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Published on: October 31, 2010
Predicting CD4 lymphocyte count <200 cells/mm(3) in an HIV type 1-infected African population
Susan C Morpeth1, John A Crump, Humphrey J Shao
1Duke University Medical Center, Durham, North Carolina, 27710., Kilimanjaro Christian Medical Centre, Moshi, Tanzania.
Insights
Simple clinical criteria can help identify HIV patients needing antiretroviral therapy when CD4 testing is unavailable. Mucocutaneous manifestations, low lymphocyte count, and high ESR strongly predict low CD4 counts, improving WHO staging sensitivity.
Area of Science:
- Infectious Diseases
- Immunology
- Public Health
Background:
- Antiretroviral therapy (ART) initiation for HIV-infected individuals is often guided by CD4 lymphocyte counts.
- CD4 testing accessibility remains a challenge in resource-limited settings.
- Clinical criteria are needed to identify patients eligible for ART when CD4 counts are unavailable.
Purpose of the Study:
- To evaluate the performance of clinical criteria, including WHO staging, anthropometrics, and simple laboratory measurements, in predicting low CD4 counts (<200 cells/mm³).
- To identify key indicators for initiating antiretroviral therapy in HIV-infected patients in Tanzania.
Main Methods:
- A cross-sectional study involving 202 HIV-infected adults in Tanzania.
- Data collection included WHO staging, anthropometry, complete blood count (CBC), erythrocyte sedimentation rate (ESR), and CD4 count.
- Univariable analysis and recursive partitioning were employed to identify predictors of CD4 count <200 cells/mm³.
Main Results:
- 54% of participants had a CD4 count <200 cells/mm³.
- Strong predictors of low CD4 counts included mucocutaneous manifestations, low total lymphocyte count (TLC), low white blood cell count, and high ESR.
- A partition tree model using TLC <1,200 cells/mm³, ESR ≥120 mm/h, or mucocutaneous manifestations achieved 85% sensitivity and 63% specificity.
Conclusions:
- Mucocutaneous manifestations, low TLC, and high ESR are strong predictors of CD4 counts <200 cells/mm³.
- These clinical parameters significantly enhance the sensitivity of the 2006 WHO Staging system for identifying patients who would benefit from ART.
- The study provides valuable tools for clinical decision-making in resource-limited settings where CD4 testing is not readily available.
Abstract:
Clinical criteria are recommended to select HIV-infected patients for initiation of antiretroviral therapy when CD4 lymphocyte testing is unavailable. We evaluated the performance characteristics of WHO staging criteria, anthropometrics, and simple laboratory measurements for predicting CD4 lymphocyte count (CD4 count) <200 cells/mm(3) among HIV-infected patients in Tanzania. A total of 202 adults, diagnosed with HIV infection through community-based testing, underwent a detailed evaluation including staging history and examination, anthropometry, complete blood count, erythrocyte sedimentation rate (ESR), and CD4 count. Univariable analysis and recursive partitioning were used to identify characteristics associated with CD4 count 200 cells/mm(3). Of 202 participants 109 (54%) had a CD4 count <200 cells/mm(3). Characteristics most strongly associated with CD4 count <200 cells/mm(3) (p-value <0.0001) were the presence of mucocutaneous manifestations (72% vs. 28%), lower total lymphocyte count (TLC) (median 1,450 vs. 2,200 cells/mm(3)), lower total white blood cell count (median 4,200 vs. 5,500 cells/mm(3)), and higher ESR (median 95 vs. 53 mm/h). In a partition tree model, TLC <1,200 cells/mm(3), ESR >or=120 mm/h, or the presence of mucocutaneous manifestations yielded a sensitivity of 0.85 and specificity of 0.63 for predicting CD4 count <200 cells/mm(3). The sensitivity of the 2006 WHO Staging system improved from 0.75 to 0.93 with inclusion of these parameters, at the expense of specificity (0.36 to 0.26). The presence of mucocutaneous manifestations, TLC <1,200 cells/mm(3), or ESR >or=120 mm/h was a strong predictor of CD4 count <200 cells/mm(3) and enhanced the sensitivity of the 2006 WHO staging criteria for identifying patients likely to benefit from antiretrovirals.
