Association between pulse width and health-related quality of life after electroconvulsive therapy in patients with unipolar or bipolar depression: an observational register-based study
Bibliographic record
Abstract
Aims To examine the association between pulse width and HRQoL measured within one week after electroconvulsive therapy (ECT) and at six-month follow-up in patients with unipolar or bipolar depression.Methods This was an observational register study using data from the Swedish National Quality Registry for ECT (2011–2019). Inclusion criteria were: age ≥18 years; index treatment for unipolar/bipolar depression; unilateral electrode placement; information on pulse width; EQ-5D measurements before and after ECT. Multiple linear regressions were performed to investigate the association between pulse width (<0.5 ms; 0.5 ms; >0.5 ms) and HRQoL (EQ-5D-3L index; EQ VAS) one week after ECT (primary outcome) and six months after ECT (secondary outcome).Results The sample included 5,046 patients with unipolar (82%) or bipolar (18%) depression. At first ECT session, 741 patients (14.7%) had pulse width <0.5 ms, 3,639 (72.1%) had 0.5 ms, and 666 (13.2%) had >0.5 ms. There were no statistically significant associations between pulse width and HRQoL one week after ECT. In the subsample of patients with an EQ-5D index recorded six months after ECT (n = 730), patients receiving 0.5 ms had significantly lower HRQoL (−0.089) compared to <0.5 ms, after adjusting for demographic and clinical characteristics (p = .011). The corresponding analysis for EQ VAS did not show any statistically significant associations.Conclusion No robust associations were observed between pulse width and HRQoL after ECT. On average, significant improvements in HRQoL were observed one week and six months after ECT for patients with unipolar or bipolar disease, independent of the pulse width received.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".