Venous thromboembolism and bleeding in a community setting
Bibliographic record
Abstract
Summary Bleeding is the most frequent complication of antithrombotic therapy for venous thromboembolism (VTE). However, little attention has been paid to the impact of bleeding after VTE in the community setting. The purpose of this investigation was to describe the incidence rate of bleeding after VTE, to characterize patients most at risk for bleeding, and to assess the impact of bleeding on rates of recurrent VTE and all-cause mortality. The medical records of residents of the Worcester (MA, USA) metropolitan area diagnosed with ICD-9 codes consistent with potential VTE during 1999, 2001, and 2003 were individually validated and reviewed by trained data abstracters. Clinical characteristics, acute treatment, and outcomes (including VTE recurrence rates, bleeding rates, and mortality) over follow-up (up to 3 years maximum) were evaluated. Bleeding occurred in 228 (12%) of 1,897 patients with VTE during our follow-up. Of these, 115 (58.8%) had evidence of early bleeding occurring within 30 days of VTE diagnosis. Patient characteristics associated with bleeding included impaired renal function and recent trauma. Other than a history of prior VTE, the occurrence of bleeding was the strongest predictor of recurrent VTE (hazard ratio [HR] 2.18; 95% confidence interval [CI] 1.54–3.09) and was also a predictor of total mortality (HR 1.97; 95%CI 1.57–2.47). The occur-rence of bleeding following VTE is associated with an increased risk of recurrent VTE and mortality. Future study of antithrombotic strategies for VTE should be informed by this finding. Advances that result in decreased bleeding rates may paradoxically decrease the risk of VTE recurrence.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".