MétaCan
Menu
Back to cohort
Record W6887723775 · doi:10.17605/osf.io/rxjkm

Effectiveness of electroconvulsive therapy (ECT) in patients without capacity to consent

2022· other· en· W6887723775 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Science Framework · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsObservational studyElectroconvulsive therapyInformed consentGrading (engineering)Data extractionPopulationMEDLINEAutonomyRandomized controlled trial

Abstract

fetched live from OpenAlex

Review Title: Effectiveness of electroconvulsive therapy (ECT) in patients without capacity to consent Background: Although clinical efficacy of ECT has been established in several randomized controlled trials, clear evidence concerning the clinical effectiveness of ECT in patients without capacity to consent is lacking because these patients have been excluded from those clinical trials. Study Aim: To investigate the clinical effectiveness of ECT in patients without capacity to consent compared to those with capacity to consent. Method: The literature search, decisions on inclusion, data extraction will be performed independently by two researchers (A.T. and D.Z-W.). Because potential studies are expected to be observational studies given the target population (i.e., patients who lack capacity to consent), we will follow the Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Literature Search PubMed, PsycINFO, Web of Science, and Embase are going to be searched using the following keywords: (Electroconvulsive OR ECT) AND (consent OR involuntary OR incapable OR capacity OR refusal OR autonomy OR coercion). A manual search of reference lists in relevant publications will be conducted to supplement the electronic search. All articles meeting the eligibility criteria are going to be assessed for their quality by two researchers (A.T. and D.Z-W.) in accordance with the Grading of Recommendations, Assessment, Development and Evaluation (GRADE). Risk of bias is going to be assessed by using the Newcastle-Ottawa Scale. Scores will be determined by consensus between the two researchers. Full-text peer-reviewed article written in English, German, Dutch, or Japanese are going to be reviewed for eligibility according to the following criteria. Eligibility criteria Study design: We will not limit the study design and include observational studies, case series, and case report because we do not expect any randomized controlled trial given the target population. Participants: We will include studies which focus on adult patients without capacity to consent. Studies including only children or adolescents will be excluded because they are usually regarded as individuals without capacity to consent regardless of severity of psychiatric symptoms. Studies which do not report consent status will be excluded. We will not limit the diagnoses (e.g., major depressive disorder, bipolar disorder, or schizophrenia) because patients without capacity to consent may present with similar symptoms/conditions regardless of their primary diagnosis (e.g., catatonic stupor, severe psychotic symptoms, or a refusal of food or pharmacological treatment due to delusional thinking). Intervention: Any types of ECT (e.g., bilateral or unilateral) will be included. Comparison: We will compare patients with/without capacity to consent. Outcomes: The primary outcome is the clinical effectiveness (e.g., symptom reduction or response rate). When any numerical rating scales for specific symptoms (e.g., Hamilton Depression Rating Scale: HAM-D, Montgomery Asberg Depression Rating Scale: MADRS, the Positive and Negative Syndrome Scale: PANSS, Brief Psychiatric Rating Scale: BPRS) are not reported, assessments for global symptoms (e.g., Clinical Global Impression: CGI) or functioning (e.g., Global Assessment of Functioning: GAF) will be extracted. When none of the assessment scales are not reported in case series/reports, clinical description will be extracted. The secondary outcomes include tolerability (e.g., incidence of side effects, such as cognitive impairment) and patients' perspective (e.g., satisfaction). Data extraction In addition to the above-mentioned outcomes, we will extract clinical characteristics of the participants (e.g., age, sex, and baseline severity) and ECT parameters (e.g., electrode placement, pulse width, number of ECT sessions). When articles do not provide sufficient information, we will contact corresponding authors to request data. Data analysis In addition to a systematic review, we will conduct a meta-analysis to numerically summarize our findings using relevant articles. First, we will select studies including both patients with/without capacity to consent to compare the clinical effectiveness of ECT between those groups. Second, we will select studies including only patients who lack capacity to consent without any comparison groups to calculate summary statistics. Data analyses are going to be performed using Comprehensive Meta-Analysis version 3.0. For studies which report clinical effectiveness of ECT in patients who lack capacity to consent compared to those who have capacity to consent, the effect size (Hedge's g for continuous outcomes and odds ratio for dichotomous outcomes) will be calculated with 95% confidence intervals, using random effect models. Heterogeneity is going to be reported using τ2, I2, Q, and P values. To investigate the effect of age, diagnosis, ECT parameters, clinical assessment (e.g., response rate or numerical rating scales), and quality of the studies on results, we will conduct a subgroup/meta-regression analysis. Egger’s regression test, followed by Duval & Tweedie’s trim and fill method, are going to be used to assess publication bias. Key Words: electroconvulsive therapy; consent; effectiveness; systematic review; meta-analysis; schizophrenia; bipolar disorder; major depressive disorder; catatonia Conflict of Interest: None

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.033
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.033
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.027
GPT teacher head0.342
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueOpen Science FrameworkFrench-language works237,207