Diagnosis of tuberculosis among COVID-19 suspected cases in Ghana

PLOS ONE(2021)

引用 4|浏览5
暂无评分
摘要
Background Tuberculosis (TB) and COVID-19 pandemics are both diseases of public health threat globally. Both diseases are caused by pathogens that infect mainly the respiratory system, and are involved in airborne transmission; they also share some clinical signs and symptoms. We, therefore, took advantage of collected sputum samples at the early stage of COVID-19 outbreak in Ghana to conduct differential diagnoses of long-standing endemic respiratory illness, particularly tuberculosis. Methodology Sputum samples collected through the enhanced national surveys from suspected COVID-19 patients and contact tracing cases were analyzed for TB. The sputum samples were processed using Cepheid's GeneXpert MTB/RIF assay in pools of 4 samples to determine the presence of Mycobacterium tuberculosis complex. Positive pools were then decoupled and analyzed individually. Details of positive TB samples were forwarded to the NTP for appropriate case management. Results Seven-hundred and seventy-four sputum samples were analyzed for Mycobacterium tuberculosis in both suspected COVID-19 cases (679/774, 87.7%) and their contacts (95/774, 12.3%). A total of 111 (14.3%) were diagnosed with SARS CoV-2 infection and six (0.8%) out of the 774 individuals tested positive for pulmonary tuberculosis: five (83.3%) males and one female (16.7%). Drug susceptibility analysis identified 1 (16.7%) rifampicin-resistant tuberculosis case. Out of the six TB positive cases, 2 (33.3%) tested positive for COVID-19 indicating a coinfection. Stratifying by demography, three out of the six (50%) were from the Ayawaso West District. All positive cases received appropriate treatment at the respective sub-district according to the national guidelines. Conclusion Our findings highlight the need for differential diagnosis among COVID-19 suspected cases and regular active TB surveillance in TB endemic settings.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要