Effect of stimulus waveform duration and E-field orientation on activation of forearm muscles
Bibliographic record
Abstract
comorbidities, frailty, and concern about effects on cognition.This study investigated the effectiveness and safety of ECT in older old people compared with other age groups across the adult lifespan.Methods: This was a retrospective study with naturalistic data collected from 310 people with depression (including 47 older old people) at three Australian hospitals between 2015 and 2022.Clinical and cognitive measures were administered at pre-and post-acute ECT using the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Montreal Cognitive Assessment (MoCA) tool.Results: Older old adults demonstrated a large reduction in average MADRS scores at post-treatment (36.3 [SD 9.1] to 7.7 [SD 6.8]).Following ECT, a greater proportion of older people (!70 years) met MADRS response (X 2 (6) ¼ 12.9, p ¼ 0.045) and remission (X 2 (6) ¼ 17.2, p ¼ 0.009) criteria compared to other age groups.The proportion of people showing clinically significant cognitive changes post-ECT also differed across age groups (X 2 (12) ¼ 36.1, p < 0.001), with a greater proportion of younger people showing cognitive decline, and a greater proportion of older people showing cognitive improvement.Conclusions: ECT is safe and effective for the treatment of depression in older old adults (!80 years).Relative to people in younger age groups, older old adults receiving ECT were more likely to respond and remit, and a greater proportion showed cognitive improvement post-ECT.The findings of this study should encourage clinicians to consider ECT, earlier, for older old people.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".