Timing of deep brain stimulation in Parkinson disease: A need for reappraisal?
Bibliographic record
Abstract
We review the current application of deep brain stimulation (DBS) in Parkinson disease (PD) and consider the evidence that earlier use of DBS confers long-term symptomatic benefit for patients compared to best medical therapy. Electronic searches were performed of PubMed, Web of Knowledge, Embase, Cochrane Database of Systematic Reviews, and Cochrane Central Register of Controlled Trials to identify all article types relating to the timing of DBS in PD. Current evidence suggests that DBS is typically performed in late stage PD, a mean of 14 to 15 years after diagnosis. Current guidelines recommend that PD patients who are resistant to medical therapies, have significant medication side effects and lengthening off periods, but are otherwise cognitively intact and medically fit for surgery be considered for DBS. If these criteria are rigidly interpreted, it may be that, by the time medical treatment options have been exhausted, the disease has progressed to the point that the patient may no longer be fit for neurosurgical intervention. From the evidence available, we conclude that surgical management of PD alone or in combination with medical therapy results in greater improvement of motor symptoms and quality of life than medical treatment alone. There is evidence to support the use of DBS in less advanced PD and that it may be appropriate for earlier stages of the disease than for which it is currently used. The improving short and long-term safety profile of DBS makes early application a realistic possibility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.092 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.005 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.012 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".