A Systematic Review and Meta-analysis on Innovative Approaches in Tuberculosis Diagnosis: Challenges and Future...

Area of Science:

• Medical Diagnostics
• Infectious Disease Research
• Public Health

Background:

• Tuberculosis (TB) remains a significant global health threat, causing millions of deaths annually and impacting vulnerable populations.
• An estimated 4 million TB cases are missed each year, contributing to the overall disease burden.
• Innovative diagnostic strategies are urgently needed to address the challenges in TB detection and control.

Purpose of the Study:

• To review and analyze innovative approaches for diagnosing tuberculosis (TB).
• To identify challenges and future directions in the field of TB diagnostics.
• To assess the diagnostic accuracy of novel TB detection methods.

Main Methods:

• A systematic literature search was conducted for studies published between 2019 and 2024.
• Included studies were screened and assessed for quality using PRISMA and relevant risk of bias tools.
• Meta-analysis techniques, including random effects models, were used to pool sensitivity and specificity data.

Main Results:

• The review analyzed 25 studies evaluating molecular methods, biomarker-based techniques, and AI applications for TB diagnosis.
• Cartridge-based molecular tests were the most frequently assessed innovative approach.
• Pooled sensitivity was 0.79 (95% CI: 0.70-0.86) and specificity was 0.93 (95% CI: 0.87-0.96), with significant heterogeneity.

Conclusions:

• Innovative diagnostic methods, especially cartridge-based molecular tests, offer potential for improved TB detection.
• Moderate sensitivity and high heterogeneity necessitate cautious implementation and further validation of new tools.
• Strategic investment and contextual deployment are vital to bridge the global TB diagnosis gap.