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Record W3111581604 · doi:10.5588/ijtld.20.0458

Impact of mental disorders on active TB treatment outcomes: a systematic review and meta-analysis

2020· review· en· W3111581604 on OpenAlexaff
Ga Eun Lee, James Scuffell, Jerome T. Galea, Sanghyuk S. Shin, E. Magill, E. Jaramillo, Annika C. Sweetland

Bibliographic record

VenueThe International Journal of Tuberculosis and Lung Disease · 2020
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill University
FundersNational Institute of Allergy and Infectious DiseasesNational Institute of Mental HealthWorld Health Organization
KeywordsMedicineMeta-analysisOdds ratioConfidence intervalRandom effects modelStudy heterogeneityComorbidityMEDLINEMental healthPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Comorbid mental disorders in patients with TB may exacerbate TB treatment outcomes. We systematically reviewed current evidence on the association between mental disorders and TB outcomes. METHODS: We searched eight databases for studies published from 1990 to 2018 that compared TB treatment outcomes among patients with and without mental disorders. We excluded studies that did not systematically assess mental disorders and studies limited to substance use. We extracted study and patient characteristics and effect measures and performed a meta-analysis using random-effects models to calculate summary odds ratios (ORs) with 95% confidence intervals (CIs). RESULTS: Of 7687 studies identified, 10 were included in the systematic review and nine in the meta-analysis. Measurement of mental disorders and TB outcomes were heterogeneous across studies. The pooled association between mental disorders and any poor outcome, loss to follow-up, and non-adherence were OR 2.13 (95%CI 0.85–5.37), 1.90 (95%CI 0.33–10.91), and 1.60 (95%CI 0.81–3.02), respectively. High statistical heterogeneity was present. CONCLUSION: Our review suggests that mental disorders in TB patients increase the risk of poor TB outcomes, but pooled estimates were imprecise due to small number of eligible studies. Integration of psychological and TB services might improve TB outcomes and progress towards TB elimination.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.089
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0060.007
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 head0.069
GPT teacher head0.444
Teacher spread0.374 · 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 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

Citations26
Published2020
Admission routes1
Has abstractyes

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