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The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
Published on: August 11, 2008
Patterns of childhood tuberculosis diagnosis in Ethiopia: A multicenter cross-sectional study
Kedir Usmael1, Tsegahun Manyazewal2, Hussen Mohammed2
1Dire Dawa University.
Insights
Diagnosing tuberculosis (TB) in children is challenging, with many cases missed annually. Combining clinical evaluation, chest X-rays, and microbiological tests improves detection rates, especially for children with fever or TB contact history.
Area of Science:
- Pediatrics
- Infectious Diseases
- Public Health
Background:
- Tuberculosis (TB) significantly impacts children globally, with high rates of missed diagnoses annually.
- Ethiopia faces challenges in childhood TB case detection, necessitating improved diagnostic strategies.
- This study investigates childhood TB diagnosis patterns and determinants in Ethiopia using various diagnostic platforms.
Approach:
- A multi-site, cross-sectional study enrolled children aged ≤15 with cough at four Ethiopian healthcare facilities.
- Diagnostic methods included sputum Xpert MTB/RIF, smear microscopy, and chest X-ray (CXR).
- Clinical and sociodemographic data were collected; multiple regression analysis identified factors influencing TB case detection.
Key Points:
- Chest X-ray (CXR) suggested TB in 13.8% of children, while Xpert MTB/RIF detected TB in 11.9%.
- Febrile children (aPR=1.3) and those with TB contact history (aPR=1.2) were more likely to be diagnosed with pulmonary TB.
- Children from rural residences had higher TB diagnosis rates (aPR=1.3) compared to urban counterparts.
Conclusions:
- Clinical diagnosis is crucial for averting underdiagnosis in children.
- Symptom screening, CXR, and microbiological tests form a sensitive diagnostic approach for childhood TB.
- An integrated algorithm combining clinical, imaging, and microbiological tests can enhance pulmonary TB diagnosis in children.
Background:
Children share 12% of the global 10 million people infected with tuberculosis (TB) each year. Closing case detection gap in children remains difficult, with 56% of all children and 65% under-five with TB missed each year. We aimed to assess the patterns of childhood TB diagnosis and underlying determinants in Ethiopia when different TB diagnostic platforms are applied.
Methods:
A multi-site, cross-sectional study was carried out in Ethiopia as part of the larger EXIT-TB study - evidence-based multiple focused integrated intensified TB screening package. Outpatient children aged ≤ 15 with cough of any duration seeking care at four healthcare facilities in Ethiopia were enrolled consecutively. Participants underwent sputum Xpert MTB/RIF and/or smear microscopy and posteroanterior chest X-ray (CXR), and their clinical and sociodemographic data were captured using a structured questionnaire. Data were analyzed using Stata version 23. Multiple regression model was computed to determine the factors that influence TB case detection, with a 95% confidence interval (CI) and p < 0.05 taken as statistically significant.
Results:
A total of 438 children were enrolled. Of these, 399 had CXR examination of which 55 (13.8%) were suggestive of TB, 270 had Xpert MTB/RIF testing of which 32 (11.9%) were positive, and AFB smear microscopy was done for 51 children of which 2 (3.9%) were positive. Febrile children were more likely to be diagnosed with pulmonary TB than those without fever [aPR = 1.3, 95% CI (1.1-1.4)], and those with a TB contact history were more likely to be diagnosed with pulmonary TB than those with no such contacts [aPR = 1.2, 95% CI (1.1-1.3)]. Children from rural residences were more likely to be diagnosed with TB than those from urban residences [aPR = 1.3, 95% CI (1.1-1.5)].
Conclusion:
The findings showed that clinical diagnosis remains an important method of TB diagnosis in children and the preferred choice to avert underdiagnosis. A more sensitive TB diagnostic method for children was symptom screening, followed by CXR and Xpert MTB/RIF assay or smear microscopy. Hence, an algorithm that combines clinical, CXR, and microbiological confirmatory tests can improve the rate of pulmonary TB diagnosis in children till more accurate and cost-effective diagnostic tools are accessible. Fever, weight loss, and TB contact history are highly associated with TB positivity rates in children.
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