Cough collection as a replacement for sputum samples for diagnosing Tuberculosis

点击翻译按钮获取中文摘要

DESCRIPTION (provided by applicant): Active Tuberculosis (TB) causes approximately 2 million annual deaths. An estimated 9.3 million people worldwide develop TB every year, of which 4.4 million are undiagnosed. When diagnosed properly, most TB cases can be treated. Currently, sputum expectorate is the most common sampling method used for TB diagnosis. Sputum is difficult to collect from some patients (children and elderly), and is unattainable from ex- pectoration deficient patients ( 20% of patients). Sputum is also contaminated by oropharyngeal flora, saliva, mucus, and cell debris which negatively affects the sensitivity and specificity of diagnostics, and lowers their impact on treatment decisions. Deton's device avoids all the disadvantages of sputum samples by collecting air- borne bacteria directly from cough aerosol for subsequent diagnosis. All patients can produce cough; therefore, samples can be collected from the entire patient population, including patients who cannot expectorate sputum. Furthermore, the cough collection concentrates bacteria in a small sample volume of buffer that supports the viability of fragile organisms; whereas, sputum concentration (fixed number of cells per mL) and medium cannot be altered. Finally, the collected cough droplet material is potentially free of the various oropharyngeal contaminants in sputum. The Phase I aims of the proposed work are: Aim 1: Investigate whether collected cough samples result in higher diagnostic sensitivity and specificity than sputum samples. Aim 2: Improve the device geometry to maximize collection efficiency and machine the new design for lab and clinical evaluations. Phase I aims will enable the testing of the device for different lung infections such as non-tuberculosis mycobacterial infections and community acquired pneumonia in Phase II. Furthermore, a more patient-friendly disposable device can be manufactured based on the second prototype and the patient data.