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Given the potential composite effect of multiple cardiovascular risk factors on cognition, we examined the ability of the Atherosclerotic Cardiovascular Disease (ASCVD) risk score and the Framingham Heart Study Global CVD risk score (FRS) to predict future cognitive function in older PLWH.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>We constructed linear regression models evaluating the association between baseline 10-year cardiovascular risk scores and cognitive function (measured by a summary z-score, the NPZ-4) at a year 4 follow-up visit.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>Among 988 participants (mean age, 52 years; 20% women), mean 10-year ASCVD risk score at entry into the cohort was 6.8% (standard deviation [SD], 7.1%) and FRS was 13.1% (SD, 10.7%). In models adjusted only for cognitive function at entry, the ASCVD risk score significantly predicted year 4 NPZ-4 in the entire cohort and after stratification by sex (for every 1% higher ASCVD risk, year 4 NPZ-4 was lower by 0.84 [SD, 0.28] overall, P = .003; lower by 2.17 [SD, 0.67] in women, P = .001; lower by 0.78 [SD, 0.32] in men, P = .016). A similar relationship was observed between FRS and year 4 NPZ-4. In multivariable models, higher 10-year ASCVD risk and FRS predicted lower NPZ-4 in women.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>Baseline 10-year ASCVD risk and FRS predicted future cognitive function in older PLWH with well-controlled infection. Cardiovascular risk scores may help to identify PLWH, especially women, who are at risk for worse cognition over time.<\/jats:p><\/jats:sec>","DOI":"10.1093\/cid\/ciz1214","type":"journal-article","created":{"date-parts":[[2019,12,31]],"date-time":"2019-12-31T12:09:20Z","timestamp":1577794160000},"page":"3079-3085","source":"Crossref","is-referenced-by-count":17,"title":["Baseline 10-Year Cardiovascular Risk Scores Predict Cognitive Function in Older Persons, and Particularly Women, Living With Human Immunodeficiency Virus Infection"],"prefix":"10.1093","volume":"71","author":[{"given":"Felicia C","family":"Chow","sequence":"first","affiliation":[{"name":"Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, California, USA"},{"name":"Department of Neurology and Division of Infectious Diseases, University of California, San Francisco, San Francisco, California, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Asya","family":"Lyass","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, Boston University, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Taylor F","family":"Mahoney","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joseph M","family":"Massaro","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, School of Public Health, Boston University, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Virginia A","family":"Triant","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Division of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kunling","family":"Wu","sequence":"additional","affiliation":[{"name":"Center for Biostatistics in AIDS Research, Harvard T. 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