Clinical Effectiveness and Tolerability of Electroconvulsive Therapy in Patients with Neuropsychiatric Symptoms of Dementia
Bibliographic record
Abstract
BACKGROUND: Dementia frequently presents with aggression, agitation, and disorganized behavior for which current treatment is partially effective and is associated with significant adverse effects. OBJECTIVE: The aim of this study was to retrospectively assess the clinical effectiveness and tolerability of electroconvulsive therapy (ECT) in a sample of patients with neuropsychiatric symptoms of dementia (NPS) and to explore factors associated with response and with cognitive adverse effects. METHODS: We examined the clinical records of 25 patients with dementia and a pre-existing psychiatric disorder treated with ECT at an academic mental health hospital between April 1, 2010 and January 28, 2016. Twenty-nine acute ECT courses and fifteen maintenance courses were reviewed. We assessed treatment effectiveness and cognitive adverse effects as well as factors associated with response to treatment, including pre-existing psychiatric disorders, concomitant pharmacological treatment and types of dementia. RESULTS: ECT resulted in a clinically meaningful response in 72% of acute treatment courses. Cognitive adverse effects affecting functioning were reported in 7% of the acute treatment courses. Maintenance treatment was effective in sustaining the response in 87% of treatment courses with two reports of significant cognitive adverse effects. One patient fell and experienced a hip fracture a day after treatment. Use of antipsychotic or antidepressant medications, pre-existing psychiatric disorder, or gender were not associated with response. CONCLUSION: This study shows meaningful clinical effectiveness and good tolerability of ECT in patients with severe NPS of dementia. Furthermore, maintenance ECT was effective in sustaining treatment response.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".