22 research outputs found

    Trends in CD4 Count Testing, Retention in Pre-ART Care, and ART Initiation Rates over the First Decade of Expansion of HIV Services in Haiti

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    Background: High attrition during the period from HIV testing to antiretroviral therapy (ART) initiation is widely reported. Though treatment guidelines have changed to broaden ART eligibility and services have been widely expanded over the past decade, data on the temporal trends in pre-ART outcomes are limited; such data would be useful to guide future policy decisions. Methods: We evaluated temporal trends and predictors of retention for each step from HIV testing to ART initiation over the past decade at the GHESKIO clinic in Port-au-Prince Haiti. The 24,925 patients >17 years of age who received a positive HIV test at GHESKIO from March 1, 2003 to February 28, 2013 were included. Patients were followed until they remained in pre-ART care for one year or initiated ART. Results: 24,925 patients (61% female, median age 35 years) were included, and 15,008 (60%) had blood drawn for CD4 count within 12 months of HIV testing; the trend increased over time from 36% in Year 1 to 78% in Year 10 (p500 cells/mm3, respectively. The trend increased over time for each CD4 strata, and in Year 10, 94%, 95%, 79%, and 74% were retained in pre-ART care or initiated ART for each CD4 strata. Predictors of pre-ART attrition included male gender, low income, and low educational status. Older age and tuberculosis (TB) at HIV testing were associated with retention in care. Conclusions: The proportion of patients completing assessments for ART eligibility, remaining in pre-ART care, and initiating ART have increased over the last decade across all CD4 count strata, particularly among patients with CD4 count ≀350 cells/mm3. However, additional retention efforts are needed for patients with higher CD4 counts

    Comparing six cardiovascular risk prediction models in Haiti: implications for identifying high-risk individuals for primary prevention

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    Abstract Background Cardiovascular diseases (CVD) are rapidly increasing in low-middle income countries (LMICs). Accurate risk assessment is essential to reduce premature CVD by targeting primary prevention and risk factor treatment among high-risk groups. Available CVD risk prediction models are built on predominantly Caucasian risk profiles from high-income country populations, and have not been evaluated in LMIC populations. We aimed to compare six existing models for predicted 10-year risk of CVD and identify high-risk groups for targeted prevention and treatment in Haiti. Methods We used cross-sectional data within the Haiti CVD Cohort Study, including 1345 adults ≄ 40 years without known history of CVD and with complete data. Six CVD risk prediction models were compared: pooled cohort equations (PCE), adjusted PCE with updated cohorts, Framingham CVD Lipids, Framingham CVD Body Mass Index (BMI), WHO Lipids, and WHO BMI. Risk factors were measured during clinical exams. Primary outcome was continuous and categorical predicted 10-year CVD risk. Secondary outcome was statin eligibility. Results Sixty percent were female, 66.8% lived on a daily income of ≀ 1 USD, 52.9% had hypertension, 14.9% had hypercholesterolemia, 7.8% had diabetes mellitus, 4.0% were current smokers, and 2.5% had HIV. Predicted 10-year CVD risk ranged from 3.6% in adjusted PCE (IQR 1.7–8.2) to 9.6% in Framingham-BMI (IQR 4.9–18.0), and Spearman rank correlation coefficients ranged from 0.86 to 0.98. The percent of the cohort categorized as high risk using model specific thresholds ranged from 1.8% using the WHO-BMI model to 41.4% in the PCE model (χ2 = 1416, p value < 0.001). Statin eligibility also varied widely. Conclusions In the Haiti CVD Cohort, there was substantial variation in the proportion identified as high-risk and statin eligible using existing models, leading to very different treatment recommendations and public health implications depending on which prediction model is chosen. There is a need to design and validate CVD risk prediction tools for low-middle income countries that include locally relevant risk factors. Trial registration clinicaltrials.gov NCT03892265 .http://deepblue.lib.umich.edu/bitstream/2027.42/173513/1/12889_2022_Article_12963.pd
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