Risk of Dementia After Electroconvulsive Therapy: A Cohort Study on the Population of Wales
Bibliographic record
Abstract
ABSTRACT Background Electroconvulsive therapy (ECT) is the most effective therapy for severe or treatment‐resistant depression. A common short‐term side effect is memory problems, and it is important to know whether ECT increases the risk for dementia later in life. Major psychiatric disorders are associated with an increased risk for developing dementia, making the analysis of dementia risk challenging. A small number of previous studies indicate that ECT does not increase this risk. We wanted to examine the association between ECT and subsequent risk of dementia in the population of Wales, UK. Methods We analysed the electronic health records of the Welsh population. We selected 110,774 people aged between 35 and 65 on 1.1.1995 who had no prior diagnosis of dementia and had been hospitalised with diagnoses of affective disorders. Of those, 1010 received at least one course of ECT between 1995 and 2024 before a diagnosis of dementia. Results The 110,774 persons were followed up until the end of the study period in 2024, or the date of dementia diagnosis, or the date of death, for a mean of 24.5 (SD = 6.3) years. 15.4% of the ECT group developed dementia, compared to 13.1% for the non‐ECT‐treated individuals. After controlling for age, sex, social deprivation status, physical comorbidities, history of alcohol abuse, the number of psychiatric hospitalisations and the age when they first occurred, the hazard ratio for dementia was not increased in the ECT group: HR = 0.888, 95% CI: 0.757–1.044, p = 0.15. Conclusions Though crude analyses found a greater risk of dementia among those receiving ECT, once confounders were accounted for, we failed to find a statistically significant risk for dementia among those who received ECT. Our findings strengthen the conclusions of previous reports and provide further reassurance for people considering this treatment.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".