TB Risk Prediction Just Got Sharper

A new algorithm from University College London researchers could boost the tricky business of determining a person’s risk of developing active TB.

The Goal: Identify those most at risk before they get sick—so they can receive preventive antibiotics, explains Rishi Gupta, author of the study in Nature Medicine. That’s key because current tests are weak; many of the ~10 million annual infections go undetected.

Drawing on tens of thousands of patient histories in low-transmission countries, the researchers found that young children, those recently exposed, and people with “higher” positive test results were at much greater risk.
 

The Guardian

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