Electrical Dose and Seizure Threshold: Relations to Clinical Outcome and Cognitive Effects in Bifrontal, Bitemporal, and Right Unilateral ECT
Bibliographic record
Abstract
In patients allocated blindly and randomly to receive bitemporal, right unilateral, or bifrontal electroconvulsive therapy, seizure length, electrophysiologic characteristics (dynamic impedance, seizure threshold, and changes in threshold), and the degree of suprathreshold stimulation were recorded. The relations of these variables to clinical outcome and cognitive effects were determined. There were no differences in seizure length between groups, and there were no significant correlations between seizure length and any measure of clinical response. There were substantial differences between the groups in mean charge per treatment, with the right unilateral group receiving lower doses than either bilateral group. Convulsion time was inversely related to applied charge and the rate of increase in charge. There were no significant correlations between impedance, charge, energy, or rate of increase in charge on the one hand, and clinical improvement on the other. The increase in threshold during the course of treatment was not related to clinical change. Cognitive impairment was related to electrical dose only in the bifrontal group, which showed the least degree of treatment-induced intellectual dysfunction. Compared with bitemporal or right unilateral treatment, bifrontal electroconvulsive therapy yields the best ratio of benefits to side effects and should be given at threshold level to minimize cognitive loss.
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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 | 0.003 |
| 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".