ANTITHROMBOTIC AGENTS INTAKE PRIOR TO INJURY DOES NOT AFFECT OUTCOME AFTER A TBI IN ELDERLY PATIENTS
Bibliographic record
Abstract
Previous studies have shown that anticoagulation is associated with a higher risk of bleeding after traumatic brain injury (TBI) and a higher mortality rate. However, other studies have shown conflicting results on the outcome after a TBI in anticoagulated patients. The purpose of this study is to investigate the effect of risk factors including international normalized ratio (INR) as well as the Partial thromboplastin time (PTT) scores on outcome following TBI in the elderly population. Data were retrospectively collected on patients (n = 982) aged 65 and above who were admitted post TBI to the McGill University Health Centre-Montreal General Hospital from 2000 to 2011. Age, Injury Severity Score (ISS), Glasgow Coma Scale score (GCS), type of trauma (isolated TBI vs polytrauma including TBI), initial CT scan results according to the Marshall classification and the INR and PTT scores and prescriptions of antiplatelet or anticoagulant agents (AP/AC) were collected. We found that age is significantly associated with an increase in the rate of death (CSHR:1.08, 95%CI(1.06, 1.11) and in the rate of discharge to a long-term facility (CSHR:1.06, 95%CI (1.03, 1.09)). PTT values above 60 adversely affected outcome in patients not on AP/AC only, and INR values had no effect on outcome or CT findings. Age and injury severity rather than antithrombotic agent intake are associated with adverse acute outcome in hospitalized elderly TBI patients.
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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".