You are viewing the site in preview mode

Skip to main content

Advertisement

Table 2 Health-system-level effects of new diagnostic algorithms: mean per year in 10 years

From: Modeling the patient and health system impacts of alternative xpert® MTB/RIF algorithms for the diagnosis of pulmonary tuberculosis in Addis Ababa, Ethiopia

Diagnostic algorithms Sputum samples tested for tuberculosis per year Lab staff utilization (%) Patients starting tuberculosis treatment per year including false positive Missed TBa per year Complete cures per year excluding false positive
Microscopy (000s) Xpert (000s) X-ray (000s) Standard regimen Treatment complete/cure Treatment failure/MDR TB
ZN-Spot-Morning-Spot 113 0 12 30 6200 5919 59 963 3154
FN-Spot-Morning-Spot 112 0 12 22 5874 5608 59 893 3228
Targeted-Xpert-ZN-Negative-Spot-Morning-Spot 93 33 6 30 5257 4927 148 785 3332
Targeted-Xpert- MDR-HIV-ZN-Spot-Morning-Spot 98 7 11 28 6165 5831 118 859 3263
Full-Xpert 17 37 6 10 5588 5189 207 622 3500
FN-Spot-Spot 86 0 12 17 6269 5984 59 800 3322
FN-Spot-Morning 82 0 12 16 6200 5919 59 963 3154
Targeted-Xpert-MDR-HIV-FN-Spot-Spot 76 7 12 1 5874 5608 59 893 3228
  1. aMissed TB- Patient with TB but not diagnosed or lost to follow up