Determinants of immunological recovery following HAART among severely immunosuppressed patients at enrolment to care in Northern Ethiopia: a retrospective study.

OBJECTIVE: This study aimed to identify determinants of immunological recovery following highly active antiretroviral therapy (HAART) among severely immunosuppressed patients at enrolment to care in Northern Ethiopia. METHODS: A retrospective study. SETTING: The study was done in Tigray Region, Northern Ethiopia. PARTICIPANTS: The study was done among severely immunosuppressed (<200 CD4 cells/mm3) individuals at initial enrolment to care and whose samples were sent for viral load determination from April 2015 to March 2019 in Tigray Health Research Institute. MAIN OUTCOMES: The main outcome variable was immunological recovery, modelled using binary logistic regression. RESULTS: Among the 9687 patients with severe immunosuppression at enrolment, 2746 (28.35%, 95% CI 27.45% to 29.26%) had immunological recovery following HAART for at least 6 months. Male gender (adjusted OR (AOR)=0.50, p<0.001), age 20-34 years old (AOR=0.33, p<0.001), age ≥50 years old (AOR=0.26, p<0.001), WHO clinical stage III (OR=0.68, p=0.036) and viral non-suppression (AOR=0.38, p<0.001) were strong predictors of immunological failure. CONCLUSIONS: Immunological recovery following HAART was low among severely immunosuppressed individuals at enrolment to care. Gender, age, WHO stage III and viral non-suppression were determinants of immunological recovery. Male patients, adolescents and virally non-suppressed patients should be identified as groups at higher risk for immunological failure. Therefore, greater support and intensive counselling should be prioritised among adolescents, men and virally non-suppressed patients for better immunological recovery.

Level of Adherence and Associated Factors Among HIV-Infected Patients on Antiretroviral Therapy in Northern Ethiopia: Retrospective Analysis.

BACKGROUND: Poor adherence to ART increases viremia, which leads to disease progression and transmission of drug-resistant HIV strains. This study aimed to assess the level of ART adherence and associated factors among adolescents and adult patients enrolled in ART care in Northern Ethiopia. METHODS: A retrospective analysis was conducted among 19,525 patients from April 2015 to March 2019. Data verification and filtration were done in Excel 2013 before exporting to STATA 14.0. Ordinal logistic regression was used to analyze the data. RESULTS: About 94.84%, 95% CI (94.52%, 95.14%) of the study subjects were in good adherence. However, about 1.46%, 95% CI (1.30%, 1.64%) and 3.70%, 95% CI (3.44%, 3.97%) of them had poor and fair adherence respectively. In the adjusted analysis, being male (AOR = 0.75; 95% CI: 0.0.65, 0.87), patients from general hospitals (AOR = 0.52; 95% CI: 0.39, 0.69), WHO staging IV (AOR = 0.57; 95% CI: 0.41, 0.81) and non-suppressed viral load (VL) status (AOR = 0.54; 95% CI: 0.47, 0.63) were negatively associated with good adherence. Whereas, age of 50+ years old (AOR = 1.68; 95% CI: 1.13, 2.50), recent CD4 count of 200-499 (AOR = 1.45; 95% CI: 1.21, 1.74) and recent CD4 count of 500 and above (AOR = 1.84; 95% CI: 1.47, 2.32) were positively associated with good ART drug adherence. CONCLUSION: There was a higher level of adherence compared to the previous studies conducted in Ethiopia. Being male, patients from general hospitals, WHO staging II, II and IV and non-suppressed VL status were negatively associated with good adherence. Whereas, older ages, recent CD4 count of 200-499 and ≥500 CD4 count were positively associated with good ART drug adherence. The health system should recognize a higher need of younger age groups and males to design targeted counseling and support to encourage consistently high levels of adherence for a better ART treatment outcome.

Incidence and factors associated with treatment failure among HIV infected adolescent and adult patients on second-line antiretroviral therapy in public hospitals of Northern Ethiopia: Multicenter retrospective study.

BACKGROUND: This study aimed to determine the incidence and factors associated with treatment failure among HIV infected adolescent and adult patients on second-line antiretroviral therapy (ART) in public hospitals of Northern Ethiopia. METHODS: A retrospective study was conducted from September 1, 2007 to July 30, 2017 on 227 patients. The data were extracted using a retrieval checklist from the patient's charts. The incidence rate of treatment failure was calculated using Kaplan-Meier methods and Cox proportional hazard model was used to assess factors associated with treatment failure. RESULT: The study subjects were followed for a total observation of 788.58 person-years with a median follow-up period of 35 (IQR: 17-60) months after switching to second-line ART. About 57 (25.11%) patients developed treatment failure, out of which, 32 (56.14%) occurred during the first two years. The overall incidence of second-line treatment failure was 72.3 per 1000 person years (95%CI: 55.75-93.71) of observation. The Kaplan-Meier estimates of cumulative treatment failure after 1, 2, and around 10 years of follow-up were 12.31% (95%CI: 8.60-17.45%), 14.99% (95%CI: 10.82%-20.57%), and 48.67% (95%CI: 32.45-67.81%) respectively. Age >45 years AHR = 3.33, 95%CI = 1.33-8.31), WHO stage IV (AHR = 3.63, 95%CI = 1.72-7.67), CD4 count <100 cells/mm3 (AHR = 3.79, 95%CI = 1.61-8.91), TB co-morbidity (AHR = 3.39 95%CI = 1.91-6.01) and poor adherence level (AHR = 3.63, 95% CI = 1.89-6.96) at the start of second line ART were significantly associated with second-line ART failure. CONCLUSION: Incidence of second-line ART treatment failure in the first 2 years of follow-up was high. The rate of second-line ART failure was higher in patients who started second-line ART with poor drug adherence, CD4 count <100 cells/mm3, TB co-morbidity, age >45 years, and being in WHO stage IV. Therefore, intensive counseling and adherence support should be given along with strong TB screening. Moreover, the government of Ethiopia should consider endorsing third-line ART drugs after careful cost-benefit analysis.

Prediction of CD4 T-Lymphocyte Count Using WHO Clinical Staging among ART-Naïve HIV-Infected Adolescents and Adults in Northern Ethiopia: A Retrospective Study.

BACKGROUND: WHO clinical staging has long been used to assess the immunological status of HIV-infected patients at initiation of antiretroviral therapy and during treatment follow-up. In setups where CD4 count determination is not readily available, WHO clinical staging is a viable option. However, correlation between CD4 count and WHO clinical staging is not known in an Ethiopian setting, and hence, the main aim of this study was to assess predictability of CD4 T-lymphocyte count using WHO clinical staging among ART-naïve HIV-infected adolescents and adults in northern Ethiopia. METHODS: A retrospective cross-sectional study was done in the Tigray Region, Ethiopia, from April 2015 to January 2019 from a secondary database of 19525 HIV-infected patients on antiretroviral treatment. Analysis was done using STATA-14.0 to estimate the frequencies, mean, and median of CD4 T-cell count in each WHO stages. Sensitivity, specificity, positive predictive value, negative predictive value, kappa test, and correlations were calculated to show the relationships between WHO stages and CD T-cell count. RESULTS: The sensitivity of WHO clinical staging to predict CD4 T-cell counts of <200 cells/µl was 94.17% with a specificity of 3.62%. The PPV was 49.03%, and the NPV was 3.62%. The sensitivity of WHO clinical staging to predict CD4 T-cell counts of <350 cells/µl was 94.75% with a specificity of 3.00%. The PPV was 75.81%, and the NPV was 15.09%. Similarly, the sensitivity of WHO clinical staging to predict CD4 T-cell counts of <500 cells/µl was 95.03% with a specificity of 2.73% and the PPV and NPV were 88.32% and 6.62%, respectively. The kappa agreement of WHO clinical stages was also insignificant when compared with the disaggregated CD4 counts in different categories. The correlation of WHO clinical staging was inversely associated with the CD4 count, and the magnitude of the correlation was 5.22%. CONCLUSIONS: The WHO clinical staging had high sensitivity but low specificity in predicting patients with CD4 count <200 cells/µl, <350 cells/µl, and <500 cells/µl. There was poor correlation and agreement between CD4 T-lymphocyte count and WHO clinical staging. Therefore, WHO clinical staging alone may not provide accurate information on the immunological status of patients, and hence, it is better to use the CDC definition rather than the WHO clinical definition.