A primary care level algorithm for identifying HIV-infected adolescents in populations at high risk through mother-to-child transmission

2011

Algorithm to Identify HIV-Infected Adolescents

Sample size: 506 publication 10 minutes Evidence: moderate

Author Information

Author(s): Ferrand Rashida A, Weiss Helen A, Nathoo Kusum, Ndhlovu Chiratidzo E, Mungofa Stanley, Munyati Shungu, Bandason Tsitsi, Gibb Diana M, Corbett Elizabeth L

Primary Institution: London School of Hygiene and Tropical Medicine

Hypothesis

Can a simple algorithm help primary care workers identify HIV-infected adolescents at high risk through mother-to-child transmission?

Conclusion

The algorithm can accurately identify adolescents likely to be HIV infected, serving as a useful screening tool in settings without universal testing.

Supporting Evidence

HIV prevalence was found to be 17% among the participants.
The algorithm achieved 74% sensitivity and 80% specificity for identifying HIV.
Using the algorithm could reduce the number of tests needed to find one HIV-positive individual by 60% in low-prevalence settings.
Orphanhood, hospitalization, recurrent skin problems, STI presentation, and poor functional ability were linked to higher HIV risk.
The algorithm correctly predicted the HIV status of 79% of participants.
The study was approved by multiple ethics committees.
Data was collected systematically and prospectively.

Takeaway

This study created a simple checklist to help doctors find teenagers who might have HIV, making it easier to test them.

Methodology

The study involved 506 adolescents aged 10-18 from two clinics in Harare, Zimbabwe, using a training set to develop an algorithm and a test set to evaluate its performance.