Survival and Health Care Use After Deep Brain Stimulation for Parkinson’s Disease
Bibliographic record
Abstract
OBJECTIVES: To compare long-term survival of Parkinson's disease (PD) patients with deep brain stimulation (DBS) to matched controls, and examine whether DBS was associated with differences in injurious falls, long-term care, and home care. METHODS: Using administrative health data (Ontario, Canada), we examined DBS outcomes within a cohort of individuals diagnosed with PD between 1997 and 2012. Patients receiving DBS were matched with non-DBS controls by age, sex, PD diagnosis date, time with PD, and a propensity score. Survival between groups was compared using the log-rank test and marginal Cox proportional hazards regression. Cumulative incidence function curves and marginal subdistribution hazard models were used to assess effects of DBS on falls, long-term care admission, and home care use, with death as a competing risk. RESULTS: There were 260 DBS recipients matched with 551 controls. Patients undergoing DBS did not experience a significant survival advantage compared to controls (log-rank test p = 0.50; HR: 0.89, 95% CI: 0.65-1.22). Among patients <65 years of age, DBS recipients had a significantly reduced risk of death (HR: 0.49, 95% CI: 0.28-0.84). Patients receiving DBS were more likely than controls to receive care for falls (HR: 1.56, 95% CI: 1.19-2.05) and home care (HR: 1.59, 95% CI: 1.32-1.90), while long-term care admission was similar between groups. CONCLUSIONS: Receiving DBS may increase survival for younger PD patients who undergo DBS. Future studies should examine whether survival benefits may be attributed to effects on PD or the absence of comorbidities that influence mortality.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".