Comparison of General and Local Anesthesia for Deep Brain Stimulator Insertion: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Subthalamic nucleus deep brain stimulation (STN-DBS) has become a standard treatment for many patients with Parkinson's disease (PD). The reported clinical outcome measures for procedures done under general anesthesia (GA) compared to traditional local anesthetic (LA) technique are quite heterogeneous and difficult to compare. The aim of this systematic review and metaanalysis was to determine whether the clinical outcome after STN-DBS insertion under GA is comparable to that under LA in patients with Parkinson's disease. METHODS: The databases of Medline Embase, Cochrane library and Pubmed were searched for eligible studies (human trials, English language, published between 1946 and January of 2016). The primary outcome of this study was to assess the postoperative improvement in the symptoms, evaluated using either Unified Parkinson's Disease Rating Scale (UPDRS) scores or levodopa equivalent dosage (LEDD) requirement. RESULTS: The literature searches yielded 395 citations and six retrospective cohort studies with a sample size of 455 (194 in GA and 261 in LA) were included in the analysis. Regarding the clinical outcomes, there were no significant differences in the postoperative Unified Parkinson's disease rating scale and levodopa equivalent drug dosage between the GA and the LA groups. Similarly, the adverse events and target accuracy were also comparable between the groups. CONCLUSIONS: This systematic review and meta-analysis shows that currently there is no good quality data to suggest equivalence of GA to LA during STN-DBS insertion in patients with PD, with some factors trending towards LA. There is a need for a prospective randomized control trial to validate our results.
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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 | 0.009 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.015 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".