Bilateral pedal edema in an HIV patient: Lopinavir/Ritonavir-containing treatment regimen as a potential cause?

A large number of patients are switched to second-line antiretroviral therapy, especially in resource limited settings. Lopinavir/Ritonavir is the main drug used in second-line treatment regimens. We describe a patient attending an HIV treatment centre in Kampala, Uganda, who presented with bilateral non-tender pitting inflammatory edema two weeks after switching to a Lopinavir/Ritonavir-containing second-line treatment regimen. The lack of an alternate explanation led us to suspect that Lopinavir/Ritonavir was potentially responsible for the edema.

Three-year outcome data of second-line antiretroviral therapy in Ugandan adults: good virological response but high rate of toxicity.

OBJECTIVE: To evaluate the safety and virological response to lopinavir/ritonavir containing second-line therapy after failing a first line nonnucleoside reverse transcriptase inhibitor (NNRTI) based regimen. DESIGN: Prospective 36 months cohort study of patients switched to zidovudine/stavudine plus didanosine plus lopinavir/ritonavir capsules as second-line regimen. METHODOLOGY: Structured interview, medical examination, and laboratory assessment performed every 6 months. RESULTS: We enrolled 40 patients; 1 died and 3 were lost to follow-up. Median CD4+ count at baseline was 108 cell/microL, median log viral load was 4.8 copies/mL. Sixteen (40%) patients had baseline genotypic resistant test, 14 (87%) had lamivudine resistance mutations, and all had NNRTIs resistance mutations. At month 36, 82% of the patients achieved viral suppression (<400 copies/ mL) and the median increase in CD4+ count was 214 cell/microL, (interquartile range: 128-295). Twenty-five patients (62%) experienced at least one adverse event. CONCLUSIONS: Our study confirms lopinavir/ ritonavir-based second-line regimen but with a high rate of toxicities.

Evaluation of Dynabeads and Cytospheres compared with flow cytometry to enumerate CD4+ T cells in HIV-infected Ugandans on antiretroviral therapy.

BACKGROUND: Laboratory-based monitoring of antiretroviral therapy is essential but adds a significant cost to HIV care. The World Health Organization 2006 guidelines support the use of CD4 lymphocyte count (CD4) to define treatment failure in resource-limited settings. METHODS: We compared CD4 obtained on replicate samples from 497 HIV-positive Ugandans (before and during ART) followed for 18 months by 2 manual bead-based assays, Dynabeads (Dynal Biotech), and Cytospheres (Beckman Coulter) with those generated by flow cytometry at the Infectious Diseases Institute in Kampala, Uganda. RESULTS: We tested 1671 samples (123 before ART) with Dynabeads and 1444 samples (91 before ART) with Cytospheres. Mean CD4 was 231 cells/mm (SD, 139) and 239 cells/mm (SD, 140) by Dynabeads and flow cytometry, respectively. Mean CD4 was 186 cells/mm (SD, 101) and 242 cells/mm (SD, 136) by Cytospheres and flow cytometry, respectively. The mean difference in CD4 count by flow cytometry versus Dynabeads were 8.8 cells/mm (SD, 76.0) and versus Cytospheres were 56.8 cells/mm (SD, 85.8). The limits of agreement were -140.9 to 158.4 cells/mm for Dynabeads and -112.2 to 225.8 cells/mm for Cytospheres. Linear regression analysis showed higher correlation between flow cytometry and Dynabeads (r=0.85, r=0.73, slope=0.85, intercept=28) compared with the correlation between flow cytometry and Cytospheres (r=0.78, r=0.60, slope=0.58, intercept=45). Area under the receiver operating characteristics curve to predict CD4<200 cells/mm was 0.928 for Dynabeads and 0.886 for Cytospheres. CONCLUSION: Although Dynabeads and Cytospheres both underestimated CD4 lymphocyte count compared with flow cytometry, in resource-limited settings with low daily throughput, manual bead-based assays may provide a less expensive alternative to flow cytometry.

Evaluation of a low-cost method, the Guava EasyCD4 assay, to enumerate CD4-positive lymphocyte counts in HIV-infected patients in the United States and Uganda.

OBJECTIVE: To evaluate the EasyCD4 assay, a less expensive method to enumerate CD4+ lymphocytes, in resource-limited settings. DESIGN: Cross-sectional study conducted in the United States and Uganda. METHODS: We compared CD4+ cell counts obtained on replicate samples from HIV-infected patients by the EasyCD4 assay, a microcapillary flow-based system, and by standard flow cytometry or FACSCount with linear regression and the Bland-Altman method. RESULTS: Two hundred eighteen samples were analyzed (77 in the United States and 141 in Uganda). In the United States, mean +/- SD CD4 was 697 +/- 438 cells/microL by standard flow cytometry and 688 +/- 451 cells/microL by EasyCD4. In Uganda, the mean +/- SD CD4 was 335 +/- 331 cells/microL by FACSCount and 340 +/- 327 cells/microL by EasyCD4. The 2 methods were highly correlated (US cohort, r2 = 0.97, slope = 1.0, intercept = -18; Ugandan cohort, r2 = 0.92; slope = 0.95; intercept = 23). The mean differences in CD4 cell counts were 9.0 and -4.6 cells/microL for the US and Ugandan cohorts, respectively, and they were not significant in either cohort. In the Ugandan cohort, sensitivity and specificity of the EasyCD4 for CD4 below 200 cells/microL were 90% and 98%, respectively. Positive predictive value was 96%; negative predictive value was 93%. CONCLUSIONS: Our results suggest that EasyCD4 may be used with high positive and negative predictive value in resource-limited settings.

A new model to monitor the virological efficacy of antiretroviral treatment in resource-poor countries.

Monitoring the efficacy of antiretroviral treatment in developing countries is difficult because these countries have few laboratory facilities to test viral load and drug resistance. Those that exist are faced with a shortage of trained staff, unreliable electricity supply, and costly reagents. Not only that, but most HIV patients in resource-poor countries do not have access to such testing. We propose a new model for monitoring antiretroviral treatment in resource-limited settings that uses patients' clinical and treatment history, adherence to treatment, and laboratory indices such as haemoglobin level and total lymphocyte count to identify virological treatment failure, and offers patients future treatment options. We believe that this model can make an accurate diagnosis of treatment failure in most patients. However, operational research is needed to assess whether this strategy works in practice.