{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T15:44:24Z","timestamp":1784735064184,"version":"3.55.0"},"reference-count":21,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T00:00:00Z","timestamp":1776988800000},"content-version":"vor","delay-in-days":113,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Microbiology"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>Rapid identification of drug\u2010resistant tuberculosis remains critical for the initiation of appropriate treatment regimens, improved success rates and reduction in the development of drug resistance. In this study, we compared the diagnostic performance of two novel diagnostic tests, Xpert MTB\/XDR and Deeplex Myc\u2010TB (both CE marked).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      Twenty clinical isolates of\n                      <jats:italic>Mycobacterium tuberculosis<\/jats:italic>\n                      (MTB) with known drug resistance patterns were used to determine the concordance\/discordance of the two rapid platforms when performing drug susceptibility testing. The limit of detection for MTB, the detection of coinfection\/cross\u2010reactivity with\n                      <jats:italic>Mycobacterium abscessus<\/jats:italic>\n                      (Mab) and the detection of heteroresistance using mixtures of wild type MTB and drug\u2010resistant MTB were also evaluated.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Xpert MTB\/XDR had a total concordance of 68% and Deeplex Myc\u2010TB had a total concordance of 100% when compared to WGS and phenotypic drug susceptibility testing. Xpert TB\/XDR had a lower limit of detection for identifying MTB at 10^3\u2009CFU\/mL, whereas Deeplex Myc\u2010TB required at least 10^4\u2009CFU\/mL. Both Xpert MTB\/XDR and Deeplex Myc\u2010TB were able to detect the wild type MTB without any cross\u2010reactivity with the drug\u2010resistant Mab. For heteroresistance detection, Deeplex Myc\u2010TB was able to detect down to 1% admix of the resistant isolates (1 out of 4), whilst Xpert MTB\/XDR was only able to detect down to 10% in 1 out of 4 mixtures of isolates tested.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Both platforms represent an attractive option for the rapid detection of drug resistance and heteroresistance contributing to the management of complex cases, but further studies are needed to assess their real clinical impact.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1155\/ijm\/8659735","type":"journal-article","created":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T15:47:31Z","timestamp":1777045651000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Evaluation of Xpert MTB\/XDR and Deeplex Myc\u2010TB for the Rapid Detection of Drug Resistance in\n                    <i>Mycobacterium tuberculosis<\/i>"],"prefix":"10.1155","volume":"2026","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7015-5943","authenticated-orcid":false,"given":"Mirae","family":"Park","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Priya","family":"Solanki","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4658-8594","authenticated-orcid":false,"given":"Timothy Daniel","family":"McHugh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2647-4688","authenticated-orcid":false,"given":"Onn Min","family":"Kon","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0120-7885","authenticated-orcid":false,"given":"Giovanni","family":"Satta","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,4,24]]},"reference":[{"key":"e_1_2_10_1_2","unstructured":"Global Tuberculosis Report 2022 (Geneva: World Health organization 2022) https:\/\/www.who.int\/teams\/global-tuberculosis-programme\/tb-reports\/global-tuberculosis-report-2022."},{"key":"e_1_2_10_2_2","unstructured":"WHO and ECDC Tuberculosis Surveillance and Monitoring in Europe 2023: 2021 Data 2023 http:\/\/www.who.int\/europe\/publications\/i\/item\/9789289058810."},{"key":"e_1_2_10_3_2","unstructured":"UK Health Security Agency Tuberculosis in England 2022 Report (Data up to End of 2021) 2023 http:\/\/www.gov.uk\/government\/publications\/tuberculosis-in-england-2022-report-data-up-to-end-of-2021."},{"key":"e_1_2_10_4_2","volume-title":"England World Leaders in the Use of Whole Genome Sequencing to Diagnose TB","author":"PHE","year":"2017"},{"key":"e_1_2_10_5_2","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.00387-2018"},{"key":"e_1_2_10_6_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cmi.2017.10.001"},{"key":"e_1_2_10_7_2","doi-asserted-by":"publisher","DOI":"10.1186\/s12879-022-07329-y"},{"key":"e_1_2_10_8_2","doi-asserted-by":"crossref","first-page":"1403","DOI":"10.1056\/NEJMoa1800474","article-title":"Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing","volume":"379","author":"Allix-B\u00e9guec C.","year":"2018","journal-title":"New England Journal of Medicine"},{"key":"e_1_2_10_9_2","unstructured":"WHO End TB Strategy 2015 http:\/\/www.who.int\/tb\/post2015_strategy\/en\/."},{"key":"e_1_2_10_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/14651858.CD014841.pub2"},{"key":"e_1_2_10_11_2","doi-asserted-by":"publisher","DOI":"10.1183\/13993003.01796-2020"},{"key":"e_1_2_10_12_2","doi-asserted-by":"publisher","DOI":"10.1590\/s1517-83822013000100042"},{"key":"e_1_2_10_13_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0028815"},{"key":"e_1_2_10_14_2","doi-asserted-by":"publisher","DOI":"10.1128\/mbio.00812-17"},{"key":"e_1_2_10_15_2","volume-title":"Catalogue of Mutations in Mycobacterium tuberculosis Complex and Their Association with Drug Resistance","author":"WHO","year":"2023"},{"key":"e_1_2_10_16_2","doi-asserted-by":"publisher","DOI":"10.1093\/jacamr\/dlab101"},{"key":"e_1_2_10_17_2","doi-asserted-by":"publisher","DOI":"10.1038\/emi.2014.21"},{"key":"e_1_2_10_18_2","unstructured":"Who WHO Consolidated Guidelines on Tuberculosis. 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