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HIV and Aging

HIV and Aging. Kathleen K Casey, MD Director, AIDS Ambulatory Care Center Jersey Shore University Medical Center. Growing Older: HIV and Aging. Estimated Percentage of Persons Living with HIV/AIDS Who Are 50 and Older by Year, 2001-2007 a. % of Patients 50 and Older. Year.

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HIV and Aging

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  1. HIV and Aging Kathleen K Casey, MD Director, AIDS Ambulatory Care Center Jersey Shore University Medical Center

  2. Growing Older: HIV and Aging Estimated Percentage of Persons Living with HIV/AIDS Who Are 50 and Older by Year, 2001-2007a % of Patients 50 and Older Year a For years 2001-2003, data are based on 33 states and US-dependent areas with confidential name-based HIV infection reporting, CDC HIV/AIDS Surveillance Report, 2005. For years 2004-2007, data are based on 34 states and 5 US-dependent areas with confidential name-based HIV infection reporting, CDC HIV/AIDS Surveillance Report, 2007. Gay Men’s Health Crisis. Growing Older With the Epidemic: HIV and Aging. 2010. 2

  3. Concurrenta HIV/AIDS Among Persons Diagnosed with HIV in the United States in 2006, by Age Group Concurrent HIV/AIDS Among Persons Diagnosed with HIV in the United States in 2006, by Age Group HIV only (non-AIDS) Concurrent HIV/AIDS 100 90 80 45 51 70 56 62 60 76 80 88 Persons Newly Diagnosed with HIV, % 50 40 30 55 49 20 44 38 10 24 20 12 0 0-12 13-19 20-29 30-39 40-49 50-59 60+ Age Group at Diagnosis a AIDS diagnosis within one year of HIV diagnosis. Gay Men’s Health Crisis. Growing Older With the Epidemic: HIV and Aging. 2010. 3

  4. How Are We Finding Our Patients Over 50? • Hospitalized patients with opportunistic infections • Screening of patients with malignancy • Partner Testing • STD clinic visits • Dialysis Screening • Dementia screening • Rarely through routine primary care assessment and routine testing despite CDC recommendations!

  5. Clinical Considerations in Aging Adults with HIV 1 Cuzin L et al. Clin Infect Dis. 2007;45:654-657. 2 Skiest DJ et al. Arch Fam Med. 1997;6:289-294. 3 Siegel K et al. AIDS Care. 1999;11:525-535. Older patients are more likely than younger patients to present late for HIV diagnosis and care1 Physicians are less likely to discuss HIV/AIDS and related risk factors with older patients2 Asymptomatic older HIV-infected individuals are less likely to seek out testing and medical care3 Symptomatic older HIV-infected individuals are more likely to attribute HIV-related symptoms to other illnesses or to the normal aging process3 5

  6. Skiest Study: Relevant Findings Physicians reported that 69.7% of their patients older than 50 years rarely or never asked them questions about HIV or AIDS 60.8% of respondents reported rarely or never discussing HIV or AIDS with their patients aged >50 years, while 40% reported rarely or never asking their patients aged >50 years about possible HIV risk factors 67.5% of respondents reported rarely or never discussing behaviors that may reduce HIV risk in their patients older than 50 years, while only 6.8% of the physicians rarely or never discussed risk factors in their patients younger than 30 years Family practitioners were more likely than internists to rarely or never ask patients aged >50 years about HIV risk factors (54.9% vs 28.9%, P=.007) Skiest DJ et al. Arch Fam Med. 1997;6:289-294. 6

  7. Siegel Study • Study explored how symptom interpretations influence the initiation of HIV testing and medical care among adults aged ≥50 years through patient interviews • N=78 patients living with HIV (58 men, 20 women) • 19 patients aged ≥60 • 32 African American, 15 Puerto Rican, 31 non-Hispanic whites • 51% identified as completely/mostly heterosexual, 42% as completely/mostly homosexual • 47 (60%) diagnosed with AIDS, 9 (12%) symptomatic HIV disease, 22 (28%) asymptomatic HIV infection • Mean CD4 cell count at first interview: 400 cells/mm3 (SD=311, range 32-1500 cells/mm3) • 91% reported other chronic health conditions: heart disease (27%), respiratory problems (36%), arthritis (36%), and other illnesses (41%) • Presence or absence of putative symptoms of AIDS most often led to patients’ HIV testing • Attributing symptoms to other illnesses (eg, hypertension, normal aging, menopause) was a common reason for delaying HIV testing • Some patients delayed or refused to seek medical care even after being diagnosed as HIV+ because they did not feel ill and/or misattributed their symptoms to other illnesses Siegel K et al. AIDS Care. 1999;11:525-535. 7

  8. How well do older patients do with HIV treatment?

  9. Kaiser Permanente of Northern California:Virologic Response and Age Achieving HIV RNA <500 Copies/mL at 12 Months Experiencing HIV RNA Rebound Within 2 Years 1.15a (1.04-1.27) 1.00 (Reference) 1.00 (Reference) 0.97 (0.88-1.06) 0.88 (0.73-1.06) 0.81b (0.69-0.96) Hazard Ratio (95% CI) Hazard Ratio (95% CI) 18-39 40-49 ≥50 18-39 40-49 ≥50 Age at Baseline (years) Age at Baseline (years) a P =.009; bP =.01. Adjusted for age only. CI, confidence interval. Silverberg MJ et al. Arch Intern Med. 2007;167:684-691. 9

  10. Higher Risk of Clinical Progression in Patients 50 Years and Older ADE, AIDS-defining event; HR, hazard ratio. Grabar S. AIDS. 2004;18:2029-2038. • Patients 50 years and older have higher risk of clinical progression but improved virologic response compared with younger patients • Prospective cohort study of 3015 treatment-naive patients initiating ART • 50 years and older: n=401 • Younger than 50 years: n=2614 • Median follow-up: 31.5 months • At baseline, older patients more likely to have • ADE (P =.0001) • Lower CD4 T-cell count (P =.0002) • Higher HIV-1 RNA level (P =.0001) 10

  11. Kaiser Permanente of Northern California:Clinical Outcomes • Kaiser Permanente of Northern California chart review study of all members who initiated ART from 1995-2004 (N=5090) • 18 years and older; starting 3 or more anti-retrovirals in combination; median follow-up: 3.8 years Age (years) <50 (n=4094) ≥50 (n=997) 47.4a 36.4b 28.8 28.5 Rates per 1000 Person-years a P ≤.001 and b P=.01 vs <50 years. 8.4 7.5 7.2a 5.9a 5.9a 2.3 2.3 1.6 AIDS Dementia AIDS-defining Illnesses (hospitalizations) Candidiasis Wasting Syndrome Death PCP AIDS Diagnoses PCP, pneumocystis pneumonia. Silverberg MJ et al. Arch Intern Med. 2007;167:684-691. 11

  12. Kaiser Permanente of Northern California: Incidence of Laboratory Abnormalities After ART Initiation, by Age Analysis of Patients Who Developed at Least Grade 2 Laboratory Abnormality After ART Initiation a Abnormal cutoff defined as ≥240 mg/dL for total cholesterol and ≥ 160 mg/dL for LDL cholesterol. b Abnormal cutoff defined as 161 mg/dL (random), 126 mg/dL (fasting) and 54 mg/dL (low). c Abnormal cutoff defined as ≥1.8 mg/dL for men and ≥1.65 mg/dL for women. LDL, low-density lipoprotein; NR, not reported; OR, odds ratio; TC, total cholesterol. Silverberg MJ. Arch Intern Med. 2007;167:684-691. 12

  13. Non-AIDS–related Causes of Death in HIV+ Persons Treated with ART (1996-2006) Renal 3.0% Respiratory 3.1% Other 9.0% Malignancy 23.5% Liver-related 14.1% Infection Non-AIDS 16.3% Violence Sub Abuse 15.4% CVD 15.7% Assessed deaths in 13 HIV-1 cohorts composed of 39,727 persons (5293 patients 50 years and older) Of 1876 deaths, definitive cause in 85% Non-AIDS–related deaths in 50.5%: Antiretroviral Therapy Cohort Collaboration (ART-CC). Clin Infect Dis. 2010;50:1387-1396. 13

  14. HIV and Age as Renal Risk Factors a GFR <60 mL/min/1.73 m2. GFR, glomerular filtration rate. • Among 2857 HIV-infected patients participating in ALLRT study1: • At baseline, 16% of patients had abnormal levels of urine protein as measured by ratio of spot urine (P/Cr ≥0.2) • Older age was significantly associated with P/Cr ≥0.2 • Per 10 years: OR 1.21 (95% CI, 1.10-1.33; P <.001) • In the EuroSIDA cohort, the rate of chronic renal failurea at baseline ranged from 3.5% to 4.7% depending on the method of GFR calculation2 • By multivariate analysis, age was a strong predictor of chronic renal failure at baseline • OR 5.47, 95% CI, 4.4-6.72; P <.00012 1 Gupta SK, et al. AntivirTher. 2009;14:543-549. 2 Mocroft A. AIDS. 2007;21:1119-1127. 14

  15. Aging, BMD Loss, and HIV Infection BMD Loss with Age in the General Population, by Sex1 30 Male n=15 Female n=21 25 n=29 n=14 n=13 Change in Bonea Volume,% 20 n=18 n=15 n=19 n=14 15 n=26 Mean ± SE 10 40 50 60 70 Age (years) 1 Aaron JE et al. Clin Orthop Relat Res. 1987;215:260-271. 2 Brown TT et al. AIDS. 2006;20:2165-2174. • Multiple studies have found increased prevalence of osteoporosis and osteopenia in persons with HIV compared with uninfected persons2 • Meta-analysis of studies2 • 67% persons with HIV had reduced BMD (OR 6.4) • 15% persons with HIV had osteoporosis (OR 3.7) 15

  16. Research Patient Data Registrya: Fracture Prevalence Is Associated with HIV Infection 8525 HIV+ and 2,208,792 HIV- Patients from 1996-2008 Women Men P =.002 (overall comparison) P <.0001 (overall comparison) Frequency per 100 Persons a Clinical care data registry from the Partners HealthCare System, which consists primarily of Brigham and Women’s Hospital and Massachusetts General Hospital. Triant VA et al. J Clin Endocrinol Metab. 2008;93:3499-3504. 16

  17. NeuropsychologicalImpairment, HIV, and Older Age • In a cross-sectional analysis of 202 patients with HIV enrolled in the Hawaii Aging with HIV Cohort (n=103 patients 50 years and older): • HIV-associated dementia was more frequent in adults aged 50 years and older vs those aged 20-39 years • OR 2.13, 95% CI, 1.02-4.44 • After adjusting for education, race, drug use, ART status, viral load, CD4 count, and Beck Depression Inventory score, risk of HIV-associated dementia was even higher among older patients • OR 3.26, 95% CI, 1.32-8.07 Valcour VG et al. Neurology. 2004;63:822-827. 17

  18. Age at ADM and NADM Diagnosis in Patients with HIV vs General Population a N=8300 patients seen at the Infectious Diseases Ponce de Leon Center during 2000-2007 (516 cancer cases). b Data gathered from 17 registries of the Surveillance, Epidemiology and End Results (SEER) database. ADM, AIDS-defining malignancy; NADM, non-AIDS—defining malignancy; SCC, squamous cell carcinoma. Nguyen ML et al. 18th IAC; Vienna; 2010. Abstract WEAB0105. 18

  19. Interplay of HIV, ART, and Traditional Risk Factors on CVD CVD • Body composition: • Lipoatrophy • Lipohypertrophy Dyslipidemia: ↑ TG ↓ HDL ↑ FFA ↑ Small, dense LDL ↕↔ LDL Inflammation Insulin resistance ↑ Glucose HIV infection ART, including specific ARVs • Predisposing factors: • Genetics, smoking, sedentary lifestyle, diet, obesity, HTN, renal disease ART, antiretroviral therapy; ARV, antiretroviral; FFA, free fatty acids; HDL, high-density lipoprotein; HTN, hypertension; LDL, low-density lipoprotein; TG, triglycerides. Adapted from Grunfeld C et al. Circulation. 2008;118:e20-e28. 19

  20. Research Patient Data Registrya:Prevalence of Cardiac Risk Factors in HIV+ Patients vs HIV- Subjects Percentage of Subjects with CV Risk Factors by ICD Code b b Patients, % b a Cohort population: all patients aged 18-84 years who presented on at least two occasions to one of two Boston health care facilities, Brigham and Women’s Hospital (BWH) or Massachusetts General Hospital (MGH) between 1996 and 2004. b P <.0001 for comparison between proportions in HIV+ and HIV- cohorts by Χ2. ICD, International Classification of Disease(s). Adapted from Triant VA et al. Clin Endocrinol Metab. 2007;92:2506-2512. 20

  21. Research Patient Data Registrya: AMI Rates in HIV+ Patients vs HIV- Subjects, by Age Group AMI Rates by Age Group 100 HIV+ (n = 3851) HIV- (n = 1,044,589) 80 60 Events per 1000 P-Y 40 20 0 18-34 35-44 45-54 55-64 65-74 Age Group (years) a Clinical care data registry from the Partners HealthCare System, which consists primarily of Brigham and Women’s Hospital and Massachusetts General Hospital; identified patients who presented at least twice from 1996-2004. AMI, acute myocardial infarction; P-Y, patient-year. Triant VA et al. J Clin Endocrinol Metab. 2007;92:2506-2512. 21

  22. Framingham Cardiovascular Risk Assessment Tool • Age • Gender • Total cholesterol • HDL • Smoking status • Systolic blood pressure • Family history of CAD • Medication used to control blood pressure

  23. D:A:D Study: Prevalence of CV Risk Factors in HIV+ Patients at Baseline Percentage of Cohort with Risk Factor at Baseline Family Historyof CHD PreviousCVD CurrentSmoking BMI>30 mg/m2 HTN DiabetesMellitus ↑TotalCholesterol ↑TG BMI, body mass index; CHD, coronary heart disease; D:A:D, data collection on adverse events of anti-HIV drugs. Adapted from Friis-Møller N et al. AIDS. 2003;17:1179-1193. Large observational cohort of HIV+ patients followed longitudinally (N = 17,852) 15,537 (87%) with previous ART exposure; 2315 (13%) ARV-naive 23

  24. SCOPE Cohorta: HIV Infection Contributes to Premature Atherosclerosis Even in the Absence of Detectable Viremia CD4 >500 P =.13 P <.001 P <.001 Mean IMT (mm) Mean Carotid IMT (mm) 2.0 2.5 HIV- HIV+ART-VL <75 HIV+ART-VL >75 HIV- HIV+EliteControllers n = 93 2.0 1.5 n = 33 n = 96 1.5 1.0 1.0 0.5 0.5 a All study participants with HIV were recruited from the UCSF SCOPE Cohort, which contains a large group of rare individuals who were recruited on the basis of their ability to control HIV replication in the absence of therapy. HIV- participants were selected mainly from those answering advertisements to participate in research studies who were similar in age and sex to participants with HIV. 0.0 0.0 cIMT, carotid intima media thickness (a validated measure of atherosclerosis); IMT, intima media thickness; VL, viral load. HIV+ treatment-naïve patients with undetectable VLs (HIV controllers) had a higher mean carotid IMT than the HIV- participants, even after controlling for traditional risk factors HIV controllers had a trend toward higher median cIMT than untreated HIV noncontrollers Hsue P et al. AIDS. 2009;23:1059-1067. 24

  25. HOPS: Attributable Risk for CVD Relative Contribution of Risk Factors to Incident CVD Attributable Risk, % CV, cardiovascular; CVR, cardiovascular risk; HDL-C, high-density lipoprotein-cholesterol; HTN, hypertension; NCEP, National Cholesterol Education Program. Lichtenstein KA et al. Clin Infect Dis. 2010;51:435-447. • Prospective observational cohort study of patients with HIV • Analysis included patients receiving care from 2002-2009; N=2005 (148 incident CV events) • Median age: 42 years • Categorized patients according to the NCEP 10-year CVR score criteria (10-yr CVR) • Analyzed incidence and rates of CVD during observation period and calculated the relative attributable risks of various traditional and HIV risk factors to incident CVD 25

  26. D:A:D Study: MI Incidence by Duration of ART Exposure MI Incidence 10 9 8 7 6 5 Incidence per 1000 Person-Years 4 3 2 1 0 <1 1-2 2-3 3-4 4-5 5-6 6-7 >7 0 Exposure (years) MI, myocardial infarction. 26 D:A:D Study Group. N Engl J Med. 2007;356:1723-1735.

  27. Metabolic Syndrome • Hypertension • Hypergylcemia • Central obesity • Hypercholesterolemia

  28. Prevalence of Metabolic Syndrome Components in HIV+ Patients vs HIV- Controls Prevalence of MS Components in HIV+ Patients and HIV- Controls P <.0001 P <.0001 P <.0001 Subjects, % NS P <.0001 BP, blood pressure; MS, metabolic syndrome; WC, waist circumference.Bonfanti PB et al. J Acquir Immune Defic Syndr. 2007;45:426-431. 28

  29. CHD Risk Increased in HIV+ Patients with Fat Redistributiona 10 FraminghamOffspring Study controls P =.002 9 7.4 8 HIV+ patientswith fat redistribution 7 P =.27 6 5.3 HIV+ patientswithout fat redistribution 10-year CHD-risk Estimate (%) 5 4.1 4 3.3 3 2 1 0 (n = 273) (n = 91) (n = 90) (n = 30) Patient Population a Study included 91 consecutive HIV+ subjects (65 men and 26 women) who reported recent changes in body fat distribution who were prospectively evaluated from December 1998 through November 1999 at the Clinical Research Center of the Massachusetts Institute of Technology. Patients with fat redistribution had significantly increased 10-year CHD risk compared with matched controls Patients without fat redistribution did not have increased 10-year CHD risk compared with matched controls Adapted from Hadigan C et al. Clin Infect Dis. 2003;36:909-916. 29

  30. Body-fat Abnormalities in Patients with HIV 1 Khunnawat C et al. Am J Cardiol. 2008;102:635-642. 2 Nachega JB et al. Curr HIV/AIDS Rep. 2009;6:121-129. • Lipodystrophy (fat redistribution) reported in large numbers of patients with HIV1 • Proportion of affected patients is greater in those receiving certain ARVs • Prevalence rates of lipodystrophy vary between 11% and 83% in cross-sectional studies • Lipodystrophy may be a clinical symptom of insulin resistance, diabetes, and increased CV risk1 • Lipodystrophy may be associated with decreased quality of life and poorer ART adherence in affected patients2 30

  31. Lichenstein et al. CID 2010; 51(4):435-447 • Looked at MI, non-embolic or hemorrhagic stroke, CAD, angina and peripheral arterial disease • Assessed the association of latest CD4 count and the CV event • CD4 <350 had a hazard ratio of 1.58 • Traditional CV risk factors and a CD4 count <500 were associated with a greater risk than any cumulative risk of any ARV class or individual drug

  32. Remaining Questions: • Is there truly a risk of increased incidence of MI in HIV infection that can be separated from background demographics? • If there is an increased risk, what is it about HIV or immune dysfunction that drives the risk? • Do potential ART related toxicities influence the incidence of MI?

  33. Freiberg,MS et al JAMA Intern Med March 2013 • Looked at MI only in men 2003 to 2009 • 82,459 participants with 33.2% being HIV positive • They were matched not only by traditional risk factors but by similar demographic and geographic backgrounds • They determined that the HIV population carried about a 50% increase in risk for MI and that the Framingham risk assessment was likely to underestimate the true risk in the HIV population

  34. D:A:D Study: Actual vs Predicted MI Rates in Patients with HIV Based on Framingham CHD Risk 8 7 6 Observed rates 5 Best estimate of predicted rate Rates Per 1000 Person-years 4 3 2 1 0 No <1 year 1-2 years 2-3 years 3-4 years 4+ years Duration of ART Schambelan M et al. Circulation. 2008;1182:e48-e53. 34

  35. IDSA Guidelines: Screening for CVD Risk and Metabolic Abnormalities in Patients with HIV HIVMA, HIV Medicine Association; IDSA, Infectious Disease Society of America. Aberg JA et al. Clin Infect Dis. 2009;49:651-681. • All patients should be assessed for CVD risk • Those with 2 risk factors should be further evaluated and managed according to the HIVMA and NCEP guidelines • All patients should be encouraged to stop smoking regardless of CVD risk, and HTN and diabetes mellitus should be managed as appropriate • A fasting glucose level and a fasting lipid profile should be obtained from all patients upon initiation of care and every 6-12 months thereafter • Consider testing 1-3 months after starting or modifying ART • Hemoglobin A1c level should be obtained every 6 months in patients with diabetes mellitus 35

  36. Why Is There an Increased Risk for Myocardial Infarction? • Is it the dyslipidemia mainly characterized by a low HDL and increased triglyceridemia? • Is it the chronic inflammation associated with years of viral replication before the disease is treated? • Is it due to an altered immune response that persists despite viral control? • Do our current anti-retroviral medications contribute in ways we have not yet appreciated? • Do the interventions we employ to decrease risk in HIV negative people work in HIV infected people? • What about women?

  37. D:A:D Study: Reduction in the Incidence of MI and CVD with Smoking Cessation in Patients with HIV IRR of CVD and Smoking Status IRR of MI and Smoking Status 5 5 2.5 2.5 IRR IRR 0.5 0.5 Stopped smoking during follow-up: Never smoked Previous smoker <1 year 2-3 years Current smoker 1-2 years >3 years IRR, incident rate ratio. Petoumenos K et al. HIV Med. 2011;12:412-421. • IRR (95% CI) vs never smoked: • MI: 3.73 (2.46, 5.64); CHD: 2.93 (2.07, 4.14); CVD: 2.32 (1.69, 3.18) within the first year of smoking cessation • MI: 2.07 (1.19, 3.63); CHD: 1.83 (1.16, 2.89); CVD: 1.49 (0.99, 2.24) after >3 years of smoking cessation 37

  38. Kaiser Permanentea: Response to Lipid-lowering Therapy in HIV+ Patients vs HIV- Controls Adjusted Percentage Changes in LDL-C and TG Levels Within 12 Months of Lipid-lowering Therapy 0 Any Lipid-lowering Therapy Any Lipid-lowering Therapy Any Statin -10 HIV+ HIV- HIV+ HIV- HIV+ HIV- -20 -41.2(P <.001) -30 -19.9(reference) Change in LDL-C Level, % Change in TG Level, % -25.6(P = .001) -19.2(P = .38) -40 0 -28.3(reference) -50 -52.1(reference) -10 -60 -20 HIV-infected patients (n = 616) HIV-infected patients (n = 213) -70 HIV-uninfected patients (n = 5451) HIV-uninfected patients (n = 1490) -30 Results are based on linear regression with adjustment for age, sex, year, lipid-lowering therapy class, months of follow-up, baseline LDL cholesterol and TG levels, number of coronary disease risk factors, past coronary disease or diabetes diagnoses, and hepatitis B or C infection. Model for any statin use is also adjusted for dose-equivalents of different individual statins and concomitant use of other lipid-lowering therapy classes. -40 a A retrospective cohort study to compare the effectiveness and safety of lipid-lowering therapy in patients with and without HIV infection in an integrated health care delivery system (1996-2005). N = 829 HIV+ patients and 6941 HIV- patients HIV infection beginning lipid-lowering therapy for elevated LDL-C or TG levels. LDL-C, low-density lipoprotein cholesterol. Silverberg M et al. Ann Intern Med. 2009;150:301-313. 38

  39. A5152sa: Viral Suppression Associated with Improved Endothelial Function 10 5 Change in FMD from Baseline to Week 24, % -0 -5 All Subjects PI-sparing NNRTI-sparing NRTI-sparing a The ACTG (AIDS Clinical Trials Group) study 5152s is a substudy of ACTG 5142, a prospective, multicenter, randomized, clinical trial that investigated time to virologic failure in ART‐naive subjects randomly assigned to receive 1 of 3 ART‐sparing regimens (N = 82). FMD, brachial-artery flow-mediated dilation; NNRTI, nonnucleoside reverse transcriptase inhibitor; NRTI, nucleoside reverse transcriptase inhibitor; PI, protease inhibitor. • HIV infection itself affects endothelial function • Baseline FMD: 3.68% • FMD improved during ART: • At Week 4: +0.74% (P ≤.01) • At Week 24: +1.48 (P <.001) • No significant differences between treatment arms • No consistent significant correlations between changes in FMD and changes in any lipids or glycemic parameter • Improvement in FMD significantly correlated with decrease in HIV-1 RNA at Week 24 • No relationship with baseline VL Torriani F et al. J Am Coll Cardiol. 2008;12;52:569-576. 39

  40. Factors That May Affect CV Risk in Patients with HIV Currier J et al. Circulation. 2008;118:e29-e35. 40

  41. Factors Potentially Contributing to Morbidity and Mortality in Patients with HIV • Residual viral replication • Persistent virus expression (in lymph nodes) • Loss of immunoregulatory cells • Collagen deposition • Microbial translocation • High pathogen load (CMV, HBV, HCV) • Thymic dysfunction Suboptimal CD4 gains Residual inflammation Hypercoagulation Non-AIDS—related events and premature mortality HBV, hepatitis B virus; HCV, hepatitis C virus; CMV, cytomegalovirus. Deeks SG. Topics HIV Med. 2009;17:118-123. 41

  42. Similarities Between HIV-associated and Age-associated Immunologic Changes Deeks SG. Annu Rev Med. 2011;62:141-155. 42

  43. Similarities Between HIV-associated and Age-associated Immunologic Changes (cont’d) Deeks SG. Annu Rev Med. 2011;62:141-155. 43

  44. Model: Effect of HIV Infection on Inflammation and Immunosenescence Untreated HIV Infection Thymic dysfunction and loss of regenerative potential Loss of gut mucosal integrity and microbial translocation Loss of immuno-regulatory cells CMV replication HIV replication ART Decreased but persistent (1) defects in T-cell regenerative potential; (2) loss of immunoregulatory function; (3) CMV and other co-pathogen levels; (4) and microbial translocation Chronic inflammation T-cell maturation Progenitor-cell exhaustion T-cell dysfunction Immunosenescence and clinical disease Deeks SG. Annu Rev Med. 2011;62:141-155. 44

  45. Summary: HIV, CVD, and Metabolic Complications • CV risk factors, including metabolic disorders, and CVD are highly prevalent in patients with HIV • Etiology of CVD and metabolic complications is multifactorial • Traditional risk factors • HIV infection • ART • Clinicians caring for patients with HIV should be cognizant of the increased risk of CVD and metabolic disorders in this patient population and manage them appropriately 45

  46. Summary: HIV and Aging • The number of HIV-infected persons 50 years and older is increasing • Morbidity associated with normal aging may be enhanced by HIV infection and/or ART • Clinicians should be aware of the challenges associated with management of an older patient with HIV • Older patients may present with more advanced HIV disease • Immunologic response in aging patients is less robust than in younger patients • Primary health care considerations in patients with HIV should include screening and management of age-related comorbidities 46

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