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Why being an expert - despite xpert -remains crucial for children in high TB burden settings
Jason M Bacha1,2, Katherine Ngo3, Petra Clowes4
1Baylor College of Medicine Children's Foundation - Tanzania, Centre of Excellence at Mbeya Zonal Referral Hospital, Mbeya, Tanzania. bacha@bcm.edu.
Insights
In high TB-burden settings, Xpert testing showed low sensitivity for childhood TB diagnosis compared to clinical assessment. Clinicians remain essential for diagnosing TB in children, even with new diagnostic tools.
Area of Science:
- Pediatric infectious diseases
- Microbiology and diagnostics
- Global health
Background:
- Childhood tuberculosis (TB) diagnosis is challenging due to infrequent bacteriological confirmation.
- The GeneXpert (Xpert) assay's utility in high TB-burden settings for children requires evaluation against clinical diagnosis.
- Understanding Xpert's performance is crucial for improving pediatric TB case detection.
Purpose of the Study:
- To characterize children with presumptive and confirmed TB disease.
- To assess the performance of Xpert, smear microscopy, and culture against a clinical diagnosis of TB in children.
- To evaluate Xpert's effectiveness under programmatic conditions in a high TB-burden area.
Main Methods:
- Retrospective review of pediatric patients evaluated for presumptive TB in Mbeya, Tanzania.
- Comparison of baseline characteristics by TB disease status and confirmation status.
- Calculation of sensitivity and specificity for Xpert, smear, and culture against clinical TB diagnosis.
Main Results:
- Of 455 children evaluated, 34.5% were diagnosed with TB; only 13.4% were bacteriologically confirmed.
- Sensitivity of Xpert against clinical diagnosis was 8%, smear was 6%, and culture was 16%.
- Xpert performance did not vary significantly based on patient disposition, nutritional status, or HIV status.
Conclusions:
- Most children with presumptive TB were treated based on clinical diagnosis, despite Xpert availability.
- New diagnostics like Xpert are valuable adjunctive tools but do not replace clinical judgment.
- Comprehensive diagnostic algorithms and astute clinical evaluation remain critical for pediatric TB management in resource-limited settings.
Background:
As access to Xpert expands in high TB-burden settings, its performance against clinically diagnosed TB as a reference standard provides important insight as the majority of childhood TB is bacteriologically unconfirmed. We aim to describe the characteristics and outcomes of children with presumptive TB and TB disease, and assess performance of Xpert under programmatic conditions against a clinical diagnosis of TB as a reference standard.
Methods:
Retrospective review of children evaluated for presumptive TB in Mbeya, Tanzania. Baseline characteristics were compared by TB disease status and, for patients diagnosed with TB, by TB confirmation status using Wilcoxon rank sum test for continuous variables and the Chi-square test for categorical variables. Sensitivity and specificity were calculated to assess the performance of Xpert, smear, and culture against clinical TB. Kappa statistics were calculated to assess agreement between Xpert and smear to culture.
Results:
Among children (N = 455) evaluated for presumptive TB, 70.3% (320/455) had Xpert and 62.8% (286/455) had culture performed on sputa. 34.5% (157/455) were diagnosed with TB: 80.3% (126/157) pulmonary TB, 13.4% (21/157) bacteriologically confirmed, 53.5% (84/157) HIV positive, and 48.4% (76/157) inpatients. Compared to the reference standard of clinical diagnosis, sensitivity of Xpert was 8% (95% CI 4-15), smear 6% (95% CI 3-12) and culture 16% (95% CI 9-24), and did not differ based on patient disposition, nutrition or HIV status.
Conclusion:
Despite access to Xpert, the majority of children with presumptive TB were treated based on clinical diagnosis. Reflecting the reality of clinical practice in resource limited settings, new diagnostics such as Xpert serve as important adjunctive tests but will not obviate the need for astute clinicians and comprehensive diagnostic algorithms.
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