Psychiatric, Motor, and Autonomic Effects of Bifrontal ECT in Depressed Parkinson’s Disease Patients
Bibliographic record
Abstract
OBJECTIVE: Depressive symptoms are a source of significant morbidity in Parkinson's disease (PD). Electroconvulsive therapy (ECT) is a promising treatment for depression in PD (dPD); however, data remain limited, including data on optimal electrode placement. In this retrospective study, the investigators aimed to characterize the effects of bifrontal ECT for dPD on psychiatric and motor symptoms, as well as autonomic response. METHODS: Clinical data were retrieved from a university-affiliated ECT service in Vancouver, British Columbia, for patients with dPD receiving bifrontal ECT between 2014 and 2018. Clinical Global Impression (depressive symptoms) and Unified Parkinson's Disease Rating Scale (motor symptoms) scores and cardiovascular measurements during ECT, as well as doses of dopaminergic medications, were recorded. RESULTS: Eight patients met criteria for inclusion. Six patients (75%) met response criteria for improvement of depressive symptoms, including 83% of patients who completed a full ECT course. Five patients went on to receive maintenance ECT, with only one patient relapsing by the 1-year follow-up (20%). For patients with motor scales reported, 60% showed a clinically significant improvement in motor symptoms. Among patients who completed ECT, a reduction in the median dopaminergic medication dose was also observed (-350 mg). Two patients discontinued ECT as a result of tolerability concerns. Participants demonstrated a relatively typical pattern of autonomic response to ECT, with low incidence of bradycardic events. CONCLUSIONS: The results provide preliminary evidence of the benefit of bifrontal ECT in dPD for both depressive and motor symptoms. The autonomic data suggest that most patients with dPD respond in a typical physiological manner to ECT stimulus; however, further investigation is needed.
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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 | 0.002 |
| 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".