A study of clinical spectrum of opportunistic infections in HIV infected children and its correlation with CD4 count and anti-retroviral therapy
Autor: | Nikita Shah, Vishal Manohar Jadhav, Mamta Manglani, Yashwant Gabhale, Mamatha Murad Lala |
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Rok vydání: | 2017 |
Předmět: | |
Zdroj: | International Journal of Contemporary Pediatrics. 4:1485 |
ISSN: | 2349-3291 2349-3283 |
DOI: | 10.18203/2349-3291.ijcp20172691 |
Popis: | Background: To determine the clinical spectrum and prevalence of opportunistic infections (OIs) in HIV infected children and correlate the occurrence of opportunistic infections with their CD4 count and Anti-retroviral treatment (ART).Methods: A total of 100 HIV infected children diagnosed with opportunistic infections were included in the study. Demographic details, clinical examination and relevant investigations were done for all the children. Clinical spectrum of OIs and HIV staging was recorded. CD4 counts were done at baseline and were repeated at 6 monthly intervals.Results: Mean age of the patients was 7.08±3.48 years (ranging from 6 months to 15 years) at enrollment with male to female ratio of 1.2:1. Fever (91%) was a common presenting symptom followed by weight loss (74%), cough (37%), abdominal pain (29%) and breathlessness (16%). CD4 count was significantly associated with presence of opportunistic infection in the study group. Tuberculosis - pulmonary (32%) and extra-pulmonary (29%) was the most common oppurtunistic infections, followed by oral thrush (13%), Herpes zoster (10%), Molluscum Contagiosum (9%), Pneumocystis jiroveci pneumonia (3%), Parvovirus infection (3%) and Pruritic Papular Eruptions (2%). 70% children were on ART as per clinical and immunological staging of HIV.Conclusions: Low CD4 count is significantly associated with severe opportunistic infections, therefore drop in CD4 count should serve as an alarming signal for the treating physician. High index of suspicion is required to detect opportunistic infections and therefore CD4 counts should be done more frequently to predict occurrence of OIs. |
Databáze: | OpenAIRE |
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