1. The Application of GeneXpert MTB/RIF for Smear-Negative TB Diagnosis as a Fee-Paying Service at a South Asian General Hospital
- Author
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Poojan Shrestha, Amit Arjyal, Sabina Dongol, Buddha Basnyat, Saruna Pathak, Shanti Pradhan Prajapati, Krishna G. Prajapati, Abhilasha Karkey, and Maxine Caws
- Subjects
medicine.medical_specialty ,Pediatrics ,Tuberculosis ,South asia ,Article Subject ,lcsh:Medicine ,Mycobacterium tuberculosis ,03 medical and health sciences ,0302 clinical medicine ,Pulmonary tuberculosis ,Internal medicine ,medicine ,030212 general & internal medicine ,Positive test ,General hospital ,0303 health sciences ,GeneXpert MTB/RIF ,biology ,030306 microbiology ,business.industry ,lcsh:R ,medicine.disease ,biology.organism_classification ,3. Good health ,Smear negative ,wf_220 ,wf_200 ,wb_141 ,business ,wf_300 ,Research Article - Abstract
The GeneXpert MTB/RIF assay (Xpert) is a novel automated diagnostic tool for tuberculosis but its optimal placement in the healthcare system has not been determined. The objective of this study was to determine the possibility of additional case detection for pulmonary tuberculosis (PTB) by offering Xpert to smear-negative patients in a low-HIV burden setting with noMycobacterium tuberculosis(M.tb.) culture facilities. Patients routinely presenting with symptoms suggestive of PTB with negative smears were offered single Xpert test on a fee-paying basis. Data were retrospectively reviewed to determine case detection in patients tested from February to December 2013. Symptoms associated with a positive test were analysed to determine if refinement of clinical criteria would reduce unnecessary testing. 258 smear-negative patients were included andM.tb.was detected in 55 (21.32%,n=55/258). Using standard clinical assessment for selection, testing 5 patients detected one case of smear-negative PTB. These results demonstrate that fee-paying Xpert service in low-income setting can increase TB case confirmation substantially and further systematic studies of health economic implications should be conducted to determine optimal implementation models to increase access to Xpert in low- and middle-income countries.
- Published
- 2015
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