Thalamic deep brain stimulation for central poststroke pain syndrome: an international multicenter study
Bibliographic record
Abstract
OBJECTIVE: The effectiveness and optimal stimulation site of deep brain stimulation (DBS) for central poststroke pain (CPSP) remain elusive. The objective of this retrospective international multicenter study was to assess clinical as well as neuroimaging-based predictors of long-term outcomes after DBS for CPSP. METHODS: The authors analyzed patient-based clinical and neuroimaging data of previously published and unpublished cohorts from 6 international DBS centers. DBS leads were reconstructed and normalized. A stimulation map was constructed on the basis of individual stimulation settings and associated outcomes. Furthermore, the authors projected the individual segmented stroke lesions and volumes of tissue activated (VTAs) of the stimulating electrode onto a normalized human connectome to obtain the connectivity profiles of the individual lesions and VTAs. RESULTS: The authors analyzed the data of 54 patients, of whom 15 were excluded from the final analysis due to a lack of imaging data. Among the remaining 39 patients from 6 different cohorts, the authors found 14 (35.9%) responders who were defined by pain relief of at least 50% at 12-month follow-up. Stimulation mapping identified areas in the posterior limb of the internal capsule, the sensorimotor thalamus, and the medial and intralaminar thalamus as effective for pain reduction. Baseline characteristics did not differ between responders and nonresponders. The stimulation sites of the responders showed significantly reduced structural connectivity to the sensory areas of the cerebral cortex compared to nonresponders. CONCLUSIONS: This comprehensive, multicenter analysis corroborates the efficacy of DBS in treating CPSP for a relevant number of patients. The posterior limb of the internal capsule and the sensorimotor thalamus emerged as potential stimulation sweet spots. The difference in structural connectivity between responders and nonresponders may constitute a biomarker of effective stimulation that can help guide surgical planning in future well-designed prospective trials.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".