Dohál Matúš, Porvazník Igor, Solovič Ivan, Mokrý Juraj
Biomedical Centre Martin, Jessenius Faculty of Medicine in Martin, Comenius University in Bratislava, Martin, Slovakia.
National Institute of Tuberculosis, Lung Diseases and Thoracic Surgery, Vyšné Hágy, Slovakia.
Front Microbiol. 2023 Oct 4;14:1225438. doi: 10.3389/fmicb.2023.1225438. eCollection 2023.
Tuberculosis is a major global health issue, with approximately 10 million people falling ill and 1.4 million dying yearly. One of the most significant challenges to public health is the emergence of drug-resistant tuberculosis. For the last half-century, treating tuberculosis has adhered to a uniform management strategy in most patients. However, treatment ineffectiveness in some individuals with pulmonary tuberculosis presents a major challenge to the global tuberculosis control initiative. Unfavorable outcomes of tuberculosis treatment (including mortality, treatment failure, loss of follow-up, and unevaluated cases) may result in increased transmission of tuberculosis and the emergence of drug-resistant strains. Treatment failure may occur due to drug-resistant strains, non-adherence to medication, inadequate absorption of drugs, or low-quality healthcare. Identifying the underlying cause and adjusting the treatment accordingly to address treatment failure is important. This is where approaches such as artificial intelligence, genetic screening, and whole genome sequencing can play a critical role. In this review, we suggest a set of particular clinical applications of these approaches, which might have the potential to influence decisions regarding the clinical management of tuberculosis patients.
结核病是一个重大的全球健康问题，每年约有1000万人患病，140万人死亡。对公共卫生最重大的挑战之一是耐药结核病的出现。在过去的半个世纪里，大多数患者治疗结核病一直遵循统一的管理策略。然而，一些肺结核患者治疗无效对全球结核病控制倡议构成了重大挑战。结核病治疗的不良结果（包括死亡率、治疗失败、失访和未评估病例）可能导致结核病传播增加和耐药菌株的出现。治疗失败可能由于耐药菌株、不坚持用药、药物吸收不足或医疗质量低下而发生。识别潜在原因并相应调整治疗以解决治疗失败问题很重要。这就是人工智能、基因筛查和全基因组测序等方法可以发挥关键作用的地方。在本综述中，我们提出了这些方法的一系列特定临床应用，它们可能有潜力影响结核病患者临床管理的决策。
