Intraoperative changes in the H-reflex pathway during deep brain stimulation surgery for Parkinson’s disease: A potential biomarker for optimal electrode placement
Bibliographic record
Abstract
BACKGROUND: Deep Brain Stimulation (DBS) targeting the subthalamic nucleus (STN) and globus pallidus interna (GPi) is an effective treatment for cardinal motor symptoms and motor complications in Parkinson's Disease (PD). However, malpositioned DBS electrodes can result in suboptimal therapeutic response. OBJECTIVE: We explored whether recovery of the H-reflex-an easily measured electrophysiological analogue of the stretch reflex, known to be altered in PD-could serve as an adjunct biomarker of suboptimal versus optimal electrode position during STN- or GPi-DBS implantation. METHODS: Changes in soleus H-reflex recovery were investigated intraoperatively throughout awake DBS target refinement across 26 nuclei (14 STN). H-reflex recovery was evaluated during microelectrode recording (MER) and macrostimulation at multiple locations within and outside target nuclei, at varying stimulus intensities. RESULTS: Following MER, H-reflex recovery normalized (i.e., became less Parkinsonian) in 21/26 nuclei, and correlated with on-table motor improvement consistent with an insertional effect. During macrostimulation, H-reflex recovery was maximally normalized in 23/26 nuclei when current was applied at the location within the nucleus producing optimal motor benefit. At these optimal sites, H-reflex normalization was greatest at stimulation intensities generating maximum motor benefit free of stimulation-induced side effects, with subthreshold or suprathreshold intensities generating less dramatic normalization. CONCLUSION: H-reflex recovery is modulated by stimulation of the STN or GPi in patients with PD and varies depending on the location and intensity of stimulation within the target nucleus. H-reflex recovery shows potential as an easily-measured, objective, patient-specific, adjunct biomarker of suboptimal versus optimal electrode position during DBS surgery for PD.
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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 | 0.000 | 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".