 95 % CI: 0.67-1.01; 6-12 months, HR 0.62, 95 % CI: 0.43-0.90; ≥ 12 months, HR: 0.50, 95 % CI: 0.33-0.74; p-value for trend ≤ 0.001). The use of statin was associated with a decreased risk of recurrent VTE in older patients. This study supports the need for randomised controlled trials to assess the efficacy and safety of statins in the long-term treatment of VTE.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".