Deep Brain Stimulation for Treatment-Resistant Depression: Follow-Up After 3 to 6 Years
Bibliographic record
Abstract
OBJECTIVE: A prevalence of at least 30% for treatment-resistant depression has prompted the investigation of alternative treatment strategies. Deep brain stimulation (DBS) is a promising targeted approach involving the bilateral placement of electrodes at specific neuroanatomical sites. Given the invasive and experimental nature of DBS for treatment-resistant depression, it is important to obtain both short-term and long-term effectiveness and safety data. This report represents an extended follow-up of 20 patients with treatment-resistant depression who received DBS to the subcallosal cingulate gyrus (Brodmann's area 25). METHOD: After an initial 12-month study of DBS, patients were seen annually and at a last follow-up visit to assess depression severity, functional outcomes, and adverse events. RESULTS: The average response rates 1, 2, and 3 years after DBS implantation were 62.5%, 46.2%, and 75%, respectively. At the last follow-up visit (range=3-6 years), the average response rate was 64.3%. Functional impairment in the areas of physical health and social functioning progressively improved up to the last follow-up visit. No significant adverse events were reported during this follow-up, although two patients died by suicide during depressive relapses. CONCLUSIONS: These data suggest that in the long term, DBS remains a safe and effective treatment for treatment-resistant depression. Additional trials with larger samples are needed to confirm these findings.
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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 | 0.002 | 0.003 |
| 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 | 0.001 |
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".