ArticleCureus2019
Tissue Xpert® MTB/RIF Assay in Peritoneal Tuberculosis: To be (Done) or Not to be (Done).
Article in Cureus, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 4 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
5 citing papers in PubMed, 4 syntheses or guidelines pooled it, 9 citations in OpenAlex.
- Efficacy of Xpert in tuberculosis diagnosis based on various specimens: a systematic review and meta-analysis.Frontiers in cellular and infection microbiology · 2023Pooled it
- Meta-analysis of diagnostic accuracy of nucleic acid amplification tests for abdominal tuberculosis.PloS one · 2023Pooled it
- Xpert Ultra versus Xpert MTB/RIF for pulmonary tuberculosis and rifampicin resistance in adults with presumptive pulmonary tuberculosis.The Cochrane database of systematic reviews · 2021Pooled it
- Xpert MTB/RIF Ultra and Xpert MTB/RIF assays for extrapulmonary tuberculosis and rifampicin resistance in adults.The Cochrane database of systematic reviews · 2021Pooled it
- Lymphocyte-Predominant Ascites as a Clue to Peritoneal Tuberculosis: Two Case Reports and a Literature Review.Infection and drug resistance · 2026Article
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 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Peritoneal tuberculosis (PTB) is a paucibacillary disease with poor mycobacterial yield in ascitic fluid. The Xpert® MTB/RIF assay (Gene Xpert) is a new tool for the diagnosis of tuberculosis (TB) and has not yet been studied on peritoneal tissue. The present study aimed to investigate the yield of the Xpert® MTB/RIF assay on peritoneal tissue obtained at peritoneoscopy. Methods This is a retrospective study and the data were collected from hospital records. The patients who underwent peritoneoscopy along with Xpert® MTB/RIF assay on peritoneal tissue were included in this study. Those with proven PTB were considered as cases while those with other diagnoses as controls. Using the reference standard of TB diagnosis, sensitivity, specificity, and accuracy of Xpert® MTB/RIF assay were calculated. Results Total of 36 patients was analyzed in this study: 28 as cases and eight as controls. Peritoneoscopy was carried out for diagnosis and biopsy. Histopathology in cases revealed caseating granulomas in 16 while 11 had non-caseating granulomas. Nine patients showed acid-fast bacillus positivity on peritoneal tissue. The most common finding on peritoneoscopy was tubercles with adhesions (n = 14, 50%), followed by tubercles only (n = 12, 42.9%). Xpert® MTB/RIF assay was positive in 17 (60.7%) patients with a sensitivity of 60.71%, specificity of 100%, and an accuracy of 69.44%. Two patients expressed rifampicin resistance. Conclusion Xpert® MTB/RIF assay on peritoneal tissue has fair sensitivity and excellent specificity. The multidrug resistance and the ability to provide results rapidly make it clinically useful.
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Registered trials
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.