Desmopressin administration and rebleeding in subarachnoid hemorrhage: analysis of an observational prospective database
Bibliographic record
Abstract
OBJECTIVE: Rebleeding remains a frequent and catastrophic event leading to poor outcome after subarachnoid hemorrhage (SAH). Reduced platelet function after the initial bleed is associated with higher risk of early rebleeding. Desmopressin (DDAVP) is a well-known hemostatic agent, and recent guidelines already suggest its use in individuals exposed to antiplatelet drugs. The authors hypothesized that DDAVP administration in patients with SAH at admission would be associated with lower risks of rebleeding. METHODS: The authors performed an observational cohort study of patients enrolled in the Columbia University SAH Outcome Project between August 1996 and July 2015. The authors compared the rate of rebleeding between patients who were and those who were not treated with DDAVP. After adjustment for known predictors, logistic regression was used to measure the association between treatment with DDAVP and risks of rebleeding. RESULTS: Among 1639 patients with SAH, 12% were treated with DDAVP. The main indication for treatment was suspected exposure to an antiplatelet agent. The overall incidence of rebleeding was 9% (1% among patients treated with DDAVP compared with 8% among those not treated). After adjustment for antiplatelet use and known predictors, treatment with DDAVP was associated with a 45% reduction in the risks of rebleeding (adjusted OR 0.55, 95% CI 0.27-0.97). DDAVP was associated with a higher incidence of hyponatremia but not with thrombotic events or delayed cerebral ischemia. CONCLUSIONS: Treatment with DDAVP was associated with a lower risk of rebleeding among patients with SAH. These findings support further study of DDAVP as first-line therapy for medical hemostasis in patients with SAH.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 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".