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Author (s) : R . Hsu 1 , K. Patton 2 , J. Liang 3 , R. Okabe 4 , J. Aberg 5 , N. Fineberg 2

WEAB0206. Independent Predictors of Carotid Intimal Thickness Differ Between HIV+ and HIV- Patients with Respect to Traditional Cardiac Risk Factors, Risk Calculators, Lipid Subfractions , and Inflammatory Markers.

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Author (s) : R . Hsu 1 , K. Patton 2 , J. Liang 3 , R. Okabe 4 , J. Aberg 5 , N. Fineberg 2

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  1. WEAB0206 Independent Predictors of Carotid Intimal Thickness Differ Between HIV+ and HIV- Patients with Respect to Traditional Cardiac Risk Factors, Risk Calculators, Lipid Subfractions, and Inflammatory Markers Author(s): R. Hsu1, K. Patton2, J. Liang3, R. Okabe4, J. Aberg5, N. Fineberg2 Institute(s):1New York University Medical Center, Internal Medicine, New York, United States, 2University of Alabama at Birmingham, Biostatistics, Birmingham, United States, 3New York University, New York, United States, 4New York University, School of Medicine, New York, United States, 5New York University Medical Center, Infectious Diseases, New York, United States

  2. Background • Carotid Intimal Thickness (CIMT) predicts CAD and helps risk-stratify patients for cardiovascular events1,2. HIV+ patients have greater and more rapid progression of CIMT than HIV- patients3. • Advantages include: • Low cost • No radiation • Insurance Coverage (1 CRF was required for study enrollment including HIV) 1Ruijter, H., “Common Carotid Intima-Media Thickness Measurements in Cardiovascular Risk Prediction, A Meta-analysis”, JAMA 2012; 308(8) 796-803. 2Nambi, V., et al., “Common carotid artery intima-media thickness is as good as carotid intima-media thickness of all carotid artery segments in improving prediction of coronary heart disease risk in the Atherosclerosis Risk in Communities (ARIC) study”, 2012, Jun; 33-183-190. 3Hsue, P., et al., “progression of atherosclerosis as assessed by carotid intima-media thickness in patients with HIV infection, Circulation, 109:1603-1608.

  3. Background • CIMT (as a surrogate marker for atherosclerosis) was then correlated with Testable Predictors of CIMT with the results differentiated between HIV+ and HIV- patients. • These Clinically Testable predictors include: • Traditional risk factor assessment • Hypertension, smoking, hyperlipidemia, diabetes, family history, and prior cardiac events, HIV (if positive) • Lipids and Lipid sub-particles • Total cholesterol, triglycerides, direct HDL-C, direct LDL-C, LDL-P (# of particles), small LDL-P (# of particles), HDL-P (# of particles), LPa-C, ApoB/A-1 ratio • Framingham, D:A:D (if HIV+) Risk calculators, Heart Age • Inflammatory markers (all commercially available) • hsCRP, D-dimer, IL-6, homocysteine, Lp-PLA2

  4. Methods 307 patients (179 HIV+,128 HIV-) had their maximal CIMT determined at the CCA and ICA (including bulb). Heart Age, traditional risk factors, Framingham and D:A:D Risk (HIV+), Lipids and sub-particles (Total Cholesterol, LDL, HDL, TG, LDL#, small LDL, Large HDL#, LP(a)-c, ApoB/A1 ratio), and inflammatory indices (d-dimer, IL-6, hsCRP, LPPLA2, homocysteine) were measured in each patient. Differences in demographics and these testable risk factors were determined between HIV+ and HIV- patients and were retrospectively analyzed with Mann Whitney and Chi-square testing to determine correlations with CIMT. Stepwise multiple regression analysis determined which variables were independently correlated with CIMT.

  5. Demographics/PMH

  6. Demographics/PMH

  7. Laboratory Data

  8. RESULTS: Univariate Correlates with CIMT HIV+ Patients: Heart age, IL-6, Diabetes, Hypertensive Medications, Framingham Risk, and D:A:D. HIV- Patients: Heart Age, Hypertension, Hypertensive meds, MI/Stroke history, HDL, Large HDL, Triglycerides, Framingham Risk scores, and hsCRP were all correlated with increased CIMT measurements.

  9. RESULTS: Multivariate Regression

  10. RESULTS: Multivariate Regression • Abacavir and duration of lopinavir/r or indinavir use was not correlated with CIMT

  11. RESULTS: Multivariate Regression • At the CCA, heart age was the only significant independent predictor for HIV+ pts. • At the ICA, IL-6 emerged as an independent predictor for HIV+ patients • At the ICA, Large HDL# and hsCRP were additional predictors for HIV- patients

  12. Conclusions Today, with HIV suppression, lipid, and hypertension control,HIV+ patients continue to have a disproportionately greater CIMT and calculated heart age than HIV- comparators. Although HIV+ patients generally had lower HDL than their HIV- counterparts, HDL was not an independent predictor of atherosclerosis in HIV+ patients, in contrast to the HIV- cohort. In the context of LDL control in this HIV+ patient population, LDL size was predictive of ICA CIMT. In the comparator HIV- population, HDL and Large HDL Particle number was predictive at the CCA CIMT, while LDL number only was predictive at the ICA CIMT.

  13. Conclusions Postulated inflammatory markers like LPPLA2 and homocysteine were not predictive of CIMT. Only IL-6 was associated with ICA CIMT in HIV+ patients, whereas hsCRP was associated with ICA in HIV- patients. This contrast in observation from markers associated with cardiovascular mortality in the SMART study (IL-6, d-dimer, hsCRP) may be partially explained by the reduction of inflammatory markers in the context of HIV suppression in this patient population and the use of standard citrate assays. Finally, there was no association with atherosclerosis as measured by CIMT with the use of abacavir, or duration of lopinavir or indinavir use, and the D:A:D cardiovascular risk equation, although predictive of CIMT, was shown to be less predictive than the Framingham risk equation in this HIV+ population.

  14. Study Limitations Retrospective analysis of data Sample Size Skewed Sex of this Patient Population (predominantly male)

  15. Part II of Study Re-stratification of cardiovascular risk by CIMT, lipid sub-particles, and/or inflammatory markers found significant in Multivariable Regression analysis will be performed, and determined ifpredictive ofatherosclerotic regression as measured by CIMT 1 year later. All patients with 1, 2, or 3 S.D.’s above the norm CIMT will be re-stratified by 1, 2, or 3 Framingham Risk categories, respectively, to achieve their new LDL goals with lipid lowering agents and also to start aspirin (option to decline). Additional new markers of monocyte immune activation like sCD14+ and sCD163+, markers correlated with unstable CVD plaque formation will also be measured before and after intervention.

  16. Case Example 44 year-old Caucasian Male, HIV+, T cells 490, VL <50, BP 135/85, Tchol 180, HDL 30, no DM, non-smoker, no hypertension. Framingham Risk Score 3%. CIMT performed showing 1.3mm CIMT at Rt. and Lft. Carotid bulbs, IL-6 level 8 Patient would be moved from Low Framingham Risk to High Risk Based on his IL6 level and CIMT 1.6S.D. above Median values.

  17. Case Example Patient would be Re-stratified two categories higher from Low Framingham Risk to High Framingham Risk based on his IL6 level and CIMT 1.6S.D. above normal Patient to Start ASA 81mg qD and attempt to reach LDL goal of <100, with re-assessment of Lipid sub-particles, Inflammatory Markers, monocyte activation markers and measurement of CIMT 1 year later to assess if atherosclerotic regression occurs.

  18. Acknowledgements • Naomi Fineberg and Kyle Patton • University of Alabama at Birmingham, Division of Biostatistics, Birmingham, United States • Judy Aberg and Hui Zhan • New York University Medical Center, Department of Infectious Diseases, New York, United States • Rachel Okabe and Jennifer Liang • New York University School of Medicine and New York University, New York, United States

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