Clinical Outcomes of Electroconvulsive Therapy (ECT) for Depression in Older Old People Relative to Other Age Groups Across the Adult Life Span: A CARE Network Study
Bibliographic record
Abstract
INTERVENTION: Electroconvulsive therapy (ECT) is a commonly used treatment for severe psychiatric illness in older adults, including in the 'older old' population aged 80 years and above. However, there can sometimes be a reluctance to treat the 80+ year old age group with ECT due to medical comorbidities, frailty, and concerns about cognition. OBJECTIVE, DESIGN, SETTING, AND PARTICIPANTS: This multi-site, longitudinal Australian study aimed to investigate the effectiveness and safety of ECT in older old people compared with younger age groups. Data from 310 people receiving ECT for depression at three participating hospitals was collected in a naturalistic setting, between 2015 and 2022. MEASUREMENTS: Clinical ratings were conducted pre-ECT and end-acute ECT using the Montgomery-Åsberg Depression Rating Scale (MADRS). Cognitive outcomes were assessed using the Montreal Cognitive Assessment (MoCA). RESULTS: Older old adults demonstrated a significant reduction MADRS scores at post-treatment. They were more likely to meet remission criteria compared with the younger age groups. Older old adults were also less likely to show clinically significant cognitive decline post-ECT, and were more likely to show clinically significant cognitive improvement post-ECT compared with younger age groups. CONCLUSIONS: ECT is highly effective in treating severe psychiatric illness in older old adults. Relative to the younger age groups, the older old group were more likely to remit with ECT and a greater proportion showed cognitive improvement post-ECT. These findings suggest that ECT should be considered as a valuable and safe treatment option for older old individuals with depression.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".