Clinico-radiologic subtypes and therapeutic observation of acute Marchiafava-Bignami disease
Bibliographic record
Abstract
We aimed to investigate the clinico-radiologic features of acute Marchiafava-Bignami disease (MBD) and its evolutionary process after effective treatment through subgroup comparison. The clinical and MRI data of 23 patients with acute MBD were retrospectively analyzed and divided into type A (12 cases, with entire callosal involvement) and type B (11 cases, with focal callosal involvement). The clinical assessments and MRI findings (before and after treatment) were compared between the two subtypes. Compared with type B, type A had lower MoCA (Montreal Cognitive Assessment) scores at admission (16.50 ± 1.73 vs 18.27 ± 1.68, P = 0.021) and were more common with extracallosal involvement (66.67% vs 18.18%, P = 0.036) and longer illness duration (18.3 ± 2.1 days vs 15.6 ± 2.4 days, P = 0.012). During the treatment, the residual lesion in the splenium was more common in type A (58.33% vs 9.09%, P = 0.027). After treatment, the MoCa scores of both subtypes gradually increased (P < 0.001), and the callosal and extracallasal lesions disappeared completely. Clinico-radiologic typing of acute MBD is related to the severity of early symptoms, but not to the prognosis. Complete clinico-radiologic recovery is possible for both subtypes with combined treatment. The clinico-radiologic reversibility is helpful for accurate diagnosis and therapeutic evaluation.
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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) | 0.001 | 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".