Comparison of clinical outcomes between different smoking cessation therapies in patients with chronic kidney disease

Comparison of clinical outcomes between different smoking cessation therapies in patients with chronic kidney disease | 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 Comparison of clinical outcomes between different smoking cessation therapies in patients with chronic kidney disease Jing-Quan Zheng, Yi-Chou Hou, Chien-Lin Lu, Joshua Wang, Hsiu-Chien Yang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9531023/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Methods We conducted a retrospective cohort study using the TriNetX global health research network to compare clinical outcomes in CKD patients who initiated smoking cessation therapy with nicotine (n = 41,361) or varenicline (n = 5,496) between 2009 and 2019. After 1:1 propensity score matching, 5,494 patients were included in each group. Primary outcomes included all-cause mortality, major adverse cardiovascular events (MACE); secondary outcomes included pneumonia, fractures, acute kidney injury (AKI), and CKD progression. Time-to-event analyses were performed using Kaplan–Meier methods and Cox proportional hazards models. Results Over 5 years, varenicline was associated with significantly lower risks of all-cause mortality (10.7% vs 19.3%; hazard ratio [HR], 2.25; 95% CI, 2.03–2.49), MACE (33.3% vs 43.4%; HR, 1.64; 95% CI, 1.52–1.76), pneumonia (10.8% vs 17.6%; HR, 2.06; 95% CI, 1.85–2.29), AKI (19.0% vs 34.9%; HR, 2.41; 95% CI, 2.23–2.62), and CKD progression (19.0% vs 34.9%; HR, 2.41; 95% CI, 2.23–2.62) compared with NRT (all P <.001). Fracture risk was similar between groups, although varenicline was associated with modestly improved fracture-free survival (HR, 1.19; 95% CI, 1.07–1.32). Subgroup analyses demonstrated consistent benefit across demographic and clinical strata. Conclusion Among CKD patients, varenicline use for smoking cessation is associated with significantly lower risks of mortality, cardiovascular events, and renal deterioration compared to NRT. These findings suggest that more complete nicotine abstinence achieved with varenicline may confer substantial cardiorenal protection. Prospective studies are needed to confirm these observations. chronic kidney disease varenicline nicotine replacement therapy mortality cardiovascular events Figures Figure 1 Figure 2 Figure 3 Introduction Chronic kidney disease (CKD) represents a major global health burden, affecting approximately 10–15% of the adult population and contributing substantially to cardiovascular morbidity, mortality, and healthcare costs ( 1 , 2 ). Among modifiable risk factors, cigarette smoking has been consistently associated with accelerated CKD progression, increased incidence of acute kidney injury (AKI), heightened cardiovascular risk, and impaired overall survival ( 3 , 4 ). Underlying mechanisms include endothelial injury, immune dysfunction, and heightened systemic inflammation, ultimately leading to poorer overall survival ( 5 , 6 ). Large-scale epidemiological studies have consistently shown that both current and former smokers are at increased risk of developing CKD compared with never-smokers ( 4 , 7 , 8 ). Furthermore, a dose–response relationship has been well established, with greater smoking duration, higher daily cigarette consumption, and increased cumulative exposure (pack-years) correlating both with CKD incidence and progression ( 7 , 8 ). These findings revealed the importance of smoking cessation as cornerstone in CKD management. Despite this, the comparative effectiveness and safety of available pharmacologic cessation therapies in patients with CKD remain insufficiently defined. Nicotine replacement therapy (NRT) and varenicline are among the most commonly prescribed pharmacotherapies for smoking cessation ( 9 , 10 ). NRT, available in multiple formulations including transdermal patches, gum, lozenges, inhalers, and nasal sprays, delivers controlled doses of nicotine to alleviate withdrawal symptoms and has generally been considered safe in CKD patients and formally used as first-line intervention ( 9 ). In contrast, varenicline is a selective partial agonist of the α4β2 nicotinic acetylcholine receptor that reduces nicotine craving while attenuating the reinforcing effects of smoking ( 11 ). Given its predominant renal excretion in unchanged form, dose adjustment is recommended in patients with later CKD stages (CrCl < 30 mL/min) ( 12 ). Although varenicline has demonstrated superior efficacy in smoking cessation in the general population, concerns regarding neuropsychiatric and cardiovascular safety have historically limited its use ( 10 , 13 , 14 ). On the other hand, patients with later CKD stages represent a particularly vulnerable population, characterized by increased risks of cardiovascular disease, infection, bone fragility, and progressive renal decline. Moreover, CKD related factors—including altered pharmacokinetics, uremia-associated inflammation, and metabolic dysregulation—may modify both the efficacy and safety profiles of smoking cessation therapies. Consequently, the comparative impact of these pharmacologic strategies on systemic outcomes in CKD remains unclear. To address these knowledge gaps, we conducted a large-scale retrospective cohort study using the TriNetX global health research network to compare systemic outcomes related with varenicline versus NRT in advanced CKD patients. This analysis aims to inform evidence-based decision-making for pharmacologic smoking cessation strategies in the CKD population. Methods This retrospective cohort study utilized the TriNetX global health research network, comprising de-identified electronic medical records from healthcare organizations. We identified 3,523,129 adults aged 18 years and older with stage 3 CKD (ICD-10: N18.3) who initiated smoking cessation therapy between January 1, 2009, and December 31, 2019. Patients were excluded if any ICD codes for kidney malignancy, received dialysis within one year or up to three years after the index date, or had documented tobacco- or vaping-related codes following smoking cessation therapy initiation. 41,361 patients received nicotine and 5,496 received varenicline were finally included in the study (Fig. 1 ). Primary and secondary outcomes included all-cause mortality (ICD-10: R99), major adverse cardiovascular events (MACE; ICD-10: I20-I25, I21, I46, I49, I50, I61, I63, R99), pneumonia (ICD-10: J18), fractures (ICD-10: S12-S92, M81.0), acute kidney injury (AKI; ICD-10: N17), and CKD progression (eGFR < 30 mL/min/1.73 m²; UMLS: LNC: 98979-8). Institutional Review Board of Taipei Tzu Chi Hospital approved the study protocol with a waiver of informed consent (IRB No. 14-IRB043). Statistical Analysis Baseline characteristics were compared using standardized differences, with values < 0.1 considered indicative of adequate balance. Time-to-event analyses were performed using Kaplan-Meier survival curves, with differences between groups assessed using log-rank tests. Hazard ratios (HR) with 95% confidence intervals were calculated using Cox proportional hazards regression models. We calculated cumulative incidence rates, risk differences, risk ratios, and odds ratios to provide comprehensive effect size measures. Subgroup analyses were performed stratified by key demographic and clinical variables including age, sex, presence of diabetes mellitus, hypertension, COPD, baseline kidney function, inflammatory markers, and nutritional status. All statistical analyses were performed with p < 0.05 for significance testing. Results 2.1 Baseline characteristics A total of 46,857 patients with stage 3 CKD who initiated smoking cessation therapy were included, comprising 41,361 patients receiving NRT and 5,496 receiving varenicline. To minimize confounding, 1:1 propensity score matching was performed with two well-balanced cohorts of 5,494 patients in each group. Before matching, patients treated with varenicline were younger, more frequently female and White, and had a higher prevalence of comorbid conditions and medication use. Following matching, baseline characteristics were well balanced across demographic variables, comorbidities, and medication profiles, with standardized differences below 0.2 for all measured covariates. Minor residual differences persisted in select laboratory parameters, including inflammatory markers (C-reactive protein), hemoglobin, and calcium levels; however, overall clinical parameters were not significantly differed in two groups (Table). 2.2. Clinical Outcomes 2.2.1. All-Cause Mortality Over a 5-year follow-up, varenicline use was associated with significantly lower all-cause mortality compared with NRT (10.7% vs 19.3%). This corresponded to an absolute risk reduction of 8.6% (95% CI, 7.3%–9.9%; P<.001). Kaplan–Meier analysis demonstrated significantly higher survival probability among varenicline users (87.3% vs 74.5%), with a hazard ratio (HR) of 2.25 (95% CI, 2.03–2.49; log-rank P<.001). 2.2.2. Major Adverse Cardiovascular Events The incidence of major adverse cardiovascular events (MACE) was significantly lower in the varenicline group compared with NRT (33.3% vs 43.4%), yielding an absolute risk reduction of 10.1%. Time-to-event analysis demonstrated improved MACE-free survival in the varenicline cohort (62.6% vs 46.6%), with an HR of 1.64 (95% CI, 1.52–1.76; P<.001). 2.2.3. Pneumonia Varenicline use was associated with a significantly reduced risk of pneumonia compared with NRT (10.8% vs 17.6%), corresponding to an absolute risk reduction of 6.9% (95% CI, 5.5%–8.2%; P<.001). Kaplan–Meier estimates demonstrated higher pneumonia-free survival among varenicline users (87.3% vs 75.9%), with an HR of 2.06 (95% CI, 1.85–2.29). 2.2.4. Fractures The crude incidence of fractures was similar between groups (13.6% for varenicline vs 13.2% for NRT; P=.47). However, time-to-event analysis revealed a modest but statistically significant improvement in fracture-free survival in the varenicline group (83.6% vs 80.9%), with an HR of 1.19 (95% CI, 1.07–1.32; P=.002). 2.2.5. Acute Kidney Injury Varenicline was associated with a markedly lower incidence of acute kidney injury (AKI) compared with NRT (19.0% vs 34.9%), representing an absolute risk reduction of 15.8% (95% CI, 14.1%–17.6%; P<.001). Kaplan–Meier analysis demonstrated substantially higher AKI-free survival in the varenicline group (77.9% vs 56.1%), with an HR of 2.41 (95% CI, 2.23–2.62). 2.2.6. CKD Progression Progression to advanced CKD (eGFR < 30 mL/min/1.73 m²) was significantly less frequent among varenicline users (19.0% vs 34.9%), corresponding to an absolute risk reduction of 15.8% (95% CI, 14.1%–17.6%; P<.001). The risk ratio was 1.83 and the odds ratio was 2.28. Kaplan–Meier analysis showed improved renal survival in the varenicline group (77.9% vs 56.1%), with an HR of 2.41 (95% CI, 2.23–2.62). 2.3. Subgroup Analyses Subgroup analyses demonstrated consistent associations across major demographic and clinical strata. The magnitude of risk reduction with varenicline was generally preserved across subgroups defined by age, sex, diabetes, hypertension, and body mass index. Notably, female sex, obesity (BMI ≥ 30), and diabetes were associated with higher risks of all-cause mortality. The risk of pneumonia showed the strongest subgroup effect, particularly among females and individuals without diabetes. Fracture risk was more pronounced in males and individuals with lower BMI, whereas AKI risk was elevated among females and non-diabetic patients. Despite these variations, the directionality of benefit associated with varenicline remained consistent across subgroups (Fig. 3 ). Table. Baseline Characteristics of CKD Stage 3 Patients Receiving Smoking Cessation Therapy Before and After Propensity Score Matching Before Matching After Matching Characteristics Nicotine (n = 41,361) Varenicline (n = 5,496) p value Std diff Nicotine (n = 5,494) Varenicline (n = 5,494) p value Std diff Demographics (%) Age at Index, mean ± SD 59.5 ± 12.1 58.5 ± 10.3 < 0.001 0.092 58.7 ± 11.2 58.5 ± 10.3 0.601 0.010 Female 47.4% 55.6% < 0.001 0.188 55.7% 55.6% 0.384 0.017 Male 47.6% 40.6% < 0.001 0.218 40.3% 40.6% 0.375 0.017 White (%) 61.9% 69.3% < 0.001 0.248 70.3% 69.3% 0.051 0.039 Black or African American (%) 23.5% 15.2% < 0.001 0.115 15.0% 15.3% 0.872 0.003 Asian (%) 1.4% 1.7% < 0.001 0.056 1.7% 1.7% 0.289 0.021 Diagnosis (%) Diabetes mellitus 10.7% 13.6% < 0.001 0.215 15.5% 13.6% 0.554 0.012 Hypertensive diseases 20.5% 27.9% < 0.001 0.292 30.9% 27.9% 0.550 0.012 Ischemic heart diseases 7.5% 8.5% 9.6% 8.5% Chronic obstructive pulmonary disease 9.9% 13.4% < 0.001 0.087 14.8% 13.4% 0.676 0.008 Medication (%) Oral Hypoglycemic Agents 11.1% 13.4% < 0.001 0.200 15.1% 13.4% 0.580 0.011 Beta Blockers 12.4% 17.5% < 0.001 0.170 19.0% 17.5% 0.496 0.013 Antilipemic Agents 12.2% 22.6% < 0.001 0.176 23.3% 22.5% 0.489 0.014 ACE Inhibitors 9.0% 14.6% < 0.001 0.104 15.3% 14.6% 0.385 0.017 Diuretics 12.3% 19.9% < 0.001 0.157 20.5% 19.9% 0.841 0.004 Calcium Channel Blockers 7.5% 11.2% 11.9% 11.2% Bronchodilators 13.3% 19.8% 22.3% 19.8% Laboratory (mean ± SD) Hemoglobin, g/dL 12.3 ± 2.4 13.0 ± 2.2 < 0.001 0.325 12.3 ± 2.4 13.0 ± 2.2 < 0.001 0.310 Hematocrit, % 36.8 ± 7.5 39.1 ± 6.1 < 0.001 0.324 36.9 ± 7.7 39.1 ± 6.1 < 0.001 0.315 Iron, ug/dL 59.5 ± 45.0 67.9 ± 46.4 0.092 0.184 57.3 ± 42.1 67.9 ± 46.4 0.088 0.240 Ferritin, ng/mL 456.5 ± 906.6 298.0 ± 437.5 0.074 0.223 410.8 ± 843.9 298.0 ± 437.5 0.211 0.168 CRP, mg/L 46.7 ± 72.0 24.9 ± 40.3 0.004 0.373 54.8 ± 74.2 25.2 ± 40.4 0.001 0.496 ESR, mm/h 43.0 ± 33.9 30.5 ± 25.3 < 0.001 0.419 39.2 ± 33.0 30.8 ± 25.3 0.027 0.288 Creatinine, mg/dL 1.4 ± 1.0 1.3 ± 0.9 0.010 0.101 1.3 ± 0.9 1.3 ± 0.9 0.378 0.043 BUN, mg/dL 22.9 ± 16.3 20.6 ± 12.1 < 0.001 0.165 22.3 ± 15.4 20.6 ± 12.1 0.015 0.126 Sodium, mmol/L 137.9 ± 4.3 138.6 ± 3.6 < 0.001 0.164 138.0 ± 4.0 138.6 ± 3.6 0.004 0.145 Potassium, mmol/L 4.1 ± 0.6 4.2 ± 0.5 0.012 0.101 4.2 ± 0.6 4.2 ± 0.5 0.608 0.026 Calcium, mg/dL 9.0 ± 0.9 9.2 ± 0.7 < 0.001 0.253 9.0 ± 0.9 9.2 ± 0.7 < 0.001 0.194 Phosphate, mg/dL 3.7 ± 1.0 3. 7 ± 0.9 0.876 0.012 3.7 ± 1.0 3.7 ± 0.9 0.866 0.016 Parathyroid .intact 140.1 ± 184.8 121.8 ± 162.8 0.499 0.105 130.3 ± 176.8 121.8 ± 162.8 0.794 0.050 Calcidiol, ng/mL 25.5 ± 18.1 25.1 ± 12.0 0.853 0.027 23.5 ± 17.7 25.2 ± 12.0 0.506 0.109 Bicarbonate, mmol/L 25.1 ± 4.3 25.8 ± 3.7 < 0.001 0.175 25.3 ± 4.3 25.8 ± 3.7 0.007 0.136 Glucose, mg/dL 132.5 ± 69.4 122.5 ± 53.5 < 0.001 0.162 133.1 ± 71.9 122.5 ± 53.5 0.001 0.167 Albumin, g/dL 3.6 ± 0.7 3.8 ± 0.6 < 0.001 0.416 3.6 ± 0.7 3.8 ± 0.6 < 0.001 0.398 Protein, g/dL 6.9 ± 0.9 7.0 ± 0.7 0.005 0.137 6.8 ± 0.8 7.0 ± 0.7 0.002 0.175 Cholesterol, mg/dL 171.0 ± 54.8 180.4 ± 51.8 0.001 0.177 169.9 ± 54.9 180.3 ± 51.8 0.004 0.195 LDL Cholesterol, mg/dL 96.7 ± 43.1 101.9 ± 39.2 0.020 0.127 95.7 ± 40.8 101.8 ± 39.1 0.025 0.152 HDL Cholesterol, mg/dL 43.0 ± 17.8 43.0 ± 15.7 0.994 < 0.001 42.1 ± 18.4 43.0 ± 15.7 0.464 0.049 Triglyceride, mg/dL 172.2 ± 167.4 188.1 ± 154.9 0.072 0.098 174.1 ± 149.8 188.3 ± 155.0 0.170 0.093 Hemoglobin A1c, % 7.3 ± 2.4 7.2 ± 2.0 0.403 0.047 7.3 ± 2.4 7.2 ± 2.0 0.410 0.056 Urate, mg/dL 6.4 ± 2.6 6.9 ± 2.0 0.137 0.214 6.5 ± 2.2 6.9 ± 2.0 0.272 0.189 ALT: Alanine aminotransferase; AST: Aspartate aminotransferase; CRP: C reactive protein; ESR: Erythrocyte sedimentation rate; PTH: Parathyroid hormone; Alk: Alkaline; BUN: Blood urea nitrogen; SD: standard deviation; Std. Diff.: Standardized difference; MCV: mean corpuscular volume, F: Ferritin, ng/mL. ESR: erythrocyte sedimentation rate Discussion In this large, propensity score–matched cohort of patients with stage 3 CKD, varenicline use was associated with significantly lower risks of all-cause mortality, major adverse cardiovascular events, pneumonia, acute kidney injury, and CKD progression compared with NRT. These findings extend prior evidence by suggesting that the choice of smoking cessation pharmacotherapy may have differential effects on cardiorenal outcomes in CKD, beyond its role in facilitating abstinence. The magnitude of renal benefit observed in the present study is particularly notable. Varenicline use was associated with substantial reductions in both AKI and CKD progression, suggesting that interruption of smoking-related injury may rapidly translate into benefits for kidney function. Mechanistically, smoking cessation improves endothelial nitric oxide bioavailability, reduces oxidative stress, and restores autoregulatory capacity within the renal microcirculation ( 15 ). These effects may reduce susceptibility to hemodynamic insults and mitigate maladaptive repair processes that drive fibrosis and progressive nephron loss ( 15 , 16 ). Our observation is consistent with recent Korean population study ( 17 ), whereas we found a greater benefits of renal outcomes than cardiovascular endpoints and suggests that the kidney may be particularly sensitive to sustained nicotine abstinence. The observed differences between varenicline and NRT likely reflect both pharmacologic and pathophysiological mechanisms. Varenicline, a selective partial agonist of the α4β2 nicotinic acetylcholine receptor, reduces nicotine craving and attenuates the reinforcing effects of smoking, resulting in higher rates of sustained abstinence compared with NRT ( 9 , 18 ). In contrast, NRT maintains ongoing exposure to nicotine, albeit at lower levels. Nicotine itself has been shown to exert direct deleterious effects on the cardiovascular and renal systems, including increased sympathetic tone, impaired endothelial function, and promotion of oxidative stress and inflammation ( 19 – 21 ). Persistent low-level nicotine exposure may therefore perpetuate microvascular injury and limit recovery of endothelial integrity ( 19 ). By facilitating more complete nicotine abstinence, varenicline might allow more effective reversal of these processes. Similarly, cigarette smoke impairs pulmonary host defenses through disruption of mucociliary clearance, epithelial barrier integrity, and innate immune responses, including altered macrophage and neutrophil function, thereby increasing susceptibility to respiratory infections ( 22 – 25 ). Smoking cessation has been shown to partially reverse these abnormalities, restoring mucosal immunity and improving epithelial repair ( 26 , 27 ). Our findings of greater reduction in pneumonia risk in varenicline rather than nicotine might reflect importance of complete and sustained nicotine abstinence. These effects are particularly relevant in CKD, who itself vulnerable for sepsis due to underlying CKD related immune dysregulation and chronic inflammation. The modest differences in fracture risks likely reflect the complex and multifactorial pathogenesis of smoking and CKD in bone disease. Smoking has been associated with reduced bone mineral density, impaired osteoblast function, and dysregulation of calcium–phosphate homeostasis, including alterations in parathyroid hormone signaling ( 28 – 30 ). These effects are further amplified in CKD patients due to CKD–mineral and bone disorder (CKD-MBD) related renal osteodystrophy, where disturbances in vitamin D metabolism, secondary hyperparathyroidism, and chronic inflammation contribute to skeletal fragility ( 31 , 32 ). Although smoking cessation may partially reverse smoking-related skeletal toxicity, its impact may be attenuated by persistent CKD-specific factors such as metabolic acidosis, uremia-associated inflammation, and hormonal dysregulation ( 33 ). Consistent with this, the modest improvement in fracture-free survival observed with varenicline suggests that while effective smoking cessation may confer some skeletal benefit, bone health in CKD remains largely determined by the broader metabolic and inflammatory milieu. Subgroup analyses demonstrated consistent benefits of varenicline across major demographic and clinical strata. Sex-specific differences in vascular function, including endothelial responsiveness and hormonal modulation of nitric oxide signaling, may contribute to differential susceptibility to smoking-related injury and recovery following cessation ( 34 , 35 ). In addition, immune and inflammatory responses are known to vary by sex, potentially influencing both cardiovascular and infectious outcomes ( 36 ). The amplified risks observed in obese patients are biologically plausible, as excess adiposity is associated with chronic low-grade inflammation, oxidative stress, and endothelial dysfunction, all of which may potentiate smoking-related vascular and renal injury ( 37 , 38 ). Conversely, the differential patterns observed in those without diabetes might reflect metabolic and inflammatory profiles that modify susceptibility to cardiorenal and infectious complications. In CKD patients, whose systemic inflammation, uremic toxicity, and immune dysregulation are already present, these interacting factors likely shape individual risk trajectories. Collectively, the benefits from smoking cessation therapies influences by individualized risk stratification and patient-specific characteristics. Several limitations should be acknowledged. First, the observational design precludes causal inference and introduces the potential for residual confounding despite rigorous propensity score matching. Second, detailed information on smoking behavior—including intensity, duration, and sustained abstinence—was not available, limiting mechanistic interpretation of the observed associations. Third, medication adherence could not be directly ascertained, raising the possibility of exposure misclassification. Fourth, outcome definitions were based on administrative coding, which may be subject to misclassification bias. Finally, although baseline characteristics were well balanced, modest residual differences in laboratory parameters may reflect unmeasured biological variability or residual confounding not fully captured in the matching process. In conclusion, among patients with stage 3 CKD, varenicline use is associated with significant reductions in mortality, cardiovascular events, pulmonary complications, and renal disease progression compared with nicotine replacement therapy. These findings suggest that complete nicotine abstinence, facilitated by varenicline, may confer substantial cardiorenal protection. Further prospective and mechanistic studies are needed to confirm these observations and to elucidate the biological pathways linking smoking cessation strategies to kidney outcomes. Declarations Author Contribution J.-Q.Z. and Y.-C.H. contributed substantially to the conception and design of the study, data acquisition, analysis, and interpretation, and drafted the manuscript. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9531023","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635726241,"identity":"1b7d0e45-032d-4196-b9d4-0f95dda7d196","order_by":0,"name":"Jing-Quan Zheng","email":"","orcid":"","institution":"Shuang Ho Hospital, Taipei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jing-Quan","middleName":"","lastName":"Zheng","suffix":""},{"id":635726242,"identity":"1eeaaa4c-cf3d-447d-a4bc-bd4f2a1a9074","order_by":1,"name":"Yi-Chou Hou","email":"","orcid":"","institution":"Cardinal-Tien Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yi-Chou","middleName":"","lastName":"Hou","suffix":""},{"id":635726244,"identity":"d3b63fd6-a7bb-4227-b092-2e7e33cbcc57","order_by":2,"name":"Chien-Lin Lu","email":"","orcid":"","institution":"Fu-Jen Catholic University","correspondingAuthor":false,"prefix":"","firstName":"Chien-Lin","middleName":"","lastName":"Lu","suffix":""},{"id":635726245,"identity":"432e1108-c284-402b-8f4e-4cc6db6eec4e","order_by":3,"name":"Joshua Wang","email":"","orcid":"","institution":"Queensland University of Technology","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"","lastName":"Wang","suffix":""},{"id":635726246,"identity":"31256c80-4e80-4ff0-879a-a571a09f9b0e","order_by":4,"name":"Hsiu-Chien Yang","email":"","orcid":"","institution":"Taoyuan Armed Forces General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hsiu-Chien","middleName":"","lastName":"Yang","suffix":""},{"id":635726247,"identity":"ec579204-92bc-488e-a2f6-11f7eaa337e8","order_by":5,"name":"Tin Tin Sandar","email":"","orcid":"","institution":"University of Oxford","correspondingAuthor":false,"prefix":"","firstName":"Tin","middleName":"Tin","lastName":"Sandar","suffix":""},{"id":635726248,"identity":"3c447481-1b4d-4ed4-9755-1cfa1b016f13","order_by":6,"name":"Cai-Mei Zheng","email":"","orcid":"","institution":"Taipei Medical University, Shuang Ho Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cai-Mei","middleName":"","lastName":"Zheng","suffix":""},{"id":635726249,"identity":"9354ca41-0cb9-4dfe-857f-d9b709438ef5","order_by":7,"name":"Kuo-Cheng Lu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACCSBmBjH4GJgPgPgyxGthY2BLAPF5SNHCYwCiCWuRnJF88HNBxR27Nomcz69u1FjwMLAfProBnxZpibRk6RlnniW3SeRus845BnQYT1raDXxa5CRyzJh52w4nswG1GOewAbVI8JgRoeUfSEvOM+Ocf0RokQZraThsB9TC/Di3jQgtkj3PkqV5jh1OYON5Zsac2yfBw0bILxLHgSHGU3PYnp89+fHnnG91cvzsh4/h1QIDiQ3AqAFFEjCCiAT2QMz8gVjVo2AUjIJRMLIAAP6oP2BflPM6AAAAAElFTkSuQmCC","orcid":"","institution":"Fu-Jen Catholic University","correspondingAuthor":true,"prefix":"","firstName":"Kuo-Cheng","middleName":"","lastName":"Lu","suffix":""}],"badges":[],"createdAt":"2026-04-26 10:08:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9531023/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9531023/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109215810,"identity":"49e29ee9-04e6-49e0-a124-29ad2d9fb269","added_by":"auto","created_at":"2026-05-13 17:56:41","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":566845,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAlgorithm for patient selection and enrollment in the study\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9531023/v1/3ecb7a11a601f7de546d65d9.png"},{"id":109215811,"identity":"80992a69-6c17-4d1e-8f53-0f54ec2735ac","added_by":"auto","created_at":"2026-05-13 17:56:41","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":253065,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan–Meier curves for clinical outcomes in stage 3 CKD patients receiving varenicline vs nicotine replacement therapy (NRT). \u003c/strong\u003eVarenicline was associated with improved survival and event-free outcomes across multiple endpoints over 5 years. (A) All-cause mortality, (B) major adverse cardiovascular events (MACE), (C) pneumonia, (D) fractures, and (E) acute kidney injury (AKI). Log-rank tests demonstrated significant differences favoring varenicline for all outcomes (P\u0026lt;.0001), except fractures (P=.005). Red lines represent varenicline; blue lines represent NRT.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9531023/v1/06d8e5a396340c2d710cfc02.png"},{"id":109249681,"identity":"4b64d364-ae4f-49ab-af4f-0d6b753a3688","added_by":"auto","created_at":"2026-05-14 08:58:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":159829,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eForest plots of subgroup analyses for clinical outcomes in stage 3 CKD. \u003c/strong\u003eOdds ratios (ORs) with 95% CIs for (A) all-cause mortality, (B) major adverse cardiovascular events, (C) acute kidney injury, (D) pneumonia, and (E) fractures are shown across subgroups stratified by sex, diabetes, hypertension, and body mass index. Across most subgroups, exposure was associated with increased risk of adverse outcomes, with consistent effect direction and greater magnitude observed for pneumonia and fractures. Vertical dashed line indicates OR=1.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9531023/v1/6d261ef14c3c80d5d396a0f1.png"},{"id":109250112,"identity":"b6a1a711-b497-44b3-bc2b-efa4152e7746","added_by":"auto","created_at":"2026-05-14 09:06:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1142021,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9531023/v1/e2b62e53-5492-456d-8175-5115526ba873.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of clinical outcomes between different smoking cessation therapies in patients with chronic kidney disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eChronic kidney disease (CKD) represents a major global health burden, affecting approximately 10\u0026ndash;15% of the adult population and contributing substantially to cardiovascular morbidity, mortality, and healthcare costs (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Among modifiable risk factors, cigarette smoking has been consistently associated with accelerated CKD progression, increased incidence of acute kidney injury (AKI), heightened cardiovascular risk, and impaired overall survival (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Underlying mechanisms include endothelial injury, immune dysfunction, and heightened systemic inflammation, ultimately leading to poorer overall survival (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Large-scale epidemiological studies have consistently shown that both current and former smokers are at increased risk of developing CKD compared with never-smokers (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Furthermore, a dose\u0026ndash;response relationship has been well established, with greater smoking duration, higher daily cigarette consumption, and increased cumulative exposure (pack-years) correlating both with CKD incidence and progression (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). These findings revealed the importance of smoking cessation as cornerstone in CKD management. Despite this, the comparative effectiveness and safety of available pharmacologic cessation therapies in patients with CKD remain insufficiently defined.\u003c/p\u003e \u003cp\u003eNicotine replacement therapy (NRT) and varenicline are among the most commonly prescribed pharmacotherapies for smoking cessation (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). NRT, available in multiple formulations including transdermal patches, gum, lozenges, inhalers, and nasal sprays, delivers controlled doses of nicotine to alleviate withdrawal symptoms and has generally been considered safe in CKD patients and formally used as first-line intervention (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In contrast, varenicline is a selective partial agonist of the α4β2 nicotinic acetylcholine receptor that reduces nicotine craving while attenuating the reinforcing effects of smoking (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Given its predominant renal excretion in unchanged form, dose adjustment is recommended in patients with later CKD stages (CrCl\u0026thinsp;\u0026lt;\u0026thinsp;30 mL/min) (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Although varenicline has demonstrated superior efficacy in smoking cessation in the general population, concerns regarding neuropsychiatric and cardiovascular safety have historically limited its use (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). On the other hand, patients with later CKD stages represent a particularly vulnerable population, characterized by increased risks of cardiovascular disease, infection, bone fragility, and progressive renal decline. Moreover, CKD related factors\u0026mdash;including altered pharmacokinetics, uremia-associated inflammation, and metabolic dysregulation\u0026mdash;may modify both the efficacy and safety profiles of smoking cessation therapies. Consequently, the comparative impact of these pharmacologic strategies on systemic outcomes in CKD remains unclear.\u003c/p\u003e \u003cp\u003eTo address these knowledge gaps, we conducted a large-scale retrospective cohort study using the TriNetX global health research network to compare systemic outcomes related with varenicline versus NRT in advanced CKD patients. This analysis aims to inform evidence-based decision-making for pharmacologic smoking cessation strategies in the CKD population.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis retrospective cohort study utilized the TriNetX global health research network, comprising de-identified electronic medical records from healthcare organizations. We identified 3,523,129 adults aged 18 years and older with stage 3 CKD (ICD-10: N18.3) who initiated smoking cessation therapy between January 1, 2009, and December 31, 2019. Patients were excluded if any ICD codes for kidney malignancy, received dialysis within one year or up to three years after the index date, or had documented tobacco- or vaping-related codes following smoking cessation therapy initiation. 41,361 patients received nicotine and 5,496 received varenicline were finally included in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Primary and secondary outcomes included all-cause mortality (ICD-10: R99), major adverse cardiovascular events (MACE; ICD-10: I20-I25, I21, I46, I49, I50, I61, I63, R99), pneumonia (ICD-10: J18), fractures (ICD-10: S12-S92, M81.0), acute kidney injury (AKI; ICD-10: N17), and CKD progression (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;30 mL/min/1.73 m\u0026sup2;; UMLS: LNC: 98979-8). Institutional Review Board of Taipei Tzu Chi Hospital approved the study protocol with a waiver of informed consent (IRB No. 14-IRB043).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics were compared using standardized differences, with values\u0026thinsp;\u0026lt;\u0026thinsp;0.1 considered indicative of adequate balance. Time-to-event analyses were performed using Kaplan-Meier survival curves, with differences between groups assessed using log-rank tests. Hazard ratios (HR) with 95% confidence intervals were calculated using Cox proportional hazards regression models. We calculated cumulative incidence rates, risk differences, risk ratios, and odds ratios to provide comprehensive effect size measures. Subgroup analyses were performed stratified by key demographic and clinical variables including age, sex, presence of diabetes mellitus, hypertension, COPD, baseline kidney function, inflammatory markers, and nutritional status. All statistical analyses were performed with p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 for significance testing.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Baseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 46,857 patients with stage 3 CKD who initiated smoking cessation therapy were included, comprising 41,361 patients receiving NRT and 5,496 receiving varenicline. To minimize confounding, 1:1 propensity score matching was performed with two well-balanced cohorts of 5,494 patients in each group. Before matching, patients treated with varenicline were younger, more frequently female and White, and had a higher prevalence of comorbid conditions and medication use. Following matching, baseline characteristics were well balanced across demographic variables, comorbidities, and medication profiles, with standardized differences below 0.2 for all measured covariates. Minor residual differences persisted in select laboratory parameters, including inflammatory markers (C-reactive protein), hemoglobin, and calcium levels; however, overall clinical parameters were not significantly differed in two groups (Table).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Clinical Outcomes\u003c/h2\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. All-Cause Mortality\u003c/h2\u003e \u003cp\u003eOver a 5-year follow-up, varenicline use was associated with significantly lower all-cause mortality compared with NRT (10.7% vs 19.3%). This corresponded to an absolute risk reduction of 8.6% (95% CI, 7.3%\u0026ndash;9.9%; P\u0026lt;.001). Kaplan\u0026ndash;Meier analysis demonstrated significantly higher survival probability among varenicline users (87.3% vs 74.5%), with a hazard ratio (HR) of 2.25 (95% CI, 2.03\u0026ndash;2.49; log-rank P\u0026lt;.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. Major Adverse Cardiovascular Events\u003c/h2\u003e \u003cp\u003eThe incidence of major adverse cardiovascular events (MACE) was significantly lower in the varenicline group compared with NRT (33.3% vs 43.4%), yielding an absolute risk reduction of 10.1%. Time-to-event analysis demonstrated improved MACE-free survival in the varenicline cohort (62.6% vs 46.6%), with an HR of 1.64 (95% CI, 1.52\u0026ndash;1.76; P\u0026lt;.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3. Pneumonia\u003c/h2\u003e \u003cp\u003eVarenicline use was associated with a significantly reduced risk of pneumonia compared with NRT (10.8% vs 17.6%), corresponding to an absolute risk reduction of 6.9% (95% CI, 5.5%\u0026ndash;8.2%; P\u0026lt;.001). Kaplan\u0026ndash;Meier estimates demonstrated higher pneumonia-free survival among varenicline users (87.3% vs 75.9%), with an HR of 2.06 (95% CI, 1.85\u0026ndash;2.29).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4. Fractures\u003c/h2\u003e \u003cp\u003eThe crude incidence of fractures was similar between groups (13.6% for varenicline vs 13.2% for NRT; P=.47). However, time-to-event analysis revealed a modest but statistically significant improvement in fracture-free survival in the varenicline group (83.6% vs 80.9%), with an HR of 1.19 (95% CI, 1.07\u0026ndash;1.32; P=.002).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.5. Acute Kidney Injury\u003c/h2\u003e \u003cp\u003eVarenicline was associated with a markedly lower incidence of acute kidney injury (AKI) compared with NRT (19.0% vs 34.9%), representing an absolute risk reduction of 15.8% (95% CI, 14.1%\u0026ndash;17.6%; P\u0026lt;.001). Kaplan\u0026ndash;Meier analysis demonstrated substantially higher AKI-free survival in the varenicline group (77.9% vs 56.1%), with an HR of 2.41 (95% CI, 2.23\u0026ndash;2.62).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section3\"\u003e \u003ch2\u003e2.2.6. CKD Progression\u003c/h2\u003e \u003cp\u003eProgression to advanced CKD (eGFR\u0026thinsp;\u0026lt;\u0026thinsp;30 mL/min/1.73 m\u0026sup2;) was significantly less frequent among varenicline users (19.0% vs 34.9%), corresponding to an absolute risk reduction of 15.8% (95% CI, 14.1%\u0026ndash;17.6%; P\u0026lt;.001). The risk ratio was 1.83 and the odds ratio was 2.28. Kaplan\u0026ndash;Meier analysis showed improved renal survival in the varenicline group (77.9% vs 56.1%), with an HR of 2.41 (95% CI, 2.23\u0026ndash;2.62).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Subgroup Analyses\u003c/h2\u003e \u003cp\u003eSubgroup analyses demonstrated consistent associations across major demographic and clinical strata. The magnitude of risk reduction with varenicline was generally preserved across subgroups defined by age, sex, diabetes, hypertension, and body mass index. Notably, female sex, obesity (BMI\u0026thinsp;\u0026ge;\u0026thinsp;30), and diabetes were associated with higher risks of all-cause mortality. The risk of pneumonia showed the strongest subgroup effect, particularly among females and individuals without diabetes. Fracture risk was more pronounced in males and individuals with lower BMI, whereas AKI risk was elevated among females and non-diabetic patients. Despite these variations, the directionality of benefit associated with varenicline remained consistent across subgroups (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eTable. Baseline Characteristics of CKD Stage 3 Patients Receiving Smoking Cessation Therapy Before and After Propensity Score Matching\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003e\u003cb\u003eBefore Matching\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003e\u003cb\u003eAfter Matching\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharacteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNicotine\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;41,361)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eVarenicline\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;5,496)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003ep value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eStd diff\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eNicotine\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;5,494)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eVarenicline\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003e(n\u0026thinsp;=\u0026thinsp;5,494)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003ep value\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eStd diff\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographics (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at Index, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e59.5\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.092\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e58.7\u0026thinsp;\u0026plusmn;\u0026thinsp;11.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e58.5\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.601\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFemale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e47.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e55.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.188\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e55.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e55.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.384\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMale\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e47.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e40.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.218\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e40.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e40.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.375\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWhite (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e61.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e69.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.248\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e70.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e69.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.051\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.039\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlack or African American (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e23.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15.2%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.115\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e15.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.872\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAsian (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.056\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.289\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.021\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiagnosis (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e10.7%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.215\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e13.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.554\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertensive diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e20.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e27.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.292\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e30.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e27.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.550\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIschemic heart diseases\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e8.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e8.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic obstructive pulmonary disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.087\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e14.8%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e13.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.676\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedication (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOral Hypoglycemic Agents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e11.1%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.200\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15.1%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e13.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.580\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBeta Blockers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12.4%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e17.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e19.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e17.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.496\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAntilipemic Agents\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12.2%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e22.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.176\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e23.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e22.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.489\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eACE Inhibitors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9.0%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e14.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.104\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e14.6%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.385\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiuretics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e19.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.157\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e20.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e19.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.841\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCalcium Channel Blockers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.5%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e11.2%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e11.9%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11.2%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBronchodilators\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e13.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e19.8%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e22.3%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e19.8%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHemoglobin, g/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e12.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.325\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e12.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e13.0\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.310\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHematocrit, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e36.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e39.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.324\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e36.9\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e39.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.315\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIron, ug/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e59.5\u0026thinsp;\u0026plusmn;\u0026thinsp;45.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;46.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.092\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.184\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e57.3\u0026thinsp;\u0026plusmn;\u0026thinsp;42.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e67.9\u0026thinsp;\u0026plusmn;\u0026thinsp;46.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.088\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.240\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFerritin, ng/mL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e456.5\u0026thinsp;\u0026plusmn;\u0026thinsp;906.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e298.0\u0026thinsp;\u0026plusmn;\u0026thinsp;437.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.074\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.223\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e410.8\u0026thinsp;\u0026plusmn;\u0026thinsp;843.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e298.0\u0026thinsp;\u0026plusmn;\u0026thinsp;437.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.211\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.168\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCRP, mg/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e46.7\u0026thinsp;\u0026plusmn;\u0026thinsp;72.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e24.9\u0026thinsp;\u0026plusmn;\u0026thinsp;40.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.373\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e54.8\u0026thinsp;\u0026plusmn;\u0026thinsp;74.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e25.2\u0026thinsp;\u0026plusmn;\u0026thinsp;40.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.496\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eESR, mm/h\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;33.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e30.5\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.419\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e39.2\u0026thinsp;\u0026plusmn;\u0026thinsp;33.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e30.8\u0026thinsp;\u0026plusmn;\u0026thinsp;25.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.288\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCreatinine, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.4\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.010\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.101\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.378\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.043\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBUN, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e20.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.165\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e22.3\u0026thinsp;\u0026plusmn;\u0026thinsp;15.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e20.6\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.015\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.126\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSodium, mmol/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e137.9\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e138.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.164\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e138.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e138.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.145\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePotassium, mmol/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4.1\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.101\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e4.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.608\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.026\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCalcium, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.253\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e9.2\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.194\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePhosphate, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3. 7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.876\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.012\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;1.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.866\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParathyroid .intact\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e140.1\u0026thinsp;\u0026plusmn;\u0026thinsp;184.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e121.8\u0026thinsp;\u0026plusmn;\u0026thinsp;162.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.499\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.105\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e130.3\u0026thinsp;\u0026plusmn;\u0026thinsp;176.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e121.8\u0026thinsp;\u0026plusmn;\u0026thinsp;162.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.794\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.050\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCalcidiol, ng/mL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;18.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25.1\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.853\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.027\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e23.5\u0026thinsp;\u0026plusmn;\u0026thinsp;17.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e25.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.506\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.109\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBicarbonate, mmol/L\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25.1\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e25.3\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e25.8\u0026thinsp;\u0026plusmn;\u0026thinsp;3.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.136\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e132.5\u0026thinsp;\u0026plusmn;\u0026thinsp;69.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e122.5\u0026thinsp;\u0026plusmn;\u0026thinsp;53.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.162\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e133.1\u0026thinsp;\u0026plusmn;\u0026thinsp;71.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e122.5\u0026thinsp;\u0026plusmn;\u0026thinsp;53.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.167\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin, g/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.416\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e3.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.398\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProtein, g/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;0.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.137\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e6.8\u0026thinsp;\u0026plusmn;\u0026thinsp;0.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e7.0\u0026thinsp;\u0026plusmn;\u0026thinsp;0.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.175\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCholesterol, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e171.0\u0026thinsp;\u0026plusmn;\u0026thinsp;54.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e180.4\u0026thinsp;\u0026plusmn;\u0026thinsp;51.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.177\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e169.9\u0026thinsp;\u0026plusmn;\u0026thinsp;54.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e180.3\u0026thinsp;\u0026plusmn;\u0026thinsp;51.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.004\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.195\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLDL Cholesterol, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e96.7\u0026thinsp;\u0026plusmn;\u0026thinsp;43.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e101.9\u0026thinsp;\u0026plusmn;\u0026thinsp;39.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.020\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.127\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e95.7\u0026thinsp;\u0026plusmn;\u0026thinsp;40.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e101.8\u0026thinsp;\u0026plusmn;\u0026thinsp;39.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.025\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.152\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHDL Cholesterol, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;17.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.994\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e42.1\u0026thinsp;\u0026plusmn;\u0026thinsp;18.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e43.0\u0026thinsp;\u0026plusmn;\u0026thinsp;15.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.464\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.049\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTriglyceride, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e172.2\u0026thinsp;\u0026plusmn;\u0026thinsp;167.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e188.1\u0026thinsp;\u0026plusmn;\u0026thinsp;154.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.072\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.098\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e174.1\u0026thinsp;\u0026plusmn;\u0026thinsp;149.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e188.3\u0026thinsp;\u0026plusmn;\u0026thinsp;155.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.170\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.093\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHemoglobin A1c, %\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.403\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.047\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e7.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e7.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.410\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.056\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrate, mg/dL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e6.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.137\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.214\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e6.5\u0026thinsp;\u0026plusmn;\u0026thinsp;2.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e6.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0.272\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.189\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eALT: Alanine aminotransferase; AST: Aspartate aminotransferase; CRP: C reactive protein; ESR: Erythrocyte sedimentation rate; PTH: Parathyroid hormone; Alk: Alkaline; BUN: Blood urea nitrogen; SD: standard deviation; Std. Diff.: Standardized difference; MCV: mean corpuscular volume, F: Ferritin, ng/mL. ESR: erythrocyte sedimentation rate\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this large, propensity score\u0026ndash;matched cohort of patients with stage 3 CKD, varenicline use was associated with significantly lower risks of all-cause mortality, major adverse cardiovascular events, pneumonia, acute kidney injury, and CKD progression compared with NRT. These findings extend prior evidence by suggesting that the choice of smoking cessation pharmacotherapy may have differential effects on cardiorenal outcomes in CKD, beyond its role in facilitating abstinence.\u003c/p\u003e \u003cp\u003eThe magnitude of renal benefit observed in the present study is particularly notable. Varenicline use was associated with substantial reductions in both AKI and CKD progression, suggesting that interruption of smoking-related injury may rapidly translate into benefits for kidney function. Mechanistically, smoking cessation improves endothelial nitric oxide bioavailability, reduces oxidative stress, and restores autoregulatory capacity within the renal microcirculation (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These effects may reduce susceptibility to hemodynamic insults and mitigate maladaptive repair processes that drive fibrosis and progressive nephron loss (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Our observation is consistent with recent Korean population study (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), whereas we found a greater benefits of renal outcomes than cardiovascular endpoints and suggests that the kidney may be particularly sensitive to sustained nicotine abstinence.\u003c/p\u003e \u003cp\u003eThe observed differences between varenicline and NRT likely reflect both pharmacologic and pathophysiological mechanisms. Varenicline, a selective partial agonist of the α4β2 nicotinic acetylcholine receptor, reduces nicotine craving and attenuates the reinforcing effects of smoking, resulting in higher rates of sustained abstinence compared with NRT (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In contrast, NRT maintains ongoing exposure to nicotine, albeit at lower levels. Nicotine itself has been shown to exert direct deleterious effects on the cardiovascular and renal systems, including increased sympathetic tone, impaired endothelial function, and promotion of oxidative stress and inflammation (\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Persistent low-level nicotine exposure may therefore perpetuate microvascular injury and limit recovery of endothelial integrity (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). By facilitating more complete nicotine abstinence, varenicline might allow more effective reversal of these processes.\u003c/p\u003e \u003cp\u003eSimilarly, cigarette smoke impairs pulmonary host defenses through disruption of mucociliary clearance, epithelial barrier integrity, and innate immune responses, including altered macrophage and neutrophil function, thereby increasing susceptibility to respiratory infections (\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Smoking cessation has been shown to partially reverse these abnormalities, restoring mucosal immunity and improving epithelial repair (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Our findings of greater reduction in pneumonia risk in varenicline rather than nicotine might reflect importance of complete and sustained nicotine abstinence. These effects are particularly relevant in CKD, who itself vulnerable for sepsis due to underlying CKD related immune dysregulation and chronic inflammation.\u003c/p\u003e \u003cp\u003eThe modest differences in fracture risks likely reflect the complex and multifactorial pathogenesis of smoking and CKD in bone disease. Smoking has been associated with reduced bone mineral density, impaired osteoblast function, and dysregulation of calcium\u0026ndash;phosphate homeostasis, including alterations in parathyroid hormone signaling (\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). These effects are further amplified in CKD patients due to CKD\u0026ndash;mineral and bone disorder (CKD-MBD) related renal osteodystrophy, where disturbances in vitamin D metabolism, secondary hyperparathyroidism, and chronic inflammation contribute to skeletal fragility (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Although smoking cessation may partially reverse smoking-related skeletal toxicity, its impact may be attenuated by persistent CKD-specific factors such as metabolic acidosis, uremia-associated inflammation, and hormonal dysregulation (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Consistent with this, the modest improvement in fracture-free survival observed with varenicline suggests that while effective smoking cessation may confer some skeletal benefit, bone health in CKD remains largely determined by the broader metabolic and inflammatory milieu.\u003c/p\u003e \u003cp\u003eSubgroup analyses demonstrated consistent benefits of varenicline across major demographic and clinical strata. Sex-specific differences in vascular function, including endothelial responsiveness and hormonal modulation of nitric oxide signaling, may contribute to differential susceptibility to smoking-related injury and recovery following cessation (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). In addition, immune and inflammatory responses are known to vary by sex, potentially influencing both cardiovascular and infectious outcomes (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). The amplified risks observed in obese patients are biologically plausible, as excess adiposity is associated with chronic low-grade inflammation, oxidative stress, and endothelial dysfunction, all of which may potentiate smoking-related vascular and renal injury (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Conversely, the differential patterns observed in those without diabetes might reflect metabolic and inflammatory profiles that modify susceptibility to cardiorenal and infectious complications. In CKD patients, whose systemic inflammation, uremic toxicity, and immune dysregulation are already present, these interacting factors likely shape individual risk trajectories. Collectively, the benefits from smoking cessation therapies influences by individualized risk stratification and patient-specific characteristics.\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, the observational design precludes causal inference and introduces the potential for residual confounding despite rigorous propensity score matching. Second, detailed information on smoking behavior\u0026mdash;including intensity, duration, and sustained abstinence\u0026mdash;was not available, limiting mechanistic interpretation of the observed associations. Third, medication adherence could not be directly ascertained, raising the possibility of exposure misclassification. Fourth, outcome definitions were based on administrative coding, which may be subject to misclassification bias. Finally, although baseline characteristics were well balanced, modest residual differences in laboratory parameters may reflect unmeasured biological variability or residual confounding not fully captured in the matching process.\u003c/p\u003e \u003cp\u003eIn conclusion, among patients with stage 3 CKD, varenicline use is associated with significant reductions in mortality, cardiovascular events, pulmonary complications, and renal disease progression compared with nicotine replacement therapy. These findings suggest that complete nicotine abstinence, facilitated by varenicline, may confer substantial cardiorenal protection. Further prospective and mechanistic studies are needed to confirm these observations and to elucidate the biological pathways linking smoking cessation strategies to kidney outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJ.-Q.Z. and Y.-C.H. contributed substantially to the conception and design of the study, data acquisition, analysis, and interpretation, and drafted the manuscript. C.-L.L. and J.W. contributed to data analysis and interpretation and critically revised the manuscript for important intellectual content. H.-C.Y. and T.T.S. contributed to data interpretation and substantive revision of the manuscript. C.-M.Z. and K.-C.L. contributed to study conception, design, supervision, and critical revision of the manuscript. K.-C.L. and C.-M.Z. take responsibility for the integrity of the work as a whole.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLuyckx VA, Tonelli M, Stanifer JW. The global burden of kidney disease and the sustainable development goals. Bull World Health Organ. 2018;96(6):414\u0026ndash;D422.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKovesdy CP. Epidemiology of chronic kidney disease: an update 2022. Kidney Int Suppl (2011) 2022; 12(1):7\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsumoto A, Nagasawa Y, Yamamoto R, et al. Cigarette smoking and progression of kidney dysfunction: a longitudinal cohort study. Clin Exp Nephrol. 2024;28(8):793\u0026ndash;802.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYacoub R, Habib H, Lahdo A, et al. Association between smoking and chronic kidney disease: a case control study. 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Kidney Int Suppl 2009(113):S1\u0026ndash;130.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNickolas TL, Stein EM, Dworakowski E, et al. Rapid cortical bone loss in patients with chronic kidney disease. J Bone Min Res. 2013;28(8):1811\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiller VM, Duckles SP. Vascular actions of estrogens: functional implications. Pharmacol Rev. 2008;60(2):210\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMendelsohn ME, Karas RH. The protective effects of estrogen on the cardiovascular system. N Engl J Med. 1999;340(23):1801\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlein SL, Flanagan KL. Sex differences in immune responses. Nat Rev Immunol. 2016;16(10):626\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHotamisligil GS. Inflammation and metabolic disorders. Nature. 2006;444(7121):860\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFurukawa S, Fujita T, Shimabukuro M, et al. Increased oxidative stress in obesity and its impact on metabolic syndrome. J Clin Invest. 2004;114(12):1752\u0026ndash;61.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"chronic kidney disease, varenicline, nicotine replacement therapy, mortality, cardiovascular events","lastPublishedDoi":"10.21203/rs.3.rs-9531023/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9531023/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a retrospective cohort study using the TriNetX global health research network to compare clinical outcomes in CKD patients who initiated smoking cessation therapy with nicotine (n\u0026thinsp;=\u0026thinsp;41,361) or varenicline (n\u0026thinsp;=\u0026thinsp;5,496) between 2009 and 2019. After 1:1 propensity score matching, 5,494 patients were included in each group. Primary outcomes included all-cause mortality, major adverse cardiovascular events (MACE); secondary outcomes included pneumonia, fractures, acute kidney injury (AKI), and CKD progression. Time-to-event analyses were performed using Kaplan\u0026ndash;Meier methods and Cox proportional hazards models.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOver 5 years, varenicline was associated with significantly lower risks of all-cause mortality (10.7% vs 19.3%; hazard ratio [HR], 2.25; 95% CI, 2.03\u0026ndash;2.49), MACE (33.3% vs 43.4%; HR, 1.64; 95% CI, 1.52\u0026ndash;1.76), pneumonia (10.8% vs 17.6%; HR, 2.06; 95% CI, 1.85\u0026ndash;2.29), AKI (19.0% vs 34.9%; HR, 2.41; 95% CI, 2.23\u0026ndash;2.62), and CKD progression (19.0% vs 34.9%; HR, 2.41; 95% CI, 2.23\u0026ndash;2.62) compared with NRT (all \u003cem\u003eP\u003c/em\u003e\u0026lt;.001). Fracture risk was similar between groups, although varenicline was associated with modestly improved fracture-free survival (HR, 1.19; 95% CI, 1.07\u0026ndash;1.32). Subgroup analyses demonstrated consistent benefit across demographic and clinical strata.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAmong CKD patients, varenicline use for smoking cessation is associated with significantly lower risks of mortality, cardiovascular events, and renal deterioration compared to NRT. These findings suggest that more complete nicotine abstinence achieved with varenicline may confer substantial cardiorenal protection. Prospective studies are needed to confirm these observations.\u003c/p\u003e","manuscriptTitle":"Comparison of clinical outcomes between different smoking cessation therapies in patients with chronic kidney disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-13 17:56:37","doi":"10.21203/rs.3.rs-9531023/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-19T09:36:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T12:19:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"267600021607529946487554981049757017963","date":"2026-05-06T18:51:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"319970987606100815004959972385431985686","date":"2026-05-05T11:04:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199027981445202866698187196894159185973","date":"2026-05-05T07:09:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"212587773402666520724634376644405209497","date":"2026-05-05T04:33:15+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-05T04:30:43+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-27T09:48:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-27T09:42:45+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medicine","date":"2026-04-26T09:53:17+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmed","sideBox":"Learn more about [BMC Medicine](http://bmcmedicine.biomedcentral.com/)","snPcode":"12916","submissionUrl":"https://submission.nature.com/new-submission/12916/3","title":"BMC Medicine","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c5f38633-3f79-48c2-8e8a-e602d3850750","owner":[],"postedDate":"May 13th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-19T09:36:36+00:00","index":39,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-13T12:19:23+00:00","index":38,"fulltext":""},{"type":"reviewerAgreed","content":"267600021607529946487554981049757017963","date":"2026-05-06T18:51:54+00:00","index":37,"fulltext":""},{"type":"reviewerAgreed","content":"319970987606100815004959972385431985686","date":"2026-05-05T11:04:40+00:00","index":35,"fulltext":""},{"type":"reviewerAgreed","content":"199027981445202866698187196894159185973","date":"2026-05-05T07:09:44+00:00","index":33,"fulltext":""},{"type":"reviewerAgreed","content":"212587773402666520724634376644405209497","date":"2026-05-05T04:33:15+00:00","index":28,"fulltext":""},{"type":"reviewersInvited","content":"24","date":"2026-05-05T04:30:43+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T17:56:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-13 17:56:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9531023","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9531023","identity":"rs-9531023","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}