SynthesisJournal of clinical microbiology2019
Diagnostic Accuracy of Stool Xpert MTB/RIF for Detection of Pulmonary Tuberculosis in Children: a Systematic Review and Meta-analysis.
Synthesis in Journal of clinical microbiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers, 11 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
62 citing papers in PubMed, 11 syntheses or guidelines pooled it, 98 citations in OpenAlex.
- Diagnostic accuracy of stool Xpert MTB/RIF assay for adult pulmonary tuberculosis: a systematic review and meta-analysis.BMC infectious diseases · 2026Pooled it
- Xpert MTB/RIF Ultra assay for tuberculosis disease and rifampicin resistance in children.The Cochrane database of systematic reviews · 2025Pooled it
- 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.The Cochrane database of systematic reviews · 2025Pooled it
- Stool specimen for diagnosis of pulmonary tuberculosis in adults: a systematic review.BMJ open · 2023Pooled it
- Stool Xpert MTB/RIF as a possible diagnostic alternative to sputum in Africa: a systematic review and meta-analysis.Frontiers in public health · 2023Pooled it
- Outlook for CRISPR-based tuberculosis assays now in their infancy.Frontiers in immunology · 2023Pooled it
- Xpert MTB/RIF Ultra assay for tuberculosis disease and rifampicin resistance in children.The Cochrane database of systematic reviews · 2022Pooled it
- Xpert Ultra stool testing to diagnose tuberculosis in children in Ethiopia and Indonesia: a model-based cost-effectiveness analysis.BMJ open · 2022Pooled it
- Evaluating the efficacy of stool sample on Xpert MTB/RIF Ultra and its comparison with other sample types by meta-analysis for TB diagnostics.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2022Pooled it
- Xpert MTB/RIF and Xpert MTB/RIF Ultra assays for active tuberculosis and rifampicin resistance in children.The Cochrane database of systematic reviews · 2020Pooled it
- Diagnostic accuracy of molecular detection of Mycobacterium tuberculosis in pediatric stool samples: A systematic review and meta-analysis.Tuberculosis (Edinburgh, Scotland) · 2019Pooled it
- Bronchoalveolar Lavage Fluid Lipoarabinomannan as a Rapid Rule-Out Tool for Smear-Negative Pulmonary Tuberculosis in a Nonhuman Immunodeficiency Virus-Predominant, High-Burden Setting: A Prospective Study.Open forum infectious diseases · 2026Article
- Current Landscape of Molecular Diagnostic Tests and Emerging Tools for Tuberculosis and Drug Resistance.Diagnostics (Basel, Switzerland) · 2026Review
- Article
- Stool Processing Methods for Xpert Ultra Testing in Childhood Tuberculosis: A Prospective, Multicountry Accuracy Study.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026Article
- Comparison of stool and gastric content samples analyzed with genexpert ultra for the diagnosis of pulmonary tuberculosis in children under five in Niger: a multi-center diagnostic study.BMC microbiology · 2026Article
- Global, Regional, and National Burden of Tuberculosis Among Children: A Population-Based Study.Tropical medicine and infectious disease · 2026Article
- GeneXpert MTB/RIF Ultra in Pediatric Tuberculosis: How Disease Characteristics Modify Test Performances.Current pediatric reviews · 2026Article
- Sputum scarcity among adolescents and adults with presumptive tuberculosis: a systematic review and meta-analysis.medRxiv : the preprint server for health sciences · 2025Article
- Utility of alternative specimens in the diagnosis of pulmonary tuberculosis in people living with human immunodeficiency virus in Guinea.BMC infectious diseases · 2025Article
2 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Invasive collection methods are often required to obtain samples for the microbiological evaluation of children with presumptive pulmonary tuberculosis (PTB). Nucleic acid amplification testing of easier-to-collect stool samples could be a noninvasive method of diagnosing PTB. We conducted a systematic review and meta-analysis to evaluate the diagnostic accuracy of testing stool with the Xpert MTB/RIF assay ("stool Xpert") for childhood PTB. Four databases were searched for publications from January 2008 to June 2018. Studies assessing the diagnostic accuracy among children of stool Xpert compared to a microbiological reference standard of conventional specimens tested by mycobacterial culture or Xpert were eligible. Bivariate random-effects meta-analyses were performed to calculate pooled sensitivity and specificity of stool Xpert against the reference standard. From 1,589 citations, 9 studies (
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.