Repetitive Transcranial Magnetic Stimulation Combined With Conventional Rehabilitation in a Patient With Lacunar Infarcts
Bibliographic record
Abstract
Lacunar infarcts, though small, can produce significant motor and cognitive impairments due to their disruption of cortico-subcortical networks. This case report describes a 45-year-old woman with subacute to chronic ischemic lacunar infarcts involving the right frontal white matter, right thalamus, and left lentiform nucleus, who presented with left-sided weakness and mild cognitive deficits. The patient underwent a six-week rehabilitation program combining repetitive transcranial magnetic stimulation (rTMS) with conventional physiotherapy. Excitatory 10 Hz rTMS was applied over the ipsilesional (right) primary motor cortex (M1) for 30 sessions across six weeks, with five sessions per week, at an intensity of 80% RMT. Functional outcomes were evaluated using the Fugl-Meyer Assessment (FMA) for motor recovery and the Montreal Cognitive Assessment (MoCA) for cognition at baseline, mid-intervention, post-intervention, and three-month follow-up. The patient showed steady improvements, with FMA scores increasing from 27 to 43 (out of 66) for the upper limb and from 15 to 24 (out of 34) for the lower limb, while MoCA scores improved from 17 to 27 (out of 30). The gains were maintained at follow-up, and no adverse effects occurred during treatment. These findings suggest that combining rTMS with physiotherapy may enhance recovery in patients with lacunar infarcts by promoting cortical reorganization and interhemispheric balance. This case highlights the feasibility and clinical relevance of rTMS-based neurorehabilitation, even in resource-limited settings.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".