Long-term Effectiveness of PCSK9 Inhibitors versus Ezetimibe as Adjunctive Therapy to Statins in Patients with Atherosclerotic Cardiovascular Disease: A TriNetX Database Analysis

Long-term Effectiveness of PCSK9 Inhibitors versus Ezetimibe as Adjunctive Therapy to Statins in Patients with Atherosclerotic Cardiovascular Disease: A TriNetX Database Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Long-term Effectiveness of PCSK9 Inhibitors versus Ezetimibe as Adjunctive Therapy to Statins in Patients with Atherosclerotic Cardiovascular Disease: A TriNetX Database Analysis Krutagni Mehta, Ritu C Tated, Umang Gupta, Akash M Singh, Sameh Elias, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8606687/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: Atherosclerotic cardiovascular disease (ASCVD) remains a leading cause of mortality. While statins are the cornerstone of therapy, many patients require intensification. This study compares the long-term real-world effectiveness of adding a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor versus ezetimibe to background statin therapy. Methods: We conducted a retrospective cohort study using the TriNetX Global Collaborative Network (January 2018–January 2023). We identified adult patients with established ASCVD on statin therapy initiating either a PCSK9 inhibitor or ezetimibe. Propensity score matching (1:1) was utilized to balance baseline demographics, comorbidities, and medications, resulting in 16,145 patients per group. The primary outcome was all-cause mortality at 3 and 5 years. Secondary outcomes included myocardial infarction (MI), stroke, revascularization, and hospital readmission. Results The PCSK9 inhibitor cohort demonstrated a significant reduction in all-cause mortality compared to the ezetimibe cohort at 3 years (OR: 0.78, HR: 0.79, p < 0.001) and 5 years (OR: 0.78, HR: 0.79, p < 0.001). All-cause readmissions were also lower in the PCSK9 inhibitor group (5-year OR: 0.89, p = 0.01; HR: 0.95, p = 0.15). Conversely, rates of MI were higher in the PCSK9 inhibitor group at 5 years (OR: 1.11, p = 0.03; HR: 1.10, p = 0.03), likely reflecting channeling bias due to higher baseline risk (residual LDL-C imbalance). Conclusion In this large real-world analysis, PCSK9 inhibitor use was associated with lower all-cause mortality and fewer hospital readmissions over 5 years compared with ezetimibe, despite preferential use in a higher-risk population. These findings are observational and hypothesis-generating, highlighting the impact of treatment channeling in real-world lipid-lowering therapy and the need for further studies with cause-specific outcome adjudication. PCSK9 inhibitors Ezetimibe ASCVD Statin therapy Real-world evidence Mortality Lipid management Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of morbidity and mortality globally, accounting for nearly 19.8 million deaths in 2022 [ 1 ]. While statin therapy serves as the cornerstone of lipid management and secondary prevention, a substantial proportion of patients fail to achieve guideline-directed low-density lipoprotein cholesterol (LDL-C) targets on statin monotherapy. This residual risk leaves patients vulnerable to recurrent ischemic events, necessitating the addition of non-statin adjunctive therapies to the existing statin regimen. Current guidelines recommend ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors as the primary agents for treatment intensification in patients already receiving maximally tolerated statins [ 2 , 3 ]. Ezetimibe, which inhibits intestinal cholesterol absorption, typically provides an additional 13% to 20% reduction in LDL-C beyond statin therapy alone and has demonstrated utility in reducing non-fatal myocardial infarction and stroke in trials such as IMPROVE-IT [ 4 ]. Conversely, PCSK9 monoclonal antibodies-when added to background statin therapy- offer potent supplemental LDL-C reductions of 36% to 61% and have demonstrated significant reductions in major adverse cardiovascular events (MACE) in the FOURIER and ODYSSEY OUTCOMES trials [ 5 , 6 ]. Despite established efficacy in randomized controlled trials (RCTs), real-world data directly comparing the long-term survival benefits of these two distinct intensification strategies-where both cohorts are maintained on a statin background, remain limited. This study utilizes a large, global federated health research database to compare the real-world, long-term effectiveness of adding a PCSK9 inhibitor versus adding ezetimibe to baseline statin therapy in patients with established ASCVD, specifically assessing all-cause mortality, cardiovascular morbidity, and revascularization requirements over a 5-year follow-up period. Methods Data Source: This study utilized the TriNetX Global Collaborative Network, a federated health research platform comprising real-time, de-identified electronic medical records (EMRs) from 146 healthcare organizations (HCOs) across multiple countries. The database includes structured information on demographics, diagnoses, procedures, medications, and laboratory results. All data are de-identified and compliant with Section 164.514 of the Health Insurance Portability and Accountability Act (HIPAA) and the U.S. Department of Health and Human Services’ standards for anonymization. No Institutional Review Board (IRB) approval was required for this analysis of de-identified data. Study Design and Population: This was a retrospective cohort study in the period between January 1, 2018, and January 1, 2023, comparing clinical outcomes in adult patients (≥ 18 years) with established atherosclerotic cardiovascular disease (ASCVD) and concomitant statin therapy who were treated with either a PCSK9 inhibitor or ezetimibe. ASCVD was defined by ICD-10 codes for acute myocardial infarction, atherosclerotic heart disease, peripheral vascular disease, cerebral infarction, or a history of coronary revascularization occurring prior to or concurrent with the index medication prescription. The earliest date meeting criteria for the respective non-statin agent (PCSK9 inhibitor or ezetimibe) alongside statin therapy was designated as the index event. Patients were excluded from a cohort if they had a history of the comparator drug use before the index date. Patients were followed from the index date until the end of the defined time windows: 3 years and 5 years. Patients with outcomes prior to the index event were excluded from analysis for that specific outcome. Propensity Score Matching: To reduce baseline differences and to minimize confounding, 1:1 PSM was performed using logistic regression based on baseline variables across four domains – demographics (current age, age at index, sex, race), comorbidities (hypertension, diabetes mellitus, chronic kidney disease, chronic ischemic heart disease, heart failure, cerebrovascular disease, peripheral vascular disease, chronic lower respiratory diseases, overweight/obesity, nicotine dependence, and sleep apnea), medications (beta-blockers, ACE inhibitors/ARBs, antiplatelet agents, anticoagulants, and antidiabetic agents), and laboratory values and vitals (LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, hemoglobin A1c, creatinine, systolic and diastolic blood pressure, and body mass index). The TriNetX platform utilizes “greedy nearest-neighbor matching” for PSM with a caliper of 0.1 pooled standard deviation of the linear propensity scores to control for differences in the two cohorts. Standardized mean differences (SMDs) were used to assess balance for the covariates, with an SMD < 0.1 considered as well-balanced. Outcomes and Definitions: Clinical outcomes were identified using International Classification of Diseases (ICD)-10th edition codes and Current Procedural Terminology (CPT) codes. These included the primary outcome all-cause mortality and secondary outcomes including Major Adverse Cardiovascular Events (MACE), myocardial infarction (MI), stroke, heart failure exacerbation, all-cause hospital readmission, and coronary revascularization (PCI or CABG). Statistical Analysis: The primary analysis was a measure of association comparing event rates between groups at 3 years and 5 years post-index. Outcomes were expressed as event proportions and compared using odds ratios (ORs) with 95% confidence intervals (CIs). Statistical significance was defined as a two-sided p-value < 0.05. Survival analyses were conducted using Kaplan-Meier estimates with censoring at last known follow-up. All analyses were performed using the in-built TriNetX Analytics Platform (TriNetX, Inc.; Cambridge, MA, USA). Data visualization and figure generation were performed using Python (Version 3.10) with the Matplotlib and Seaborn libraries. Results Baseline Characteristics In the 5-year study period, 192,319 patients with established ASCVD met the inclusion criteria for receiving either ezetimibe (n=176,169) or a PCSK9 inhibitor (n=16,150) in addition to statin therapy. Before propensity score matching (PSM), the cohorts exhibited significant differences in baseline lipid profiles. The calculated mean LDL-C level for the PCSK9 inhibitor group was significantly higher than that of the ezetimibe group (114.2 ± 54.5 mg/dL vs. 98.9 ± 41.1 mg/dL, p<0.01), confirming that PCSK9 inhibitors were preferentially prescribed to a higher-risk phenotype. Following 1:1 PSM, 16,145 patients were identified in each group. While demographics, comorbidities, and concomitant medication use were generally well balanced, a significant imbalance in baseline LDL-C levels persisted despite matching (Standardized Difference 0.317). This persistent difference confirms that the matched cohorts retained systematic differences in disease severity consistent with channeling bias (Table 1). Table 1 Baseline Characteristics of ASCVD Patients concomitant statin therapy who were treated with either a PCSK9 inhibitor or ezetimibe Before and After Propensity Score Matching Before Propensity Matching After Propensity Matching Variable PCSK9 (n=16,150) Ezetimibe (n=176,169) P value Std Diff PCSK9 (n=16,145) Ezetimibe (n=16,145) P value Std Diff Demographics Age (Current), mean ± SD 70.2 ± 10.2 72.5 ± 10.6 <0.01 0.224 70.2 ± 10.2 70.1 ± 10.9 0.74 0.004 Age (Index), mean ± SD 65.7 ± 10.2 67.8 ± 10.7 <0.01 0.205 65.7 ± 10.2 65.6 ± 11.0 0.89 0.002 Female, % 38.00% 36.50% <0.01 0.032 38.00% 38.10% 0.93 0.001 Male, % 55.70% 60.40% <0.01 0.096 55.70% 56.00% 0.55 0.007 White Race, % 74.80% 68.00% <0.01 0.149 74.80% 75.30% 0.22 0.014 Asian Race, % 3.00% 5.70% <0.01 0.13 3.00% 3.00% 0.82 0.003 Unknown Race, % 11.70% 14.10% <0.01 0.072 11.70% 11.30% 0.2 0.014 Diagnoses (Comorbidities) Neoplasms, % 36.00% 36.00% 0.96 <0.001 36.00% 36.10% 0.78 0.003 Thyroid Disorders, % 23.50% 20.50% <0.01 0.073 23.50% 23.80% 0.63 0.005 Diabetes Mellitus, % 37.80% 40.60% <0.01 0.059 37.80% 37.10% 0.18 0.015 Chronic Lower Resp. Dis., % 27.20% 26.80% 0.28 0.009 27.20% 27.20% 0.91 0.001 Liver Diseases, % 13.20% 10.90% <0.01 0.071 13.20% 13.10% 0.84 0.002 Overweight & Obesity, % 31.00% 27.70% <0.01 0.073 31.00% 31.40% 0.51 0.007 Alcohol Related Disorders, % 3.50% 3.70% 0.15 0.012 3.50% 3.60% 0.47 0.008 Opioid Related Disorders, % 1.50% 1.40% 0.13 0.012 1.50% 1.50% 0.93 0.001 Cannabis Related Disorders, % 1.30% 1.40% 0.3 0.009 1.30% 1.40% 0.66 0.005 Other Stimulant Disorders, % 0.40% 0.30% 0.66 0.004 0.40% 0.30% 0.71 0.004 Nicotine Dependence, % 17.80% 16.90% <0.01 0.025 17.80% 17.60% 0.6 0.006 Hypertension, % 78.70% 75.30% <0.01 0.081 78.70% 78.70% 0.89 0.002 Chronic Ischemic Heart Dis, % 87.10% 77.70% <0.01 0.249 87.10% 86.60% 0.16 0.016 Cerebral Infarction, % 12.10% 13.60% <0.01 0.044 12.10% 11.60% 0.19 0.015 Atherosclerosis, % 16.60% 15.10% <0.01 0.041 16.60% 16.30% 0.53 0.007 Other Peripheral Vasc Dis, % 19.00% 16.80% <0.01 0.057 19.00% 19.10% 0.83 0.002 GERD, % 38.20% 34.70% <0.01 0.073 38.20% 37.80% 0.51 0.007 Chronic Kidney Disease, % 18.10% 21.10% <0.01 0.077 18.10% 17.80% 0.45 0.008 Sleep Apnea, % 25.20% 20.50% <0.01 0.111 25.20% 25.50% 0.55 0.007 Medications Beta Blockers, % 76.00% 68.00% <0.01 0.18 76.00% 75.90% 0.81 0.003 Alpha Blockers, % 16.70% 17.00% 0.33 0.008 16.70% 16.90% 0.6 0.006 Ca Channel Blockers, % 49.40% 45.00% <0.01 0.088 49.40% 49.00% 0.46 0.008 Antianginals, % 54.50% 44.70% <0.01 0.198 54.50% 54.50% 0.92 0.001 Antiarrhythmics, % 57.90% 50.40% <0.01 0.151 57.90% 57.90% 0.88 0.002 Antilipemic Agents, % 95.20% 85.40% <0.01 0.334 95.20% 94.70% 0.08 0.02 Diuretics, % 51.00% 47.00% <0.01 0.079 51.00% 51.00% 0.96 <0.001 ACE Inhibitors, % 42.90% 39.10% <0.01 0.078 42.90% 43.10% 0.82 0.003 Angiotensin II Inhibitors, % 36.10% 32.20% <0.01 0.083 36.10% 36.30% 0.77 0.003 Direct Renin Inhibitors, % 0.20% 0.20% 0.04 0.016 0.20% 0.20% 0.48 0.008 Rivaroxaban, % 5.80% 4.50% <0.01 0.059 5.80% 5.90% 0.76 0.003 Warfarin, % 7.50% 7.80% 0.13 0.013 7.50% 7.30% 0.58 0.006 Apixaban, % 9.70% 7.90% <0.01 0.065 9.70% 9.80% 0.91 0.001 Heparin, % 46.60% 39.50% <0.01 0.144 46.60% 46.10% 0.33 0.011 Aspirin, % 75.10% 66.10% <0.01 0.2 75.10% 75.00% 0.78 0.003 Clopidogrel, % 44.10% 35.50% <0.01 0.177 44.10% 43.60% 0.34 0.011 Insulin, % 31.70% 29.90% <0.01 0.038 31.70% 31.10% 0.33 0.011 Oral Hypoglycemics, % 27.40% 27.60% 0.53 0.005 27.40% 27.50% 0.86 0.002 Laboratory & Vitals at baseline Creatinine, mg/dL 1.1 ± 1.1 1.2 ± 1.6 <0.01 0.062 1.1 ± 1.1 1.1 ± 1.8 0.14 0.018 Glucose, mg/dL 121.6 ± 48.9 124.3 ± 52.5 <0.01 0.053 121.6 ± 48.9 122.2 ± 51.1 0.37 0.011 INR 1.1 ± 0.4 1.2 ± 0.5 <0.01 0.05 1.1 ± 0.4 1.2 ± 0.9 0.08 0.026 Total Cholesterol, mg/dL 193.2 ± 66.1 173.9 ± 50.6 <0.01 0.327 193.2 ± 66.1 174.9 ± 50.3 <0.01 0.311 LDL Cholesterol, mg/dL 114.2 ± 54.5 98.4 ± 41.6 <0.01 0.326 114.2 ± 54.5 98.9 ± 41.1 <0.01 0.317 HDL Cholesterol, mg/dL 44.3 ± 17.8 44.6 ± 17.3 0.07 0.017 44.3 ± 17.8 43.7 ± 17.8 <0.01 0.037 Triglycerides, mg/dL 180.3 ± 222.1 154.2 ± 133.3 <0.01 0.142 180.2 ± 222.1 159.6 ± 144.2 <0.01 0.11 Troponin I, ng/mL 2.7 ± 11.1 2.5 ± 12.6 0.21 0.023 2.7 ± 11.1 2.6 ± 14.3 0.61 0.012 BNP, pg/mL 372.6 ± 1035.8 479.0 ± 1832.7 <0.01 0.071 372.7 ± 1036.1 540.0 ± 2078.3 <0.01 0.102 HbA1c, % 6.6 ± 1.8 6.7 ± 1.7 <0.01 0.05 6.6 ± 1.8 6.6 ± 1.8 0.05 0.028 LVEF, % 55.8 ± 13.5 56.2 ± 13.6 0.16 0.029 55.8 ± 13.5 55.7 ± 13.9 0.66 0.012 Respiratory Rate, /min 16.6 ± 2.7 16.8 ± 2.8 <0.01 0.078 16.6 ± 2.7 16.8 ± 2.9 <0.01 0.048 Heart Rate, /min 72.7 ± 14.3 73.1 ± 14.1 0.01 0.026 72.7 ± 14.3 72.8 ± 14.2 0.51 0.009 Body Temperature, °F 96.2 ± 9.2 95.6 ± 10.9 <0.01 0.06 96.2 ± 9.3 95.6 ± 11.0 <0.01 0.061 Body Height, inches 67.1 ± 4.0 66.8 ± 4.1 <0.01 0.056 67.1 ± 4.0 67.0 ± 4.1 0.03 0.027 BMI, kg/m² 30.3 ± 6.1 30.1 ± 6.4 <0.01 0.034 30.3 ± 6.1 30.6 ± 6.5 <0.01 0.04 Systolic BP, mmHg 129.5 ± 19.5 128.3 ± 20.9 <0.01 0.059 129.5 ± 19.5 127.5 ± 20.1 <0.01 0.101 Diastolic BP, mmHg 73.8 ± 11.7 72.1 ± 12.7 <0.01 0.138 73.8 ± 11.7 72.6 ± 12.4 <0.01 0.101 Data are presented as frequency (percentage) or mean ± SD. All-Cause Mortality: The PCSK9 inhibitor cohort was associated with a lower all-cause mortality at each follow-up compared to the ezetimibe cohort. At 3 years, the PCSK9 inhibitor group demonstrated a 22% lower risk of mortality (OR: 0.78, p < 0.001; HR: 0.785, p < 0.001) (Table 2). This survival advantage was maintained at 5 years (OR: 0.777, p < 0.001; HR: 0.79, p < 0.001) (Table 3). Kaplan-Meier survival curves demonstrated survival differences between the PCSK9 inhibitor and ezetimibe groups over time (log-rank p < 0.001) (Figures 1 and 2) Table 2. Comparison of 3-year Clinical Outcomes Between PCSK9 inhibitors and ezetimibe with ASCVD and on statin therapy. Outcome PCSK9 Inhibitor Events / N (%) Ezetimibe Events / N (%) Odds Ratio (95% CI) P-Value (OR) Hazard Ratio (95% CI) P-Value All-Cause Mortality 918 / 16,085 (5.7%) 1,160 / 16,105 (7.2%) 0.780 (0.713–0.853) <0.001 0.785 (0.720–0.856) <0.001 All-Cause Readmission 1,191 / 4,622 (25.8%) 1,080 / 3,882 (27.8%) 0.901 (0.818–0.992) 0.033 0.939 (0.865–1.020) 0.135 Myocardial Infarction 804 / 11,583 (6.9%) 750 / 11,544 (6.5%) 1.073 (0.968–1.190) 0.177 1.060 (0.960–1.171) 0.249 Revascularization 581 / 12,576 (4.6%) 499 / 13,064 (3.8%) 1.220 (1.079–1.378) 0.001 1.202 (1.067–1.355) 0.002 Ischemic Stroke 548 / 14,103 (3.9%) 504 / 14,150 (3.6%) 1.095 (0.968–1.238) 0.151 1.085 (0.962–1.225) 0.185 Heart Failure Exacerbation 1,445 / 10,301 (14.0%) 1,445 / 10,139 (14.3%) 0.982 (0.907–1.062) 0.646 0.977 (0.908–1.050) 0.525 MACE 1,308 / 9,987 (13.1%) 1,386 / 10,014 (13.8%) 0.938 (0.865–1.018) 0.124 0.947 (0.878–1.021) 0.156 Table 3. Comparison of 5-year Clinical Outcomes Between PCSK9 inhibitors and ezetimibe with ASCVD and on statin therapy. Outcome PCSK9 Inhibitor Events / N (%) Ezetimibe Events / N (%) Odds Ratio (95% CI) P-Value (OR) Hazard Ratio (95% CI) P-Value All-Cause Mortality 1,202 / 16,085 (7.5%) 1,517 / 16,105 (9.4%) 0.777 (0.718–0.841) <0.001 0.789 (0.731–0.851) <0.001 All-Cause Readmission 1,391 / 4,622 (30.1%) 1,267 / 3,882 (32.6%) 0.889 (0.811–0.974) 0.012 0.946 (0.877–1.021) 0.154 Myocardial Infarction 1,025 / 11,583 (8.8%) 929 / 11,544 (8.0%) 1.109 (1.011–1.217) 0.028 1.101 (1.007–1.203) 0.034 Revascularization 703 / 12,576 (5.6%) 617 / 13,064 (4.7%) 1.194 (1.069–1.335) 0.002 1.182 (1.061–1.317) 0.002 Ischemic Stroke 682 / 14,103 (4.8%) 659 / 14,150 (4.7%) 1.040 (0.932–1.161) 0.48 1.037 (0.931–1.154) 0.511 Heart Failure Exacerbation 1,744 / 10,301 (16.9%) 1,719 / 10,139 (17.0%) 0.998 (0.928–1.074) 0.964 0.996 (0.932–1.065) 0.909 MACE 1,634 / 9,987 (16.4%) 1,733 / 10,014 (17.3%) 0.935 (0.868–1.007) 0.074 0.954 (0.892–1.021) 0.172 Figure.1 Kaplan-Meier survival analysis comparing 3-year all-cause mortality in matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe Figure.2 Kaplan-Meier survival analysis comparing 5-year all-cause mortality in matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe Ischemic and Revascularization Outcomes: Despite the observed survival benefit, the PCSK9 inhibitor group was associated with higher rates of specific ischemic events and procedural interventions. The risk of myocardial infarction (MI) was higher in the PCSK9 inhibitor group at 5 years (OR: 1.109, p = 0.002; HR: 1.101, p = 0.03) (Figures 3 and 4). Similarly, a sustained higher risk for coronary revascularization was observed in the PCSK9 inhibitor group over both follow-up periods: at 3 years (OR: 1.22, p = 0.01; HR: 1.202, p = 0.002) and at 5 years (OR: 1.194, p = 0.002; HR: 1.182, p = 0.002) (Figures 5 and 6). Figure.3 Kaplan-Meier curve comparing 3-year myocardial infarction rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe Figure.4 Kaplan-Meier curve comparing 5-year myocardial infarction rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe Figure. 5 Kaplan-Meier curve comparing 3-year revascularization rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe Figure.6 Figure Kaplan-Meier curve comparing 5-year revascularization rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe Readmission and Other Cardiovascular Outcomes: All-cause readmission occurred less frequently in the PCSK9 inhibitor group compared to the ezetimibe group at both assessment points. A statistically significant reduction in readmission risk was observed at 3 years (OR: 0.901, p = 0.03) and 5 years (OR: 0.889, p = 0.012). Regarding other cardiovascular outcomes, no statistically significant differences were observed between the PCSK9 inhibitor and ezetimibe groups for the composite Major Adverse Cardiovascular Events (MACE), stroke, or heart failure exacerbation at either the 3-year or 5-year follow-up intervals (Figure7) Discussion In this large-scale, propensity score–matched retrospective cohort study, we evaluated the real-world utilization and clinical outcomes of PCSK9 inhibitors compared with ezetimibe among statin-treated patients with established ASCVD. The primary observation was a discordant pattern of associations, with PCSK9 inhibitor use associated with an apparent reduction in all-cause mortality and hospital readmissions, alongside a higher incidence of myocardial infarction and coronary revascularization. These findings must be interpreted collectively, as they strongly suggest the influence of residual confounding rather than opposing causal effects. The observed association with lower all-cause mortality warrants cautious interpretation, as it contrasts with evidence from randomized controlled trials (RCTs). Large RCTs such as FOURIER and ODYSSEY OUTCOMES were powered to detect reductions in major adverse cardiovascular events and adjudicated cardiovascular mortality. Although these trials demonstrated robust reductions in LDL-C and ischemic outcomes, they did not show a consistent or definitive reduction in all-cause mortality during their primary follow-up periods [ 5 , 6 ]. The magnitude of the mortality association observed in this analysis (22% reduction) exceeds the level of evidence established by these Level 1 studies and therefore cannot be interpreted as a treatment effect. This discrepancy highlights a fundamental limitation of observational data: the inability to fully account for channeling bias and the healthy user effect. In RCTs, randomization balances both measured and unmeasured socioeconomic and behavioral factors. In contrast, real-world prescribing patterns reflect differential access to care, whereby patients receiving PCSK9 inhibitors often have unmeasured survival advantages, including higher socioeconomic status, greater health literacy, stronger medication adherence, and more consistent access to preventive and specialty care compared with those prescribed ezetimibe [ 10 ]. Consequently, the observed association with lower all-cause mortality likely reflects these non-cardiovascular survival advantages rather than a direct pharmacologic effect of PCSK9 inhibition. Despite the likely influence of bias on mortality outcomes, the biological effects of PCSK9 inhibitors on lipid parameters are well established. Consistent with the Cholesterol Treatment Trialists’ (CTT) Collaboration, reductions in vascular risk are proportional to the absolute magnitude of LDL-C lowering [ 11 ]. In this study, PCSK9 inhibitors achieved substantially greater LDL-C reductions compared with ezetimibe [ 12 , 13 , 14 ]. Furthermore, intravascular imaging studies such as GLAGOV and PACMAN-AMI have demonstrated that PCSK9 inhibition promotes plaque regression and increases fibrous cap thickness [ 15 , 16 , 17 ]. PCSK9 inhibitors also reduce lipoprotein(a) [Lp(a)] levels by approximately 20–25% [ 18 , 19 ]. Elevated Lp(a) is an independent driver of ASCVD mortality [ 20 ], and its reduction may contribute to residual cardiovascular risk modification [ 21 ]. However, these mechanistic findings do not validate the mortality association observed in this study. The higher rates of non-fatal myocardial infarction and coronary revascularization observed among PCSK9 inhibitor users further support the presence of confounding by indication [ 22 ]. In clinical practice, PCSK9 inhibitors are preferentially prescribed to patients with more severe disease phenotypes, including multivessel coronary disease or refractory hyperlipidemia [ 23 , 24 ]. Baseline characteristics in our study confirm this systematic difference: even after propensity score matching, the PCSK9 cohort retained significantly higher baseline LDL-C levels [ 25 ]. This persistent imbalance suggests a higher residual burden of atherosclerotic risk, plausibly driving the increased incidence of ischemic events [ 26 , 27 ]. The coexistence of higher ischemic event rates and lower all-cause mortality within the same cohort is biologically inconsistent with a unidirectional treatment effect and instead reflects the complex interplay of residual confounding, channeling bias, and unmeasured socioeconomic factors (the healthy adherer effect) [ 28 ]. The observed reduction in all-cause hospital readmissions among patients treated with PCSK9 inhibitors is clinically relevant, given that ASCVD-related readmissions represent a substantial driver of healthcare utilization and costs [ 29 ]. While PCSK9 inhibitors have historically been scrutinized for high acquisition costs, recent price reductions and the potential to reduce expensive hospitalizations may improve their cost-effectiveness in selected high-risk populations [ 30 , 31 ]. Our findings suggest that, in real-world practice, higher upfront medication costs may be partially offset by reduced healthcare resource utilization [ 32 ]. However, as with mortality outcomes, this association should be interpreted cautiously due to the influence of unmeasured confounders. Limitations These findings must be interpreted within the context of several important methodological limitations [ 33 ]. First, despite propensity score matching, baseline LDL-C levels remained imbalanced between groups, indicating incomplete comparability. Second, reliance on ICD-10 coding introduces the potential for misclassification of comorbidities and clinical outcomes [ 34 ]. Third, all-cause mortality was used as the primary survival endpoint because the TriNetX analytic platform applies Boolean “OR” logic to outcome definitions and does not support temporal linkage required for reliable adjudication of cardiovascular death [ 35 ]. As a result, the observed mortality association cannot be attributed specifically to cardiovascular causes or lipid-lowering effects. Finally, although PCSK9 inhibitors are generally well tolerated, we were unable to account for statin-associated adverse effects or differences in adherence to background lipid-lowering therapy that may have influenced outcomes [ 36 ]. Despite these limitations, this study leverages a large, global real-world dataset to provide complementary evidence to randomized trials by characterizing outcomes across a broad, generalizable population treated in routine clinical practice. Conclusion In this real-world retrospective cohort, PCSK9 inhibitor use was associated with an apparent reduction in all-cause mortality and hospital readmissions compared with ezetimibe, alongside a higher incidence of non-fatal ischemic events. These discordant findings should not be interpreted as evidence of therapeutic superiority or causal benefit. Rather, they underscore the substantial influence of channeling bias and residual confounding inherent in observational lipid-lowering research. These results are hypothesis-generating and highlight the need for future real-world studies incorporating cause-specific mortality adjudication and detailed measures of disease severity and social determinants of health to disentangle pharmacologic effects from socioeconomic and structural factors influencing access to advanced lipid-lowering therapies. Declarations Disclosure: The authors have no conflicts of interest to declare. Ethics Approval: This study utilized the TriNetX Global Collaborative Network containing de-identified patient data. The study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. As the data is de-identified, the study was deemed exempt from full Institutional Review Board (IRB) review. Consent to Participate Informed consent was waived due to the retrospective nature of the study and the use of de-identified data. Consent for Publication Not applicable. Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests The authors have no relevant financial or non-financial interests to disclose. Author Contribution All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Krutagni Mehta, Ritu Tated, and Rafey Feroze. Figure 7 was prepared by Akash Singh. The first draft of the manuscript was written by Krutagni Mehta, Ritu Tated, and Umang Gupta. Critical revision for important intellectual content was performed by Sameh Elias, Saurabh Sharma, Rafey Feroze, and Shilp Arora. All authors read and approved the final manuscript. Acknowledgments: None declared. Data Availability Data are available from TriNetX (Cambridge, MA) for researchers who meet the data access requirements. 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BMJ 333(7578):1091. 10.1136/bmj.38985.646481.55 Navarese EP, Robinson JG, Kowalewski M et al (2018) Association between baseline LDL-C level and total and cardiovascular mortality after LDL-C lowering: a systematic review and meta-analysis. JAMA 319(15):1566–1579. 10.1001/jama.2018.2525 Wang G, Zhang Z, Ayala C et al (2014) Costs of hospitalization for stroke patients aged 18–64 years in the United States. J Stroke Cerebrovasc Dis 23(5):1062–1069. 10.1016/j.jstrokecerebrovasdis.2013.09.001 Kazi DS, Penko J, Coxson PG et al (2019) Cost-effectiveness of alirocumab: a just-in-time analysis based on the ODYSSEY OUTCOMES trial. Ann Intern Med 170(4):221–229. 10.7326/M18-1776 Fonarow GC, Keech AC, Pedersen TR et al (2017) Cost-effectiveness of evolocumab therapy for reducing cardiovascular events in patients with atherosclerotic cardiovascular disease. JAMA Cardiol 2(10):1069–1078. 10.1001/jamacardio.2017.2762 Annemans L, Packard CJ, Briggs A, Ray KK (2020) Cost-effectiveness of PCSK9 inhibitors in Europe: an economic analysis of the ODYSSEY OUTCOMES trial. Eur Heart J Qual Care Clin Outcomes 6(4):259–266. 10.1093/ehjqcco/qcz061 Fermann JL, Peterson SE (2022) Electronic medical record data limitations and their implications for clinical research. Cureus 14(9):e28886. 10.7759/cureus.28886 Birman-Deych E, Waterman AD, Yan Y et al (2005) Accuracy of ICD-9-CM codes for identifying cardiovascular and stroke risk factors. Med Care 43(5):480–485. 10.1097/01.mlr.0000160417.39497.a9 Benjamin EJ, Virani SS, Callaway CW et al (2018) Heart disease and stroke statistics—2018 update: a report from the American Heart Association. Circulation 137(12):e67–e492. 10.1161/CIR.0000000000000558 Collins R, Reith C, Emberson J et al (2016) Interpretation of the evidence for the efficacy and safety of statin therapy. Lancet 388(10059):2532–2561. 10.1016/S0140-6736(16)31357-5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-8606687","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":585664238,"identity":"d86efad9-54b0-4a64-9c74-22b479f7072a","order_by":0,"name":"Krutagni 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shilp","middleName":"","lastName":"Arora","suffix":""}],"badges":[],"createdAt":"2026-01-15 04:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8606687/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8606687/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102296775,"identity":"933fa58b-6fd3-4cbb-9ba0-af574909c3a2","added_by":"auto","created_at":"2026-02-10 10:21:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":72541,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKaplan-Meier survival analysis comparing 3-year all-cause mortality in matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/fae47dd945f6d6717026d306.png"},{"id":102181165,"identity":"c23a755e-bbbe-4c14-8e24-2a307cb55a49","added_by":"auto","created_at":"2026-02-09 07:16:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":75086,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKaplan-Meier survival analysis comparing 5-year all-cause mortality in matched ASCVD patients treated with statin + PCSK9 inhibitor versus\u003c/em\u003e \u003cem\u003estatin + ezetimibe\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/a9331dba0935f2b3f390a4dd.png"},{"id":102181167,"identity":"c8a51431-c09c-4f83-97c8-adf2dab12b4c","added_by":"auto","created_at":"2026-02-09 07:16:20","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":68945,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKaplan-Meier curve comparing 3-year myocardial infarction rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus\u003c/em\u003e \u003cem\u003estatin + ezetimibe\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/069aaf358c8a3729f15f02de.png"},{"id":102181170,"identity":"9d623b6f-6ce0-4ee2-800a-970fad0fe8d2","added_by":"auto","created_at":"2026-02-09 07:16:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":75977,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKaplan-Meier curve comparing 5-year myocardial infarction rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/22e076ad6e7f8b44a9bb989f.png"},{"id":102181172,"identity":"9214b53d-6664-4b97-89d8-a15f6991bca3","added_by":"auto","created_at":"2026-02-09 07:16:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":64131,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eKaplan-Meier curve comparing 3-year revascularization rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus\u003c/em\u003e \u003cem\u003estatin + ezetimibe\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/18815df0a10f10e7ca098e77.png"},{"id":102181169,"identity":"88148904-9ae3-426d-beb1-6c94c8179f15","added_by":"auto","created_at":"2026-02-09 07:16:20","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":66692,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eFigure Kaplan-Meier curve comparing 5-year revascularization rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/361528faf1e1a34974b23f0d.png"},{"id":102181171,"identity":"94299f30-2e50-49f9-9564-17cee2151703","added_by":"auto","created_at":"2026-02-09 07:16:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":153061,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eForest plots displaying Hazard Ratios (HR) with 95% Confidence Intervals (CI) for clinical outcomes at 3-year (Top) and 5-year (Bottom) follow-up. The vertical dashed line represents an HR of 1.0. Values to the left favor PCSK9 inhibitors, and values to the right favor ezetimibe.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/9242b6ac67942d35ab9d1104.png"},{"id":104401394,"identity":"fff174d1-ec04-40a9-88d4-c6f28f894ceb","added_by":"auto","created_at":"2026-03-11 12:12:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1359324,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8606687/v1/3fccdcf9-acb6-4718-973e-cbda8bd07890.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Long-term Effectiveness of PCSK9 Inhibitors versus Ezetimibe as Adjunctive Therapy to Statins in Patients with Atherosclerotic Cardiovascular Disease: A TriNetX Database Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAtherosclerotic cardiovascular disease (ASCVD) remains the leading cause of morbidity and mortality globally, accounting for nearly 19.8\u0026nbsp;million deaths in 2022 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While statin therapy serves as the cornerstone of lipid management and secondary prevention, a substantial proportion of patients fail to achieve guideline-directed low-density lipoprotein cholesterol (LDL-C) targets on statin monotherapy. This residual risk leaves patients vulnerable to recurrent ischemic events, necessitating the addition of non-statin adjunctive therapies to the existing statin regimen. Current guidelines recommend ezetimibe and proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors as the primary agents for treatment intensification in patients already receiving maximally tolerated statins [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Ezetimibe, which inhibits intestinal cholesterol absorption, typically provides an additional 13% to 20% reduction in LDL-C beyond statin therapy alone and has demonstrated utility in reducing non-fatal myocardial infarction and stroke in trials such as IMPROVE-IT [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Conversely, PCSK9 monoclonal antibodies-when added to background statin therapy- offer potent supplemental LDL-C reductions of 36% to 61% and have demonstrated significant reductions in major adverse cardiovascular events (MACE) in the FOURIER and ODYSSEY OUTCOMES trials [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Despite established efficacy in randomized controlled trials (RCTs), real-world data directly comparing the long-term survival benefits of these two distinct intensification strategies-where both cohorts are maintained on a statin background, remain limited. This study utilizes a large, global federated health research database to compare the real-world, long-term effectiveness of adding a PCSK9 inhibitor versus adding ezetimibe to baseline statin therapy in patients with established ASCVD, specifically assessing all-cause mortality, cardiovascular morbidity, and revascularization requirements over a 5-year follow-up period.\u003c/p\u003e "},{"header":"Methods","content":" \u003cp\u003eData Source: This study utilized the TriNetX Global Collaborative Network, a federated health research platform comprising real-time, de-identified electronic medical records (EMRs) from 146 healthcare organizations (HCOs) across multiple countries. The database includes structured information on demographics, diagnoses, procedures, medications, and laboratory results. All data are de-identified and compliant with Section 164.514 of the Health Insurance Portability and Accountability Act (HIPAA) and the U.S. Department of Health and Human Services\u0026rsquo; standards for anonymization. No Institutional Review Board (IRB) approval was required for this analysis of de-identified data.\u003c/p\u003e \u003cp\u003eStudy Design and Population: This was a retrospective cohort study in the period between January 1, 2018, and January 1, 2023, comparing clinical outcomes in adult patients (\u0026ge;\u0026thinsp;18 years) with established atherosclerotic cardiovascular disease (ASCVD) and concomitant statin therapy who were treated with either a PCSK9 inhibitor or ezetimibe. ASCVD was defined by ICD-10 codes for acute myocardial infarction, atherosclerotic heart disease, peripheral vascular disease, cerebral infarction, or a history of coronary revascularization occurring prior to or concurrent with the index medication prescription. The earliest date meeting criteria for the respective non-statin agent (PCSK9 inhibitor or ezetimibe) alongside statin therapy was designated as the index event. Patients were excluded from a cohort if they had a history of the comparator drug use before the index date. Patients were followed from the index date until the end of the defined time windows: 3 years and 5 years. Patients with outcomes prior to the index event were excluded from analysis for that specific outcome.\u003c/p\u003e \u003cp\u003ePropensity Score Matching: To reduce baseline differences and to minimize confounding, 1:1 PSM was performed using logistic regression based on baseline variables across four domains \u0026ndash; demographics (current age, age at index, sex, race), comorbidities (hypertension, diabetes mellitus, chronic kidney disease, chronic ischemic heart disease, heart failure, cerebrovascular disease, peripheral vascular disease, chronic lower respiratory diseases, overweight/obesity, nicotine dependence, and sleep apnea), medications (beta-blockers, ACE inhibitors/ARBs, antiplatelet agents, anticoagulants, and antidiabetic agents), and laboratory values and vitals (LDL cholesterol, HDL cholesterol, total cholesterol, triglycerides, hemoglobin A1c, creatinine, systolic and diastolic blood pressure, and body mass index). The TriNetX platform utilizes \u0026ldquo;greedy nearest-neighbor matching\u0026rdquo; for PSM with a caliper of 0.1 pooled standard deviation of the linear propensity scores to control for differences in the two cohorts. Standardized mean differences (SMDs) were used to assess balance for the covariates, with an SMD\u0026thinsp;\u0026lt;\u0026thinsp;0.1 considered as well-balanced.\u003c/p\u003e \u003cp\u003eOutcomes and Definitions: Clinical outcomes were identified using International Classification of Diseases (ICD)-10th edition codes and Current Procedural Terminology (CPT) codes. These included the primary outcome all-cause mortality and secondary outcomes including Major Adverse Cardiovascular Events (MACE), myocardial infarction (MI), stroke, heart failure exacerbation, all-cause hospital readmission, and coronary revascularization (PCI or CABG).\u003c/p\u003e \u003cp\u003eStatistical Analysis: The primary analysis was a measure of association comparing event rates between groups at 3 years and 5 years post-index. Outcomes were expressed as event proportions and compared using odds ratios (ORs) with 95% confidence intervals (CIs). Statistical significance was defined as a two-sided p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Survival analyses were conducted using Kaplan-Meier estimates with censoring at last known follow-up. All analyses were performed using the in-built TriNetX Analytics Platform (TriNetX, Inc.; Cambridge, MA, USA). Data visualization and figure generation were performed using Python (Version 3.10) with the Matplotlib and Seaborn libraries.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eBaseline Characteristics\u0026nbsp;In the 5-year study period, 192,319 patients with established ASCVD met the inclusion criteria for receiving either ezetimibe (n=176,169) or a PCSK9 inhibitor (n=16,150) in addition to statin therapy. Before propensity score matching (PSM), the cohorts exhibited significant differences in baseline lipid profiles. The calculated mean LDL-C level for the PCSK9 inhibitor group was significantly higher than that of the ezetimibe group (114.2 \u0026plusmn; 54.5 mg/dL vs. 98.9 \u0026plusmn; 41.1 mg/dL, p\u0026lt;0.01), confirming that PCSK9 inhibitors were preferentially prescribed to a higher-risk phenotype.\u003c/p\u003e\n\u003cp\u003eFollowing 1:1 PSM, 16,145 patients were identified in each group. While demographics, comorbidities, and concomitant medication use were generally well balanced, a significant imbalance in baseline LDL-C levels persisted despite matching (Standardized Difference 0.317). This persistent difference confirms that the matched cohorts retained systematic differences in disease severity consistent with channeling bias (Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1 Baseline Characteristics of ASCVD Patients concomitant statin therapy who were treated with either a PCSK9 inhibitor or ezetimibe Before and After Propensity Score Matching\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"732\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 310px;\"\u003e\n \u003cp\u003eBefore Propensity Matching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"bottom\" style=\"width: 297px;\"\u003e\n \u003cp\u003eAfter Propensity Matching\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePCSK9\u003c/p\u003e\n \u003cp\u003e(n=16,150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003eEzetimibe\u003c/p\u003e\n \u003cp\u003e(n=176,169)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eStd Diff\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003ePCSK9\u003c/p\u003e\n \u003cp\u003e(n=16,145)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003eEzetimibe\u003c/p\u003e\n \u003cp\u003e(n=16,145)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003eStd Diff\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDemographics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAge (Current), mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e70.2 \u0026plusmn; 10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e72.5 \u0026plusmn; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.224\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e70.2 \u0026plusmn; 10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e70.1 \u0026plusmn; 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAge (Index), mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e65.7 \u0026plusmn; 10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e67.8 \u0026plusmn; 10.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e65.7 \u0026plusmn; 10.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e65.6 \u0026plusmn; 11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eFemale, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e38.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e36.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e38.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e38.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eMale, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e55.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e60.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e55.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e56.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eWhite Race, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e74.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e68.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e74.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e75.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAsian Race, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e5.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e3.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e3.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eUnknown Race, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e11.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e14.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e11.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e11.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDiagnoses (Comorbidities)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eNeoplasms, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e36.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e36.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e36.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e36.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eThyroid Disorders, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e23.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e20.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e23.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e23.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDiabetes Mellitus, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e37.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e40.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e37.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e37.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eChronic Lower Resp. Dis., %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e27.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e26.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e27.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e27.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eLiver Diseases, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e13.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e10.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e13.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e13.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eOverweight \u0026amp; Obesity, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e31.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e27.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e31.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e31.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAlcohol Related Disorders, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e3.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e3.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e3.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e3.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eOpioid Related Disorders, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCannabis Related Disorders, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eOther Stimulant Disorders, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eNicotine Dependence, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e17.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e17.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHypertension, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e78.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e75.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e78.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e78.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eChronic Ischemic Heart Dis, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e87.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e77.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e87.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e86.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCerebral Infarction, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e12.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e13.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e12.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e11.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAtherosclerosis, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e16.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e15.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e16.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eOther Peripheral Vasc Dis, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e19.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e19.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eGERD, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e38.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e34.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e38.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e37.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eChronic Kidney Disease, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e18.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e21.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e17.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSleep Apnea, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e25.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e20.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e25.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e25.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eMedications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eBeta Blockers, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e76.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e68.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e76.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e75.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAlpha Blockers, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e16.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e17.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e16.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCa Channel Blockers, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e49.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e45.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.088\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e49.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e49.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAntianginals, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e54.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e44.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e54.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e54.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAntiarrhythmics, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e57.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e50.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e57.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e57.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAntilipemic Agents, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e95.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e85.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e95.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e94.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDiuretics, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e51.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e47.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e51.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e51.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eACE Inhibitors, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e42.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e39.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e42.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e43.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAngiotensin II Inhibitors, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e36.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e32.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e36.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e36.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDirect Renin Inhibitors, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e0.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e0.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e0.20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eRivaroxaban, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e5.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e4.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e5.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e5.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eWarfarin, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e7.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e7.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e7.30%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eApixaban, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e9.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e7.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e9.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e9.80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHeparin, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e46.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e39.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e46.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e46.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eAspirin, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e75.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e66.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e75.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e75.00%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eClopidogrel, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e44.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e35.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e44.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e43.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eInsulin, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e31.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e29.90%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e31.70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e31.10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eOral Hypoglycemics, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e27.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e27.60%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e27.40%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e27.50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eLaboratory \u0026amp; Vitals at baseline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eCreatinine, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.1 \u0026plusmn; 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.2 \u0026plusmn; 1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.1 \u0026plusmn; 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.1 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eGlucose, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e121.6 \u0026plusmn; 48.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e124.3 \u0026plusmn; 52.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e121.6 \u0026plusmn; 48.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e122.2 \u0026plusmn; 51.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eINR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.1 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e1.2 \u0026plusmn; 0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e1.1 \u0026plusmn; 0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e1.2 \u0026plusmn; 0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTotal Cholesterol, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e193.2 \u0026plusmn; 66.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e173.9 \u0026plusmn; 50.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.327\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e193.2 \u0026plusmn; 66.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e174.9 \u0026plusmn; 50.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eLDL Cholesterol, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e114.2 \u0026plusmn; 54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e98.4 \u0026plusmn; 41.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e114.2 \u0026plusmn; 54.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e98.9 \u0026plusmn; 41.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHDL Cholesterol, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e44.3 \u0026plusmn; 17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e44.6 \u0026plusmn; 17.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e44.3 \u0026plusmn; 17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e43.7 \u0026plusmn; 17.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTriglycerides, mg/dL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e180.3 \u0026plusmn; 222.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e154.2 \u0026plusmn; 133.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.142\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e180.2 \u0026plusmn; 222.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e159.6 \u0026plusmn; 144.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eTroponin I, ng/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e2.7 \u0026plusmn; 11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e2.5 \u0026plusmn; 12.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e2.7 \u0026plusmn; 11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e2.6 \u0026plusmn; 14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eBNP, pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e372.6 \u0026plusmn; 1035.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e479.0 \u0026plusmn; 1832.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e372.7 \u0026plusmn; 1036.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e540.0 \u0026plusmn; 2078.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.102\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHbA1c, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e6.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e6.7 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e6.6 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eLVEF, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e55.8 \u0026plusmn; 13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e56.2 \u0026plusmn; 13.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e55.8 \u0026plusmn; 13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e55.7 \u0026plusmn; 13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eRespiratory Rate, /min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e16.6 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e16.8 \u0026plusmn; 2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.078\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.6 \u0026plusmn; 2.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e16.8 \u0026plusmn; 2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eHeart Rate, /min\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e72.7 \u0026plusmn; 14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e73.1 \u0026plusmn; 14.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e72.7 \u0026plusmn; 14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e72.8 \u0026plusmn; 14.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eBody Temperature, \u0026deg;F\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e96.2 \u0026plusmn; 9.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e95.6 \u0026plusmn; 10.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e96.2 \u0026plusmn; 9.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e95.6 \u0026plusmn; 11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eBody Height, inches\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e67.1 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e66.8 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e67.1 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e67.0 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eBMI, kg/m\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e30.3 \u0026plusmn; 6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e30.1 \u0026plusmn; 6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e30.3 \u0026plusmn; 6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e30.6 \u0026plusmn; 6.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eSystolic BP, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e129.5 \u0026plusmn; 19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e128.3 \u0026plusmn; 20.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e129.5 \u0026plusmn; 19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e127.5 \u0026plusmn; 20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 125px;\"\u003e\n \u003cp\u003eDiastolic BP, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 90px;\"\u003e\n \u003cp\u003e73.8 \u0026plusmn; 11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e72.1 \u0026plusmn; 12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 70px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e0.138\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 79px;\"\u003e\n \u003cp\u003e73.8 \u0026plusmn; 11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 82px;\"\u003e\n \u003cp\u003e72.6 \u0026plusmn; 12.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 71px;\"\u003e\n \u003cp\u003e0.101\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eData are presented as frequency (percentage) or mean \u0026plusmn; SD.\u003c/p\u003e\n\u003cp\u003eAll-Cause Mortality: The PCSK9 inhibitor cohort was associated with a lower all-cause mortality at each follow-up compared to the ezetimibe cohort. At 3 years, the PCSK9 inhibitor group demonstrated a 22% lower risk of mortality (OR: 0.78, p \u0026lt; 0.001; HR: 0.785, p \u0026lt; 0.001) (Table 2). This survival advantage was maintained at 5 years (OR: 0.777, p \u0026lt; 0.001; HR: 0.79, p \u0026lt; 0.001) (Table 3). Kaplan-Meier survival curves demonstrated survival differences between the PCSK9 inhibitor and ezetimibe groups over time (log-rank p \u0026lt; 0.001) (Figures 1 and 2)\u003c/p\u003e\n\u003cp\u003eTable 2. Comparison of 3-year Clinical Outcomes Between PCSK9 inhibitors and ezetimibe with ASCVD and on statin therapy.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"738\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003ePCSK9 Inhibitor Events / N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eEzetimibe Events / N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003eP-Value (OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003eP-Value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAll-Cause Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e918 / 16,085 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,160 / 16,105 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.780 (0.713\u0026ndash;0.853)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.785 (0.720\u0026ndash;0.856)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eAll-Cause Readmission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,191 / 4,622 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,080 / 3,882 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.901 (0.818\u0026ndash;0.992)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.033\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.939 (0.865\u0026ndash;1.020)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.135\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMyocardial Infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e804 / 11,583 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e750 / 11,544 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.073 (0.968\u0026ndash;1.190)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.177\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.060 (0.960\u0026ndash;1.171)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eRevascularization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e581 / 12,576 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e499 / 13,064 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.220 (1.079\u0026ndash;1.378)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.202 (1.067\u0026ndash;1.355)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eIschemic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e548 / 14,103 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e504 / 14,150 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.095 (0.968\u0026ndash;1.238)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e1.085 (0.962\u0026ndash;1.225)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eHeart Failure Exacerbation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,445 / 10,301 (14.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,445 / 10,139 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.982 (0.907\u0026ndash;1.062)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.646\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.977 (0.908\u0026ndash;1.050)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003eMACE\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,308 / 9,987 (13.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1,386 / 10,014 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.938 (0.865\u0026ndash;1.018)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 72px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 102px;\"\u003e\n \u003cp\u003e0.947 (0.878\u0026ndash;1.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 3. Comparison of 5-year Clinical Outcomes Between PCSK9 inhibitors and ezetimibe with ASCVD and on statin therapy.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"726\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePCSK9 Inhibitor Events / N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEzetimibe Events / N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eOdds Ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP-Value (OR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHazard Ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eP-Value\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAll-Cause Mortality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,202 / 16,085 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,517 / 16,105 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.777 (0.718\u0026ndash;0.841)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.789 (0.731\u0026ndash;0.851)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAll-Cause Readmission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,391 / 4,622 (30.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,267 / 3,882 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.889 (0.811\u0026ndash;0.974)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.946 (0.877\u0026ndash;1.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMyocardial Infarction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,025 / 11,583 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e929 / 11,544 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.109 (1.011\u0026ndash;1.217)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.101 (1.007\u0026ndash;1.203)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRevascularization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e703 / 12,576 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e617 / 13,064 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.194 (1.069\u0026ndash;1.335)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.182 (1.061\u0026ndash;1.317)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eIschemic Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e682 / 14,103 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e659 / 14,150 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.040 (0.932\u0026ndash;1.161)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1.037 (0.931\u0026ndash;1.154)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHeart Failure Exacerbation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,744 / 10,301 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,719 / 10,139 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.998 (0.928\u0026ndash;1.074)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.964\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.996 (0.932\u0026ndash;1.065)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.909\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMACE\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,634 / 9,987 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1,733 / 10,014 (17.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.935 (0.868\u0026ndash;1.007)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.954 (0.892\u0026ndash;1.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eFigure.1 Kaplan-Meier survival analysis comparing 3-year all-cause mortality in matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure.2 Kaplan-Meier survival analysis comparing 5-year all-cause mortality in matched ASCVD patients treated with statin + PCSK9 inhibitor versus\u003c/em\u003e \u003cem\u003estatin + ezetimibe\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIschemic and Revascularization Outcomes: Despite the observed survival benefit, the PCSK9 inhibitor group was associated with higher rates of specific ischemic events and procedural interventions. The risk of myocardial infarction (MI) was higher in the PCSK9 inhibitor group at 5 years (OR: 1.109, p = 0.002; HR: 1.101, p = 0.03) (Figures 3 and 4). Similarly, a sustained higher risk for coronary revascularization was observed in the PCSK9 inhibitor group over both follow-up periods: at 3 years (OR: 1.22, p = 0.01; HR: 1.202, p = 0.002) and at 5 years (OR: 1.194, p = 0.002; HR: 1.182, p = 0.002) (Figures 5 and 6).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure.3 Kaplan-Meier curve comparing 3-year myocardial infarction rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus\u003c/em\u003e \u003cem\u003estatin + ezetimibe\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure.4 Kaplan-Meier curve comparing 5-year myocardial infarction rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure. 5 Kaplan-Meier curve comparing 3-year revascularization rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus\u003c/em\u003e \u003cem\u003estatin + ezetimibe\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFigure.6 Figure Kaplan-Meier curve comparing 5-year revascularization rates between matched ASCVD patients treated with statin + PCSK9 inhibitor versus statin + ezetimibe\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eReadmission and Other Cardiovascular Outcomes: All-cause readmission occurred less frequently in the PCSK9 inhibitor group compared to the ezetimibe group at both assessment points. A statistically significant reduction in readmission risk was observed at 3 years (OR: 0.901, p = 0.03) and 5 years (OR: 0.889, p = 0.012). Regarding other cardiovascular outcomes, no statistically significant differences were observed between the PCSK9 inhibitor and ezetimibe groups for the composite Major Adverse Cardiovascular Events (MACE), stroke, or heart failure exacerbation at either the 3-year or 5-year follow-up intervals (Figure7)\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":" \u003cp\u003eIn this large-scale, propensity score\u0026ndash;matched retrospective cohort study, we evaluated the real-world utilization and clinical outcomes of PCSK9 inhibitors compared with ezetimibe among statin-treated patients with established ASCVD. The primary observation was a discordant pattern of associations, with PCSK9 inhibitor use associated with an \u003cem\u003eapparent\u003c/em\u003e reduction in all-cause mortality and hospital readmissions, alongside a higher incidence of myocardial infarction and coronary revascularization. These findings must be interpreted collectively, as they strongly suggest the influence of residual confounding rather than opposing causal effects.\u003c/p\u003e \u003cp\u003eThe observed association with lower all-cause mortality warrants cautious interpretation, as it contrasts with evidence from randomized controlled trials (RCTs). Large RCTs such as FOURIER and ODYSSEY OUTCOMES were powered to detect reductions in major adverse cardiovascular events and adjudicated cardiovascular mortality. Although these trials demonstrated robust reductions in LDL-C and ischemic outcomes, they did not show a consistent or definitive reduction in all-cause mortality during their primary follow-up periods [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The magnitude of the mortality association observed in this analysis (22% reduction) exceeds the level of evidence established by these Level 1 studies and therefore cannot be interpreted as a treatment effect.\u003c/p\u003e \u003cp\u003eThis discrepancy highlights a fundamental limitation of observational data: the inability to fully account for channeling bias and the healthy user effect. In RCTs, randomization balances both measured and unmeasured socioeconomic and behavioral factors. In contrast, real-world prescribing patterns reflect differential access to care, whereby patients receiving PCSK9 inhibitors often have unmeasured survival advantages, including higher socioeconomic status, greater health literacy, stronger medication adherence, and more consistent access to preventive and specialty care compared with those prescribed ezetimibe [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Consequently, the observed association with lower all-cause mortality likely reflects these non-cardiovascular survival advantages rather than a direct pharmacologic effect of PCSK9 inhibition.\u003c/p\u003e \u003cp\u003eDespite the likely influence of bias on mortality outcomes, the biological effects of PCSK9 inhibitors on lipid parameters are well established. Consistent with the Cholesterol Treatment Trialists\u0026rsquo; (CTT) Collaboration, reductions in vascular risk are proportional to the absolute magnitude of LDL-C lowering [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In this study, PCSK9 inhibitors achieved substantially greater LDL-C reductions compared with ezetimibe [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Furthermore, intravascular imaging studies such as GLAGOV and PACMAN-AMI have demonstrated that PCSK9 inhibition promotes plaque regression and increases fibrous cap thickness [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. PCSK9 inhibitors also reduce lipoprotein(a) [Lp(a)] levels by approximately 20\u0026ndash;25% [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Elevated Lp(a) is an independent driver of ASCVD mortality [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and its reduction may contribute to residual cardiovascular risk modification [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, these mechanistic findings do not validate the mortality association observed in this study.\u003c/p\u003e \u003cp\u003eThe higher rates of non-fatal myocardial infarction and coronary revascularization observed among PCSK9 inhibitor users further support the presence of confounding by indication [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. In clinical practice, PCSK9 inhibitors are preferentially prescribed to patients with more severe disease phenotypes, including multivessel coronary disease or refractory hyperlipidemia [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Baseline characteristics in our study confirm this systematic difference: even after propensity score matching, the PCSK9 cohort retained significantly higher baseline LDL-C levels [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This persistent imbalance suggests a higher residual burden of atherosclerotic risk, plausibly driving the increased incidence of ischemic events [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. The coexistence of higher ischemic event rates and lower all-cause mortality within the same cohort is biologically inconsistent with a unidirectional treatment effect and instead reflects the complex interplay of residual confounding, channeling bias, and unmeasured socioeconomic factors (the healthy adherer effect) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe observed reduction in all-cause hospital readmissions among patients treated with PCSK9 inhibitors is clinically relevant, given that ASCVD-related readmissions represent a substantial driver of healthcare utilization and costs [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. While PCSK9 inhibitors have historically been scrutinized for high acquisition costs, recent price reductions and the potential to reduce expensive hospitalizations may improve their cost-effectiveness in selected high-risk populations [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Our findings suggest that, in real-world practice, higher upfront medication costs may be partially offset by reduced healthcare resource utilization [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, as with mortality outcomes, this association should be interpreted cautiously due to the influence of unmeasured confounders.\u003c/p\u003e \u003cp\u003eLimitations\u003c/p\u003e \u003cp\u003eThese findings must be interpreted within the context of several important methodological limitations [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. First, despite propensity score matching, baseline LDL-C levels remained imbalanced between groups, indicating incomplete comparability. Second, reliance on ICD-10 coding introduces the potential for misclassification of comorbidities and clinical outcomes [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. Third, all-cause mortality was used as the primary survival endpoint because the TriNetX analytic platform applies Boolean \u0026ldquo;OR\u0026rdquo; logic to outcome definitions and does not support temporal linkage required for reliable adjudication of cardiovascular death [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. As a result, the observed mortality association cannot be attributed specifically to cardiovascular causes or lipid-lowering effects. Finally, although PCSK9 inhibitors are generally well tolerated, we were unable to account for statin-associated adverse effects or differences in adherence to background lipid-lowering therapy that may have influenced outcomes [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Despite these limitations, this study leverages a large, global real-world dataset to provide complementary evidence to randomized trials by characterizing outcomes across a broad, generalizable population treated in routine clinical practice.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this real-world retrospective cohort, PCSK9 inhibitor use was associated with an apparent reduction in all-cause mortality and hospital readmissions compared with ezetimibe, alongside a higher incidence of non-fatal ischemic events. These discordant findings should not be interpreted as evidence of therapeutic superiority or causal benefit. Rather, they underscore the substantial influence of channeling bias and residual confounding inherent in observational lipid-lowering research. These results are hypothesis-generating and highlight the need for future real-world studies incorporating cause-specific mortality adjudication and detailed measures of disease severity and social determinants of health to disentangle pharmacologic effects from socioeconomic and structural factors influencing access to advanced lipid-lowering therapies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDisclosure:\u003c/h2\u003e \u003cp\u003eThe authors have no conflicts of interest to declare.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eEthics Approval:\u003c/h2\u003e \u003cp\u003eThis study utilized the TriNetX Global Collaborative Network containing de-identified patient data. The study was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. As the data is de-identified, the study was deemed exempt from full Institutional Review Board (IRB) review.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate\u003c/strong\u003e \u003cp\u003e Informed consent was waived due to the retrospective nature of the study and the use of de-identified data.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for Publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e \u003cp\u003eCompeting Interests The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Krutagni Mehta, Ritu Tated, and Rafey Feroze. Figure 7 was prepared by Akash Singh. The first draft of the manuscript was written by Krutagni Mehta, Ritu Tated, and Umang Gupta. Critical revision for important intellectual content was performed by Sameh Elias, Saurabh Sharma, Rafey Feroze, and Shilp Arora. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgments:\u003c/h2\u003e \u003cp\u003eNone declared.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData are available from TriNetX (Cambridge, MA) for researchers who meet the data access requirements.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLindstrom M, DeCleene N, Dorsey H et al (2023) Global burden of cardiovascular diseases and risks, 1990\u0026ndash;2022. 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Lancet 388(10059):2532\u0026ndash;2561. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(16)31357-5\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(16)31357-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PCSK9 inhibitors, Ezetimibe, ASCVD, Statin therapy, Real-world evidence, Mortality, Lipid management","lastPublishedDoi":"10.21203/rs.3.rs-8606687/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8606687/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose:\u003c/h2\u003e \u003cp\u003eAtherosclerotic cardiovascular disease (ASCVD) remains a leading cause of mortality. While statins are the cornerstone of therapy, many patients require intensification. This study compares the long-term real-world effectiveness of adding a proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitor versus ezetimibe to background statin therapy.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort study using the TriNetX Global Collaborative Network (January 2018\u0026ndash;January 2023). We identified adult patients with established ASCVD on statin therapy initiating either a PCSK9 inhibitor or ezetimibe. Propensity score matching (1:1) was utilized to balance baseline demographics, comorbidities, and medications, resulting in 16,145 patients per group. The primary outcome was all-cause mortality at 3 and 5 years. Secondary outcomes included myocardial infarction (MI), stroke, revascularization, and hospital readmission.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe PCSK9 inhibitor cohort demonstrated a significant reduction in all-cause mortality compared to the ezetimibe cohort at 3 years (OR: 0.78, HR: 0.79, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 5 years (OR: 0.78, HR: 0.79, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). All-cause readmissions were also lower in the PCSK9 inhibitor group (5-year OR: 0.89, p\u0026thinsp;=\u0026thinsp;0.01; HR: 0.95, p\u0026thinsp;=\u0026thinsp;0.15). Conversely, rates of MI were higher in the PCSK9 inhibitor group at 5 years (OR: 1.11, p\u0026thinsp;=\u0026thinsp;0.03; HR: 1.10, p\u0026thinsp;=\u0026thinsp;0.03), likely reflecting channeling bias due to higher baseline risk (residual LDL-C imbalance).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn this large real-world analysis, PCSK9 inhibitor use was associated with lower all-cause mortality and fewer hospital readmissions over 5 years compared with ezetimibe, despite preferential use in a higher-risk population. These findings are observational and hypothesis-generating, highlighting the impact of treatment channeling in real-world lipid-lowering therapy and the need for further studies with cause-specific outcome adjudication.\u003c/p\u003e","manuscriptTitle":"Long-term Effectiveness of PCSK9 Inhibitors versus Ezetimibe as Adjunctive Therapy to Statins in Patients with Atherosclerotic Cardiovascular Disease: A TriNetX Database Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-09 07:16:14","doi":"10.21203/rs.3.rs-8606687/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"24c592b4-75b3-425e-a19f-7d9ee23bbda3","owner":[],"postedDate":"February 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-03-03T18:39:30+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-09 07:16:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8606687","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8606687","identity":"rs-8606687","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}