Time trends in intracranial bleeding associated with direct oral anticoagulants: a 5-year cohort study
Bibliographic record
Abstract
BACKGROUND: Over the past 5 years, dabigatran, rivaroxaban and apixaban were approved for stroke prevention. Phase III studies have shown a lower risk of intracranial bleeding with these direct oral anticoagulants than with warfarin; however, there is a lack of real-life data to validate this. We analyzed time trends in atraumatic intracranial bleeding from 2009 to 2013 among patients prescribed oral anticoagulants and those not prescribed oral anticoagulants. METHODS: We used ICD-10-CA (enhanced Canadian version of the 10th revision of the International Statistical Classification of Diseases and Related Health Problems) codes to identify all patients with atraumatic intracranial bleeding who presented to our neurosurgical centre (serving a population of more than 1.2 million). Trained researchers extracted data on anticoagulant medications used in the week before diagnosis of the intracranial bleed. Provincial prescription data for oral anticoagulants were obtained from IMS Brogan CompuScript Market Dynamics. The primary outcome was the time trend in incident intracranial bleeds associated with oral anticoagulation during the period 2009-2013. The secondary outcomes were the time trend in intracranial bleeds not associated with oral anticoagulation and the provincial prescribing patterns for oral anticoagulants during the same period. RESULTS: A total of 2050 patients presented with atraumatic intracranial bleeds during the study period. Of the 371 (18%) prescribed an anticoagulant in the week before presentation, 335 were prescribed an oral anticoagulant. There was an increasing time trend in intracranial bleeding associated with oral anticoagulants (p = 0.009; 6 additional events per year) and in intracranial bleeding not associated with oral anticoagulation (p = 0.06). During 2013, prescriptions for warfarin decreased to 70% of all oral anticoagulant prescriptions in the province, whereas those for dabigatran and rivaroxaban increased to 17% and 12%, respectively. INTERPRETATION: We observed increasing time trends in intracranial bleeding, both associated with and not associated with oral anticoagulants, over the study period. Although aggregate provincial data showed increased prescribing of oral anticoagulants, other more likely explanations for our findings include an aging population or increasing frailty.
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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 | 0.001 |
| 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".