Association of Fisher scale and changes of language in patients with aneurysmal subarachnoid hemorrhage
Bibliographic record
Abstract
Cognitive deficits caused by subarachnoid hemorrhage (SAH) after rupture of cerebral aneurysms are common, as approximately half of patients have severe, or at least striking, declines in one or more functions of the cognitive domain. The Fisher Scale is associated with the development of vasospasm and thus with the final performance of the patient after SAH. The association of this scale with language disorders in the period preceding the treatment has not been reported yet in the literature. Associate the presence of language deficits with varying degrees of the Fisher Scale in patients with SAH in the period preceding the treatment of aneurysm, as well as compare the various degrees of this scale, identifying the Fisher Scale degrees more associated with the decline of language. The database of 185 preoperative evaluations of language was studied, through the Montreal Toulouse Protocol Alpha version and verbal fluency through CERAD battery, of patients of Hospital da Restauração with aneurysmal SAH. The data relating to the Fisher Scale, the location of the aneurysm, the age and the gender of patients were obtained through review of medical records. Patients were divided according to the Fisher Scale (Fisher I, II, III or IV) and compared with a control group of individuals considered normal. Disorders in language and verbal fluency in patients with SAH in the preoperative period were evidenced. The classification of the patients according to the Fisher Scale allowed to identify differences between the sub-groups and to conclude that patients with bulkier bleeding (Fisher III and IV) have larger declines in the analyzed functions.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".