Diagnostic accuracy of GeneXpert Ultra for tuberculosis in weakly positive results.

Background: The GeneXpert Ultra assay has improved sensitivity for tuberculosis diagnosis, but it is associated with an increased rate of false positive results, particularly in weakly positive categories.

Aim: To assess the diagnostic accuracy of the GeneXpert Ultra assay by comparing 3 approaches to interpreting weakly positive results.

Methods: We collected laboratory data from 620 (all) individuals referred to the tuberculosis laboratory affiliated with Shiraz University of Medical Sciences laboratory, southern Islamic Republic of Iran, between 21 March 2022 and 20 March 2023. We performed GeneXpert Ultra, acid-fast bacilli smear microscopy and culture, and used results from the culture as reference standard for calculating diagnostic accuracy indices. We analysed the weakly positive results (trace and very low) using 3 approaches in which they were classified as positive or negative, or excluded from the analysis. We used SPSS version 22.0 to describe the characteristics of the participants, MedCalc version 20.104 to analyse the data and 2-tailed binomial test to compare the diagnostic indices. P < 0.05 was considered statistically significant.

Results: GeneXpert 1 showed a low positive predictive value (68.60%) and lower specificity (90.72%) than smear microscopy (95.46%). Compared with GeneXpert 2, GeneXpert 1 demonstrated higher sensitivity (98.99%) and negative predictive value (99.77%), while GeneXpert 2 showed higher specificity (97.32%) and positive predictive value (87.66%). GeneXpert 3 showed high sensitivity (98.92%) and negative predictive value (99.77%), as well as high specificity (97.13%) and positive predictive value (87.60%), resulting in the highest overall accuracy (97.43%) and agreement with culture (Fleiss' kappa = 0.91).

Conclusion: Weakly positive GeneXpert Ultra results should not be interpreted automatically as either negative or positive. Clinic, laboratory and radiologic data should be considered together to identify patients most likely to benefit from tuberculosis treatment.