Continuous infusion of low-dose unfractionated heparin after aneurysmal subarachnoid hemorrhage: a preliminary study of cognitive outcomes
Bibliographic record
Abstract
OBJECTIVE: Cognitive dysfunction occurs in up to 70% of aneurysmal subarachnoid hemorrhage (aSAH) survivors. Low-dose intravenous heparin (LDIVH) infusion using the Maryland protocol was recently shown to reduce clinical vasospasm and vasospasm-related infarction. In this study, the Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive changes in aSAH patients treated with the Maryland LDIVH protocol compared with controls. METHODS: A retrospective analysis of all patients treated for aSAH between July 2009 and April 2014 was conducted. Beginning in 2012, aSAH patients were treated with LDIVH in the postprocedural period. The MoCA was administered to all aSAH survivors prospectively during routine follow-up visits, at least 3 months after aSAH, by trained staff blinded to treatment status. Mean MoCA scores were compared between groups, and regression analyses were performed for relevant factors. RESULTS: No significant differences in baseline characteristics were observed between groups. The mean MoCA score for the LDIVH group (n = 25) was 26.4 compared with 22.7 in controls (n = 22) (p = 0.013). Serious cognitive impairment (MoCA ≤ 20) was observed in 32% of controls compared with 0% in the LDIVH group (p = 0.008). Linear regression analysis demonstrated that only LDIVH was associated with a positive influence on MoCA scores (β = 3.68, p =0.019), whereas anterior communicating artery aneurysms and fevers were negatively associated with MoCA scores. Multivariable linear regression analysis resulted in all 3 factors maintaining significance. There were no treatment complications. CONCLUSIONS: This preliminary study suggests that the Maryland LDIVH protocol may improve cognitive outcomes in aSAH patients. A randomized controlled trial is needed to determine the safety and potential benefit of unfractionated heparin in aSAH 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".