Continuation Electroconvulsive Therapy for Patients With Clozapine-Resistant Schizophrenia
Bibliographic record
Abstract
OBJECTIVES: The risk of relapse after a successful acute course of treatment is a clinical challenge in electroconvulsive therapy (ECT) practice, particularly in patients with a history of marked resistance to previous treatments. Research suggests that a gradual decrease of ECT or its long-term continuation might be the best strategy. Notwithstanding, current studies do not address the role of continuation ECT in the truly refractory cases, that is, the clozapine-resistant patients. Our group published a randomized controlled trial of ECT augmentation of clozapine in clozapine-resistant patients with schizophrenia, where the augmentation was vastly superior in efficacy for the acute treatment. The aim of the current study is to evaluate the efficacy of continuation ECT for patients who showed response to the combination of acute ECT and clozapine for treatment-resistant schizophrenia. METHODS: Continuation ECT was offered to all patients who completed the acute study and who met response criterion. We followed a tapered schedule of 4 weekly ECT sessions, followed by 4 ECT sessions every 2 weeks and 2 monthly ECT sessions for a total of 10 sessions. RESULTS: Patients sustained the gains achieved with the acute course of ECT, and no individual patient presented with clinically relevant worsening of symptoms. Moreover, the long-term use of ECT was not associated with added adverse effects. CONCLUSIONS: This is an open pilot study with a small sample size, and results should be interpreted accordingly, but this report offers a relevant starting point for much needed future studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".