Comparison of the target-controlled infusion and the manual infusion of propofol anesthesia during electroconvulsive therapy: an open-label randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Target-controlled infusion (TCI) of propofol is a well-established method of procedural sedation and has been used in Japan for anesthesia during electroconvulsive therapy (ECT). However, the usefulness of the TCI of propofol for ECT has yet to be determined. This study aimed to compare the TCI and manual infusion (MI) of propofol anesthesia during ECT. METHODS: A total of forty psychiatric inpatients receiving bitemporal ECT were enrolled in the present study and randomized into the TCI group (N = 20) and the MI group (N = 20). Clinical Global Impression (CGI) and Montreal Cognitive Assessment (MoCA) scores were measured before and after ECT. The clinical outcomes, anesthesia-related variables, and ECT-related variables were compared between the two groups. Generalized estimating equations (GEEs) were used to model the comparison throughout the course of ECT. RESULTS: A total of 36 subjects completed the present study, with 18 subjects in each group. Both the groups didn't significantly differ in the post-ECT changes in CGI and MoCA scores. However, concerning MoCA scores after 6 treatments of ECT, the MI group had improvement while the TCI group had deterioration. Compared with the MI group, the TCI group had higher doses of propofol, and longer procedural and recovery time. The TCI group seemed to have more robust seizures in the early course of ECT but less robust seizures in the later course of ECT compared with the MI group. CONCLUSIONS: The present study does not support the use of TCI of propofol for anesthesia of ECT. TRIAL REGISTRATION: (ClinicalTrials.gov): NCT03863925 . Registered March 5, 2019 - Retrospectively registered.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".