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Record W3135862968 · doi:10.4236/ojpsych.2021.112006

A Prospective Study of Maintenance Electroconvulsive Therapy in an Elderly Depressed Population

2021· article· en· W3135862968 on OpenAlexafffund
P. Murali Krishna, Lakyntiew Aulakh, Declan Boylan, Louis Lakatos

Bibliographic record

VenueOpen Journal of Psychiatry · 2021
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsNOSM UniversityLaurentian UniversityHealth Sciences North
FundersNorthern Ontario Academic Medicine Association
KeywordsElectroconvulsive therapyGeneralizability theoryDepression (economics)PopulationPsychologyTreatment and control groupsQuality of life (healthcare)MedicinePsychiatryClinical psychologyInternal medicineCognitionPsychotherapist

Abstract

fetched live from OpenAlex

Objective: This study was conducted to discern the efficacy of maintenance electroconvulsive therapy (M-ECT) in a population of depressed elderly individuals with treatment-resistant depression. Methodology: Twenty-nine (N = 29) individuals over the age of 65 years of age and older were assigned to a control or treatment group on the basis of their decision to receive M-ECT (treatment group) or to refrain from receiving the treatment (control group). A battery of psychometric tests designed to measure severity of depression, quality of life, and cognition were administered at baseline as well as at 6-month and 1-year intervals. Results: Statistical analysis of the data indicated no significant differences in the efficacy of M-ECT between the control and treatment groups in any of the tests administered during the participation of the study. Conclusion: The results of the study suggest that there is no added benefit for patients administered M-ECT. However, study sample size and availability of alternative treatment regimens for the control group limit generalizability of these findings and warrant further investigation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.548

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.341
Teacher spread0.322 · 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.

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
Published2021
Admission routes2
Has abstractyes

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