Stimulus Pulse-Frequency-Dependent Efficacy and Cognitive Adverse Effects of Ultrabrief-Pulse Electroconvulsive Therapy in Patients With Major Depression
Bibliographic record
Abstract
BACKGROUND: : Electroconvulsive therapy (ECT) is a highly effective treatment for major depression. New ECT devices with shorter pulse widths seem to induce seizures more effectively at a lower seizure threshold and with fewer cognitive adverse effects. Suprathreshold right unilateral (RUL) ultrabrief-pulse ECT with pulse widths between 0.25 and 0.30 millisecond seem to be especially effective with regard to efficacy and cognitive adverse effects. A lower pulse frequency (50 pulses per second) in RUL ECT was found to be more efficient than a higher pulse frequency (200 pulses per second) in inducing seizures. However, effective stimulus dose can often be achieved only with high stimulus frequency, whereas the impact of increased stimulus frequency on antidepressant efficacy and cognitive adverse effects is not known. METHODS: : Forty patients with major depression according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition were randomly assigned to 2 groups of 20 patients each and stimulated with either 40 or 100 Hz with equal initial stimulus doses in 9 sessions of suprathreshold RUL ultrabrief-pulse ECT. Depressive symptoms and measures of verbal and working memory were assessed for both groups. RESULTS: : Patients in the 40-Hz condition showed significantly more improvement in Hamilton Rating Scale for Depression scores compared with patients in the 100-Hz condition after 9 ECT sessions. Frequency group had no significant impact on measures of verbal and working memory. CONCLUSIONS: : Within the discussed limitations, our preliminary data suggest an advantage for administering stimulus dose in suprathreshold RUL ultrabrief-pulse ECT with a lower stimulus frequency (40 Hz) as compared with a higher frequency (100 Hz). Further studies are needed to assess whether increasing pulse widths or frequency is the better option for augmenting stimulus dose once other stimulus parameters are at a maximum.
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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".