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Record W4221114263 · doi:10.1016/s2352-3018(22)00002-9

Tuberculosis screening among HIV-positive inpatients: a systematic review and individual participant data meta-analysis

2022· article· en· W4221114263 on OpenAlexaff

Bibliographic record

VenueThe Lancet HIV · 2022
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsTrillium Health Centre
FundersFogarty International CenterNational Institutes of HealthCochrane South AfricaDepartment of Science and Technology, Ministry of Science and Technology, IndiaMedical Research CouncilSouth African Medical Research CouncilNational Research FoundationGovernment of the United KingdomWellcome TrustWorld Health Organization
KeywordsTuberculosisMEDLINESystematic reviewPublic healthAlternative medicineEpidemiology

Abstract

fetched live from OpenAlex

BACKGROUND: Since 2011, WHO has recommended that HIV-positive inpatients be routinely screened for tuberculosis with the WHO four-symptom screen (W4SS) and, if screened positive, receive a molecular WHO-recommended rapid diagnostic test (eg, Xpert MTB/RIF [Xpert] assay). To inform updated WHO tuberculosis screening guidelines, we conducted a systematic review and individual participant data meta-analysis to assess the performance of W4SS and alternative screening tests to guide Xpert testing and compare the diagnostic accuracy of the WHO Xpert algorithm (ie, W4SS followed by Xpert) with Xpert for all HIV-positive inpatients. METHODS: We searched MEDLINE, Embase, and Cochrane Library from Jan 1, 2011, to March 1, 2020, for studies of adult and adolescent HIV-positive inpatients enrolled regardless of tuberculosis signs and symptoms. The separate reference standards were culture and Xpert. Xpert was selected since it is most likely to be the confirmatory test used in practice. We assessed the proportion of inpatients eligible for Xpert testing using the WHO algorithm; assessed the accuracy of W4SS and alternative screening tests or strategies to guide diagnostic testing; and compared the accuracy of the WHO Xpert algorithm (W4SS followed by Xpert) with Xpert for all. We obtained pooled proportion estimates with a random-effects model, assessed diagnostic accuracy by fitting random-effects bivariate models, and assessed diagnostic yield descriptively. This systematic review has been registered on PROSPERO (CRD42020155895). FINDINGS: ), and lymphadenopathy had higher specificities (61-90%) but suboptimal sensitivities (12-57%). The WHO Xpert algorithm (W4SS followed by Xpert) had a sensitivity of 76% (95% CI 67-84) and specificity of 93% (88-96; n=637). Xpert for all had similar accuracy to the WHO Xpert algorithm: sensitivity was 78% (95% CI 69-85) and specificity was 93% (87-96; n=639). In two cohorts that had sputum and non-sputum samples collected for culture or Xpert, diagnostic yield of sputum Xpert was 41-70% and 61-64% for urine Xpert. INTERPRETATION: The W4SS and other potential screening tests to guide Xpert testing have suboptimal accuracy in HIV-positive inpatients. On the basis of these findings, WHO now strongly recommends molecular rapid diagnostic testing in all medical HIV-positive inpatients in settings where tuberculosis prevalence is higher than 10%. FUNDING: World Health Organization.

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)0.006
metaresearch head score (Gemma)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.867
Threshold uncertainty score0.794

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.304
GPT teacher head0.395
Teacher spread0.091 · 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
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

Citations42
Published2022
Admission routes1
Has abstractyes

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