Caracterização das afasias na hemorragia subaracnóidea aneurismática
Bibliographic record
Abstract
PURPOSE: Characterize the profile of aphasic syndromes determined by aneurysmal subarachnoid hemorrhage (aSAH) of the left middle cerebral artery (LMCA). METHODS: An analytical, retrospective, cross-sectional study was conducted using a database of cognitive assessments of 193 patients with aSAH admitted to Hospital da Restauração between March 2007 and November 2009. Of these, a total of 26 patients with aSAH in the LMCA territory confirmed by digital angiography were selected. Aphasia was assessed through the Montreal-Toulouse Language Assessment Alpha Version Protocol (Alpha Version) and the CERAD Neuropsychological Test Battery (Verbal fluency). RESULTS: Language and verbal fluency impairments were identified in patients with aSAH in the LMCA territory when compared with the control population (50 individuals). Of the 26 patients with aSAH, 11 presented aphasic characteristics preoperatively. CONCLUSION: The results of this research corroborate the literature, showing that the aSAH frame causes cognitive impairments even in the preoperative phase for aneurysm occlusion. Considering the observed aspects, the predominant aphasic syndromes characterize comprehension aphasia due to sequels in the posterior cerebral artery territory.
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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 | 0.002 |
| 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".