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Published on: October 31, 2010
Diagnosis of paediatric HIV infection in a primary health care setting with a clinical algorithm
C Horwood1, S Liebeschuetz, D Blaauw
1Human Resource Development, KwaZulu-Natal Department of Health, South Africa. christiane@telkomsa.net
Insights
Primary healthcare workers can effectively identify children with symptomatic human immunodeficiency virus (HIV) using an improved algorithm. This tool aids in managing HIV in children within the Integrated Management of Childhood Illness strategy.
Area of Science:
- Pediatrics
- Infectious Diseases
- Public Health
Background:
- Human immunodeficiency virus (HIV) is a major cause of childhood mortality in Southern Africa.
- The Integrated Management of Childhood Illness (IMCI) strategy aims to reduce childhood morbidity and mortality.
- Diagnosis of symptomatic HIV infection was integrated into the IMCI algorithm in South Africa.
Purpose of the Study:
- To validate an algorithm for identifying symptomatic HIV infection in children by primary care workers.
- To improve the existing IMCI HIV algorithm using clinical data.
Main Methods:
- 690 children attending a district hospital outpatient department in South Africa were assessed.
- Children were evaluated using the HIV algorithm, by a pediatrician, and tested for HIV viral load.
- Clinical data were analyzed to refine the algorithm's predictors.
Main Results:
- 28.7% of enrolled children were HIV-positive.
- The original IMCI/HIV algorithm identified 56.1% of HIV-infected children, while a pediatrician identified 71.7%.
- An improved algorithm demonstrated 67.2% sensitivity and 81.5% specificity.
Conclusions:
- Primary healthcare workers can effectively identify symptomatic HIV-infected children using an algorithm.
- The enhanced HIV algorithm can assist IMCI practitioners in high-prevalence settings.
- Improved identification and care for HIV-infected children are crucial for reducing childhood mortality.
Objective:
To determine the validity of an algorithm used by primary care health workers to identify children with symptomatic human immunodeficiency virus (HIV) infection. This HIV algorithm is being implemented in South Africa as part of the Integrated Management of Childhood Illness (IMCI), a strategy that aims to improve childhood morbidity and mortality by improving care at the primary care level. As AIDS is a leading cause of death in children in southern Africa, diagnosis and management of symptomatic HIV infection was added to the existing IMCI algorithm.
Methods:
In total, 690 children who attended the outpatients department in a district hospital in South Africa were assessed with the HIV algorithm and by a paediatrician. All children were then tested for HIV viral load. The validity of the algorithm in detecting symptomatic HIV was compared with clinical diagnosis by a paediatrician and the result of an HIV test. Detailed clinical data were used to improve the algorithm.
Findings:
Overall, 198 (28.7%) enrolled children were infected with HIV. The paediatrician correctly identified 142 (71.7%) children infected with HIV, whereas the IMCI/HIV algorithm identified 111 (56.1%). Odds ratios were calculated to identify predictors of HIV infection and used to develop an improved HIV algorithm that is 67.2% sensitive and 81.5% specific in clinically detecting HIV infection.
Conclusions:
Children with symptomatic HIV infection can be identified effectively by primary level health workers through the use of an algorithm. The improved HIV algorithm developed in this study could be used by countries with high prevalences of HIV to enable IMCI practitioners to identify and care for HIV-infected children.
