Treatment of Patients with High-Grade Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
functional independence.Only 15% of those treated with an aggressive approach survived in a poor or dependent condition.Thus, it appears that the selective, aggressive approach taken by the authors has not resulted in a high proportion of devastated survivors.The Calgary results are consistent with those reported from other contemporary series 2-4 as well as my own personal experience.After selecting for those who improve after early resuscitation and treatment of acute hydrocephalus, there seems to be a bimodal distribution in terms of cognitive and functional outcomes, with a majority of this small, selected subgroup achieving at least some degree of functional independence.Measures of cognitive functioning and quality of life suggest that these individuals can get along reasonably well in spite of having been hit hard by their bleed.A nihilistic approach to all highgrade SAH patients would deny these patients and their families the potential for recovery.Many patients with high-grade SAH have suffered irreversible brain injury and will not survive despite aggressive interventions.However, as Diaz and Wong have shown, among these patients there exists a small subgroup with the potential for good recovery.Identification of those with the potential for recovery relies on good clinical judgment and experience.Selection of treatment approach based on the response to initial resuscitation measures seems to be a fairly reliable method to distinguish those for whom aggressive measures would be futile from those with the capacity to recover.In these patients, with such a high proportion recovering to good physical and cognitive function, aggressive treatment efforts are justified.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".