Abstract
Background
HIV-infected individuals are at higher risk for developing cardiovascular disease (CVD). We aimed to develop a model to predict 10-year cardiovascular (CV) risk given that commonly used CVD risk assessment tools might not be accurate for HIV-infected patients.
Methods
We conducted a retrospective cohort study of HIV-infected patients seen at Boston Medical Center between March 2012 and January 2017. Exclusion criteria are shown in Figure 1. Patients were divided into model development and validation cohorts. Logistic regression was used to create a risk model for CV events using data from the development cohort. The relationship between risk factors and CVD risk was summarized using a point-based risk-scoring system. Areas under the receiver-operating-characteristics curve (AUC) were used to evaluate model discrimination. The model was subsequently tested using the validation cohort.
Results
Of 3,867 eligible HIV-infected patients, 1,914 individuals met inclusion criteria (Figure 1). There were 256 CV events in the development cohort. Ten independent prognostic factors were incorporated into the prediction function (Pmodel < 0.001). The model had excellent discrimination for CVD risk [AUC 0.94; (95% CI:0.93–0.96)] (Figure 2) and included the following variables: male sex (P < 0.001), African-American ethnicity (P = 0.023), current age (P = 0.020), age at HIV diagnosis (P = 0.006), peak HIV viral load (P = 0.012), nadir CD4 lymphocyte count (P < 0.001), hypertension (P < 0.001), hyperlipidemia (P = 0.001), diabetes (P < 0.001), and chronic kidney disease (P < 0.001). Scoring system and score sheets of risk estimates were developed to predict CV events in a 10-year follow-up period (Figures 3 and 4). The 10-parameter multiple logistic regression model also had excellent discrimination [AUC 0.96; (95% CI: 0.89–0.99)] when applied to the validation cohort.
Conclusion
We developed and validated a risk-scoring system based on 10 clinical factors that accurately predict the 10-year risk for CV events in an HIV-infected population. This assessment tool may provide clinicians with a rapid assessment of cardiovascular disease risk among HIV-infected patients and inform prevention measures during the era of effective antiretroviral therapy.
Disclosures
All Authors: No reported Disclosures.
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