Long-Term Cardiovascular Benefits and Neurocognitive Risks of Statin Therapy in People Living With HIV: A Global Real-World Cohort Study

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Statins are recommended for primary and secondary prevention of ASCVD; however, their potential impact on cognitive function among PLWH is uncertain. We evaluated the association between statin use and incident cognitive impairment in a large, real-world cohort of adults with HIV. Methods Using the TriNetX Global Collaborative Network, we identified adults (≥ 18 years) with HIV and comorbidities and stratified them into two cohorts based on statin use versus no statin use. Individuals with pre-existing dementia, substance use disorders, major psychiatric illness, or use of CNS-active antipsychotics were excluded. Outcomes included cognitive impairment, major adverse cardiovascular events (MACE: myocardial infarction, stroke, or death), all-cause mortality, hospital utilization, myopathy, and transaminitis. Propensity score matching (1:1) balanced demographics, comorbidities, medications, and laboratory values. Cox proportional-hazards models estimated hazard ratios (HRs) with 95% confidence intervals (CIs); p < 0.05 was considered statistically significant. Results After matching, 38,292 individuals were analyzed (mean age 54 ± 13 years; 24% female, 76% White). Cognitive impairment occurred in 9.1% of statin users versus 6.6% of non-users (HR 1.20, 95% CI:1.11–1.29; p < 0.001). All-cause mortality was lower among statin users (5.3% vs 8.0%; HR 0.58, 95% CI: 0.53–0.63; p < 0.001). MACE was lower among statin users (7.9% vs 8.7%; HR 0.79, 95% CI: 0.74–0.85; p < 0.001). Statin use was associated with higher risks of myopathy (2.9% vs 2.0%; HR 1.25, 95% CI: 1.09–1.43; p = 0.001), transaminitis (12.4% vs 9.2%; HR 1.20, 95% CI:1.12–1.28; p < 0.001), and hospital utilization (2.2% vs 1.7%; HR 1.12, 95% CI:1.05–1.20; p < 0.001). Appendicitis (negative control) was similar between groups (0.2% each; HR 0.86, 95% CI:0.53–1.38; p = 0.52). Conclusions In this large, real-world cohort of PLWH, statin use was associated with lower all-cause mortality and MACE but a modestly increased risk of cognitive impairment (11–29%) over ten years. Statin users had greater comorbidity burden, highlighting the need to balance cardiovascular benefits against potential neurocognitive risks. Health sciences/Cardiology Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Health sciences/Neurology Health sciences/Risk factors HIV statins cognitive impairment mortality stroke TriNetX real-world evidence Figures Figure 1 Figure 2 Background With the advent of effective combination antiretroviral therapy (ART), people living with HIV (PLWH) are living longer to experience chronic age-related comorbidities( 1 – 3 ). By 2050, PLWH are projected to face rising non-AIDS-related deaths due to ageing, highlighting a shift in health priorities from AIDS to age-related chronic conditions( 4 ). Among these chronic conditions, cardiometabolic disorders are major contributors to morbidity and mortality in the modern HIV era( 5 – 7 ). The global burden of HIV-associated cardiovascular disease has tripled over the past two decades, with people living with HIV being twice as likely to develop cardiovascular disease. Persistent systemic inflammation, immune activation, endothelial dysfunction, and dyslipidemia remain hallmarks of HIV infection despite viral suppression under suppressive ART( 6 , 8 ). These processes accelerate vascular aging and predispose PLWH to atherosclerosis-related cerebrovascular disease( 5 ). Lipid lowering agents such as statins, 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, are widely recommended for primary and secondary prevention of atherosclerotic cardiovascular disease (ASCVD) ( 9 – 15 ). PLWH are twice as likely to develop ASCVD, and the global burden of HIV-associated ASCVD has tripled over the past two decades ( 16 ). Fortunately, the use of statins by PLWH reduces risk for major adverse cardiovascular events( 17 ). Beyond their lipid-lowering effects, statins reduce inflammatory biomarkers such as C-reactive protein, soluble CD14, and interleukin-6 among PLWH( 13 , 18 – 21 ). Based on these benefits, the Infectious Diseases Society of America in 2024 recommended statins for PLWH older than 40 years regardless of ASCVD risk or lipid levels unless there is a contraindication to statin use( 22 ). Notably, the brain contains approximately 25% of the body’s total cholesterol, and myelin is composed of about 85% cholesterol( 23 , 24 ). Because nearly all brain cholesterol is synthesized locally, inhibition of cholesterol biosynthesis within the central nervous system impairs neuronal membrane integrity, synaptic plasticity, and myelin repair. These processes are already particularly vulnerable with ageing and HIV infection( 25 – 28 ). Clinically, such neuronal disruptions may manifest as cognitive decline, motor dysfunction, memory impairment, and/or mood disorders. However, the impact of statin therapy on neurocognition, particularly in PLWH, in the real world remains poorly defined. To bridge this knowledge gap, a comprehensive assessment of the impact of statin therapy on neurocognitive outcomes and survival among PLWH in a non-clinical-trial-controlled setting is warranted. Leveraging the TriNetX Global Collaborative Network( 29 ), which aggregates longitudinal electronic health record data from diverse healthcare systems worldwide, we examined whether statin use among PLWH with ASCVD comorbidities is associated with differences in the risk of cognitive impairment, stroke or transient ischemic attack (TIA), and all-cause mortality. This real-world study aimed to clarify the balance between potential neuroprotective and neurotoxic effects of statins within a population already vulnerable to both metabolic and neuroinflammatory injury. Results Cohort characteristics A total of 94,200 adults living with HIV met inclusion criteria across the TriNetX Global Collaborative Network. After applying all exclusion criteria and performing 1:1 propensity score matching, 38,292 individuals (19,146 statin users and 19,146 non-users) were included in the final analytic cohort (Fig. 1 ) . The mean ± SD age at index was 53.5 ± 11 years; 23.3% were female, and 41.5% identified as Black or African American. Before propensity score matching, statin users were older (55.2 ± 11 vs. 47.9 ± 13.2 years) and exhibited a higher burden of cardiometabolic comorbidities (hypertension 34.6% vs 10.3%; diabetes 16.9% vs 4.0%; ischemic heart disease 9.9% vs 1.6%; dyslipidemia 35.6% vs 4.2%, obesity 7.6% vs 3.5%, heart failure 4.9% vs 1.5% chronic kidney disease 10% vs 2.8%, all p < 0.001) than non-statin users. Following propensity score matching across demographics, comorbidities, medications, and laboratory indices, balance was achieved for all variables with standardized mean differences < 0.1. Matched cohorts had comparable distributions of age (53.9 ± 11 vs. 54.6 ± 12.4 years), sex (23.8% vs 23.3% female), race (Black 40.7% vs 38.8%), diabetes (10.3% vs 9.1%), hypertension (22.1% vs 20.5%), dyslipidemia (14.3% vs 12.9%) and mean BMI (29.0 ± 6.8 vs 28.4 ± 6.8 kg/m²). Mean hemoglobin, glucose, and liver enzyme values were similar across groups, confirming adequate baseline comparability (Table 1 ). Table 1 Baseline characteristic before and after propensity score matching. Before propensity score matching After propensity score matching Characteristic Statin Use N = 29,886 No Statin Use N = 64,314 SMD Statin Use N = 19,146 No Statin Use N = 19,146 SMD Demographics Age, years 55.2 ± 11.0 47.9 ± 13.2 0.61 53.9 ± 11.0 54.6 ± 12.4 0.06 Female 6,714 (22.7%) 16,914 (27.8%) 0.12 4,560 (23.8%) 4,454 (23.3%) 0.01 Male 22,913 (77.3%) 43,941 (72.2%) 0.12 14,580 (76.2%) 14,685 (76.7%) 0.01 White 12,254 (41.3%) 20,987 (34.5%) 0.14 7,603 (39.7%) 7,945 (41.5%) 0.04 Black or African American 11,699 (39.5%) 27,344 (44.9%) 0.11 7,794 (40.7%) 7,431 (38.8%) 0.04 Comorbidities Hypertension 10,264 (34.6%) 6,247 (10.3%) 0.61 4,225 (22.1%) 3,919 (20.5%) 0.04 Diabetes mellitus 5,007 (16.9%) 2,457 (4.0%) 0.43 1,973 (10.3%) 1,738 (9.1%) 0.04 Dyslipidemia 10,559 (35.6% 2,570 (4.2%) 0.86 2,745 (14.3%) 2,471 (12.9%) 0.04 Ischemic heart disease 2,938 (9.9%) 981 (1.6%) 0.36 1,011 (5.3%) 826 (4.3%) 0.05 Heart failure 1,449 (4.9%) 931 (1.5%) 0.19 608 (3.2%) 554 (2.9%) 0.02 Chronic kidney disease 2,953 (10%) 1,688 (2.8%) 0.30 1,200 (6.3%) 1,121 (5.9%) 0.02 Liver disease 355 (1.1%) 522 (0.9%) 0.03 189 (1.0%) 180 (0.9%) 0.01 COPD 996 (3.4%) 906 (1.5%) 0.12 489 (2.6%) 457 (2.4%) 0.01 Depression 1,689 (5.7%) 2,236 (3.7%) 0.10 827 (4.3%) 796 (4.2%) 0.01 Vitamin D deficiency 1,982 (6.7%) 1,712 (2.8%) 0.18 823 (4.3%) 797 (4.2%) 0.01 Hypothyroidism 870 (2.9%) 697 (1.1%) 0.13 381 (2.0%) 358 (1.9%) 0.01 Obesity/Overweight 2,250 (7.6%) 2,158 (3.5%) 0.18 984 (5.1%) 927 (4.8%) 0.01 Alcohol-related disorders 65 (0.2%) 415 (0.7%) 0.07 48 (0.3%) 49 (0.3%) 0.00 Nicotine dependence 1,068 (3.6%) 1,486 (2.4%) 0.07 531 (2.8%) 498 (2.6%) 0.01 Vital signs and weight assessment Systolic BP (mmHg) 130.9 ± 19.1 129.8 ± 19.1 0.06 130.6 ± 19.0 130.4 ± 19.7 0.01 Diastolic BP (mmHg) 79.4 ± 12.4 80.0 ± 12.6 0.05 80.0 ± 12.5 79.3 ± 12.5 0.06 Heart rate (/min) 79.0 ± 14.7 81.0 ± 15.2 0.14 79.4 ± 14.8 79.8 ± 14.9 0.02 Body mass index (kg/m²) 28.9 ± 6.6 28.6 ± 7.6 0.05 29.0 ± 6.8 28.4 ± 6.8 0.09 Medications Ezetimibe 267 (0.9%) 118 (0.2%) 0.10 92 (0.5%) 93 (0.5%) 0.00 Fibrates 634 (2.1%) 284 (0.5%) 0.15 225 (1.2%) 197 (1.0%) 0.01 Antihypertensives 1,873 (6.3%) 1,743 (2.9%) 0.17 945 (4.9%) 902 (4.7%) 0.01 Oral hypoglycemics 2,451 (8.3%) 1,200 (2.0%) 0.29 999 (5.2%) 911 (4.8%) 0.02 Antiplatelets 2,809 (9.5%) 1,700 (2.8%) 0.28 1,242 (6.5%) 1,114 (5.8%) 0.03 Antiretroviral therapy Protease inhibitors 3,092 (10.4%) 3,270 (5.4%) 0.19 1,612 (8.4%) 1,649 (8.6%) 0.01 Integrase inhibitors 6,310 (21.3%) 6,239 (10.2%) 0.31 3,207 (16.8%) 3,294 (17.2%) 0.01 NRTIs 12,691 (42.8%) 13,849 (22.7%) 0.44 6,697 (35.0%) 6,988 (36.5%) 0.03 Laboratory results Hemoglobin (g/dL) 13.9 ± 2.2 13.4 ± 2.4 0.19 13.9 ± 2.2 13.5 ± 2.3 0.14 Platelet count (×10⁹/L) 232.8 ± 75.6 234.2 ± 86 0.02 234.9 ± 75.2 230.7 ± 83.2 0.05 Leukocytes (WBC ×10⁹/L) 6.4 ± 2.0 6.6 ± 2.2 0.09 6.5 ± 2.1 6.5 ± 2.2 0.01 Hemoglobin A1c (%) 6.5 ± 1.8 6.0 ± 1.6 0.27 6.4 ± 1.8 6.1 ± 1.5 0.18 Glucose (mg/dL) 115.4 ± 57.9 104.9 ± 46.4 0.20 112.6 ± 55.4 108.1 ± 47.3 0.07 TSH (mIU/L) 3.2 ± 22.9 3.8 ± 31.7 0.02 3.4 ± 22 4.4 ± 36.5 0.03 Lipid profile Total cholesterol (mg/dL) 200.4 ± 53.8 180.7 ± 47.5 0.35 203.5 ± 53.7 180.5 ± 45.8 0.46 LDL cholesterol (mg/dL) 121.9 ± 44.8 106.6 ± 37.7 0.37 125.4 ± 44.5 105.3 ± 37.1 0.49 HDL cholesterol (mg/dL) 45.6 ± 16.0 44.2 ± 18.3 0.08 45.8 ± 15.9 44.7 ± 17.8 0.06 Triglycerides (mg/dL) 184.7 ± 167.4 164.9 ± 136.1 0.13 183.1 ± 154.7 163.1 ± 125.5 0.14 HIV disease specific labs Plasma HIV RNA (log copies/mL) 2.4 ± 1.4 4.0 ± 40.7 0.06 2.4 ± 1.5 3.5 ± 19.9 0.08 CD4 count (cells/µL) 662.6 ± 348.9 581.0 ± 380.3 0.22 675.1 ± 357.9 598.9 ± 394.6 0.20 Renal function and serum electrolyte profile Creatinine (mg/dL) 1.8 ± 6.9 1.6 ± 6.3 0.02 1.8 ± 7.2 1.6 ± 5.0 0.04 Blood urea nitrogen (mg/dL) 18.1 ± 12.1 15.8 ± 10.1 0.21 17.4 ± 11.9 17.1 ± 10.9 0.03 Sodium (mmol/L) 138.7 ± 3.7 138.5 ± 3.6 0.06 138.7 ± 3.8 138.7 ± 3.3 0.00 Potassium (mmol/L) 4.2 ± 0.5 4.1 ± 0.5 0.10 4.2 ± 0.5 4.2 ± 0.5 0.02 eGFR (mL/min/1.73m²) 73.2 ± 27.7 83.1 ± 31.7 0.33 75.1 ± 28.0 77.2 ± 29.7 0.07 Nutritional and Micronutrient Markers Folate (ng/mL) 11.8 ± 6.6 11.1 ± 6.8 0.11 11.7 ± 6.9 11.5 ± 7.7 0.03 Vitamin B12 (pg/mL) 643.1 ± 761.8 724.8 ± 1530.2 0.07 641.2 ± 934.8 748 ± 1082.1 0.08 Liver function AST (U/L) 28.6 ± 34.1 35.8 ± 89.4 0.11 28.6 ± 29.4 34.4 ± 108 0.07 ALT (U/L) 30.3 ± 41.9 35.1 ± 78.1 0.08 30.3 ± 37.1 32.9 ± 77.9 0.04 Albumin (g/dL) 4.2 ± 0.6 4.0 ± 0.7 0.21 4.2 ± 0.6 4.0 ± 0.6 0.21 Bilirubin (mg/dL) 0.8 ± 3 0.8 ± 3 0.03 0.8 ± 3.1 0.8 ± 2.7 0.01 Abbreviations: ALT, alanine aminotransferase; ALP, alkaline phosphatase; AST, aspartate aminotransferase; HbA1c, hemoglobin A1c; BP, blood pressure; CD4, cluster of differentiation 4; CD8, cluster of differentiation 8; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; Hb, hemoglobin; HDL, high density lipoprotein; HIV RNA, human immunodeficiency virus ribonucleic acid; HR, heart rate; LDL, low density lipoprotein; NRTIs, nucleoside/nucleotide reverse transcriptase inhibitors; PI, protease inhibitors; PP, pulse pressure; SMD, standardized mean difference; SBP, systolic blood pressure; TSH, thyroid stimulating hormone; T4, thyroxine, WBC, white blood cell count. Values are mean ± standard deviation (SD) or n (%). SMD derived from difference in means or proportions divided by pooled standard deviation. Primary outcome: Cognitive impairment At ten years of follow-up, the cumulative incidence of cognitive impairment was 9.1% (1,494/16,457) among individuals on statins compared with 6.6% (1,112/16,734) among individuals not on statins corresponding to an absolute risk difference of 2.4% (95% CI: 1.9–3.0%) excluding individuals with cognitive impairment diagnoses prior to statin therapy. The hazard of incident cognitive impairment was 1.2 (95% CI: 1.11–1.29) consistent with a 20% higher cumulative occurrence of cognitive impairment with statin use over ten years. At ten years, cognitive-impairment-free survival was 79.3% for statin users versus 83.8% for non-statin-users, log rank test p value < 0.001 (Table 2 ). Table 2 Outcomes over ten years measured after propensity score matching. Outcome Statin n/N (%) No Statin n/N (%) HR (95% CI) p value Primary Cognitive impairment 1,494 / 16,457 (9.1%) 1,112/ 16,734 (6.6%) 1.20 (1.11–1.29) < 0.001 Secondary All-cause mortality 1,019 / 19,094 (5.3%) 1,519 / 19,021 (8.0%) 0.58 (0.53–0.63) < 0.001 Major adverse cardiovascular events (MACE) 1,362 / 17,210 (7.9%) 1,579 / 18,169 (8.7%) 0.79 (0.74–0.85) 3x ULN 1,824 / 14,765 (12.4%) 1,424 / 15,512 (9.2%) 1.20 (1.12–1.28) < 0.001 Hospital utilization (ED + inpatient) 2,130 / 9,895 (21.5%) 1,726 / 10,228 (16.9%) 1.12 (1.05–1.20) < 0.001 Acute appendicitis (Negative control) 34 / 19,062 (0.2%) 34 / 19,062 (0.2%) 0.86 (0.53–1.38) 0.524 HR = hazard ratio; CI = confidence interval; ED = emergency department; ULN, upper limit of normal. Values are n/N (%). Hazard ratios are derived from Cox proportional hazard model, and p values are by log rank testing. Denominators (N) vary by outcome based on available follow‑up and exclusion of prior events before the index point of starting statin therapy. Secondary outcomes: All-cause mortality At ten years, cumulative incidence of all-cause mortality was 5.3% (1,019/19,094) among statin users vs 8.0% (1,519/19,021) among non-statin users representing an absolute risk reduction of 2.6% (95% CI: 2.1–3.1%, p < 0.001) with statin therapy. Kaplan-Meier survival curves demonstrated a clear and sustained survival advantage among statin users throughout the 10-year follow-up period. Hazard for mortality from any cause was 0.58 (95% CI: 0.53–0.63), corresponding to a 42% (95% CI: 37–47%) lower risk of mortality among statin users compared with matched non-statin users (Fig. 2 ). Major adverse cardiovascular events (MACE) The cumulative incidence of MACE (composite of myocardial infarction, stroke or death) was 7.9% (1,362/17,210) among statin users versus 8.7% (1,579/18,169) among non-statin users (RR 0.91, 95% CI: 0.85–0.98). The hazard ratio of MACE was 0.79 (95% CI: 0.74–0.85) consistent with a 21% lower risk among statin users. Myopathy Over ten years, the cumulative incidence of myopathy, defined by ICD-10 code M79.1, was 2.9% (532/18,309) among statin users versus 2.0% (370/18,497) among non-users, resulting in an absolute risk increase of 0.9% (95% CI: 0.6–1.2). The Kaplan-Meier curves for myopathy showed consistent separation over time, with the log-rank test demonstrating a statistically significant difference (p = 0.001). The HR for myopathy was 1.25 (95% CI: 1.09–1.43), indicating a 25% higher risk among statin users. Transaminitis (Elevated liver enzymes) At ten years, the cumulative incidence of elevated liver enzymes was 12.0% (1,824/14,765) in statin users compared with 9.0% (1,424/15,512) in non-statin users, an absolute increase of 3.2% (95% CI: 2.5–3.9). The Kaplan-Meier survival analysis revealed progressive divergence in liver-enzyme-free survival between cohorts (p < 0.001). The HR for transaminitis was 1.20 (95% CI: 1.12–1.28), consistent with a 20% greater risk among statin users. Hospital utilization Hospital utilization defined as the composite of emergency visits and inpatient admission occurred in 21.5% (2,130/9,895) of statin users compared with 16.9% (1,726/10,228) of non-users yielding an absolute risk increase of 4.7% (95% CI: 3.6–5.7. The hazard ratio of hospital utilization was 1.12 (95% CI: 1.05–1.2), corresponding to a 12% increased risk of healthcare encounters among statin users versus non-statin users. Negative control outcome Appendicitis, included as a negative control outcome not biologically associated with statin exposure, occurred in 0.2% (34/19,062) of both groups. Over a ten-year follow up period, there was no statistically significant difference in cumulative incidence between statin users and non-statin users (HR 0.86 [95% CI: 0.53–1.38; p = 0.524]), supporting the absence of unmeasured bias or residual confounding in our analytic model. Discussion In this large real-world analysis of over 38,000 adults living with HIV, statin use was associated with benefits and risks over ten years of follow-up. Statin use was associated with significant cardiovascular and survival benefits, with a 44% lower risk of all-cause mortality, and a 21% reduction in major adverse cardiovascular events. However, statin use was associated with a 20% increase in likelihood of cognitive impairment than non-statin use. Consistent with known pharmacologic toxicities, statin use was associated with a 20% increased risk for statin induced myopathy, and 25% increased risk for elevation of liver enzymes more than three times the upper limit of normal. Collectively, our findings highlight the double sword nature of statin therapy; on the one hand, statins offer cardioprotective and survival benefits while on the other hand individuals on statins are likely to experience cognitive impairment, myopathy and elevation of liver enzymes. Our findings are testament to the real-world clinical practice, where patient requiring statin therapy often present with multiple comorbidities, most of which are cardiometabolic in nature. For instance, in our study, before propensity score matching, PLWH on statins were older and exhibited a statistically significant higher burden of cardiometabolic comorbidities i.e., markedly higher rates of hypertension, diabetes, dyslipidemia, ischemic heart disease, obesity, heart failure, and chronic kidney disease; compared with individuals not on statins. This is consistent with the clinical profile of individuals at elevated ASCVD risk for whom lipid-lowering therapy is clinically indicated as per various medical society guidelines( 9 – 15 ). However, after rigorous propensity score matching across more than 70 demographic, clinical, medication, and laboratory covariates, balance was achieved for all baseline variables, with standardized mean differences below 0.1. The matched cohorts were comparable in age, sex distribution, race, metabolic comorbidities, and key laboratory parameters including hemoglobin, glucose, and liver enzymes. This high degree of balance supports that subsequent outcome differences likely reflect associations with statin exposure rather than baseline confounding. Furthermore, we included appendicitis as a negative control outcome, showing no significant difference between groups, supporting the internal validity of our analytic approach and mitigates concerns about residual confounding or systematic bias. Statins are well recognized for their anti-atherogenic, anti-inflammatory properties and protecting from ASCVD-associated mortality( 17 , 18 , 21 , 30 , 31 ). In HIV, chronic immune activation, dyslipidemia, and endothelial dysfunction accelerate atherosclerosis and microvascular/endothelial injury. By lowering LDL cholesterol and dampening systemic inflammation, statins plausibly contribute to the overall survival advantage we observed( 17 , 21 , 32 ). However, cholesterol plays a critical role in neuronal membrane integrity, synaptic vesicle formation, and myelin maintenance( 24 ). Excessive inhibition of central cholesterol synthesis or altered transport across the blood brain barrier may impair neuronal repair and neurotransmission( 33 ). However, multiple prior studies report no association of statins with cognitive impairment( 34 ). Notably, the statin doses in some of these studies were low, not the current recommended high-intensity statin doses for individuals with high ASCVD risk. Studies in the general population have produced inconsistent findings about statin use and cognition. Some report cognitive protection with statin use( 35 – 37 ). Whereas other studies report potential cognitive impairment, especially with lipophilic agents( 38 – 40 ). However, evidence within HIV cohorts has been scarce. The REPRIEVE trial, a randomized, placebo-controlled study of pitavastatin in more than 7,700 PLWH, reported a 35% reduction in major cardiovascular events but did not assess neurocognitive outcomes( 17 ). In contrast, our analysis with far larger sample size and longer follow-up identified statistically significant associations with cognitive decline, suggesting that prolonged exposure or drug-drug interactions unique to HIV care may underlie these discrepancies. These results argue for careful risk-benefit assessment when initiating statins for PLWH. For patients with established cardiovascular disease or high ASCVD risk, statins remain essential, given their pronounced mortality reduction. Yet clinicians should maintain vigilance for new-onset neurocognitive symptoms particularly among older adults, those with metabolic co-morbidities, or individuals on polypharmacy involving CNS-active or ART agents. Routine cognitive screening and periodic liver and muscle enzyme monitoring may improve safety. Where feasible, selection of statins with minimal antiretroviral interactions (e.g., rosuvastatin, pitavastatin, pravastatin) or statins with lower CNS penetration to preserve central cholesterol synthesis (e.g., rosuvastatin and pravastatin) may mitigate risk. Growing pharmacovigilance evidence from the U.S. Food and Drug Administration’s Adverse Event Reporting System (FAERS) supports the neurocognitive safety signal we observed. In a large FAERS analysis of 6,959 neurocognitive disorder reports, both lipophilic and hydrophilic statins including atorvastatin, simvastatin, pravastatin, rosuvastatin, lovastatin, fluvastatin, and pitavastatin demonstrated significant disproportionality signals, with higher reporting odds ratios among adults older than 65 years( 41 ). A complementary FAERS and Mendelian randomization study further showed that atorvastatin was associated with amnesia and memory impairment and provided genetic evidence suggesting a potential causal pathway partially mediated through mitochondrial dysfunction( 42 ). Together, these real-world and genetic data reinforce the plausibility of our observed association between statin use and cognitive impairment among PLWH. Our study possesses several notable strengths. First, it leveraged a large, diverse, and contemporary global cohort of over 38,000 propensity-score-matched individuals across 162 healthcare organizations, enhancing statistical power and external generalizability. Second, the use of federated electronic health record data reflecting authentic real-world/pragmatic clinical practice encompassing heterogeneous comorbidity profiles beyond the constraints of stringent inclusion criteria for randomized clinical trials. Third, rigorous confounding control was achieved through propensity score matching on more than seventy demographic, clinical, and laboratory variables resulting in near-perfect covariate balance. Forth, multiple complementary analyses including risk ratios, odds ratios, and time-to-event hazard models that yielded concordant results. Fifth, we incorporated a comprehensive set of outcomes encompassing both neurological and safety endpoints, allowing a balanced evaluation of potential benefits and harms of statin therapy. Finally, the inclusion of a biologically unrelated negative control outcome (i.e., appendicitis) that showed no significant difference between groups serves as an internal validity check, supporting robustness of the analytical framework and reducing concern of unmeasured/residual confounding. Using federated databases comes with benefits and limitations( 43 ). We note a couple of limitations that merit consideration when interpreting our findings. First the observational design precludes definitive causal inference, and despite extensive propensity score matching, residual confounding may persist. For examples, individuals prescribed with statins had greater baseline cardiovascular risk and had more hospital utilization potentially influencing outcome detection and reporting than individuals not on statins. Second, diagnostic misclassification is possible, as reliance on ICD-10 codes may under- or over-estimate cognitive impairment, especially for subtle or undiagnosed neurocognitive disorders. Third, TriNetX captures prescription records but not patient adherence, statin potency, or treatment duration limiting exposure precision. Forth, unmeasured confounders including lipid profiles, inflammatory biomarkers, ART class, and nadir CD4 counts were not uniformly available across sites. Fifth, outcome heterogeneity exists because “Cognitive impairment” encompasses multiple ICD codes, and detailed neuropsychological test data were unavailable. Sixth, the associations we report do not imply causality. In this global, real-world study of adults living with HIV, statin therapy was associated with significant reduction in mortality, MACE, and stroke but higher risks of cognitive impairment. These findings highlight the dual biological and clinical complexity of lipid-lowering therapy in chronic HIV infection. Future prospective studies, ideally randomized or mechanistically anchored, are needed to delineate which statin types, doses, and patient subgroups derive maximal net benefit. Meanwhile, clinicians should personalize statin prescribing by integrating cardiovascular risk, ART regimen, age, and neurocognitive status into shared decision-making. Methods Study Design and Setting We conducted a retrospective, propensity-matched cohort study using real-world data from the TriNetX Global Collaborative Network, a federated electronic health record (EHR) platform that integrates de-identified patient-level data from 162 healthcare organizations (HCOs) across North America, Europe, the Middle East, Asia, and South America( 29 ). The network includes data from academic medical centers, community hospitals, and integrated delivery systems, capturing demographics, diagnoses, procedures, medications, vital signs, laboratory results, and mortality outcomes from over 200 million patients worldwide. The study was performed entirely within the secure TriNetX analytics environment on November 7, 2025. All data were de-identified at source in compliance with the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation. The TriNetX platform operates under a business associate agreement with contributing organizations and does not permit re-identification. Only aggregated, de-identified data were accessed; therefore, the analysis was exempt from institutional review board oversight and did not require individual informed consent. Study Population and Cohort Definition We included adults (≥ 18 years) with a confirmed diagnosis of HIV infection (ICD-10-CM code B20) and comorbidities including ischemic heart disease (ICD-10-CM code I25) or hypertension (ICD-10-CM code I10) or chronic kidney disease (ICD-10-CM code N18) or stroke/transient ischemic attack (ICD-10-CM code I63, G45) or chronic liver disease (ICD-10-CM code K74) or dyslipidemia (ICD-10-CM code E78), or diabetes mellitus (ICD-10-CM code E08-E13). We defined two mutually exclusive cohorts. Cohort 1 (statin users) included PLWH who initiated any statin (atorvastatin [RxNorm 83367], rosuvastatin [301542], simvastatin [36567], pravastatin [42463], lovastatin [6472], fluvastatin [41127], or pitavastatin [861634]) after the recorded HIV diagnosis. Cohort 2 (non-users) included PLWH with no documentation of any statin prescription during the entire observation period. The index date was defined as the date of first statin prescription for Cohort 1 and an equivalent matched date (based on time since HIV diagnosis) for Cohort 2. To minimize confounding by baseline neurological or psychiatric illness, we excluded patients with any diagnosis of; major psychiatric disorders or substance use disorders (ICD-10 F10–F19); dementia or neurodegenerative diseases including Alzheimer’s disease (G30), vascular dementia (F01), or other degenerative diseases of the nervous system (G31); post-viral fatigue syndromes (G93.3); and prior use of CNS-active medications such as phenothiazines (VA code CN701), other antipsychotics (CN709), CNS stimulants (CN800), or CNS medications not otherwise specified (CN900). This approach was consistent with TriNetX’s “exclude-prior-outcome” function, ensuring that all included participants were free of the study outcomes before cohort entry. Outcomes Our primary outcome was incident cognitive impairment, defined as a new diagnosis after index date using any of the following ICD-10-CM codes: R40-R46 (symptoms and signs involving cognition, perception, emotional state, and behavior); R41.89 (other cognitive symptoms); G31.84 (mild cognitive impairment); F06 (mental disorders due to known physiological conditions). Our secondary outcomes included all-cause mortality, stroke or transient ischemic attack (TIA), major adverse cardiovascular events (MACE), hospital utilization, myopathy, and elevated liver enzymes (transaminitis). All-cause mortality was identified using the TriNetX mortality flag (“Deceased”); stroke/TIA was identified by ICD-10 I63 (cerebral infarction) or G45 (transient cerebral ischemic attack and related syndromes). MACE was defined as a composite of acute myocardial infarction (ICD-10 I21), stroke (ICD-10 I63) and death (deceased). Hospital utilization was defined as a composite of emergency department (ED) visits and inpatient admissions identified using standardized HL7 visit-type ontologies within the TriNetX network: UMLS: HL7V3.0: Visit Type: EMER (Emergency Visit), ACUTE (Inpatient Acute), IMP (Inpatient Encounter), NONAC (Inpatient Non-acute), and OBSENC (Observation Encounter). Both ED and inpatient encounters were aggregated to represent overall healthcare utilization during follow-up. Statin-associated myopathy was identified by ICD-10 M79.1, elevated liver enzymes/transaminitis by ICD-10 R74.8 (abnormal levels of serum enzymes) or laboratory thresholds of alanine aminotransferase (TNX:9044) and aspartate aminotransferase (TNX:9047) > 60 U/L. A negative control outcome, appendicitis (ICD-10 code K35) was included as an outcome not known to be associated with statin use. Outcomes were evaluated beginning one day after the index date and followed ten years post index. Covariates and confounder adjustment Baseline covariates were measured at or prior to the index date and encompassed four major domains. Demographics: age at index date, sex (male, female), and race/ethnicity (White, Black or African American). Comorbidities: disorders of lipoprotein metabolism and other lipidemias (E78), diabetes mellitus (E10-E14), hypertensive diseases (I10-I15), ischemic heart disease (I20-I25), cerebral infarction due to unspecified occlusion or stenosis (I63.5), other peripheral vascular diseases (I73), chronic obstructive pulmonary disease (J44), chronic kidney disease (N18), liver diseases including fibrosis and cirrhosis (K74, K76), obesity (E66), heart failure (I50), late syphilis (A52), neurosyphilis (A52.1), alcohol-related disorders (F10), nicotine dependence (F17.2), other hypothyroidism (E03.8), vitamin D deficiency (E55), and depressive episode (F32). Medications: lipid-lowering and cardiometabolic agents including ezetimibe, fibrates, alirocumab, evolocumab, antihypertensives, oral hypoglycemics, and platelet aggregation inhibitors, as well as antiretroviral classes i.e., protease inhibitors, nucleoside/nucleotide reverse transcriptase inhibitors, and integrase inhibitors. Laboratory and vital parameters: serum total cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL), and very low density lipoprotein (VLDL) cholesterol; triglycerides; hemoglobin A1c; thyroid function (TSH, T4); vitamin B12; folate; liver indices (AST, ALT, bilirubin, albumin); renal indices (creatinine, blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), urine albumin); glucose; sodium; potassium; inflammatory markers i.e., c-reactive protein (CRP), erythrocyte sedimentation rate (ESR); hematologic indices (leucocytes, hemoglobin, platelets); body mass index (BMI), systolic and diastolic blood pressure, heart rate; and HIV-specific markers including CD3/CD4 counts and plasma or cerebrospinal fluid HIV-1 RNA viral load (quantitative and log-transformed). HIV-related variables were included to account for baseline immunologic and virologic status, given their potential influence on both statin use and neurologic outcomes. Each variable was standardized and coded as continuous or categorical depending on its distribution. Missing laboratory or demographic values were handled by pairwise deletion during propensity score modeling, consistent with TriNetX default procedures. Propensity score matching To reduce confounding by indication, 1:1 nearest-neighbor propensity score matching without replacement was performed between statin users and non-users, using a caliper width of 0.1 standard deviations of the logit of the propensity score. The model incorporated all baseline covariates including demographics, comorbidities, laboratory values, vital signs, and HIV-specific markers listed above. Covariate balance was assessed using standardized mean differences (SMDs), with SMD < 0.1 considered indicative of adequate balance. Propensity score density plots were visually inspected to confirm overlap. After matching, each cohort included 19,146 patients, ensuring comparable demographic, clinical, and laboratory characteristics prior to outcome analyses. Statistical Analysis Baseline demographics, clinical, and laboratory characteristics were summarized using means ± standard deviations (SD) for continuous variables and counts with proportions (n, %) for categorical variables, both before and after propensity score matching. Standardized mean differences (SMD) were used to evaluate covariate balance, with SMD < 0.1 indicating adequate balance. All outcomes were evaluated using the validated modules of the TriNetX Analytics platform v12.5 (TriNetX, LLC, Cambridge, Massachusetts, USA). Risk-based analyses estimated absolute risks, risk differences, risk ratios (RR), and odds ratios (OR) with corresponding 95% confidence intervals (CIs) were estimated for each outcome. Time-to-event outcomes were analyzed using Kaplan-Meier survival functions with censoring applied at the last recorded encounter. Log-rank tests compared survival distributions between cohorts, and hazard ratios (HR) were estimated using Cox proportional hazards models adjusted for matched covariates. Proportional hazards assumptions were verified by Schoenfeld residuals and visual inspection of survival curves. All statistical tests were two-sided, with p < 0.05 considered significant. Patients with outcomes recorded prior to the index date were excluded from all analyses to ensure temporal validity. Analyses were conducted natively within TriNetX Global Collaborative Network’s validated, audit-traceable analytic engine to ensure reproducibility. Declarations Acknowledgements: We would like to thank Health Care Organizations who contribute de-identified data to the TriNetX platform, without whom we would not have been able to do this study. Disclosures: All authors declare no conflicts of interest to disclose. Human Ethics and Consent to Participate declarations : not applicable. Funding: This research did not receive funding. Author Contribution: S.M.M. and K.S. conceived and designed the study. K.S., M.D., and M.M. conducted the data analysis. K.S., W.A., and S.M.M. drafted the manuscript. All authors contributed to interpretation of the data, critically revised the manuscript for important intellectual content, and approved the final version. Data Availability : This study used de-identified data from the TriNetX Global Health Research Network. Data access is governed by data-use agreements and is available to authorized users through the TriNetX platform. References Collins LF, Sheth AN, Mehta CC, Naggie S, Golub ET, Anastos K, et al. The Prevalence and Burden of Non-AIDS Comorbidities Among Women Living With or at Risk for Human Immunodeficiency Virus Infection in the United States. 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Lipid composition of the normal human brain: gray matter, white matter, and myelin. J Lipid Res [Internet]. 1965;6(4):537–44. Available from: http://dx.doi.org/10.1016/S0022-2275(20)39619-X Björkhem I, Meaney S, Fogelman AM. Brain Cholesterol: Long Secret Life behind a Barrier. Arterioscler Thromb Vasc Biol. 2004;24(5):806–15. Epstein LG, Gelbard HA. HIV-1-induced neuronal injury in the developing brain. J Leukoc Biol. 1999;65(4):453–7. Groh J, Simons M. White matter aging and its impact on brain function. Neuron [Internet]. 2025;113(1):127–39. Available from: https://doi.org/10.1016/j.neuron.2024.10.019 Ellis R, Langford D, Masliah E. HIV and antiretroviral therapy in the brain: neuronal injury and repair. Nat Rev Neurosci [Internet]. 2007;8(1):33–44. Available from: https://doi.org/10.1038/nrn2040 Burke SN, Barnes CA. Neural plasticity in the ageing brain. Nat Rev Neurosci [Internet]. 2006;7(1):30–40. Available from: https://doi.org/10.1038/nrn1809 TriNetX operates the world’s largest federated network of real-world data in collaboration with healthcare organizations, applying advanced analytics to accelerate research, improve clinical outcomes and drive innovation across the healthcare ecosystem. TriNetX LLC [Internet]. [cited 2025 Nov 7]. Available from: https://trinetx.com/ Funderburg NT, Jiang Y, Debanne SM, Labbato D, Juchnowski S, Ferrari B, et al. Rosuvastatin Reduces Vascular Inflammation and T-cell and Monocyte Activation in HIV-Infected Subjects on Antiretroviral Therapy. JAIDS [Internet]. 2015;68(4):396–404. Available from: www.jaids.com Ridker P, Danielson E, Fonseca FA., Genest J. Rosuvastatin to Prevent Vascular Events in Men and Women with Elevated C-Reactive Protein. N Engl J Med. 2008;365(21):2195–207. Toribio M, Fitch K V., Sanchez L, Burdo TH, Williams KC, Sponseller CA, et al. Effects of pitavastatin and pravastatin on markers of immune activation and arterial inflammation in HIV. AIDS. 2017;31(6):797–806. Vanherle S, Loix M, Miron VE, Hendriks JJA, Bogie JFJ. Lipid metabolism, remodelling and intercellular transfer in the CNS. Nat Rev Neurosci [Internet]. 2025;26(4):214–31. Available from: https://doi.org/10.1038/s41583-025-00908-3 Erlandson KM, McKhann A, Kitch DW, Palella FJ, Ellis RJ, Ances BM, et al. No Evidence of a Detrimental Effect of Pitavastatin on Neurocognitive Function Among People with HIV. AIDS. 2025;13(39):1913–9. Richardson K, Schoen M, French B, Umscheid CA, Mitchell MD, Arnold SE, et al. Statins and cognitive function: a systematic review. Ann Intern Med. 2013;159(10):688–97. Zissimopoulos JM, Barthold D, Brinton RD, Joyce G. Sex and Race Differences in the Association Between Statin Use and the Incidence of Alzheimer Disease. JAMA Neurol. 2017;74(2):225–32. Petek B, Häbel H, Xu H, Villa-Lopez M, Kalar I, Hoang MT, et al. Statins and cognitive decline in patients with Alzheimer’s and mixed dementia: a longitudinal registry-based cohort study. Alzheimers Res Ther. 2023;15(1):220. Evans MA, Golomb BA. Statin-associated adverse cognitive effects: survey results from 171 patients. Pharmacotherapy. 2009;29(7):800–11. Padmanabham P, Liu S, Silverman D. Lipophilic Statins in Subjects with Early Mild Cognitive Impairment: Associations with Conversion to Dementia and Decline in Posterior Cingulate Brain Metabolism in a Long-term Prospective Longitudinal Multi-Center Study. J Nucl Med [Internet]. 2021;62(supplement 1):102 LP – 102. Available from: http://jnm.snmjournals.org/content/62/supplement_1/102.abstract Muldoon MF, Ryan CM, Sereika SM, Flory JD, Manuck SB. Randomized trial of the effects of simvastatin on cognitive functioning in hypercholesterolemic adults. Am J Med. 2004;117(11):823–9. Xiao M, Li L, Zhu W, Wu F, Wu B. Statin-related neurocognitive disorder: a real-world pharmacovigilance study based on the FDA adverse event reporting system. Expert Rev Clin Pharmacol. 2024;17(3):255–61. Chen K, Chen Y, Huang H. Exploring the Relationship Between Atorvastatin and Memory Loss: A Comprehensive Analysis Integrating Real-World Pharmacovigilance and Mendelian Randomization. Drugs R D [Internet]. 2024;24(2):317–29. Available from: https://doi.org/10.1007/s40268-024-00474-6 Nassar M, Abosheaishaa H, Elfert K, Beran A, Ismail A, Mohamed M, et al. TriNetX and Real-World Evidence: A Critical Review of Its Strengths, Limitations, and Bias Considerations in Clinical Research. ASIDE Intern Med. 2025;1(2):24–32. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 08 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviews received at journal 22 Apr, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers agreed at journal 28 Jan, 2026 Reviewers invited by journal 28 Jan, 2026 Editor assigned by journal 27 Jan, 2026 Submission checks completed at journal 18 Jan, 2026 First submitted to journal 13 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8596799","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":582238218,"identity":"b8561f0e-8ba2-462b-94de-8a29052ef70a","order_by":0,"name":"Kenneth Ssebambulidde","email":"","orcid":"","institution":"Howard University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Kenneth","middleName":"","lastName":"Ssebambulidde","suffix":""},{"id":582238220,"identity":"9a86c86b-eeff-46cc-8440-145950159af2","order_by":1,"name":"Wail Alsafi","email":"","orcid":"","institution":"Howard University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Wail","middleName":"","lastName":"Alsafi","suffix":""},{"id":582238222,"identity":"9aea0fdd-70fe-4933-95a1-0ef9b45ebf7d","order_by":2,"name":"Mrinalini Deverapalli","email":"","orcid":"","institution":"Howard University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Mrinalini","middleName":"","lastName":"Deverapalli","suffix":""},{"id":582238225,"identity":"b4da96cb-8c1b-426d-ae51-da07dc24c180","order_by":3,"name":"Miriam Michael","email":"","orcid":"","institution":"Howard University College of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Miriam","middleName":"","lastName":"Michael","suffix":""},{"id":582238227,"identity":"deb999e4-60ae-4bdd-b090-cb23978dde67","order_by":4,"name":"Siham M Mahgoub","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYDACZh4IbQBiM1QcAHMkQGwitZwhRgsDshbGNiK0yLfzHvx0g2GbvDn/4mPShfPuyBkcP/vwBkOFdWIDDi0Gh/mSpXMYbhvunPEsTXrmtmfGBmfSjS0YzqTj1sLMYwDSwrjhxhkzad5thxO3HUhjk2BsO4xTi3wzj/FvoBZ7iJY5QC3nnwG1/MOtheEwjxnIlsQN53uAWhqAWm6AbGnArcUAqMU6x+B28oYbbMnWM44dNra/8YzZIuFYujFOh/WfMb6dU3HbdsP5wwdvF9QclpPsT2O88aHGWhanwyB2AbFEApJAAnZ1aID/AFHKRsEoGAWjYAQCAIYmXRIm/EgHAAAAAElFTkSuQmCC","orcid":"","institution":"Howard University College of Medicine","correspondingAuthor":true,"prefix":"","firstName":"Siham","middleName":"M","lastName":"Mahgoub","suffix":""}],"badges":[],"createdAt":"2026-01-14 03:08:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8596799/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8596799/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101751598,"identity":"fc5c00c4-c94e-4382-a4ad-92d2495b534b","added_by":"auto","created_at":"2026-02-03 10:21:37","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":51627,"visible":true,"origin":"","legend":"\u003cp\u003eStudy cohort construction and exclusion criteria.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8596799/v1/5ad58d0fb5ed7c11bca1fad4.png"},{"id":101491913,"identity":"9b2aaafb-abd2-4977-a95a-06a2bb48db17","added_by":"auto","created_at":"2026-01-30 10:49:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122321,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier survival curves comparing statin users and non-statin users over a 10-year period. Statin users are shown with a solid line, and non-statin users with a dotted line. (A) Cognitive impairment-free survival; (B) All-cause mortality; and (C) major adverse cardiovascular events (MACE), a composite of stroke, myocardial ischemia, and death. The analysis includes hazard ratio (HR), 95% confidence interval, and log-rank test p-value by Cox proportional hazard.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8596799/v1/76040ff31f747ec15bb89a34.png"},{"id":101943056,"identity":"a700edd3-be51-4bbc-bd9e-70f1e531939d","added_by":"auto","created_at":"2026-02-05 09:40:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1303109,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8596799/v1/f9b036fb-94d3-409b-9656-9f09860ff850.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Long-Term Cardiovascular Benefits and Neurocognitive Risks of Statin Therapy in People Living With HIV: A Global Real-World Cohort Study","fulltext":[{"header":"Background","content":"\u003cp\u003eWith the advent of effective combination antiretroviral therapy (ART), people living with HIV (PLWH) are living longer to experience chronic age-related comorbidities(\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). By 2050, PLWH are projected to face rising non-AIDS-related deaths due to ageing, highlighting a shift in health priorities from AIDS to age-related chronic conditions(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Among these chronic conditions, cardiometabolic disorders are major contributors to morbidity and mortality in the modern HIV era(\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). The global burden of HIV-associated cardiovascular disease has tripled over the past two decades, with people living with HIV being twice as likely to develop cardiovascular disease. Persistent systemic inflammation, immune activation, endothelial dysfunction, and dyslipidemia remain hallmarks of HIV infection despite viral suppression under suppressive ART(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These processes accelerate vascular aging and predispose PLWH to atherosclerosis-related cerebrovascular disease(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eLipid lowering agents such as statins, 3-hydroxy-3-methylglutaryl coenzyme A (HMG-CoA) reductase inhibitors, are widely recommended for primary and secondary prevention of atherosclerotic cardiovascular disease (ASCVD) (\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13 CR14\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). PLWH are twice as likely to develop ASCVD, and the global burden of HIV-associated ASCVD has tripled over the past two decades (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Fortunately, the use of statins by PLWH reduces risk for major adverse cardiovascular events(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Beyond their lipid-lowering effects, statins reduce inflammatory biomarkers such as C-reactive protein, soluble CD14, and interleukin-6 among PLWH(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Based on these benefits, the Infectious Diseases Society of America in 2024 recommended statins for PLWH older than 40 years regardless of ASCVD risk or lipid levels unless there is a contraindication to statin use(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNotably, the brain contains approximately 25% of the body\u0026rsquo;s total cholesterol, and myelin is composed of about 85% cholesterol(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Because nearly all brain cholesterol is synthesized locally, inhibition of cholesterol biosynthesis within the central nervous system impairs neuronal membrane integrity, synaptic plasticity, and myelin repair. These processes are already particularly vulnerable with ageing and HIV infection(\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Clinically, such neuronal disruptions may manifest as cognitive decline, motor dysfunction, memory impairment, and/or mood disorders. However, the impact of statin therapy on neurocognition, particularly in PLWH, in the real world remains poorly defined.\u003c/p\u003e \u003cp\u003eTo bridge this knowledge gap, a comprehensive assessment of the impact of statin therapy on neurocognitive outcomes and survival among PLWH in a non-clinical-trial-controlled setting is warranted. Leveraging the TriNetX Global Collaborative Network(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e), which aggregates longitudinal electronic health record data from diverse healthcare systems worldwide, we examined whether statin use among PLWH with ASCVD comorbidities is associated with differences in the risk of cognitive impairment, stroke or transient ischemic attack (TIA), and all-cause mortality. This real-world study aimed to clarify the balance between potential neuroprotective and neurotoxic effects of statins within a population already vulnerable to both metabolic and neuroinflammatory injury.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eCohort characteristics\u003c/p\u003e \u003cp\u003eA total of 94,200 adults living with HIV met inclusion criteria across the TriNetX Global Collaborative Network. After applying all exclusion criteria and performing 1:1 propensity score matching, 38,292 individuals (19,146 statin users and 19,146 non-users) were included in the final analytic cohort (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD age at index was 53.5\u0026thinsp;\u0026plusmn;\u0026thinsp;11 years; 23.3% were female, and 41.5% identified as Black or African American.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBefore propensity score matching, statin users were older (55.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11 vs. 47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2 years) and exhibited a higher burden of cardiometabolic comorbidities (hypertension 34.6% vs 10.3%; diabetes 16.9% vs 4.0%; ischemic heart disease 9.9% vs 1.6%; dyslipidemia 35.6% vs 4.2%, obesity 7.6% vs 3.5%, heart failure 4.9% vs 1.5% chronic kidney disease 10% vs 2.8%, all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than non-statin users. Following propensity score matching across demographics, comorbidities, medications, and laboratory indices, balance was achieved for all variables with standardized mean differences\u0026thinsp;\u0026lt;\u0026thinsp;0.1. Matched cohorts had comparable distributions of age (53.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11 vs. 54.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4 years), sex (23.8% vs 23.3% female), race (Black 40.7% vs 38.8%), diabetes (10.3% vs 9.1%), hypertension (22.1% vs 20.5%), dyslipidemia (14.3% vs 12.9%) and mean BMI (29.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 vs 28.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8 kg/m\u0026sup2;). Mean hemoglobin, glucose, and liver enzyme values were similar across groups, confirming adequate baseline comparability (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristic before and after propensity score matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBefore propensity score matching\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eAfter propensity score matching\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatin Use\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;29,886\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Statin Use\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;64,314\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStatin Use\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;19,146\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNo Statin Use\u003c/p\u003e \u003cp\u003eN\u0026thinsp;=\u0026thinsp;19,146\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSMD\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.2\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;13.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.9\u0026thinsp;\u0026plusmn;\u0026thinsp;11.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,714 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,914 (27.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,560 (23.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4,454 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22,913 (77.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43,941 (72.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14,580 (76.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14,685 (76.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,254 (41.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20,987 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,603 (39.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,945 (41.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11,699 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27,344 (44.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7,794 (40.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7,431 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,264 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,247 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,225 (22.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,919 (20.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5,007 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,457 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,973 (10.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,738 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,559 (35.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,570 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,745 (14.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2,471 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIschemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,938 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e981 (1.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,011 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e826 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,449 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e931 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e608 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e554 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,953 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,688 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,200 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,121 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiver disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e355 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e522 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e189 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e180 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCOPD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e996 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e906 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e489 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e457 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDepression\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,689 (5.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,236 (3.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e827 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e796 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin D deficiency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,982 (6.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,712 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e823 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e797 (4.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypothyroidism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e870 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e697 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e381 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e358 (1.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eObesity/Overweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,250 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,158 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e984 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e927 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcohol-related disorders\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e415 (0.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49 (0.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNicotine dependence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,068 (3.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,486 (2.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e531 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e498 (2.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVital signs and weight assessment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic BP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130.9\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129.8\u0026thinsp;\u0026plusmn;\u0026thinsp;19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e130.6\u0026thinsp;\u0026plusmn;\u0026thinsp;19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e130.4\u0026thinsp;\u0026plusmn;\u0026thinsp;19.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic BP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate (/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.0\u0026thinsp;\u0026plusmn;\u0026thinsp;14.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.4\u0026thinsp;\u0026plusmn;\u0026thinsp;14.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e79.8\u0026thinsp;\u0026plusmn;\u0026thinsp;14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedications\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzetimibe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e267 (0.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e93 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFibrates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e634 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e284 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e225 (1.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e197 (1.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntihypertensives\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,873 (6.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,743 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e945 (4.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e902 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOral hypoglycemics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,451 (8.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,200 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e999 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e911 (4.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAntiplatelets\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,809 (9.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,700 (2.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,242 (6.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,114 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAntiretroviral therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtease inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,092 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,270 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,612 (8.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1,649 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntegrase inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,310 (21.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,239 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,207 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3,294 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRTIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12,691 (42.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,849 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,697 (35.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6,988 (36.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory results\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlatelet count (\u0026times;10⁹/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e232.8\u0026thinsp;\u0026plusmn;\u0026thinsp;75.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e234.2\u0026thinsp;\u0026plusmn;\u0026thinsp;86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e234.9\u0026thinsp;\u0026plusmn;\u0026thinsp;75.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e230.7\u0026thinsp;\u0026plusmn;\u0026thinsp;83.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLeukocytes (WBC \u0026times;10⁹/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin A1c (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.0\u0026thinsp;\u0026plusmn;\u0026thinsp;1.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115.4\u0026thinsp;\u0026plusmn;\u0026thinsp;57.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104.9\u0026thinsp;\u0026plusmn;\u0026thinsp;46.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e112.6\u0026thinsp;\u0026plusmn;\u0026thinsp;55.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e108.1\u0026thinsp;\u0026plusmn;\u0026thinsp;47.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTSH (mIU/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2\u0026thinsp;\u0026plusmn;\u0026thinsp;22.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4\u0026thinsp;\u0026plusmn;\u0026thinsp;22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4\u0026thinsp;\u0026plusmn;\u0026thinsp;36.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eLipid profile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200.4\u0026thinsp;\u0026plusmn;\u0026thinsp;53.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180.7\u0026thinsp;\u0026plusmn;\u0026thinsp;47.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e203.5\u0026thinsp;\u0026plusmn;\u0026thinsp;53.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e180.5\u0026thinsp;\u0026plusmn;\u0026thinsp;45.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL cholesterol (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121.9\u0026thinsp;\u0026plusmn;\u0026thinsp;44.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106.6\u0026thinsp;\u0026plusmn;\u0026thinsp;37.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e125.4\u0026thinsp;\u0026plusmn;\u0026thinsp;44.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105.3\u0026thinsp;\u0026plusmn;\u0026thinsp;37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL cholesterol (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44.2\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e45.8\u0026thinsp;\u0026plusmn;\u0026thinsp;15.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e44.7\u0026thinsp;\u0026plusmn;\u0026thinsp;17.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184.7\u0026thinsp;\u0026plusmn;\u0026thinsp;167.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e164.9\u0026thinsp;\u0026plusmn;\u0026thinsp;136.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e183.1\u0026thinsp;\u0026plusmn;\u0026thinsp;154.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e163.1\u0026thinsp;\u0026plusmn;\u0026thinsp;125.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eHIV disease specific labs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlasma HIV RNA (log copies/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;40.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.5\u0026thinsp;\u0026plusmn;\u0026thinsp;19.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4 count (cells/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662.6\u0026thinsp;\u0026plusmn;\u0026thinsp;348.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e581.0\u0026thinsp;\u0026plusmn;\u0026thinsp;380.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e675.1\u0026thinsp;\u0026plusmn;\u0026thinsp;357.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e598.9\u0026thinsp;\u0026plusmn;\u0026thinsp;394.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eRenal function and serum electrolyte profile\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;6.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood urea nitrogen (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.4\u0026thinsp;\u0026plusmn;\u0026thinsp;11.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.1\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e138.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e138.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePotassium (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR (mL/min/1.73m\u0026sup2;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73.2\u0026thinsp;\u0026plusmn;\u0026thinsp;27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83.1\u0026thinsp;\u0026plusmn;\u0026thinsp;31.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.1\u0026thinsp;\u0026plusmn;\u0026thinsp;28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77.2\u0026thinsp;\u0026plusmn;\u0026thinsp;29.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eNutritional and Micronutrient Markers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFolate (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;6.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.7\u0026thinsp;\u0026plusmn;\u0026thinsp;6.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVitamin B12 (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643.1\u0026thinsp;\u0026plusmn;\u0026thinsp;761.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e724.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1530.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e641.2\u0026thinsp;\u0026plusmn;\u0026thinsp;934.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e748\u0026thinsp;\u0026plusmn;\u0026thinsp;1082.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eLiver function\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;34.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.8\u0026thinsp;\u0026plusmn;\u0026thinsp;89.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28.6\u0026thinsp;\u0026plusmn;\u0026thinsp;29.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.4\u0026thinsp;\u0026plusmn;\u0026thinsp;108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALT (U/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;41.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.1\u0026thinsp;\u0026plusmn;\u0026thinsp;78.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.3\u0026thinsp;\u0026plusmn;\u0026thinsp;37.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.9\u0026thinsp;\u0026plusmn;\u0026thinsp;77.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBilirubin (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eAbbreviations: ALT, alanine aminotransferase; ALP, alkaline phosphatase; AST, aspartate aminotransferase; HbA1c, hemoglobin A1c; BP, blood pressure; CD4, cluster of differentiation 4; CD8, cluster of differentiation 8; COPD, chronic obstructive pulmonary disease; eGFR, estimated glomerular filtration rate; Hb, hemoglobin; HDL, high density lipoprotein; HIV RNA, human immunodeficiency virus ribonucleic acid; HR, heart rate; LDL, low density lipoprotein; NRTIs, nucleoside/nucleotide reverse transcriptase inhibitors; PI, protease inhibitors; PP, pulse pressure; SMD, standardized mean difference; SBP, systolic blood pressure; TSH, thyroid stimulating hormone; T4, thyroxine, WBC, white blood cell count.\u003c/p\u003e \u003cp\u003eValues are mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or n (%). SMD derived from difference in means or proportions divided by pooled standard deviation.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePrimary outcome: Cognitive impairment\u003c/p\u003e \u003cp\u003eAt ten years of follow-up, the cumulative incidence of cognitive impairment was 9.1% (1,494/16,457) among individuals on statins compared with 6.6% (1,112/16,734) among individuals not on statins corresponding to an absolute risk difference of 2.4% (95% CI: 1.9\u0026ndash;3.0%) excluding individuals with cognitive impairment diagnoses prior to statin therapy. The hazard of incident cognitive impairment was 1.2 (95% CI: 1.11\u0026ndash;1.29) consistent with a 20% higher cumulative occurrence of cognitive impairment with statin use over ten years. At ten years, cognitive-impairment-free survival was 79.3% for statin users versus 83.8% for non-statin-users, log rank test p value\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOutcomes over ten years measured after propensity score matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStatin n/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Statin n/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCognitive impairment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,494 / 16,457 (9.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,112/ 16,734 (6.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20 (1.11\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAll-cause mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,019 / 19,094 (5.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,519 / 19,021 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.58 (0.53\u0026ndash;0.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMajor adverse cardiovascular events (MACE)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,362 / 17,210 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,579 / 18,169 (8.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79 (0.74\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e532 / 18,309 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370 / 18,497 (2.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.25 (1.09\u0026ndash;1.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated liver enzymes, \u0026gt;3x ULN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,824 / 14,765 (12.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,424 / 15,512 (9.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.20 (1.12\u0026ndash;1.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital utilization (ED\u0026thinsp;+\u0026thinsp;inpatient)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,130 / 9,895 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,726 / 10,228 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12 (1.05\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcute appendicitis (Negative control)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34 / 19,062 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 / 19,062 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.86 (0.53\u0026ndash;1.38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eHR\u0026thinsp;=\u0026thinsp;hazard ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval; ED\u0026thinsp;=\u0026thinsp;emergency department; ULN, upper limit of normal.\u003c/p\u003e \u003cp\u003eValues are n/N (%). Hazard ratios are derived from Cox proportional hazard model, and p values are by log rank testing.\u003c/p\u003e \u003cp\u003eDenominators (N) vary by outcome based on available follow‑up and exclusion of prior events before the index point of starting statin therapy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSecondary outcomes:\u003c/p\u003e \u003cp\u003eAll-cause mortality\u003c/p\u003e \u003cp\u003eAt ten years, cumulative incidence of all-cause mortality was 5.3% (1,019/19,094) among statin users vs 8.0% (1,519/19,021) among non-statin users representing an absolute risk reduction of 2.6% (95% CI: 2.1\u0026ndash;3.1%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) with statin therapy. Kaplan-Meier survival curves demonstrated a clear and sustained survival advantage among statin users throughout the 10-year follow-up period. Hazard for mortality from any cause was 0.58 (95% CI: 0.53\u0026ndash;0.63), corresponding to a 42% (95% CI: 37\u0026ndash;47%) lower risk of mortality among statin users compared with matched non-statin users (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMajor adverse cardiovascular events (MACE)\u003c/p\u003e \u003cp\u003eThe cumulative incidence of MACE (composite of myocardial infarction, stroke or death) was 7.9% (1,362/17,210) among statin users versus 8.7% (1,579/18,169) among non-statin users (RR 0.91, 95% CI: 0.85\u0026ndash;0.98). The hazard ratio of MACE was 0.79 (95% CI: 0.74\u0026ndash;0.85) consistent with a 21% lower risk among statin users.\u003c/p\u003e \u003cp\u003eMyopathy\u003c/p\u003e \u003cp\u003eOver ten years, the cumulative incidence of myopathy, defined by ICD-10 code M79.1, was 2.9% (532/18,309) among statin users versus 2.0% (370/18,497) among non-users, resulting in an absolute risk increase of 0.9% (95% CI: 0.6\u0026ndash;1.2). The Kaplan-Meier curves for myopathy showed consistent separation over time, with the log-rank test demonstrating a statistically significant difference (p\u0026thinsp;=\u0026thinsp;0.001). The HR for myopathy was 1.25 (95% CI: 1.09\u0026ndash;1.43), indicating a 25% higher risk among statin users.\u003c/p\u003e \u003cp\u003eTransaminitis (Elevated liver enzymes)\u003c/p\u003e \u003cp\u003eAt ten years, the cumulative incidence of elevated liver enzymes was 12.0% (1,824/14,765) in statin users compared with 9.0% (1,424/15,512) in non-statin users, an absolute increase of 3.2% (95% CI: 2.5\u0026ndash;3.9). The Kaplan-Meier survival analysis revealed progressive divergence in liver-enzyme-free survival between cohorts (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The HR for transaminitis was 1.20 (95% CI: 1.12\u0026ndash;1.28), consistent with a 20% greater risk among statin users.\u003c/p\u003e \u003cp\u003eHospital utilization\u003c/p\u003e \u003cp\u003eHospital utilization defined as the composite of emergency visits and inpatient admission occurred in 21.5% (2,130/9,895) of statin users compared with 16.9% (1,726/10,228) of non-users yielding an absolute risk increase of 4.7% (95% CI: 3.6\u0026ndash;5.7. The hazard ratio of hospital utilization was 1.12 (95% CI: 1.05\u0026ndash;1.2), corresponding to a 12% increased risk of healthcare encounters among statin users versus non-statin users.\u003c/p\u003e \u003cp\u003eNegative control outcome\u003c/p\u003e \u003cp\u003eAppendicitis, included as a negative control outcome not biologically associated with statin exposure, occurred in 0.2% (34/19,062) of both groups. Over a ten-year follow up period, there was no statistically significant difference in cumulative incidence between statin users and non-statin users (HR 0.86 [95% CI: 0.53\u0026ndash;1.38; p\u0026thinsp;=\u0026thinsp;0.524]), supporting the absence of unmeasured bias or residual confounding in our analytic model.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large real-world analysis of over 38,000 adults living with HIV, statin use was associated with benefits and risks over ten years of follow-up. Statin use was associated with significant cardiovascular and survival benefits, with a 44% lower risk of all-cause mortality, and a 21% reduction in major adverse cardiovascular events. However, statin use was associated with a 20% increase in likelihood of cognitive impairment than non-statin use. Consistent with known pharmacologic toxicities, statin use was associated with a 20% increased risk for statin induced myopathy, and 25% increased risk for elevation of liver enzymes more than three times the upper limit of normal. Collectively, our findings highlight the double sword nature of statin therapy; on the one hand, statins offer cardioprotective and survival benefits while on the other hand individuals on statins are likely to experience cognitive impairment, myopathy and elevation of liver enzymes.\u003c/p\u003e \u003cp\u003eOur findings are testament to the real-world clinical practice, where patient requiring statin therapy often present with multiple comorbidities, most of which are cardiometabolic in nature. For instance, in our study, before propensity score matching, PLWH on statins were older and exhibited a statistically significant higher burden of cardiometabolic comorbidities i.e., markedly higher rates of hypertension, diabetes, dyslipidemia, ischemic heart disease, obesity, heart failure, and chronic kidney disease; compared with individuals not on statins. This is consistent with the clinical profile of individuals at elevated ASCVD risk for whom lipid-lowering therapy is clinically indicated as per various medical society guidelines(\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13 CR14\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). However, after rigorous propensity score matching across more than 70 demographic, clinical, medication, and laboratory covariates, balance was achieved for all baseline variables, with standardized mean differences below 0.1. The matched cohorts were comparable in age, sex distribution, race, metabolic comorbidities, and key laboratory parameters including hemoglobin, glucose, and liver enzymes. This high degree of balance supports that subsequent outcome differences likely reflect associations with statin exposure rather than baseline confounding. Furthermore, we included appendicitis as a negative control outcome, showing no significant difference between groups, supporting the internal validity of our analytic approach and mitigates concerns about residual confounding or systematic bias.\u003c/p\u003e \u003cp\u003eStatins are well recognized for their anti-atherogenic, anti-inflammatory properties and protecting from ASCVD-associated mortality(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). In HIV, chronic immune activation, dyslipidemia, and endothelial dysfunction accelerate atherosclerosis and microvascular/endothelial injury. By lowering LDL cholesterol and dampening systemic inflammation, statins plausibly contribute to the overall survival advantage we observed(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). However, cholesterol plays a critical role in neuronal membrane integrity, synaptic vesicle formation, and myelin maintenance(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Excessive inhibition of central cholesterol synthesis or altered transport across the blood brain barrier may impair neuronal repair and neurotransmission(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, multiple prior studies report no association of statins with cognitive impairment(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Notably, the statin doses in some of these studies were low, not the current recommended high-intensity statin doses for individuals with high ASCVD risk.\u003c/p\u003e \u003cp\u003eStudies in the general population have produced inconsistent findings about statin use and cognition. Some report cognitive protection with statin use(\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Whereas other studies report potential cognitive impairment, especially with lipophilic agents(\u003cspan additionalcitationids=\"CR39\" citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). However, evidence within HIV cohorts has been scarce. The REPRIEVE trial, a randomized, placebo-controlled study of pitavastatin in more than 7,700 PLWH, reported a 35% reduction in major cardiovascular events but did not assess neurocognitive outcomes(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In contrast, our analysis with far larger sample size and longer follow-up identified statistically significant associations with cognitive decline, suggesting that prolonged exposure or drug-drug interactions unique to HIV care may underlie these discrepancies. These results argue for careful risk-benefit assessment when initiating statins for PLWH. For patients with established cardiovascular disease or high ASCVD risk, statins remain essential, given their pronounced mortality reduction. Yet clinicians should maintain vigilance for new-onset neurocognitive symptoms particularly among older adults, those with metabolic co-morbidities, or individuals on polypharmacy involving CNS-active or ART agents. Routine cognitive screening and periodic liver and muscle enzyme monitoring may improve safety. Where feasible, selection of statins with minimal antiretroviral interactions (e.g., rosuvastatin, pitavastatin, pravastatin) or statins with lower CNS penetration to preserve central cholesterol synthesis (e.g., rosuvastatin and pravastatin) may mitigate risk.\u003c/p\u003e \u003cp\u003eGrowing pharmacovigilance evidence from the U.S. Food and Drug Administration\u0026rsquo;s Adverse Event Reporting System (FAERS) supports the neurocognitive safety signal we observed. In a large FAERS analysis of 6,959 neurocognitive disorder reports, both lipophilic and hydrophilic statins including atorvastatin, simvastatin, pravastatin, rosuvastatin, lovastatin, fluvastatin, and pitavastatin demonstrated significant disproportionality signals, with higher reporting odds ratios among adults older than 65 years(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). A complementary FAERS and Mendelian randomization study further showed that atorvastatin was associated with amnesia and memory impairment and provided genetic evidence suggesting a potential causal pathway partially mediated through mitochondrial dysfunction(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). Together, these real-world and genetic data reinforce the plausibility of our observed association between statin use and cognitive impairment among PLWH.\u003c/p\u003e \u003cp\u003eOur study possesses several notable strengths. First, it leveraged a large, diverse, and contemporary global cohort of over 38,000 propensity-score-matched individuals across 162 healthcare organizations, enhancing statistical power and external generalizability. Second, the use of federated electronic health record data reflecting authentic real-world/pragmatic clinical practice encompassing heterogeneous comorbidity profiles beyond the constraints of stringent inclusion criteria for randomized clinical trials. Third, rigorous confounding control was achieved through propensity score matching on more than seventy demographic, clinical, and laboratory variables resulting in near-perfect covariate balance. Forth, multiple complementary analyses including risk ratios, odds ratios, and time-to-event hazard models that yielded concordant results. Fifth, we incorporated a comprehensive set of outcomes encompassing both neurological and safety endpoints, allowing a balanced evaluation of potential benefits and harms of statin therapy. Finally, the inclusion of a biologically unrelated negative control outcome (i.e., appendicitis) that showed no significant difference between groups serves as an internal validity check, supporting robustness of the analytical framework and reducing concern of unmeasured/residual confounding.\u003c/p\u003e \u003cp\u003eUsing federated databases comes with benefits and limitations(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). We note a couple of limitations that merit consideration when interpreting our findings. First the observational design precludes definitive causal inference, and despite extensive propensity score matching, residual confounding may persist. For examples, individuals prescribed with statins had greater baseline cardiovascular risk and had more hospital utilization potentially influencing outcome detection and reporting than individuals not on statins. Second, diagnostic misclassification is possible, as reliance on ICD-10 codes may under- or over-estimate cognitive impairment, especially for subtle or undiagnosed neurocognitive disorders. Third, TriNetX captures prescription records but not patient adherence, statin potency, or treatment duration limiting exposure precision. Forth, unmeasured confounders including lipid profiles, inflammatory biomarkers, ART class, and nadir CD4 counts were not uniformly available across sites. Fifth, outcome heterogeneity exists because \u0026ldquo;Cognitive impairment\u0026rdquo; encompasses multiple ICD codes, and detailed neuropsychological test data were unavailable. Sixth, the associations we report do not imply causality.\u003c/p\u003e \u003cp\u003eIn this global, real-world study of adults living with HIV, statin therapy was associated with significant reduction in mortality, MACE, and stroke but higher risks of cognitive impairment. These findings highlight the dual biological and clinical complexity of lipid-lowering therapy in chronic HIV infection. Future prospective studies, ideally randomized or mechanistically anchored, are needed to delineate which statin types, doses, and patient subgroups derive maximal net benefit. Meanwhile, clinicians should personalize statin prescribing by integrating cardiovascular risk, ART regimen, age, and neurocognitive status into shared decision-making.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective, propensity-matched cohort study using real-world data from the TriNetX Global Collaborative Network, a federated electronic health record (EHR) platform that integrates de-identified patient-level data from 162 healthcare organizations (HCOs) across North America, Europe, the Middle East, Asia, and South America(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e). The network includes data from academic medical centers, community hospitals, and integrated delivery systems, capturing demographics, diagnoses, procedures, medications, vital signs, laboratory results, and mortality outcomes from over 200\u0026nbsp;million patients worldwide. The study was performed entirely within the secure TriNetX analytics environment on November 7, 2025. All data were de-identified at source in compliance with the Health Insurance Portability and Accountability Act (HIPAA) and the General Data Protection Regulation. The TriNetX platform operates under a business associate agreement with contributing organizations and does not permit re-identification. Only aggregated, de-identified data were accessed; therefore, the analysis was exempt from institutional review board oversight and did not require individual informed consent.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population and Cohort Definition\u003c/h3\u003e\n\u003cp\u003eWe included adults (\u0026ge;\u0026thinsp;18 years) with a confirmed diagnosis of HIV infection (ICD-10-CM code B20) and comorbidities including ischemic heart disease (ICD-10-CM code I25) or hypertension (ICD-10-CM code I10) or chronic kidney disease (ICD-10-CM code N18) or stroke/transient ischemic attack (ICD-10-CM code I63, G45) or chronic liver disease (ICD-10-CM code K74) or dyslipidemia (ICD-10-CM code E78), or diabetes mellitus (ICD-10-CM code E08-E13). We defined two mutually exclusive cohorts. Cohort 1 (statin users) included PLWH who initiated any statin (atorvastatin [RxNorm 83367], rosuvastatin [301542], simvastatin [36567], pravastatin [42463], lovastatin [6472], fluvastatin [41127], or pitavastatin [861634]) after the recorded HIV diagnosis. Cohort 2 (non-users) included PLWH with no documentation of any statin prescription during the entire observation period. The index date was defined as the date of first statin prescription for Cohort 1 and an equivalent matched date (based on time since HIV diagnosis) for Cohort 2.\u003c/p\u003e \u003cp\u003eTo minimize confounding by baseline neurological or psychiatric illness, we excluded patients with any diagnosis of; major psychiatric disorders or substance use disorders (ICD-10 F10\u0026ndash;F19); dementia or neurodegenerative diseases including Alzheimer\u0026rsquo;s disease (G30), vascular dementia (F01), or other degenerative diseases of the nervous system (G31); post-viral fatigue syndromes (G93.3); and prior use of CNS-active medications such as phenothiazines (VA code CN701), other antipsychotics (CN709), CNS stimulants (CN800), or CNS medications not otherwise specified (CN900). This approach was consistent with TriNetX\u0026rsquo;s \u0026ldquo;exclude-prior-outcome\u0026rdquo; function, ensuring that all included participants were free of the study outcomes before cohort entry.\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eOur primary outcome was incident cognitive impairment, defined as a new diagnosis after index date using any of the following ICD-10-CM codes: R40-R46 (symptoms and signs involving cognition, perception, emotional state, and behavior); R41.89 (other cognitive symptoms); G31.84 (mild cognitive impairment); F06 (mental disorders due to known physiological conditions). Our secondary outcomes included all-cause mortality, stroke or transient ischemic attack (TIA), major adverse cardiovascular events (MACE), hospital utilization, myopathy, and elevated liver enzymes (transaminitis). All-cause mortality was identified using the TriNetX mortality flag (\u0026ldquo;Deceased\u0026rdquo;); stroke/TIA was identified by ICD-10 I63 (cerebral infarction) or G45 (transient cerebral ischemic attack and related syndromes). MACE was defined as a composite of acute myocardial infarction (ICD-10 I21), stroke (ICD-10 I63) and death (deceased). Hospital utilization was defined as a composite of emergency department (ED) visits and inpatient admissions identified using standardized HL7 visit-type ontologies within the TriNetX network: UMLS: HL7V3.0: Visit Type: EMER (Emergency Visit), ACUTE (Inpatient Acute), IMP (Inpatient Encounter), NONAC (Inpatient Non-acute), and OBSENC (Observation Encounter). Both ED and inpatient encounters were aggregated to represent overall healthcare utilization during follow-up. Statin-associated myopathy was identified by ICD-10 M79.1, elevated liver enzymes/transaminitis by ICD-10 R74.8 (abnormal levels of serum enzymes) or laboratory thresholds of alanine aminotransferase (TNX:9044) and aspartate aminotransferase (TNX:9047)\u0026thinsp;\u0026gt;\u0026thinsp;60 U/L. A negative control outcome, appendicitis (ICD-10 code K35) was included as an outcome not known to be associated with statin use. Outcomes were evaluated beginning one day after the index date and followed ten years post index.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCovariates and confounder adjustment\u003c/h2\u003e \u003cp\u003eBaseline covariates were measured at or prior to the index date and encompassed four major domains. Demographics: age at index date, sex (male, female), and race/ethnicity (White, Black or African American). Comorbidities: disorders of lipoprotein metabolism and other lipidemias (E78), diabetes mellitus (E10-E14), hypertensive diseases (I10-I15), ischemic heart disease (I20-I25), cerebral infarction due to unspecified occlusion or stenosis (I63.5), other peripheral vascular diseases (I73), chronic obstructive pulmonary disease (J44), chronic kidney disease (N18), liver diseases including fibrosis and cirrhosis (K74, K76), obesity (E66), heart failure (I50), late syphilis (A52), neurosyphilis (A52.1), alcohol-related disorders (F10), nicotine dependence (F17.2), other hypothyroidism (E03.8), vitamin D deficiency (E55), and depressive episode (F32). Medications: lipid-lowering and cardiometabolic agents including ezetimibe, fibrates, alirocumab, evolocumab, antihypertensives, oral hypoglycemics, and platelet aggregation inhibitors, as well as antiretroviral classes i.e., protease inhibitors, nucleoside/nucleotide reverse transcriptase inhibitors, and integrase inhibitors. Laboratory and vital parameters: serum total cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL), and very low density lipoprotein (VLDL) cholesterol; triglycerides; hemoglobin A1c; thyroid function (TSH, T4); vitamin B12; folate; liver indices (AST, ALT, bilirubin, albumin); renal indices (creatinine, blood urea nitrogen (BUN), estimated glomerular filtration rate (eGFR), urine albumin); glucose; sodium; potassium; inflammatory markers i.e., c-reactive protein (CRP), erythrocyte sedimentation rate (ESR); hematologic indices (leucocytes, hemoglobin, platelets); body mass index (BMI), systolic and diastolic blood pressure, heart rate; and HIV-specific markers including CD3/CD4 counts and plasma or cerebrospinal fluid HIV-1 RNA viral load (quantitative and log-transformed). HIV-related variables were included to account for baseline immunologic and virologic status, given their potential influence on both statin use and neurologic outcomes. Each variable was standardized and coded as continuous or categorical depending on its distribution. Missing laboratory or demographic values were handled by pairwise deletion during propensity score modeling, consistent with TriNetX default procedures.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePropensity score matching\u003c/h3\u003e\n\u003cp\u003eTo reduce confounding by indication, 1:1 nearest-neighbor propensity score matching without replacement was performed between statin users and non-users, using a caliper width of 0.1 standard deviations of the logit of the propensity score. The model incorporated all baseline covariates including demographics, comorbidities, laboratory values, vital signs, and HIV-specific markers listed above. Covariate balance was assessed using standardized mean differences (SMDs), with SMD\u0026thinsp;\u0026lt;\u0026thinsp;0.1 considered indicative of adequate balance. Propensity score density plots were visually inspected to confirm overlap. After matching, each cohort included 19,146 patients, ensuring comparable demographic, clinical, and laboratory characteristics prior to outcome analyses.\u003c/p\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eBaseline demographics, clinical, and laboratory characteristics were summarized using means\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviations (SD) for continuous variables and counts with proportions (n, %) for categorical variables, both before and after propensity score matching. Standardized mean differences (SMD) were used to evaluate covariate balance, with SMD\u0026thinsp;\u0026lt;\u0026thinsp;0.1 indicating adequate balance. All outcomes were evaluated using the validated modules of the TriNetX Analytics platform v12.5 (TriNetX, LLC, Cambridge, Massachusetts, USA). Risk-based analyses estimated absolute risks, risk differences, risk ratios (RR), and odds ratios (OR) with corresponding 95% confidence intervals (CIs) were estimated for each outcome. Time-to-event outcomes were analyzed using Kaplan-Meier survival functions with censoring applied at the last recorded encounter. Log-rank tests compared survival distributions between cohorts, and hazard ratios (HR) were estimated using Cox proportional hazards models adjusted for matched covariates. Proportional hazards assumptions were verified by Schoenfeld residuals and visual inspection of survival curves. All statistical tests were two-sided, with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 considered significant. Patients with outcomes recorded prior to the index date were excluded from all analyses to ensure temporal validity. Analyses were conducted natively within TriNetX Global Collaborative Network\u0026rsquo;s validated, audit-traceable analytic engine to ensure reproducibility.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe would like to thank Health Care Organizations who contribute de-identified data to the TriNetX platform, without whom we would not have been able to do this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosures:\u0026nbsp;\u003c/strong\u003eAll authors declare no conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e: not applicable.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis research did not receive funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution:\u0026nbsp;\u003c/strong\u003eS.M.M. and K.S. conceived and designed the study. K.S., M.D., and M.M. conducted the data analysis. K.S., W.A., and S.M.M. drafted the manuscript. All authors contributed to interpretation of the data, critically revised the manuscript for important intellectual content, and approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e: This study used de-identified data from the TriNetX Global Health Research Network. Data access is governed by data-use agreements and is available to authorized users through the TriNetX platform.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCollins LF, Sheth AN, Mehta CC, Naggie S, Golub ET, Anastos K, et al. The Prevalence and Burden of Non-AIDS Comorbidities Among Women Living With or at Risk for Human Immunodeficiency Virus Infection in the United States. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40268-024-00474-6\u003c/span\u003e\u003cspan address=\"10.1007/s40268-024-00474-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNassar M, Abosheaishaa H, Elfert K, Beran A, Ismail A, Mohamed M, et al. TriNetX and Real-World Evidence: A Critical Review of Its Strengths, Limitations, and Bias Considerations in Clinical Research. ASIDE Intern Med. 2025;1(2):24\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"npj-cardiovascular-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Cardiovascular Health](https://www.nature.com/npjcardiohealth)","snPcode":"44325","submissionUrl":"https://submission.springernature.com/new-submission/44325/3","title":"npj Cardiovascular Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HIV, statins, cognitive impairment, mortality, stroke, TriNetX, real-world evidence","lastPublishedDoi":"10.21203/rs.3.rs-8596799/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8596799/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePeople living with HIV (PLWH) are at risk for atherosclerotic cardiovascular disease (ASCVD) and neurocognitive impairment. Statins are recommended for primary and secondary prevention of ASCVD; however, their potential impact on cognitive function among PLWH is uncertain. We evaluated the association between statin use and incident cognitive impairment in a large, real-world cohort of adults with HIV.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing the TriNetX Global Collaborative Network, we identified adults (\u0026ge;\u0026thinsp;18 years) with HIV and comorbidities and stratified them into two cohorts based on statin use versus no statin use. Individuals with pre-existing dementia, substance use disorders, major psychiatric illness, or use of CNS-active antipsychotics were excluded. Outcomes included cognitive impairment, major adverse cardiovascular events (MACE: myocardial infarction, stroke, or death), all-cause mortality, hospital utilization, myopathy, and transaminitis. Propensity score matching (1:1) balanced demographics, comorbidities, medications, and laboratory values. Cox proportional-hazards models estimated hazard ratios (HRs) with 95% confidence intervals (CIs); p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAfter matching, 38,292 individuals were analyzed (mean age 54\u0026thinsp;\u0026plusmn;\u0026thinsp;13 years; 24% female, 76% White). Cognitive impairment occurred in 9.1% of statin users versus 6.6% of non-users (HR 1.20, 95% CI:1.11\u0026ndash;1.29; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). All-cause mortality was lower among statin users (5.3% vs 8.0%; HR 0.58, 95% CI: 0.53\u0026ndash;0.63; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). MACE was lower among statin users (7.9% vs 8.7%; HR 0.79, 95% CI: 0.74\u0026ndash;0.85; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Statin use was associated with higher risks of myopathy (2.9% vs 2.0%; HR 1.25, 95% CI: 1.09\u0026ndash;1.43; p\u0026thinsp;=\u0026thinsp;0.001), transaminitis (12.4% vs 9.2%; HR 1.20, 95% CI:1.12\u0026ndash;1.28; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and hospital utilization (2.2% vs 1.7%; HR 1.12, 95% CI:1.05\u0026ndash;1.20; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Appendicitis (negative control) was similar between groups (0.2% each; HR 0.86, 95% CI:0.53\u0026ndash;1.38; p\u0026thinsp;=\u0026thinsp;0.52).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this large, real-world cohort of PLWH, statin use was associated with lower all-cause mortality and MACE but a modestly increased risk of cognitive impairment (11\u0026ndash;29%) over ten years. Statin users had greater comorbidity burden, highlighting the need to balance cardiovascular benefits against potential neurocognitive risks.\u003c/p\u003e","manuscriptTitle":"Long-Term Cardiovascular Benefits and Neurocognitive Risks of Statin Therapy in People Living With HIV: A Global Real-World Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-30 10:49:41","doi":"10.21203/rs.3.rs-8596799/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-05-08T16:18:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T08:41:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315118799182652038677538731904127727653","date":"2026-05-07T08:33:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"259725963656813397237603376924911213183","date":"2026-05-05T09:28:01+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-22T05:18:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137248591563564209810757591803838294132","date":"2026-03-31T20:08:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"216331899917414152736003162664311280273","date":"2026-02-12T08:58:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"315447580984437679959943075454466200661","date":"2026-01-28T21:47:34+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-28T12:41:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-27T11:56:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-19T04:45:11+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Cardiovascular Health","date":"2026-01-14T02:53:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-cardiovascular-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [npj Cardiovascular Health](https://www.nature.com/npjcardiohealth)","snPcode":"44325","submissionUrl":"https://submission.springernature.com/new-submission/44325/3","title":"npj Cardiovascular Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"46485266-4412-46f2-8b9e-f476d09c5d56","owner":[],"postedDate":"January 30th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Revision requested","date":"2026-05-08T16:18:22+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T08:41:56+00:00","index":102,"fulltext":""},{"type":"reviewerAgreed","content":"315118799182652038677538731904127727653","date":"2026-05-07T08:33:21+00:00","index":101,"fulltext":""},{"type":"reviewerAgreed","content":"259725963656813397237603376924911213183","date":"2026-05-05T09:28:01+00:00","index":99,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[{"id":61943311,"name":"Health sciences/Cardiology"},{"id":61943312,"name":"Health sciences/Diseases"},{"id":61943313,"name":"Health sciences/Health care"},{"id":61943314,"name":"Health sciences/Medical research"},{"id":61943315,"name":"Health sciences/Neurology"},{"id":61943316,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-05-08T16:44:38+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-30 10:49:41","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8596799","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8596799","identity":"rs-8596799","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}