Impact of Anesthesia on Electroconvulsive Therapy–Related Impairments in Global Cognitive Function in Patients With Treatment-Resistant Depression
Bibliographic record
Abstract
INTRODUCTION: Electroconvulsive therapy (ECT) in patients with treatment-resistant depression frequently leads to impairments in global cognitive function. Propofol and etomidate are the 2 most frequently used drugs for anesthetic induction during ECT. However, only few studies compared their differential impact on ECT-related impairments in global cognitive function. METHODS: We studied retrospectively 75 patients hospitalized at Centre Hospitalier Le Vinatier (Bron, France) who met the DSM-V criteria for major depressive disorder and were treated with bilateral ECT to compare the effects of propofol and etomidate on ECT-related cognitive impairment. Global cognitive function was assessed with the Montreal Cognitive Assessment (MoCA), and symptom severity was assessed using the Montgomery-Åsberg Depression Rating Scale (MADRS), both before and after treatment. The primary endpoint of the study was the change in MoCA score. RESULTS: We found no significant difference in MoCA score variation between the etomidate and propofol groups. There were also no significant differences in MADRS score variation, responder, remission rate or ECT parameters between the 2 groups (except duration of electroencephalogram crisis). CONCLUSIONS: In this retrospective study, choice of etomidate or propofol as anesthetic agent had no impact on the adverse effects associated with ECT on global cognitive function in patients with treatment-resistant depression.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".