Analysis of 21 Patients With Alcoholic Marchiafava–Bignami Disease in Chongqing, China
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the characteristics and prognosis of patients with alcoholic Marchiafava-Bignami disease (MBD), a rare neurological disorder commonly associated with chronic alcoholism, in Chongqing, China. METHODS: We conducted a retrospective analysis of clinical data from 21 alcoholic MBD patients treated at the First Affiliated Hospital of Chongqing University between 2012 and 2022. RESULTS: The study included 21 patients with alcoholic MBD who had a mean age of 59 ± 9.86 years and an average drinking history of 35.48 ± 8.65 years. Acute onset was observed in 14 (66.7%) patients. The primary clinical signs observed were psychiatric disorders (66.7%), altered consciousness (61.9%), cognitive disorders (61.9%), and seizures (42.9%). Magnetic resonance imaging revealed long T1 and long T2 signal changes in the corpus callosum, with lesions predominantly found in the genu (76.2%) and splenium (71.4%) of the corpus callosum. The poor prognosis group demonstrated an increased incidence of altered consciousness (100% vs 50%, P = 0.044), pyramidal signs (80% vs 18.8%, P = 0.011), and pneumonia (100% vs 31.3%, P = 0.007). Patients with a longer drinking history (45.0 ± 10.0 years vs 32.69 ± 5.99 years, p = 0.008) and a lower thiamine dose (p = 0.035) had a poorer prognosis at 1 year. CONCLUSIONS: This study identified altered consciousness, pyramidal signs, and pneumonia as predictors of a poor prognosis in patients with alcoholic MBD. A longer duration of alcohol consumption and inadequate thiamine supplementation were associated with a poorer prognosis.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".