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The Impact of Clinically Diagnosed Personality Disorders on Acute and One-Year Outcomes of Electroconvulsive Therapy

2000· article· en· W1979350490 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Ect · 2000
Typearticle
Languageen
FieldMedicine
TopicElectroconvulsive Therapy Studies
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsElectroconvulsive therapyDepression (economics)Retrospective cohort studyPersonality disordersPsychiatryMedicinePersonalityMajor depressive disorderComorbidityInternal medicinePsychologyClinical psychologySchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

Clinical experience suggests that patients with depression and a comorbid personality disorder (PD) may have a poorer response to electroconvulsive therapy (ECT). Only a few published studies have examined the relationship between comorbid personality disorders and response of major depression to ECT. These studies have used relatively small numbers of patients. The present study is a retrospective review of 107 inpatients with a major depressive episode referred for ECT. Patients with a clinically diagnosed PD, especially a cluster B PD, had a significantly poorer acute response to ECT than those without a PD. During the first year after treatment, ECT responders with a comorbid PD had a higher rate of relapse of depression. The retrospective study design limits the strength of conclusions that can be drawn. Nevertheless, it appears that clinically diagnosed PDs may be predictive of poor outcome in patients receiving ECT for depression. Further prospective study of the relationship between both clinically diagnosed PDs and structured interview based PD diagnoses and ECT treatment response is warranted.

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.

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)0.001
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 score0.068
Threshold uncertainty score0.371

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.020
GPT teacher head0.360
Teacher spread0.341 · 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