Treatment of Poststroke Pain by Epidural Motor Cortex Stimulation With a New Octopolar Lead
Bibliographic record
Abstract
BACKGROUND: Chronic, drug-resistant neuropathic pain can be treated by surgically implanted motor cortex stimulation (MCS). The leads used for MCS have not been specifically designed for this application. OBJECTIVE: To study the value of a new 8-contact lead for MCS therapy in a series of 6 patients with refractory central poststroke pain. METHODS: The study comprised a 1-month randomized phase, starting 1 month after implantation, during which the neurostimulator was switched on in one-half of the patients or remained off in the other half, followed by an open phase of 10 months, during which the stimulator was switched on in all patients. Clinical assessment was performed at baseline and 1, 2, 3, 6, and 12 months after implantation with the following scales: Visual Analog Scale, Verbal Rating Scale, Brief Pain Inventory, McGill Pain Questionnaire, Sickness Impact Profile, and Medication Quantification Scale. RESULTS: In the randomized phase, clinical scores were found to be globally reduced in the on- vs off-stimulation condition. In the open follow-up phase, all clinical scores improved significantly over time. The ratio between affective and sensory McGill Pain Questionnaire subscores decreased, suggesting a preferential effect of MCS on the affective component of pain. Compared with preoperative baseline, 2 patients were totally relieved of central poststroke pain, 3 patients were very much relieved, and 1 patient remained unchanged at the final examination. CONCLUSION: A good clinical outcome was observed in all patients except 1, suggesting that this new octopolar lead could be used for MCS therapy to treat refractory central poststroke pain.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".