Bibliographic record
Abstract
Background: Ischemic stroke is the third cause of mortality in the world even though it decreased over the last decade, it remains a major etiology of a lifelong handicap. In fact, approximately one third of the patients will experience aphasia, a devastating impairment for the patient and his family. The language rehabilitation enable variant degrees of recovery and mild improvement occurs within the first six months but results still less efficient than desired. Objective: The aim of the study is to assess the effects of hyperbaric oxygenotherapy in post stroke aphasia during the chronic phase. Methods: We report a case series of 3 patients suffering from post-ischemic stroke Broca’s aphasia, all hospitalized and taken in charge in the neurology department of the military hospital of Tunis, between 2018 and 2020. Each patient had around 30 to 40 sessions of Hyperbaric Oxygenotherapy (HBO). The evaluation of the language was performed with the Montreal Toulouse MT 86 using the Arabic version before and after HBO. Results and discussion: Recovery after HBO was recorded in the three patients with the improvement of variant dimension of the language: Output of spontaneous speech besides oral and written expression. HBO through hyperoxia, induces several effects permitting the restoration of cerebral cell metabolism and blood brain barrier structure. Conclusion: The presented results suggest that HBO could be an efficient and reliable therapy that helps recover from post stroke aphasia sequelae. Even though its mechanisms aren’t well elucidated, further studies are needed to confirm its benefits.
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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 | 0.000 |
| 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".