The Effect of Antipsychotic Treatment on Recurrent Venous Thromboembolic Disease
Bibliographic record
Abstract
BACKGROUND: Venous thromboembolism (VTE) represents a major cause of morbidity and mortality worldwide. Antipsychotic treatment is associated with an increased risk of thromboembolic disease, an effect that seems to be constant across the spectrum of distinct agents. This study sought to delineate the effect of new antipsychotic use on the risk of recurrent thromboembolic events after a first episode of either deep venous thrombosis or pulmonary embolism. METHODS: This cohort study, conducted between January 2010 and June 2017, was based on a prospectively collected database of adult patients with VTE. The main exposure was the new onset of antipsychotic treatment after having a first episode of venous thromboembolic disease. The primary outcome was defined as recurrent VTE, either deep venous thrombosis or pulmonary embolism, during long-term follow-up. The composite of all-cause mortality and recurrent VTE served as the secondary outcome. An inverse probability weighted multivariable Cox proportional hazards model was fitted to adjust for measured confounding and competing risks. RESULTS: One thousand one hundred three patients were included in the present analysis, of whom 136 were identified as new users of antipsychotic agents. A total of 67% of patients were currently treated with full-dose anticoagulation at baseline. No association was found between the new use of antipsychotic agents and recurrent VTE during follow-up (adjusted hazard ratio (HR) = 1.08; 95% CI, 0.38-3.08). However, the use of these agents was associated with a 63% increased risk of recurrent VTE or all-cause mortality (adjusted HR = 1.63; 95% CI, 1.26-2.10). CONCLUSIONS: The use of antipsychotic agents among patients with a first episode of VTE and full-dose anticoagulation was not associated with an increased risk of recurrent thromboembolic events. However, antipsychotic treatment was associated with a higher risk of both VTE and all-cause mortality. Further studies are warranted to confirm these findings.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".