Prospective study of hippocampal volume and function in human subjects treated with corticosteroids
Bibliographic record
Abstract
PURPOSE: Decreased hippocampal volume reported in neuropsychiatric and endocrine disorders is considered a result of putative neuronal damage mediated by corticosteroids. This is the first prospective study of hippocampal volume and function in patients treated with corticosteroids. METHODS: 14 subjects treated systemically with prednisone or betamethasone for dermatological or rheumatic disorders underwent prospective neurocognitive testing (Auditory Verbal Learning Test-AVLT, Trail Making Test-TMT, Digit Span-DS) and nine of them also repeated magnetic resonance volumetry. RESULTS: The mean duration of treatment between the first and the second assessment was 73+/- 38 days with mean daily dose of 37+/- 17 mg prednisone and 193+/- 29 days, with mean daily dose of 24+/- 15 mg prednisone between the first and the third assessment. There was a trend towards decreases in total AVLT scores and an improvement in the TMT and DS, but no significant changes in the volumes of the right or the left hippocampi between the assessments. Prednisone dose did not correlate with the hippocampal volume change. CONCLUSION: We observed a trend for decline in verbal memory despite improvement in psychomotor speed, attention/working memory and no macroscopic hippocampal volume changes during 36-238 days of treatment with therapeutic doses of corticosteroids.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".