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Improving the diagnosis of tuberculosis: old and new laboratory tools.
Solanki, Priya; Elton, Linzy; Honeyborne, Isobella; Park, Mirae; Satta, Giovanni; McHugh, Timothy D.
Afiliación
  • Solanki P; UCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, London, UK.
  • Elton L; UCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, London, UK.
  • Honeyborne I; UCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, London, UK.
  • Park M; Respiratory Medicine, Imperial Healthcare NHS Trust, London, UK.
  • Satta G; UCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, London, UK.
  • McHugh TD; UCL-TB and Centre for Clinical Microbiology, Division of Infection & Immunity, Royal Free Campus, London, UK.
Expert Rev Mol Diagn ; : 1-10, 2024 Jun 05.
Article en En | MEDLINE | ID: mdl-38832527
ABSTRACT

INTRODUCTION:

Despite recent advances in diagnostic technologies and new drugs becoming available, tuberculosis (TB) remains a major global health burden. If detected early, screened for drug resistance, and fully treated, TB could be easily controlled. AREAS COVERED Here the authors discuss M. tuberculosis culture methods which are considered the definitive confirmation of M. tuberculosis infection, and limited advances made to build on these core elements of TB laboratory diagnosis. Literature searches showed that molecular techniques provide enhanced speed of turnaround, sensitivity, and richness of data. Sequencing of the whole genome, is becoming well established for identification and inference of drug resistance. PubMed® literature searches were conducted (November 2022-March 2024). EXPERT OPINION This section highlights future advances in diagnosis and infection control. Prevention of prolonged hospital admissions and rapid TAT are of the most benefit to the overall patient experience. Host transcriptional blood markers have been used in treatment monitoring studies and, with appropriate evaluation, could be rolled out in a diagnostic setting. Additionally, the MBLA is being incorporated into latest clinical trial designs. Whole genome sequencing has enhanced epidemiological evidence. Artificial intelligence, along with machine learning, have the ability to revolutionize TB diagnosis and susceptibility testing within the next decade.
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Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Expert Rev Mol Diagn Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Banco de datos: MEDLINE Idioma: En Revista: Expert Rev Mol Diagn Asunto de la revista: BIOLOGIA MOLECULAR Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido