Deep Brain Stimulation for Major Depressive Disorder Resistant to Four or More Treatments
Bibliographic record
Abstract
INTRODUCTION: Major depressive disorder (MDD) is a severely disabling illness, and in 2005, Mayberg et al. reported on the effectiveness of deep brain stimulation (DBS) to SCg25 for MDD in patients resistant to more than four treatments. The purpose of this study is to expand on the preliminary Toronto work and obtain additional data in support of the hypothesis. METHODS: Three academic health science centers in Canada (McGill University; Vancouver Coastal Health Authority; and University Health Network, University of Toronto) recruited 20 patients who met stringent criteria for MDD resistant to four or more treatments, comparable to the previously published inclusion and exclusion criteria. Bilateral quadripolar DBS electrodes were implanted in white matter immediately adjacent to SCg25 using magnetic resonance imaging-guided stereotactic localization. Surgeries were completed between November 1, 2005 and March 7, 2008. RESULTS: Presently, 14 patients have completed 6 months of postsurgery evaluation, 10 of whom have been evaluated after 1 year. The response rate (based on a 40% reduction from baseline severity score on Hamilton Rating Scale for Depression 17 Item-HRSD-17) was 56.3% at 6 months and 78.9% after 1 year. Updated results on 18 patient at 6 months and 14 at 1 year will be presented, with examination of lead location versus response plus additional psychiatric and social function assessments. CONCLUSION: These results from a multisite trial confirm the initial findings at 6 months that DBS to SCg25 is an effective intervention for MDD resistant to more than four treatments and suggest that benefits improve and are sustained after 1 year.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".