Repetitive transcranial magnetic stimulation for treatment of elderly patients with depression - an open label trial.
Bibliographic record
Abstract
BACKGROUND: RTMS has been developed as a novel tool for treating depression but the clinical significance of this treatment has been variable, especially in the older depressed subjects. METHODS: Medication-resistant depressed patients 60 years or older were treated for two weeks (10 sessions) with high-frequency rTMS delivered to the left dorsolateral prefrontal cortex at 100% of motor threshold. Each session consisted of 20 trains at 10Hz delivered in 8-second duration. The patients continued taking their psychotropic medications throughout the study. RESULTS: Nineteen of the 20 subjects completed the trial. One subject dropped out after 8 sessions because of discomfort. The average age of our patients was 66.8 years (6 males and 14 females). Six patients responded and there was a 31.6% mean reduction in Hamilton Depression Rating Scale (HDRS) scores from baseline at the end of the treatment. There was statistically significant decrease from baseline in both HDRS and HARS scores at the end of treatment. rTMS was generally well tolerated. CONCLUSION: These preliminary finding suggests that rTMS may be an effective treatment alternative to a subpopulation of medication resistant older depressed patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".