Deep brain stimulation versus nonsurgical treatment for severe Alzheimer's disease: A long-term retrospective cohort study
Bibliographic record
Abstract
Background: Severe Alzheimer's disease (AD) is characterized by significant neuropsychiatric symptoms and sleep disorders, with limited effectiveness of conservative drug treatments. Deep brain stimulation (DBS) offers a potential alternative. Objective: To evaluate the efficacy, safety, and long-term outcomes of DBS versus conservative treatment in patients with severe AD. Methods: We retrospectively analyzed 40 patients with severe AD diagnosed at the People's Liberation Army General Hospital from 2015 to 2022. Twenty patients received DBS, and twenty received conservative treatment. Treatment effects were assessed using standardized scales at three- and twelve-months post-treatment. Primary outcomes included changes in cognitive function [Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Alzheimer's Disease Rating Scale-Cognitive subscale, Clinical Dementia Rating). Secondary outcomes included quality of life, sleep quality, neuropsychiatric symptoms, and caregiver burden (Barthel Index, Functional Activity Questionnaire, Functional Independence Measure (FIM), Neuropsychiatric Inventory (NPI), Hamilton Anxiety Rating Scale (HAM-A), Hamilton Depression Rating Scale (HAM-D), Pittsburgh Sleep Quality Index (PDQI), Zarit Burden Interview (ZBI)]. Results: DBS patients showed significantly greater improvements in MMSE, MoCA, FIM, and ZBI scores than controls, suggesting improved cognitive function and quality of life, and reduced caregiver burden (p < 0.05). Notably, DBS significantly reduced HAM-A, HAM-D, and PSQI scores, and improved NPI scores more than controls, indicating significant amelioration of neuropsychiatric symptoms and sleep disorders (p < 0.05). Conclusions: DBS is a safe and reversible treatment that potentially enhances cognitive function and quality of life in severe AD patients and alleviates caregiver burden. For the first time, we report that DBS also improves neuropsychiatric symptoms and sleep disorders, highlighting its clinical potential in AD.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".