Bibliographic record
Abstract
Dyke-Davidoff-Masson Syndrome (DDMS) is a rare neurological disorder marked by cerebral hemiatrophy, presenting with contralateral hemiparesis, seizures, developmental delays, and facial asymmetry. This case report examines an 18-year-old male diagnosed with DDMS, who presented with right-sided weakness, impaired mobility, and speech difficulties that severely impacted his daily activities. Symptoms began at age eight, following an undocumented febrile episode, and progressively worsened, leading to significant functional limitations. MRI findings confirmed cerebral atrophy on the left side with compensatory hypertrophy of the right hemisphere, supporting a DDMS diagnosis. A multidisciplinary rehabilitation approach was implemented, led by a physiatrist and includes neurologist, psychiatrist, physiotherapist, occupational therapist, orthotist, speech therapist, vocational counselor etc. Over six months, the patient’s Functional Independence Measure (FIM) score improved from 82 to 90 (9.8% increase), and his Barthel Index rose from 75 to 80 (6.7% increase). Gross motor, fine motor and speech clarity is also increased. This case highlights the importance of a structured, multidisciplinary approach in managing DDMS, demonstrating that significant functional gains and improved quality of life are achievable despite the challenges of this rare condition.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".