Global treatment outcomes of extensively drug-resistant tuberculosis in adults: A systematic review and meta-analysis

Pedersen, Oluf; Holmgaard, Freja Breth; Mikkelsen, Mark E.; Lange, Christoph; Sotgiu, Giovanni; Lillebæk, Troels; Andersen, Aase Bengaard; Wejse, Christian; Mathiasen, Victor Dahl

doi:10.1016/j.jinf.2023.06.014

Cited by 8 publications

(3 citation statements)

References 118 publications

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“…Previous exposure to those drugs (i.e., bedaquiline, linezolid, fluoroquinolones) has been associated with worse patient outcomes compared with patients without previous exposure ( 5 ). Altogether, those factors explain the treatment success of only 31% for XDR TB, even lower than that recently found in a meta-analysis involving 10,223 XDR TB patients (94 studies, 26 countries) using the former definition, which together showed a pooled successful treatment outcome of 44% (95% CI 38%–50%) ( 3 ). That review found a XDR TB treatment success of 6% and 25% in 2 studies from Ukraine (n = 126).…”

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confidence: 65%

“…In early 2021, the World Health Organization (WHO) recommended new definitions of extensively drug resistant (XDR) and pre-XDR tuberculosis (TB) ( 1 , 2 ). Previously, pre-XDR TB was informally defined as TB caused by Mycobacterium tuberculosis strains with resistance to rifampin and isoniazid plus resistance to either a fluoroquinolone or a second-line injectable, but not both ( 1 – 3 ). Now, pre-XDR TB is officially defined as strains with resistance to rifampin, isoniazid, and a fluoroquinolone (levofloxacin or moxifloxacin), whereas XDR TB is now defined as additional resistance to > 1 group A drug (bedaquiline or linezolid), replacing the second-line injectables used in the former definitions ( 1 – 3 ).…”

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confidence: 99%

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Drug-Resistant Tuberculosis, Georgia, Kazakhstan, Kyrgyzstan, Moldova, and Ukraine, 2017–2022

Dahl,

Butova,

Rosenthal

et al. 2024

Emerg. Infect. Dis.

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confidence: 65%

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confidence: 99%

Drug-Resistant Tuberculosis, Georgia, Kazakhstan, Kyrgyzstan, Moldova, and Ukraine, 2017–2022

Dahl,

Butova,

Rosenthal

et al. 2024

Emerg. Infect. Dis.

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“… 3 Extensively drug‐resistant tuberculosis (XDR‐TB), the most advanced subtype of DR‐TB, 4 with less than half successful treatment and being more prone to long‐term sequelae, is of great concern as well. 5 , 6 Consequently, DR‐TB remains a substantial threat to public hygiene, and prompt diagnosis and optimal therapeutic strategy‐making based on the susceptibility profiles of DR‐TB are crucial for TB supervision.…”

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confidence: 99%

Deep learning for precise diagnosis and subtype triage of drug‐resistant tuberculosis on chest computed tomography

Liang,

Xu,

Yang

et al. 2024

MedComm

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Deep learning, transforming input data into target prediction through intricate network structures, has inspired novel exploration in automated diagnosis based on medical images. The distinct morphological characteristics of chest abnormalities between drug‐resistant tuberculosis (DR‐TB) and drug‐sensitive tuberculosis (DS‐TB) on chest computed tomography (CT) are of potential value in differential diagnosis, which is challenging in the clinic. Hence, based on 1176 chest CT volumes from the equal number of patients with tuberculosis (TB), we presented a Deep learning‐based system for TB drug resistance identification and subtype classification (DeepTB), which could automatically diagnose DR‐TB and classify crucial subtypes, including rifampicin‐resistant tuberculosis, multidrug‐resistant tuberculosis, and extensively drug‐resistant tuberculosis. Moreover, chest lesions were manually annotated to endow the model with robust power to assist radiologists in image interpretation and the Circos revealed the relationship between chest abnormalities and specific types of DR‐TB. Finally, DeepTB achieved an area under the curve (AUC) up to 0.930 for thoracic abnormality detection and 0.943 for DR‐TB diagnosis. Notably, the system demonstrated instructive value in DR‐TB subtype classification with AUCs ranging from 0.880 to 0.928. Meanwhile, class activation maps were generated to express a human‐understandable visual concept. Together, showing a prominent performance, DeepTB would be impactful in clinical decision‐making for DR‐TB.

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Delineating the evolutionary pathway to multidrug-resistant outbreaks of a Mycobacterium tuberculosis L4.1.2.1/Haarlem sublineage

Dekhil,

Mardassi

2024

International Journal of Infectious Diseases

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Global treatment outcomes of extensively drug-resistant tuberculosis in adults: A systematic review and meta-analysis

Cited by 8 publications

References 118 publications

Drug-Resistant Tuberculosis, Georgia, Kazakhstan, Kyrgyzstan, Moldova, and Ukraine, 2017–2022

Drug-Resistant Tuberculosis, Georgia, Kazakhstan, Kyrgyzstan, Moldova, and Ukraine, 2017–2022

Deep learning for precise diagnosis and subtype triage of drug‐resistant tuberculosis on chest computed tomography

Delineating the evolutionary pathway to multidrug-resistant outbreaks of a Mycobacterium tuberculosis L4.1.2.1/Haarlem sublineage

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