Desflurane general anesthesia for deep brain stimulation in Parkinson′s disease patients
Bibliographic record
Abstract
Objective Feasibility application of microelectrode recording (MER) during sub thalamic nucleus deep brain stimulation (STN-DBS) implantation under desflurane general anesthesia(GA) in patients with Parkinson′s disease (PD). Methods A prospective cohort of 20 PD patients undergoing STN-DBS under desflurane general anesthesia were enrolled. Intraoperative MER quality, pos-operative acute pain, cognitive function, anxiety/depression status, quality of life, and clinical efficacy of DBS were evaluated. Results Among the patients, 14 were male with average PD duration of (8.1±3.6)years. Hoehn-Yahr staging averaged 2.8±0.5 in “on” state and 2.3±0.5 in “off” state. The mean DBS surgery duration was 87.4 minutes. Highly normalized root-mean-square (NRMS) signals were successfully recorded in all cases, with remedial measures applied in 4 patients to achieve satisfactory MER signals. Post-operative Visual Analogue Scale (VAS) pain scores on days 1, 2, and 3 were 3.7±2.2, 2.8±1.6,and 1.8±2.0, respectively. Montreal Cognitive Assessment (MoCA) scores showed no statistical difference during hospitalization as compared to pre-operative values, but significantly decreased at 6-month follow-up (24.3±4.1 vs. 21.5±3.5, P＜0.05). All patients demonstrated significant reduction in Hamilton Anxiety Scale (HAMA), Hamilton Depression Rating Scale (HAMD), and Parkinson′s disease Questionnaire-39 (PDQ-39) scores at 6-month follow-up. The unified Parkinson′s disease rating scale (UPDRS-Ⅲ) improvement rates were 51.4%±39.2% (medication-on) and 61.6%±26.8% (medication-off) respectively with Levodopa Equivalent Daily Dose (LEDD) improvement rate of 48.6%±23.0%. Conclusions Desflurane general anesthesia is safe and feasible for electrods implantation in STN-DBS of PD patients, without interfering with intra-operative MER or postoperative outcomes.
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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".