Email this article Prediction Models for HIV Infection in Infants: Analysis of Scoring Systems on Maternal, Infants, and Mode of Delivery Risk Factors
- Authors: Latupeirissa D.1, Akib A.2, Hadinegoro S.R.3, Ibrahim F.4, Aminullah A.5, Bardosono S.6, Ismoedijanto 7, Utomo B.8
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Affiliations:
- Department of Child Health, Division of Tropical Pediatric and Infectious Diseases, Fatmawati General Hospital, Division of Tropical Pediatric and Infectious Diseases
- Department of Child Health, Faculty of Medicine, Division of Allergy and Immunology, University of Indonesia, Division of Allergy and Immunology, Cipto Mangunkusumo Hospital
- Department of Child Health, Division of Tropical Pediatric and Infectious Diseases, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
- Department of Microbiology, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
- Department of Child Health, Division of Neonatology, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
- Department of Nutrition, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
- Department of Child Health, Division of Tropical Pediatric and Infectious Diseases, Faculty of Medicine, University of Airlangga, Dr. Soetomo General Hospital
- Department of Community Medicine, Faculty of Medicine, University of Indonesia
- Issue: Vol 22, No 5 (2024)
- Pages: 329-335
- Section: Medicine
- URL: https://rjmseer.com/1570-162X/article/view/644165
- DOI: https://doi.org/10.2174/011570162X304984240822052915
- ID: 644165
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Abstract
Background:Diagnosis for HIV in infants is hard to determine, particularly in limited- resource areas. A delay in the diagnosis of HIV-infected infants will lead to high morbidity and mortality. The purpose of this project is to construct a model of an HIV-positive infant and develop a useful and practical scoring system to estimate the likelihood of mother-to-child transmission that can be applied in the field.
Methods:A cross-sectional study on 100 subjects through medical records of infants born to HIV-infected mothers was conducted at four hospitals and one community health center. Several models of risk prediction scores of HIV-infected infants were then made. Furthermore, the performed validation was performed on 20 subjects of infants born to mothers with HIV in three hospitals by comparing the scoring system and the result of the PCR RNA examination performed at the age of 6 weeks old.
Results:The risk of HIV-infected infants was higher in mothers who did not receive ARV through PMTCT programs (OR 33.6; 95% CI 4.0 to 282.2), pulmonary TB infection (OR 5.1; IK95% 1.6 to 16.0) and vaginal delivery (OR 9.2; IK95 2.2 to 38.0%). Two models can predict the occurrence of infected HIV infants effectively. Model 1 consists of maternal age, maternal ARVs, lung TB infection, gestational age, mode of delivery, and sex of the infants with sensitivity and specificity of 78.9% and 70.8% (AUC=0.817 [95% CI 0.709 to 0.926]) and likelihood ratio score of 4. Model 2 consists of ARVs to the mother, pulmonary TB infection, and mode of delivery with sensitivity and specificity of 73.7% and 86.1%; AUC value of 0.812 (95% CI 0.687 to 0.938) and likelihood ratio of 5. External Validation gave similar results to the Model 2 scoring system with PCR RNA.
Conclusion:The prediction score of HIV-infected infants in Model 2 can be used in newborns of HIV-positive mothers as an effective and practical risk screening tool for HIV-infected infants before the gold standard examination by PCR.
About the authors
Debbie Latupeirissa
Department of Child Health, Division of Tropical Pediatric and Infectious Diseases, Fatmawati General Hospital, Division of Tropical Pediatric and Infectious Diseases
Author for correspondence.
Email: info@benthamscience.net
Arwin Akib
Department of Child Health, Faculty of Medicine, Division of Allergy and Immunology, University of Indonesia, Division of Allergy and Immunology, Cipto Mangunkusumo Hospital
Email: info@benthamscience.net
Sri Rezeki Hadinegoro
Department of Child Health, Division of Tropical Pediatric and Infectious Diseases, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
Email: info@benthamscience.net
Fera Ibrahim
Department of Microbiology, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
Email: info@benthamscience.net
Asril Aminullah
Department of Child Health, Division of Neonatology, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
Email: info@benthamscience.net
Saptawati Bardosono
Department of Nutrition, Faculty of Medicine, University of Indonesia, Cipto Mangunkusumo Hospital
Email: info@benthamscience.net
Ismoedijanto
Department of Child Health, Division of Tropical Pediatric and Infectious Diseases, Faculty of Medicine, University of Airlangga, Dr. Soetomo General Hospital
Email: info@benthamscience.net
Budi Utomo
Department of Community Medicine, Faculty of Medicine, University of Indonesia
Email: info@benthamscience.net
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