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Prevalence of suicidal ideations and suicide attempts in patients with tuberculosis: A systematic review and meta-analysis

2023· review· en· W4318035719 on OpenAlexaboutno aff
Rahul Patwal, Aishwarya Sachdeva, Binukumar Bhaskarapillai, Rashmi Arasappa, Krishna Prasad Muliyala, Geetha Desai

Bibliographic record

VenueJournal of Psychosomatic Research · 2023
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisMedicinePsychiatryClinical psychologyPsychologyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Suicide and suicidal behaviors are reported to be common in patients with Tuberculosis (TB). This systematic review and meta-analysis aimed to quantitively assess the prevalence of suicidality and identify the factors associated with suicidality in patients with TB. METHODS: We searched databases PubMed, SCOPUS, Web of Science, PsycINFO, and Google Scholar for studies that reported the prevalence of suicide, suicidal ideations, or suicide attempts in patients with TB. We assessed the quality of studies with the Newcastle Ottawa scale. Random-effects models were used to calculate the pooled prevalence with 95% confidence intervals (CI). RESULTS: Nine studies (8770 participants) were included. Pooled prevalence for current suicidal ideations within the last year was 8.5% [95% CI: 5.8%12.3%]. Pooled prevalence for current suicidal attempts within the last year was 3.1% [2.2%- 4.5%]. Suicide was reported in 0.92% of TB patients at the end of 2 years, whereas 2.2% to 8.4% of all TB deaths were reported due to suicide. Factors associated with suicidality were female gender, TB retreatment, comorbid HIV, presence of another chronic medical illness, psychological distress, and comorbid psychiatric illnesses. CONCLUSION: The prevalence rates of suicidal ideation and attempts were higher in patients with TB than in the general population. Integrating mental health services with TB programs will help develop interventions for high-risk individuals. Prospero registration number: CRD42021281849.

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)0.007
metaresearch head score (Gemma)0.001
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 score0.727
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0090.001
Bibliometrics0.0030.004
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 head0.252
GPT teacher head0.491
Teacher spread0.239 · 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

Citations12
Published2023
Admission routes1
Has abstractyes

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