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Parallel use of low-complexity automated nucleic acid amplification tests on respiratory and stool samples with or without lateral flow lipoarabinomannan assays to detect pulmonary tuberculosis disease in children

2025· review· en· W4411214689 on OpenAlexaff
Laura Olbrich, Bada Yang, Hayley Poore, Alia Razid, Brittney Sweetser, Mathias Damkjær, Alexander Kay, Johanna Åhsberg, Ruvandhi R. Nathavitharana, Ian Schiller, Nandini Dendukuri, Andreas Lundh, Maunank Shah, Stephanie Bjerrum, Devan Jaganath

Bibliographic record

VenueCochrane Database of Systematic Reviews · 2025
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill University Health Centre
FundersFogarty International Center
KeywordsLipoarabinomannanNucleic acidRespiratory systemMedicineNucleic Acid Amplification TestsPulmonary diseaseDiseasePulmonary tuberculosisTuberculosisMycobacterium tuberculosisMicrobiologyVirologyBiologyPathologyInternal medicineBiochemistry

Abstract

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BACKGROUND: Low-complexity automated nucleic acid amplification tests (LC-aNAATs) are molecular assays widely used to diagnose tuberculosis disease in children. The lateral flow urine lipoarabinomannan assay (LF-LAM) is recommended for use amongst children with HIV. Previous systematic reviews have assessed the diagnostic accuracy of LC-aNAATs and LF-LAM separately in children, but in clinical practice the tests may be used concurrently, i.e. in 'parallel'. OBJECTIVES: To compare the diagnostic accuracy of the parallel use of LC-aNAAT on respiratory and stool specimens in children, and with LF-LAM on urine amongst children with HIV, versus each assay alone for detecting pulmonary tuberculosis disease. SEARCH METHODS: We searched MEDLINE, Embase, Science Citation Index-Expanded, Conference Proceedings Citation Index - Science, Biosis Previews, the Cochrane Central Register of Controlled Trials, Scopus, WHO (World Health Organization) Global Index Medicus, ClinicalTrials.gov, and the WHO International Clinical Trials Registry up to 3 November 2023. There was a WHO public call for data on the accuracy of LC-aNAAT and LF-LAM for children until December 2023. SELECTION CRITERIA: We included studies that enroled children under 10 years of age with presumptive pulmonary tuberculosis, and provided data to assess the accuracy of parallel testing and at least one of the component tests, against a microbiological reference standard (MRS) based on culture or composite reference standard (CRS) that included clinical diagnosis. DATA COLLECTION AND ANALYSIS: We extracted data using a standardised form and assessed study quality using QUADAS-2 and QUADAS-C tools. We performed bivariate random-effects meta-analysis using a Bayesian approach to estimate sensitivity and specificity and absolute differences between index tests. Diagnostic accuracy estimates were calculated primarily against the MRS and secondarily against the CRS. We used GRADE to assess the certainty of the evidence on comparative accuracy. MAIN RESULTS: We included 14 studies to assess parallel testing in children with and without HIV. In addition, six of the 14 studies were included to evaluate LC-aNAATs with LF-LAM amongst children with HIV. Other than a high risk of bias with the CRS due to the potential incorporation of index results in clinical diagnoses, studies generally had low risk of bias across QUADAS-2 and QUADAS-C domains. Parallel use of respiratory and stool LC-aNAATs Children without HIV or HIV status unknown We included eight studies (2145 participants, tuberculosis prevalence 8.1% (173/2145)) for assessment against the MRS. Parallel use of LC-aNAAT on respiratory samples and stool had an estimated pooled sensitivity of 79.9% (95% credible interval (CrI) 67.9 to 89.8) and an estimated pooled specificity of 93.4% (95% CrI 87.2 to 97.0). Compared to LC-aNAAT on respiratory samples alone, parallel testing had 7.1 (95% CrI 3.2 to 13.4) percentage points higher sensitivity and -1.7 (95% CrI -3.8 to -0.6) percentage point change in specificity (both low-certainty evidence). Compared to LC-aNAAT on stool alone, parallel testing had 22.1 (95% CrI 13.7 to 32.7) percentage points higher sensitivity (moderate-certainty evidence) and a -4.1 (95% CrI -8.0 to -1.7) percentage point difference in specificity (low-certainty evidence). Children with HIV Against the MRS (seven studies, 697 participants, tuberculosis prevalence 6.3% (44/697)), parallel use of LC-aNAAT on respiratory samples and stool had an estimated pooled sensitivity of 70.2% (95% CrI 51.1 to 84.7) and specificity of 95.4% (95% CrI 91.7 to 97.8). Compared to LC-aNAAT on respiratory samples alone, parallel testing had 4.0 (95% CrI 0.6 to 12.9) percentage points higher sensitivity (moderate-certainty evidence) and -1.9 (95% CrI -3.9 to -0.7) percentage point difference in specificity (moderate-certainty evidence). Compared to LC-aNAAT on stool alone, parallel testing had 8.5 (95% CrI 2.4 to 20.9) percentage points higher sensitivity and -1.4 (95% CrI -3.3 to -0.4) percentage point difference in specificity (both moderate-certainty evidence). Composite reference standard The parallel use of respiratory and stool LC-aNAATs had lower sensitivity than the CRS in children with and without HIV, with smaller differences compared to using each component test alone (very low-certainty evidence for children without HIV; low-certainty evidence for children with HIV). The specificity of parallel testing was similar between MRS and CRS. Parallel use of respiratory and stool LC-aNAATs and LF-LAM amongst children with HIV We included six studies for the evaluation of diagnostic accuracy against the MRS (653 participants, tuberculosis prevalence 6.6% (43/653)). Parallel use of LC-aNAAT on respiratory and stool samples and LF-LAM had an estimated pooled sensitivity of 77.6% (95% CrI 60.0 to 89.6) and an estimated pooled specificity of 83.9% (95% CrI 73.9 to 90.4). Compared to LC-aNAAT on respiratory and stool samples, parallel testing had 6.9 (95% CrI 1.5 to 20.1) percentage points higher sensitivity (low-certainty evidence) and a -10.2 (95% CrI -19.6 to -4.9) percentage point difference in specificity (moderate-certainty evidence). Composite reference standard Against the CRS (six studies, 674 participants, tuberculosis prevalence 42.4% (286/674)), parallel use of LC-aNAAT on respiratory and stool samples and LF-LAM had a pooled sensitivity of 30.0% (95% CrI 13.2 to 54.8) and specificity of 83.3% (95% CrI 69.8 to 90.2). Compared to LC-aNAAT on respiratory and stool samples, parallel testing had 11.5 (95% CrI 3.8 to 26.7) percentage points higher sensitivity (very low-certainty evidence) and -10.1 (95% CrI -21.6 to -4.9) percentage point difference in specificity (low-certainty evidence). AUTHORS' CONCLUSIONS: Using LC-aNAAT with both respiratory and stool samples may increase the sensitivity of diagnostic testing for tuberculosis in children, including those with HIV, and the addition of LF-LAM for children with HIV may further increase sensitivity, although at the cost of reduced specificity. Stool and urine testing is non-invasive and may complement testing respiratory samples to increase tuberculosis case detection in children. The benefits of parallel testing may be greater in settings with high tuberculosis prevalence, while there may be a larger proportion of false-positive results and greater risk of overtreatment in areas of low tuberculosis prevalence. FUNDING: Liverpool School of Tropical Medicine, Foreign, Commonwealth and Development Office (FCDO) WHO, TB Prevention, Diagnosis, Treatment, Care & Innovation (PCI), Global TB Programme REGISTRATION: Protocol available via https://doi.org/10.1002/14651858.CD016071, version published 13 May 2024.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.065
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.065
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0070.007
Science and technology studies0.0000.001
Scholarly communication0.0030.003
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.151
GPT teacher head0.400
Teacher spread0.249 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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".

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Citations1
Published2025
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