Evaluation of the quality of life of patients with high grade subarachnoid hemorrhage following aneurysmal rupture
Bibliographic record
Abstract
Introduction: Patients presenting with high grade (HG) subarachnoid hemorrhage (SAH) from aneurysmal rupture may have persisting neurologic deficits which may lead to questioning the decision of treating aggressively. The objective of this study aims at analyzing outcome and long-term quality of life (QOL) of patients with HG SAH treated surgically. Methods: Retrospective study of patients with Hunt Hess (HH) grade IV or V SAH treated surgically at our institution. Long-term outcome was evaluated based on the modified Rankin Scale (mRS) at 3 years. Survivors were evaluated for QOL using various scales. Results: 63 patients (mean age of 52 year-old) were included. Intraparenchymal hemorrhage (IPH) was found in 85% of cases. 19 patients died. Predictive factors of poor prognosis and mortality were initial cerebral ischemia (p=0.003) and IPH (p=0.007). Favourable outcome (mRS 0-3) was found in 41% of patients. QOL questionnaires revealed that 80 % of responders showed more than 50% recovery. Mild or absent depression was observed in 78% of patients. Conclusion: In this surgical series, performed in an endovascular era, nearly all patients presented with SAH-associated IPH at admission. Despite the presence of such negative prognostic factor and the poor condition at admission, a high rate of favourable outcome and QOL was observed, therefore justifying aggressive surgical treatment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".