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Record W2604111259 · doi:10.1192/bjp.bp.116.195826

Adjunctive ketamine in electroconvulsive therapy: Updated systematic review and meta-analysis

2017· review· en· W2604111259 on OpenAlexafffund
Alexander McGirr, Marcelo T. Berlim, David J. Bond, Peter Y. Chan, Lakshmi N. Yatham, Raymond W. Lam

Bibliographic record

VenueThe British Journal of Psychiatry · 2017
Typereview
Languageen
FieldMedicine
TopicTreatment of Major Depression
Canadian institutionsVancouver General HospitalMcGill UniversityDouglas Mental Health University InstituteUniversity of British Columbia
FundersCanadian Institutes of Health ResearchVictoria General Hospital FoundationCanadian Network for Mood and Anxiety TreatmentsMichael Smith Health Research BCGlaxoSmithKlineServierFondation Brain CanadaPfizerAstraZenecaEli Lilly and CompanyBristol-Myers Squibb
KeywordsElectroconvulsive therapyKetamineMeta-analysisMedicinePsychologyPsychotherapistPsychiatryInternal medicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

Background Ketamine has emerged as a novel therapeutic agent for major depressive episodes, spurring interest in its potential to augment electroconvulsive therapy (ECT). Aims We sought to update our preliminary systematic review and meta-analysis, focusing on randomised controlled trials (RCTs) involving an index course of ECT, and testing the hypothesis that lack of efficacy is due to barbiturate anaesthetic co-administration. Method We searched EMBASE, CENTRAL and Medline to identify RCTs examining the efficacy of ketamine during a course of ECT. Data were synthesised from ten trials (ketamine group n = 333, comparator group n = 269) using pooled random effects models. Results Electroconvulsive therapy with ketamine was not associated with greater improvements in depressive symptoms or higher rates of clinical response or remission, nor did it result in pro-cognitive effects. This held true when limiting analysis to trials without barbiturate anaesthetic co-administration. Increased rates of confusion were reported. Conclusions Overall, our analyses do not support using ketamine over other induction agents in ECT.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.323
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0120.004
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.377
Teacher spread0.298 · 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 teacher head, not a consensus.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations66
Published2017
Admission routes2
Has abstractyes

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