Severe cerebellar atrophy following salicylate poisoning and respiratory insufficiency: A case report
Bibliographic record
Abstract
INTRODUCTIONOver-the-counter (OTC) drugs have sometimes been used for suicide attempt and it was reported that among OTC drugs used in adults the most common was acetaminophen in emergency hospitals in Canada [1]. Other OTC analgesics in their cases included acetylsalicylates, ibuprofen and others, and deaths were observed in case of acetaminophen and acetylsalicylate intoxications [1]. Respiratory insufficiency could occur in acetylsalicylate intoxications by way of central nervous system involvements, metabolic disorders or vomiting-induced suffocation [1]. Severe respiratory insufficiency will cause miscellaneous neurological manifestations because of secondary hypoxic-ischemic encephalopathy (HIE). In these cases the cerebellum is one of the vulnerable sites [2, 3]. However, exclusive severe cerebellar atrophy associated with remarkable cerebellar symptoms after respiratory insufficiency has not been reported probably because patients with HIE usually show extensive brain lesions as a whole.We experienced a patient who exhibited exclusively marked cerebellar dysfunction and atrophy on magnetic resonance imaging three years after salicylate poisoning and respiratory insufficiency. Cerebellar atrophy was considered to be induced in these unique clinical situations, although its definite pathophysiology remained unknown.
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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) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".