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Record W2472927631 · doi:10.1016/s0924-9338(15)30858-0

Early Outcomes of the Integrated Care Pathway for Concurrent Major Depressive Disorder and Alcohol Dependence

2015· article· en· W2472927631 on OpenAlexaff
Andriy V. Samokhvalov, S. Awan, Peter Voore

Bibliographic record

VenueEuropean Psychiatry · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsCentre for Addiction and Mental Health
Fundersnot available
KeywordsMajor depressive disorderSample size determinationMedicineAlcohol use disorderDownloadDepressive symptomsSocioeconomic statusDepression (economics)PsychiatryClinical psychologyPsychologyInternal medicineAlcoholAnxietyPopulation

Abstract

fetched live from OpenAlex

Both Major Depressive Disorder (MDD) and Alcohol Dependence (AD) are highly prevalent, comorbid and have significant impact on morbidity, mortality and socioeconomic burden. Several studies have suggested that these concurrent conditions lead to suboptimal treatment outcomes. Combined psycho- and pharmacotherapies for both conditions promise better outcomes than treatment as usual. We developed and implemented an Integrated Care Pathway (ICP) specifically for concurrent MDD and AD. The aim of the study is to assess the clinical effectiveness of the ICP approach. To compare treatment completion rates between the ICP and historical controls To describe the changes in patterns of drinking and severity of depressive symptoms in ICP patients. Review of clinical charts of ICP patients (n=28) and historical controls (n=92). The ICP patients had significantly higher treatment completion rates compared to historical controls (53.8% vs 21.7%; Fig. 1) Download : Download full-size image Data on patterns of drinking (reduction of percent heavy drinking days from 51.4% to 34.5%), and severity of cravings and depressive symptoms (Fig. 2) were not sufficient for proper statistical testing due to small sample size and multiple missing data points, but showed a tendency for improvement. Download : Download full-size image2 2 ICP patients showed a tendency for improvement and significantly greater treatment completion rates than historical controls. Larger sample size and further data collection are needed to corroborate these findings.

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 score0.139
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.018
GPT teacher head0.278
Teacher spread0.260 · 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

Citations5
Published2015
Admission routes1
Has abstractyes

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