The aim of this study is to develop and follow a cohort of human immunodeficiency virus (HIV)-infected adults who are starting HIV drugs at health facilities in Kenya. Blood and urine samples will be collected from all participants in order to establish a sample bank of samples in order to further the understanding of the levels of inflammatory biomarkers and coagulation biomarkers in African patients and the effect of taking HIV drugs on these biomarkers. This study will enroll and follow 685 men and women who are starting HIV drugs and collect blood and urine specimens from them at 4 study visits. These samples will be frozen and stored for future testing related to inflammatory and coagulation biomarkers.
Biomarkers have been investigated as predictors of HIV disease progression, i.e. development of acquired immunodeficiency syndrome (AIDS) defining diagnoses or death. There are limited data on the levels of these biomarkers among HIV-infected individuals in sub Saharan Africa and on the effect of antiretroviral therapy (ART) initiation on these levels. In addition, further work is needed to examine the association between such markers and various complications associated with HIV as well as mortality in sub Saharan Africa. The overall aim of this study is to develop a cohort of HIV-infected adults who are initiating ART at health facilities in Kenya and to establish a sample bank of plasma and urine samples in order to further the understanding of the levels of inflammatory biomarkers (IBM) and coagulation biomarkers (CBM) in African patients and the effect of ART initiation on these biomarkers. The study objectives are as follows: * To recruit, establish and follow a cohort of HIV-infected individuals who are eligible for initiation of ART through 12 months * To obtain blood and urine samples on all cohort participants at baseline, months 2, 6, and 12 for future HIV and related research * To describe the demographic and disease characteristics of cohort participants and associations with various biomarkers
Study Type
OBSERVATIONAL
Enrollment
685
Ahero Sub District Hospital
Ahero, Nyanza, Kenya
Ambira Sub District Hospital
Ambira, Nyanza, Kenya
Awasi Mission
Awasi, Nyanza, Kenya
Bondo District Hospital
Bondo, Nyanza, Kenya
Nyakach District Hospital
Kisumu, Nyanza, Kenya
Masogo Sub District Hospital
Masogo, Nyanza, Kenya
Nyangoma Dispensary
Nyangoma, Nyanza, Kenya
Sigomere Health Centre
Sigomere, Nyanza, Kenya
Sondu Health Center
Sondu, Nyanza, Kenya
Change in mean high-sensitivity C-reactive protein (hsCRP) levels measured in mg/L
Blood and urine samples of participants will be analyzed for inflammatory and coagulation biomarkers at four different times during this study to assess the change in marker levels.
Time frame: Baseline to 12 months
Change in mean interleukin-6 (IL-6) levels measured in ng/mL
Blood and urine samples of participants will be analyzed for inflammatory and coagulation biomarkers at four different times during this study to assess the change in marker levels.
Time frame: Baseline to 12 months
Prevalence (% of participants) of smoking in the study population
Using baseline surveys, human specimens, and other physiological measures (i.e. BP screenings), the prevalence of risk factors for non-communicable diseases will be assessed.
Time frame: 12 months
Prevalence (% of participants) of high BMI in the study population
Using baseline surveys, human specimens, and other physiological measures (i.e. BP screenings), the prevalence of risk factors for non-communicable diseases will be assessed.
Time frame: 12 months
Prevalence (% of participants) of cotinine in blood in the study population.
Using baseline surveys, human specimens, and other physiological measures (i.e. BP screenings), the prevalence of risk factors for non-communicable diseases will be assessed.
Time frame: 12 months
Prevalence (% of participants) of hypertension in the study population.
Using biomarkers, self-report, and other physiological tests (i.e. BP screenings), researchers will assess the prevalence of co-morbid conditions.
Time frame: 12 months
Prevalence (% of participants) of diabetes in the study population.
Using biomarkers, self-report, and other physiological tests (i.e. BP screenings), researchers will assess the prevalence of co-morbid conditions.
Time frame: 12 months
Prevalence (% of participants) of overweight/obesity in the study population.
Using biomarkers, self-report, and other physiological tests (i.e. BP screenings), researchers will assess the prevalence of co-morbid conditions.
Time frame: 12 months
Prevalence (% of participants) of tuberculosis in the study population.
Using biomarkers, self-report, and other physiological tests (i.e. BP screenings), researchers will assess the prevalence of co-morbid conditions.
Time frame: 12 months
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