A Retrospective Study of Patients Undergoing Acute Electroconvulsive Therapy for Predominately Manic or Mixed Episodes With and Without Lithium in Singapore
Bibliographic record
Abstract
OBJECTIVE: The effect of lithium therapy during Electroconvulsive Therapy (ECT) on cognition and treatment effectiveness is unclear. In this study, we compare the cognitive and symptomatic outcomes of patients undergoing ECT with and without lithium in a large tertiary psychiatric institution. METHODS: Patients with predominantly manic or mixed episodes on lithium were propensity score matched with controls. Cognition was assessed using the Montreal Cognitive Assessment (MoCA), while severity of symptoms was assessed using the Brief Psychiatric Rating Scale (BPRS) and Clinical Global Impression-Severity Scale. Quality of life was assessed using the Quality of Life Enjoyment and Satisfaction Questionnaire Short Form (Q-LES-Q-SF) and EuroQol Five Dimension (EQ-5D). Linear mixed-effects modeling and conditional logistic regression were conducted as appropriate. RESULTS: 87 patients were included in the study. There was no significant difference in cognitive and symptomatic outcomes for patients receiving ECT with or without lithium after 6 sessions of ECT. CONCLUSIONS: Concurrent lithium administration during the initial acute ECT course was not associated with differential cognitive or symptomatic outcomes. Lithium administration should not be a contraindication for appropriate acute ECT treatment in patients. Larger controlled studies to confirm these findings are warranted.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".