Atrial Fibrillation Versus Non-Atrial Fibrillation in Postoperative Complications Following Lumbar Surgery: A retrospective case-control study

Atrial Fibrillation Versus Non-Atrial Fibrillation in Postoperative Complications Following Lumbar Surgery: A retrospective case-control study | 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 Atrial Fibrillation Versus Non-Atrial Fibrillation in Postoperative Complications Following Lumbar Surgery: A retrospective case-control study Chaojun Wang, Yiming Mai, Jimei Zhang, Jian Wang, Jiong Lin, Qinfeng Yang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7693596/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 06 Apr, 2026 Read the published version in Perioperative Medicine → Version 1 posted 11 You are reading this latest preprint version Abstract Background With aging population and high prevalence rate of atrial fibrillation (AF) in old individuals, more elderly patients with AF receive lumbar operations. Nevertheless, there has been little study discussing the perioperative outcomes of AF in lumbar surgery, especially using a national database. Methods A population-based, retrospective cohort survey was conducted on adults receiving lumbar surgery who were divided into 2 cohorts based on the diagnosis of AF or not using the 2016–2019 Nationwide Inpatient Sample database. Propensity score matching was applied to eliminate founding bias. Univariate and multivariate analyses were performed to explore the impact of AF on postoperative complications following AF. Results Overall, 222,557 lumbar surgical patients were finally involved in the present study, 10,929 (4.9%) of whom had AF. Irrespective of potential confounders, the in-hospital death risk of patients undergoing lumbar surgery with AF was 1.75-fold compared to those without AF. Additionally, AF was an apparently independent risk factor for cardiac arrest, postoperative delirium, pneumonia, pulmonary embolism, acute respiratory failure, continuous trauma ventilation, acute renal failure, urinary tract infection, gastrointestinal bleeding, blood transfusion, pyemia, septicemia, death, wound infection, and hemorrhage/hematoma/seroma. Conclusion AF seems to be associated with increased perioperative mortality and complications. Orthopedists should be cognizant of the adverse impact in patients with AF. Atrial fibrillation Lumbar surgery Complications Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Due to the aging population, the demand of lumbar fusion and decompression procedures for acute degeneration disease with the symptoms of pain and impairment continuously rises. [ 1 , 2 ] There are over 4.83 million patients undergoing spine surgery procedures around the world each year. From 2004 to 2015, the rate of lumbar spine fusion surgeries among US adults has gone up, climbing from 60.4 per 100,000 to 79.8 per 100,000. [ 3 ] Meanwhile, as the general surgical approaches popularized for lumbar fusion and decompression operations, the number of perioperative complications may increase. Currently, atrial fibrillation (AF) affects approximately 1–2% people around the world and its prevalence was estimated to double in the next five decades due to aging population. [ 4 ] Furthermore, it has been shown to be associated with serious adverse cardiovascular events, such as thrombo-embolic events and heart failure, affecting the life quality of these patients. Additionally, AF can lead to dementia or cognitive decline, especially in older patients. [ 5 , 6 ] A number of studies have demonstrated that AF poses a significant risk of perioperative complications and mortality in both cardiac and orthopedic operations. [ 7 , 8 ] All these adverse influences of AF seem to make surgeries such as lumbar surgeries riskier. Nevertheless, there has been a dearth of research examining the effects of AF on perioperative outcomes subsequent to lumbar spine surgery. Therefore, the objective of this study is to examine the impact of AF on the occurrence of complications among all patients who were hospitalized and underwent lumbar fusion or decompression surgery between 2016 and 2019. Methods Data source Nationwide Inpatient Sample (NIS) was used in this study to screen the situation of more than 25 million hospitalized patients in the United States from 2016 to 2019. It includes demographics, payment type, and clinical data, including International Classification of Diseases, Tenth Revision (ICD-10) diagnosis and procedure code. A key advantage of NIS is that it is the largest database of all-paid hospitals in the United States, which collects 20% medical records of all inpatient discharges in American community hospitals (excluding long-term emergency care and rehabilitation hospitals) with nearly 8 million admission representative samples each year. [ 9 ] Since NIS contains completely de-identified medical record data, this study was granted exempt status by our Institutional Review Board. Data collection From 2016 to 2019, patients with a primary ICD-10 procedure code for either lumbar fusion (0S.G0-G1) or lumbar vertebral decompression (0S.T2-T4 and 0S.B2-B4) were included in the lumbar spine surgery research cohort (n = 236,939). Among them, patients with missing age data or younger than 18 (n = 6049), patients with missing gender (n = 34), patients with missing payment (n = 256), as well as patients with missing race (n = 8043) were excluded. Ultimately, the remaining patients (n = 222,557) were separated into two groups, 10,929 with AF and 211,628 without AF (ICD-10-CM codes were I480/I481/I482/I4891). Outcomes We used the ICD-10-CM diagnostic code to identify the perioperative complications. The term "any complication" represented one or more complications occurred. medical complications include acute myocardial infarction (AMI), cardiac arrest, acute heart failure, shock, acute cerebrovascular disease, postoperative delirium (POD), pneumonia, pulmonary embolism (PE), acute respiratory failure, continuous trauma ventilation, acute renal failure (ARF), urinary retention, urinary tract infection (UTI), gastrointestinal bleeding (GI bleeding), blood transfusion, deep vein thrombosis (DVT), thrombocytopenia, pyemia and septicemia. Surgical complications include wound infection, wound rupture, hemorrhage/seroma/hematoma, and nerve injuries (Table 1 ). Table 1 Variables Used in Propensity Score Matching. Variables Categories Specific Variables Patient demographics Sex (male and female), race (White, Black, Hispanic, Asian or Pacific Islander, Native American and Other), age group (18–44, 45–54, 55–64, 65–74, ≥ 75) Hospital characteristics Type of admission (non-elective, elective), bed size of hospital (small, medium, large), teaching status of hospital (nonteaching, teaching), location of hospital (rural, urban), type of insurance (medicare, medicaid, private insurance, self-pay, no charge, other), Comorbidities AIDS, alcohol abuse, deficiency anemia, rheumatoid arthritis, chronic blood loss anemia, congestive heart failure, coagulopathy, depression, diabetes (uncomplicated), diabetes (with chronic complications), drug abuse, hypertension, hypothyroidism, liver disease, fluid and electrolyte disorders, metastatic cancer, neurological disorders, obesity, paralysis, peripheral vascular disorders, psychoses, pulmonary circulation disorders, solid tumor without metastasis, peptic ulcer disease, weight loss, chronic lung disease, psychoses, pulmonary circulatory disease, lymphoma AIDS: Acquired immunodeficiency syndrome Propensity-matched analysis To eliminate the confounding impact of demographic variables and comorbidities, covariates were input into the propensity score, including social demographics (age, race, sex, payment type, and hospital characteristics) and pre-existing comorbidities inherently kept in the database. Patients with AF were matched 1:1 with non-AF by calipers of a width equal to 0.05 of the standard deviation of the logit of the propensity score via the greedy (or nearest neighbor without replacement) matching method. After matching, the matched lumbar surgery cohort consisted of 10,840 AF patients and 10,840 non-AF patients. Data analysis Demographics, comorbidities, perioperative complications and mortality were compared between patients undergoing lumbar surgery with a diagnosis of atrial fibrillation (L-AF) and without a diagnosis of atrial fibrillation (non-L-AF). The Pearson chi-square test was performed for univariate analysis of all categorical variables between L-AF cohort and non-L-AF cohort. Mann-Whitney U test was utilized for continuous variables. To control demographic variables and comorbidities, covariates were matched in 1:1 propensity score. Multivariate logistic analyzes were used to calculate odds ratios (OR) and 95% confidence intervals (CIs) by R version 4.3.2. P <0.05 were identified as statistical difference. Results Baseline Patient and Providers’ Characteristics The NIS database identified 236,939 patients who underwent lumbar fusion operation or lumbar decompression operation from 2016 to 2019. 22,415 cases were excluded from analysis for missing demographic variables, and the remaining cases (222,557) were included (Fig. 1 ). 10,929 patients with concomitant atrial fibrillation were identified, accounting for 4.9% of lumbar spine surgeries. Lumbar spine surgeries for patients with AF showed an upward trend, increasing from 4.5 cases per 100 people in 2016 to 5.1 cases per 100 people in 2019 (Fig. 2 ). Patients with AF who underwent lumbar surgery were older than patients without AF (72 years vs 62 years, P < 0.001), predominately the white race; patients with AF tended to hospitalized in large and teaching hospitals, and had a higher prevalence of comorbidities than patients without AF (Table 2 ). Table 2 Cohort Characteristics for Patients Undergoing Lumbar Surgery with and without Atrial Fibrillation before and after Matching. Characteristic Prior to matching After Matching L-AF Whole non-L-AF P value Matched L-AF Matched non-L-AF P value L-AU & matched non-L-AU Number of patients 10,915 211,642 10,840 10,840 Gender <0.001 0.901 Male 60.1% 46.1% 59.9% 60.0% -0.002 Female 39.9% 53.9% 40.1% 40.0% 0.002 Age (Medium, years) 72 (66–77) 62(52–70) <0.001 72 (66–77) <0.001 -0.018 Age subgroup 0.000 0.052 18–44 1.0% 14.1% 1.0% 1.0% 45–54 3.5% 16.8% 3.5% 2.9% 0.031 55–64 19.0% 29.6% 19.1% 18.3% 0.021 65–74 38.3% 26.4% 38.5% 39.6% -0.023 ≥ 75 38.2% 13.2% 37.9% 38.1% RACE <0.001 0.906 White 89.6% 80.5% 89.6% 89.4% Black 4.3% 8.3% 4.3% 4.4% 0.003 Hispanic 3.3% 6.8% 3.3% 3.2% 0.014 Asian or pacific islander 1.0% 1.4% 1.0% 1.1% 0.000 Native American 0.2% 0.5% 0.2% 0.3% 0.008 Other 1.6% 2.5% 1.6% 1.6% 0.001 Pay type <0.001 0.426 Medicare 75.7% 45.6% 75.6% 76.7% Medicaid 2.5% 7.6% 2.5% 2.3% 0.017 Private insurance 18.1% 38.3% 18.2% 17.3% 0.023 Self-pay 0.4% 1.2% 0.4% 0.5% -0.006 No charge 0.0% 1.0% 0.0% 0.0% 0.000 Other 3.2% 7.2% 3.2% 3.3% -0.002 Hospital bed size <0.001 0.705 Small 20.4% 23.3% 20.5% 20.2% -0.01 Medium 27.0% 26.6% 27.0% 27.4% 0.004 -0.100 Large 52.6% 50.1% 52.5% 52.3% -0.005 0.004 Hospital location 0.616 0.616 Rural 96.6% 96.7% 96.6% 96.7% -0.005 Urban 3.4% 3.3% 3.4% 3.3% Hospital teaching status <0.001 0.495 Non-teaching 24.3% 26.2% 24.3% 23.9% Teaching 75.7% 73.8% 75.7% 76.1% -0.009 Hypertension 82.2% 57.2% 0.000 82.1% 82.6% 0.318 -0.014 Obesity 26.9% 22.3% <0.001 26.9% 27.5% 0.352 -0.013 Uncomplicated diabetes mellitus 16.7% 14.1% <0.001 16.8% 17.3% 0.338 0.008 Hypothyroidism 18.4% 13.6% <0.001 18.4% 17.9% 0.398 0.011 Chronic lung disease 22.8% 16.9% <0.001 22.7% 22.7% 0.948 0.001 Depression 15.4% 16.9% <0.001 15.4% 15.6% 0.338 -0.005 Deficiency anemia 2.4% 1.3% <0.001 2.4% 2.2% 0.362 0.012 Fluid and electrolyte disorders 18.2% 8.5% <0.001 18.0% 17.7% 0.489 0.014 Renal failure 15.4% 5% 0.000 15.2% 14.7% 0.312 0.014 Valvular disease 9.9% 2.2% 0.000 9.5% 9.1% 0.293 0.014 Other neurological disorders 5.6% 2.1% <0.001 5.5% 5.6% 0.766 -0.004 Rheumatoid arthritis 5.3% 4.0% <0.001 5.2% 5.3% 0.879 -0.002 Peripheral vascular disorders 7.4% 2.9% <0.001 7.3% 7.3% 0.814 -0.003 Congestive heart failure 17.1% 2.3% 0.000 16.6% 15.7% 0.086 -0.023 Complicated diabetes mellitus 15.7% 7.8% <0.001 15.6% 15.3% 0.535 -0.013 Coagulopathy 6.1% 2.4% <0.001 5.9% 5.6% 0.399 0.011 Psychoses 2.0% 2.7% <0.001 2.0% 2.3% 0.101 -0.023 Chronic blood loss anemia 0.6% 0.4% 0.005 0.6% 0.6% 0.932 0.012 Pulmonary circulatory disease 3.5% 0.5% 0.000 3.2% 2.8% 0.066 0.023 Alcohol abuse 2.2% 1.5% <0.001 2.2% 2.2% 0.889 0.002 Liver disease 2.6% 2.3% 0.040 2.6% 2.6% 0.932 -0.001 Solid tumor without metastasis 1.7% 0.8% <0.001 1.7% 1.7% 0.792 -0.004 Drug abuse 1.7% 2.0% 0.024 1.7% 1.8% 0.756 -0.004 Lymphoma 0.6% 0.3% <0.001 0.6% 0.6% 1.000 0.000 Paralysis 3.5% 3.0% 0.005 3.5% 3.3% 0.574 0.008 Weight loss 2.6% 1.0% <0.001 2.6% 2.4% 0.431 0.010 Metastatic cancer 1.2% 0.6% <0.001 1.2% 1.2% 0.852 -0.003 Peptic ulcer disease excluding bleeding 0.5% 0.3% <0.001 0.5% 0.6% 0.643 -0.006 Acquired immune deficiency syndrome 0.1% 0.3% 0.007 0.1% 0.1% 0.857 -0.002 Charlson comorbidity index subgroup <0.001 0.774 0 4.4% 19.0% 4.5% 4.5% 1 15.6% 25.3% 15.7% 15.5% 0.005 2 21.8% 23.7% 22.0% 22.6% -0.014 3 58.2% 31.9% 57.8% 57.4% 0.008 L-AF: patients who had had lumbar surgery was diagnosis of atrial fibrillation non-L-AF: patients who had had lumbar surgery was not diagnosis of atrial fibrillation Propensity score-matched cohort analysis In this study, 10,840 L-AF patients were successfully matched with non-L-AF patients (Table 2 ). After matching, the absolute standardized difference of all measurement confounding factors was < 10%, indicating successful matching and group balance. Outcomes after matching The results (Figs. 3 & 4 ) of the multivariate logistic analyzes were consistent with the propensity-matched analysis. After adjustments for possible confounding factors, the L-AF cohort demonstrated a higher risk of any complication (OR, 1.301; 95% CI, 1.228 to 1.378; P < 0.001), any medical complication (OR, 1.296; 95% CI, 1.223–1.374; P < 0.001); and any surgical complication (OR, 1.316; 95% CI, 1.098 to 1.578; P = 0.003). Moreover, compared with non-AF, AF patients were more likely to die during the hospitalization (OR, 1.751; 95% CI, 1.240 to 2.471; P = 0.001). In addition, AF was a risk factor for the below medical complications: cardiac arrest (OR, 1.748; 95%CI, 1.087–2.810; P = 0.021), POD (OR, 1.252; 95% CI, 1.053 to 1.488; P = 0.011), pneumonia (OR, 1.418; 95% CI, 1.164 to 1.728; P < 0.001), PE (OR, 1.700; 95% CI, 1.258 to 2.298; P < 0.001), acute respiratory failure (OR, 1.469; 95% CI, 1.225 to 1.761; P < 0.001), continuous trauma ventilation (OR, 1.687; 95%CI, 1.359 to 2.093; P < 0.001), acute renal failure (OR, 1.291; 95% CI, 1.168 to 1.426; P < 0.001), UTI (OR, 1.322; 95% CI, 1.158 to 1.509; P < 0.001) GI bleeding (OR, 2.058; 95% CI, 1.204 to 3.519; P = 0.008), blood transfusion (OR, 1.301; 95% CI, 1.228 to 1.291; P < 0.001), pyemia (OR, 1.351; 95% CI, 1.120 to 1.629; P = 0.002) and septicemia (OR, 1.335; 95% CI, 1.107 to 1.610; P = 0.003),. It was found that patients with AF have an evaluated risk of such surgical complications: hemorrhage/hematoma/seroma (OR, 1.435; 95%CI, 1.060 to 1.941; P = 0.019), and wound infection (OR, 1.621; 95%CI, 2.489 to 1.378; P = 0.027). Discussion The demand of lumbar surgery, a primary treatment option for degeneration diseases unresponsive to medication, is steadily increasing, driven by an aging population experiencing persistent pain and impairment. As more elderly people tend to suffer from AF (Fig. 5 ), a leading cause of complications and mortality, there is already a growing need for lumbar surgery among patients with AF. However, little study has demonstrated the relationship between AF and outcomes for lumbar spine surgery, especially based on a large-scale database. A rare case report of 73-year-old man with AF was detected arterial thromboembolism after lumbar decompressive surgery. [ 10 ] Our study included 10,840 patients with AF and 10,840 matched controls and found that AF patients had a significantly higher mortality and incidence of complications. To our knowledge, it is the first large population-based survey to investigate how AF affects the outcomes of lumbar surgery in matched patients, controlling for various potential confounders. It is also the first study to investigate the complete impact of pre-existing AF on the postoperative outcomes. AF is a common cardiac arrhythmia characterized by rapid and irregular atrial electrical activity, resulting in ineffective atrial contractions, irregular ventricular rhythm and decreased cardiac output. [ 4 ] This AF-induced hemodynamic instability may exacerbate the risk of cardiac arrest by predisposing patients to myocardial ischemia and hypoxia, which is in agreement with our result. Wang et al [ 11 ] found that 16% of the 921 patients with AF subsequently developed congestive heart failure in the Framingham heart study. Conen et al [ 12 ] found that patients who develop new postoperative atrial fibrillation face an elevated risk of MI during the initial year following surgery. However, there is nonsignificant observed increased in postoperative AMI or acute heart failure. Further prospective studies need to be completed. Anticoagulation therapy is the primary treatment for patients with AF, aimed at reducing the risk of acute cerebrovascular disease and other thromboembolic events. However, all anticoagulants increase the risk of bleeding complications with different level of severity, such as GI bleeding and blood transfusion during the operation. [ 13 ] And it is proved in several clinical case reports. [ 8 , 14 ] A patient, receiving dabigatran, died of cerebral hemorrhage; [ 15 ] an 89-year-old patient receiving dabigatran, developed severe rectal bleeding; [ 16 ] a 78-year-old patient receiving dabigatran, developed splenic hemorrhage and hemoperitoneum. [ 17 ] Similar findings were observed in our study that AF increased the risk of blood transfusion, hemorrhage/hematoma/seroma and GI bleeding. Our observation of an increased of PE among patients with AF may be explained by hemodynamics and coagulation related to AF. In AF, the rapid and irregular atria quiver result in ineffective atrial contraction, which decreases cardiac output. Furthermore, it reduces venous return and worsens venous stasis. Additionally, thrombi that forms in the atrial appendage can fall off and lead to embolism. [ 18 ] Both of these can result in DVT and PE. However, we found no notable differences in increased risk of DVT or acute cerebrovascular disease. These results are in accordance with finding reported by Wang et al, [ 19 ] who reported that AF elevated the risk of PE but not posed a similar threat to DVT without comorbidities. It indicated that the occurrence of DVT may require a combination or complex interaction of AF and other comorbidities. This finding is consistent with a guideline that the cumulative risk of stroke in patients with "AF alone" without a clinical history or echocardiographic evidence of cardiovascular disease is low. [ 4 ] Ammar et al conducted a case-control study of 110 patients with AF and concluded that AF is secondary to stroke. [ 20 ] However, Leif et al. [ 21 ] reported that AF was not associated with a higher risk of PE alone. We speculate that this is might be due to the exclusion of atrial fibrillation OAC treatment. Given the limitation of our database, we could not divide the AF patients into OAC treatment group and without OAC group. And Leif et al. [ 21 ] concluded OAC treatment was associated with a reduction of PE. However, there are few findings about these phenomena and further research is needed to validate this. Since OAC therapy significantly reduces the incidence of PE, it was recommended that surgeons should provide OAC treatment to patients who have a high risk of PE. Our cohort-match study adds evidence that there are significantly difference in risk of acute respiratory failure and continuous trauma ventilation with a comparison of L-AF and non-L-AF. Postoperative PE may contribute to acute respiratory failure under the mechanism of ventilation-perfusion (V/Q) mismatch resulting from vascular obstruction and pulmonary vasoconstriction. [ 22 ] Among the general population, atrial fibrillation is related to poor renal function outcomes and is one of the most common disorders in patients at risk for renal impairment. [ 23 , 24 ] Consistently, we found that AF was associated with acute renal failure and the possibility for acute renal failure is 1.3-folds compared with patients without AF (irrespective of basic information and 29 comorbidities). This may be strongly associated with acute/subacute hemodynamic changes due to AF. Furthermore, myocardial fibrosis and similar modifications in the kidney are also promoted by AF. [ 25 , 26 ] The hypothesis of pathogenic mechanisms is still to be verified by further studies. Furthermore, consistent with the results showed by Wei-Syun et al, who exclaimed that AF elevated the risk of the aforementioned adverse renal outcomes. In this regard, the clinical relevance and significance are clear; patients after lumbar spine surgery with AF had higher risk of acute renal failure. Therefore, physicians should take this issue seriously when caring for patients with AF in lumbar spine surgery and increase the monitoring of patients with atrial fibrillation and/or utilizing nephroprotective therapies as early as possible. In addition, we found that AF increased risk of sepsis. Limitation Although the present study has included a large number of subjects, it is still not without limitations. Firstly, an analysis of administrative databases can only make observations but not establish causality, which prevents us from reaching any decisions regarding AF and perioperative complications. Furthermore, the data set used for this research was restricted to procedures and diagnoses during each patient’s hospital day and provided little information on long-time outcomes, which included readmission for delayed medical and surgical complications, revision surgery, and failure of implant procedures. Additionally, we are unable to judge the severity of complication or the diagnostic criteria used based on ICD-9 and 10. Most importantly, neither the information with regard to the type of AF nor the treatment choices are considered in this study, which is possible to be a crucial problem. However, AF is such a wide spectrum of conditions. Despite all these limitations, the NIS remains a significantly convincing tool for conducting outcome-based orthopedic survey. With a large sample of total joint surgery admissions over a four-year period, the findings from the research are pretty powerful. Moreover, the usage of a matched cohort in outcome analyses reduced the bias related to demographic differences between patients with AF. Conclusion The study showed that patients with AF in lumbar surgery had a crucially increased venture for mortality and other complications (Fig. 6 ). Patients with AF tended to have more comorbidities related to cardiovascular disease. The findings of the present study are beneficial for surgeons to counsel patients preoperatively about the potential risks of AF following lumbar surgery. Moreover, surgeons should further improve perioperative management for these patients. Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interest. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution C.W made substantial contributions to the conception.Y.M and J.Z wrote the main manuscript text.J.W and J.L made substantial contributions to the acquisition, analysis.Q.Y have drafted the work or substantively revised it. Data Availability This study is based on data provided by Nationwide Inpatient Sample (NIS) database, part of the Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. The NIS database is a large publicly availablefull-payer inpatient care database in the United States and the direct web link to the database is https://www.ahrq.gov/data/hcup/index.html. Data could be shared by corresponding author on reasonable request. References Alpert JN. Review of the Diagnosis and Management of Lumbar Spinal Stenosis. Jama. 2022;328(8):779–80. Laubach M, Kobbe P, Hutmacher DW. Biodegradable interbody cages for lumbar spine fusion: Current concepts and future directions. Biomaterials. 2022;288:121699. Yoshida B, Nguyen A, Formanek B, Alam M, Wang JC, Buser Z. Hypoalbuminemia and Elevated CRP are Risk Factors for Deep Infections and Urinary Tract Infections After Lumbar Spine Surgery in a Large Retrospective Patient Population. Global Spine J. 2023;13(1):33–44. 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Cite Share Download PDF Status: Published Journal Publication published 06 Apr, 2026 Read the published version in Perioperative Medicine → Version 1 posted Editorial decision: Revision requested 16 Feb, 2026 Reviews received at journal 16 Feb, 2026 Reviewers agreed at journal 13 Feb, 2026 Reviews received at journal 09 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 09 Feb, 2026 Reviewers agreed at journal 27 Jan, 2026 Reviewers invited by journal 14 Jan, 2026 Editor assigned by journal 24 Sep, 2025 Submission checks completed at journal 24 Sep, 2025 First submitted to journal 23 Sep, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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1","display":"","copyAsset":false,"role":"figure","size":80980,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of demographic, comorbidity and perioperative complications in patients with AF following lumbar surgery.\u003c/p\u003e","description":"","filename":"Fig.1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/b0cd06bb9005ceddec2ae08a.jpg"},{"id":100599948,"identity":"e5a6c5d4-44cb-4722-8671-7615b022e611","added_by":"auto","created_at":"2026-01-19 14:45:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":29189,"visible":true,"origin":"","legend":"\u003cp\u003eMorbidity of atrial fibrillation between 2016-2019.\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/1917eb479d6200e1fcc19a80.jpg"},{"id":100600140,"identity":"12c10772-8109-498d-a93c-8ff1671d57b4","added_by":"auto","created_at":"2026-01-19 14:46:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":412316,"visible":true,"origin":"","legend":"\u003cp\u003eHospital Outcomes for Patients Undergoing Lumbar Surgery with and without Atrial Fibrillation before Matching.\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/7edf2048da90aaf4d6370dc8.jpg"},{"id":100600328,"identity":"96266151-2c0d-4c06-8fce-3262db4c5ee8","added_by":"auto","created_at":"2026-01-19 14:47:30","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":417776,"visible":true,"origin":"","legend":"\u003cp\u003eHospital Outcomes for Patients Undergoing Lumbar Surgery with and without Atrial Fibrillation after Matching.\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/12edd3ae2bae1c232b56dd58.jpg"},{"id":100599786,"identity":"fd3f9768-31ff-4797-a277-9a6e499d2f4d","added_by":"auto","created_at":"2026-01-19 14:45:01","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":60574,"visible":true,"origin":"","legend":"\u003cp\u003ePatient demographics and hospital characteristics between the two surgical groups. A Hospital location distribution analysis of non-AF patients. B Hospital location distribution of L-AF patients. C Pay type distribution analysis of non-AF patients. D Pay type analysis of L-AF patients. E Hospital bedsize distribution analysis of non-AF patients. F Hospital bedsize distribution analysis of L-AF patients. G Hospital teaching status distribution analysis of non-AF patients. H Hospital teaching status distribution analysis of L-AF patients.\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/6c32fc09342e7c4acbe745a1.jpg"},{"id":100600126,"identity":"e31f56f4-5fa6-4c07-b059-679c3541ade8","added_by":"auto","created_at":"2026-01-19 14:46:27","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":427157,"visible":true,"origin":"","legend":"\u003cp\u003eOutcomes of postoperative complications related to atrial fibrillation.\u003c/p\u003e","description":"","filename":"Fig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/f24b73e3b871c9ac97ec3287.jpg"},{"id":106809345,"identity":"8320029f-b44f-4254-b370-a143060e812e","added_by":"auto","created_at":"2026-04-13 16:09:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2923218,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7693596/v1/0644bc32-8ab1-41e0-a23e-8c5a5cc2c4a5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Atrial Fibrillation Versus Non-Atrial Fibrillation in Postoperative Complications Following Lumbar Surgery: A retrospective case-control study","fulltext":[{"header":"Background","content":"\u003cp\u003eDue to the aging population, the demand of lumbar fusion and decompression procedures for acute degeneration disease with the symptoms of pain and impairment continuously rises.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThere are over 4.83\u0026nbsp;million patients undergoing spine surgery procedures around the world each year. From 2004 to 2015, the rate of lumbar spine fusion surgeries among US adults has gone up, climbing from 60.4 per 100,000 to 79.8 per 100,000.\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e Meanwhile, as the general surgical approaches popularized for lumbar fusion and decompression operations, the number of perioperative complications may increase.\u003c/p\u003e \u003cp\u003eCurrently, atrial fibrillation (AF) affects approximately 1\u0026ndash;2% people around the world and its prevalence was estimated to double in the next five decades due to aging population.\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e Furthermore, it has been shown to be associated with serious adverse cardiovascular events, such as thrombo-embolic events and heart failure, affecting the life quality of these patients. Additionally, AF can lead to dementia or cognitive decline, especially in older patients.\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e A number of studies have demonstrated that AF poses a significant risk of perioperative complications and mortality in both cardiac and orthopedic operations.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e All these adverse influences of AF seem to make surgeries such as lumbar surgeries riskier.\u003c/p\u003e \u003cp\u003eNevertheless, there has been a dearth of research examining the effects of AF on perioperative outcomes subsequent to lumbar spine surgery. Therefore, the objective of this study is to examine the impact of AF on the occurrence of complications among all patients who were hospitalized and underwent lumbar fusion or decompression surgery between 2016 and 2019.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eNationwide Inpatient Sample (NIS) was used in this study to screen the situation of more than 25\u0026nbsp;million hospitalized patients in the United States from 2016 to 2019. It includes demographics, payment type, and clinical data, including International Classification of Diseases, Tenth Revision (ICD-10) diagnosis and procedure code. A key advantage of NIS is that it is the largest database of all-paid hospitals in the United States, which collects 20% medical records of all inpatient discharges in American community hospitals (excluding long-term emergency care and rehabilitation hospitals) with nearly 8\u0026nbsp;million admission representative samples each year.\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e Since NIS contains completely de-identified medical record data, this study was granted exempt status by our Institutional Review Board.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eFrom 2016 to 2019, patients with a primary ICD-10 procedure code for either lumbar fusion (0S.G0-G1) or lumbar vertebral decompression (0S.T2-T4 and 0S.B2-B4) were included in the lumbar spine surgery research cohort (n\u0026thinsp;=\u0026thinsp;236,939). Among them, patients with missing age data or younger than 18 (n\u0026thinsp;=\u0026thinsp;6049), patients with missing gender (n\u0026thinsp;=\u0026thinsp;34), patients with missing payment (n\u0026thinsp;=\u0026thinsp;256), as well as patients with missing race (n\u0026thinsp;=\u0026thinsp;8043) were excluded. Ultimately, the remaining patients (n\u0026thinsp;=\u0026thinsp;222,557) were separated into two groups, 10,929 with AF and 211,628 without AF (ICD-10-CM codes were I480/I481/I482/I4891).\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eWe used the ICD-10-CM diagnostic code to identify the perioperative complications. The term \"any complication\" represented one or more complications occurred. medical complications include acute myocardial infarction (AMI), cardiac arrest, acute heart failure, shock, acute cerebrovascular disease, postoperative delirium (POD), pneumonia, pulmonary embolism (PE), acute respiratory failure, continuous trauma ventilation, acute renal failure (ARF), urinary retention, urinary tract infection (UTI), gastrointestinal bleeding (GI bleeding), blood transfusion, deep vein thrombosis (DVT), thrombocytopenia, pyemia and septicemia. Surgical complications include wound infection, wound rupture, hemorrhage/seroma/hematoma, and nerve injuries (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eVariables Used in Propensity Score Matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables Categories\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSpecific Variables\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient demographics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex (male and female), race (White, Black, Hispanic, Asian or Pacific Islander, Native American and Other), age group (18\u0026ndash;44, 45\u0026ndash;54, 55\u0026ndash;64, 65\u0026ndash;74, \u0026ge;\u0026thinsp;75)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospital characteristics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType of admission (non-elective, elective), bed size of hospital (small, medium, large), teaching status of hospital (nonteaching, teaching), location of hospital (rural, urban), type of insurance (medicare, medicaid, private insurance, self-pay, no charge, other),\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAIDS, alcohol abuse, deficiency anemia, rheumatoid arthritis, chronic blood loss anemia, congestive heart failure, coagulopathy, depression, diabetes (uncomplicated), diabetes (with chronic complications), drug abuse, hypertension, hypothyroidism, liver disease, fluid and electrolyte disorders, metastatic cancer, neurological disorders, obesity, paralysis, peripheral vascular disorders, psychoses, pulmonary circulation disorders, solid tumor without metastasis, peptic ulcer disease, weight loss, chronic lung disease, psychoses, pulmonary circulatory disease, lymphoma\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003eAIDS: Acquired immunodeficiency syndrome\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003ePropensity-matched analysis\u003c/h3\u003e\n\u003cp\u003eTo eliminate the confounding impact of demographic variables and comorbidities, covariates were input into the propensity score, including social demographics (age, race, sex, payment type, and hospital characteristics) and pre-existing comorbidities inherently kept in the database. Patients with AF were matched 1:1 with non-AF by calipers of a width equal to 0.05 of the standard deviation of the logit of the propensity score via the greedy (or nearest neighbor without replacement) matching method. After matching, the matched lumbar surgery cohort consisted of 10,840 AF patients and 10,840 non-AF patients.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eDemographics, comorbidities, perioperative complications and mortality were compared between patients undergoing lumbar surgery with a diagnosis of atrial fibrillation (L-AF) and without a diagnosis of atrial fibrillation (non-L-AF). The Pearson chi-square test was performed for univariate analysis of all categorical variables between L-AF cohort and non-L-AF cohort. Mann-Whitney U test was utilized for continuous variables. To control demographic variables and comorbidities, covariates were matched in 1:1 propensity score. Multivariate logistic analyzes were used to calculate odds ratios (OR) and 95% confidence intervals (CIs) by R version 4.3.2. \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 were identified as statistical difference.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Patient and Providers\u0026rsquo; Characteristics\u003c/h2\u003e \u003cp\u003eThe NIS database identified 236,939 patients who underwent lumbar fusion operation or lumbar decompression operation from 2016 to 2019. 22,415 cases were excluded from analysis for missing demographic variables, and the remaining cases (222,557) were included (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). 10,929 patients with concomitant atrial fibrillation were identified, accounting for 4.9% of lumbar spine surgeries. Lumbar spine surgeries for patients with AF showed an upward trend, increasing from 4.5 cases per 100 people in 2016 to 5.1 cases per 100 people in 2019 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Patients with AF who underwent lumbar surgery were older than patients without AF (72 years \u003cem\u003evs\u003c/em\u003e 62 years, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), predominately the white race; patients with AF tended to hospitalized in large and teaching hospitals, and had a higher prevalence of comorbidities than patients without AF (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCohort Characteristics for Patients Undergoing Lumbar Surgery with and without Atrial Fibrillation before and after Matching.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003ePrior to matching\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c8\" namest=\"c5\"\u003e \u003cp\u003eAfter Matching\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eL-AF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eWhole non-L-AF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eMatched L-AF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eMatched non-L-AF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eP value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eL-AU \u0026amp; matched non-L-AU\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\u003eNumber of patients\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10,915\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e211,642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10,840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10,840\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.901\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\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\u003e60.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e60.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.002\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\u003e39.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e40.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge (Medium, years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72 (66\u0026ndash;77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62(52\u0026ndash;70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72 (66\u0026ndash;77)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge subgroup\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.052\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e18\u0026ndash;44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e45\u0026ndash;54\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e55\u0026ndash;64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e65\u0026ndash;74\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e39.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e\u0026ge;\u0026thinsp;75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRACE\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\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\u003e89.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e89.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBlack\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHispanic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAsian or pacific islander\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNative American\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePay type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.426\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedicare\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedicaid\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePrivate insurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSelf-pay\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo charge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital bed size\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.705\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmall\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedium\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLarge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e52.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital location\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.616\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRural\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrban\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHospital teaching status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNon-teaching\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTeaching\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e76.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.318\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eObesity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e26.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.352\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUncomplicated diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypothyroidism\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic lung disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDepression\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.338\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDeficiency anemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFluid and electrolyte disorders\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRenal failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eValvular disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.293\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOther neurological disorders\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.766\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRheumatoid arthritis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeripheral vascular disorders\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.814\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCongestive heart failure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComplicated diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCoagulopathy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePsychoses\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.101\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic blood loss anemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePulmonary circulatory disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlcohol abuse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiver disease\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSolid tumor without metastasis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.792\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrug abuse\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.756\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphoma\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eParalysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeight loss\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.431\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMetastatic cancer\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.852\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePeptic ulcer disease excluding bleeding\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAcquired immune deficiency syndrome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCharlson comorbidity index subgroup\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.774\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.3%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.5%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.7%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.6%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e-0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.9%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e57.8%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57.4%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003eL-AF: patients who had had lumbar surgery was diagnosis of atrial fibrillation\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003enon-L-AF: patients who had had lumbar surgery was not diagnosis of atrial fibrillation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePropensity score-matched cohort analysis\u003c/h3\u003e\n\u003cp\u003eIn this study, 10,840 L-AF patients were successfully matched with non-L-AF patients (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After matching, the absolute standardized difference of all measurement confounding factors was \u0026lt;\u0026thinsp;10%, indicating successful matching and group balance.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes after matching\u003c/h2\u003e \u003cp\u003eThe results (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) of the multivariate logistic analyzes were consistent with the propensity-matched analysis. After adjustments for possible confounding factors, the L-AF cohort demonstrated a higher risk of any complication (OR, 1.301; 95% CI, 1.228 to 1.378; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), any medical complication (OR, 1.296; 95% CI, 1.223\u0026ndash;1.374; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001); and any surgical complication (OR, 1.316; 95% CI, 1.098 to 1.578; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). Moreover, compared with non-AF, AF patients were more likely to die during the hospitalization (OR, 1.751; 95% CI, 1.240 to 2.471; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). In addition, AF was a risk factor for the below medical complications: cardiac arrest (OR, 1.748; 95%CI, 1.087\u0026ndash;2.810; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.021), POD (OR, 1.252; 95% CI, 1.053 to 1.488; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.011), pneumonia (OR, 1.418; 95% CI, 1.164 to 1.728; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), PE (OR, 1.700; 95% CI, 1.258 to 2.298; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), acute respiratory failure (OR, 1.469; 95% CI, 1.225 to 1.761; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), continuous trauma ventilation (OR, 1.687; 95%CI, 1.359 to 2.093; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), acute renal failure (OR, 1.291; 95% CI, 1.168 to 1.426; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), UTI (OR, 1.322; 95% CI, 1.158 to 1.509; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) GI bleeding (OR, 2.058; 95% CI, 1.204 to 3.519; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008), blood transfusion (OR, 1.301; 95% CI, 1.228 to 1.291; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), pyemia (OR, 1.351; 95% CI, 1.120 to 1.629; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002) and septicemia (OR, 1.335; 95% CI, 1.107 to 1.610; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003),. It was found that patients with AF have an evaluated risk of such surgical complications: hemorrhage/hematoma/seroma (OR, 1.435; 95%CI, 1.060 to 1.941; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019), and wound infection (OR, 1.621; 95%CI, 2.489 to 1.378; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.027).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe demand of lumbar surgery, a primary treatment option for degeneration diseases unresponsive to medication, is steadily increasing, driven by an aging population experiencing persistent pain and impairment. As more elderly people tend to suffer from AF (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), a leading cause of complications and mortality, there is already a growing need for lumbar surgery among patients with AF.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eHowever, little study has demonstrated the relationship between AF and outcomes for lumbar spine surgery, especially based on a large-scale database. A rare case report of 73-year-old man with AF was detected arterial thromboembolism after lumbar decompressive surgery.\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e Our study included 10,840 patients with AF and 10,840 matched controls and found that AF patients had a significantly higher mortality and incidence of complications. To our knowledge, it is the first large population-based survey to investigate how AF affects the outcomes of lumbar surgery in matched patients, controlling for various potential confounders. It is also the first study to investigate the complete impact of pre-existing AF on the postoperative outcomes.\u003c/p\u003e \u003cp\u003eAF is a common cardiac arrhythmia characterized by rapid and irregular atrial electrical activity, resulting in ineffective atrial contractions, irregular ventricular rhythm and decreased cardiac output.\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e This AF-induced hemodynamic instability may exacerbate the risk of cardiac arrest by predisposing patients to myocardial ischemia and hypoxia, which is in agreement with our result. Wang et al\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e found that 16% of the 921 patients with AF subsequently developed congestive heart failure in the Framingham heart study. Conen et al\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e found that patients who develop new postoperative atrial fibrillation face an elevated risk of MI during the initial year following surgery. However, there is nonsignificant observed increased in postoperative AMI or acute heart failure. Further prospective studies need to be completed.\u003c/p\u003e \u003cp\u003eAnticoagulation therapy is the primary treatment for patients with AF, aimed at reducing the risk of acute cerebrovascular disease and other thromboembolic events. However, all anticoagulants increase the risk of bleeding complications with different level of severity, such as GI bleeding and blood transfusion during the operation.\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e And it is proved in several clinical case reports.\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e A patient, receiving dabigatran, died of cerebral hemorrhage;\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e an 89-year-old patient receiving dabigatran, developed severe rectal bleeding;\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e a 78-year-old patient receiving dabigatran, developed splenic hemorrhage and hemoperitoneum.\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e Similar findings were observed in our study that AF increased the risk of blood transfusion, hemorrhage/hematoma/seroma and GI bleeding.\u003c/p\u003e \u003cp\u003eOur observation of an increased of PE among patients with AF may be explained by hemodynamics and coagulation related to AF. In AF, the rapid and irregular atria quiver result in ineffective atrial contraction, which decreases cardiac output. Furthermore, it reduces venous return and worsens venous stasis. Additionally, thrombi that forms in the atrial appendage can fall off and lead to embolism.\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e Both of these can result in DVT and PE. However, we found no notable differences in increased risk of DVT or acute cerebrovascular disease. These results are in accordance with finding reported by Wang et al,\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e who reported that AF elevated the risk of PE but not posed a similar threat to DVT without comorbidities. It indicated that the occurrence of DVT may require a combination or complex interaction of AF and other comorbidities. This finding is consistent with a guideline that the cumulative risk of stroke in patients with \"AF alone\" without a clinical history or echocardiographic evidence of cardiovascular disease is low.\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e Ammar et al conducted a case-control study of 110 patients with AF and concluded that AF is secondary to stroke.\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e However, Leif et al.\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e reported that AF was not associated with a higher risk of PE alone. We speculate that this is might be due to the exclusion of atrial fibrillation OAC treatment. Given the limitation of our database, we could not divide the AF patients into OAC treatment group and without OAC group. And Leif et al.\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e concluded OAC treatment was associated with a reduction of PE. However, there are few findings about these phenomena and further research is needed to validate this. Since OAC therapy significantly reduces the incidence of PE, it was recommended that surgeons should provide OAC treatment to patients who have a high risk of PE.\u003c/p\u003e \u003cp\u003eOur cohort-match study adds evidence that there are significantly difference in risk of acute respiratory failure and continuous trauma ventilation with a comparison of L-AF and non-L-AF. Postoperative PE may contribute to acute respiratory failure under the mechanism of ventilation-perfusion (V/Q) mismatch resulting from vascular obstruction and pulmonary vasoconstriction.\u003csup\u003e[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAmong the general population, atrial fibrillation is related to poor renal function outcomes and is one of the most common disorders in patients at risk for renal impairment.\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e Consistently, we found that AF was associated with acute renal failure and the possibility for acute renal failure is 1.3-folds compared with patients without AF (irrespective of basic information and 29 comorbidities). This may be strongly associated with acute/subacute hemodynamic changes due to AF. Furthermore, myocardial fibrosis and similar modifications in the kidney are also promoted by AF.\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e The hypothesis of pathogenic mechanisms is still to be verified by further studies. Furthermore, consistent with the results showed by Wei-Syun et al, who exclaimed that AF elevated the risk of the aforementioned adverse renal outcomes. In this regard, the clinical relevance and significance are clear; patients after lumbar spine surgery with AF had higher risk of acute renal failure. Therefore, physicians should take this issue seriously when caring for patients with AF in lumbar spine surgery and increase the monitoring of patients with atrial fibrillation and/or utilizing nephroprotective therapies as early as possible. In addition, we found that AF increased risk of sepsis.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitation\u003c/h2\u003e \u003cp\u003eAlthough the present study has included a large number of subjects, it is still not without limitations. Firstly, an analysis of administrative databases can only make observations but not establish causality, which prevents us from reaching any decisions regarding AF and perioperative complications.\u003c/p\u003e \u003cp\u003eFurthermore, the data set used for this research was restricted to procedures and diagnoses during each patient\u0026rsquo;s hospital day and provided little information on long-time outcomes, which included readmission for delayed medical and surgical complications, revision surgery, and failure of implant procedures.\u003c/p\u003e \u003cp\u003eAdditionally, we are unable to judge the severity of complication or the diagnostic criteria used based on ICD-9 and 10.\u003c/p\u003e \u003cp\u003eMost importantly, neither the information with regard to the type of AF nor the treatment choices are considered in this study, which is possible to be a crucial problem. However, AF is such a wide spectrum of conditions.\u003c/p\u003e \u003cp\u003eDespite all these limitations, the NIS remains a significantly convincing tool for conducting outcome-based orthopedic survey. With a large sample of total joint surgery admissions over a four-year period, the findings from the research are pretty powerful. Moreover, the usage of a matched cohort in outcome analyses reduced the bias related to demographic differences between patients with AF.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study showed that patients with AF in lumbar surgery had a crucially increased venture for mortality and other complications (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Patients with AF tended to have more comorbidities related to cardiovascular disease. The findings of the present study are beneficial for surgeons to counsel patients preoperatively about the potential risks of AF following lumbar surgery. Moreover, surgeons should further improve perioperative management for these patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no competing interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eC.W made substantial contributions to the conception.Y.M and J.Z wrote the main manuscript text.J.W and J.L made substantial contributions to the acquisition, analysis.Q.Y have drafted the work or substantively revised it.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThis study is based on data provided by Nationwide Inpatient Sample (NIS) database, part of the Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. The NIS database is a large publicly availablefull-payer inpatient care database in the United States and the direct web link to the database is https://www.ahrq.gov/data/hcup/index.html. Data could be shared by corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlpert JN. Review of the Diagnosis and Management of Lumbar Spinal Stenosis. Jama. 2022;328(8):779\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaubach M, Kobbe P, Hutmacher DW. Biodegradable interbody cages for lumbar spine fusion: Current concepts and future directions. Biomaterials. 2022;288:121699.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYoshida B, Nguyen A, Formanek B, Alam M, Wang JC, Buser Z. Hypoalbuminemia and Elevated CRP are Risk Factors for Deep Infections and Urinary Tract Infections After Lumbar Spine Surgery in a Large Retrospective Patient Population. Global Spine J. 2023;13(1):33\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCamm AJ, Kirchhof P, Lip GY, Schotten U, Savelieva I, Ernst S, et al. Guidelines for the management of atrial fibrillation: the Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Eur Heart J. 2010;31(19):2369\u0026ndash;429.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBunch TJ. Atrial Fibrillation and Dementia. Circulation. 2020;142(7):618\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnecht S, Oelschl\u0026auml;ger C, Duning T, Lohmann H, Albers J, Stehling C, et al. Atrial fibrillation in stroke-free patients is associated with memory impairment and hippocampal atrophy. Eur Heart J. 2008;29(17):2125\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLaPar DJ, Speir AM, Crosby IK, Fonner E, Jr., Brown M, Rich JB, et al. Postoperative atrial fibrillation significantly increases mortality, hospital readmission, and hospital costs. Ann Thorac Surg. 2014;98(2):527\u0026ndash;33; discussion 33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeller K, Hobohm L, Engelhardt M. Impact of Atrial Fibrillation on Postoperative Adverse Outcomes of Surgical Patients With Knee Endoprosthetic Surgery. J Arthroplasty. 2018;33(11):3567\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIssa K, Boylan MR, Naziri Q, Perfetti DC, Maheshwari AV, Mont MA. The Impact of Hepatitis C on Short-Term Outcomes of Total Joint Arthroplasty. J Bone Joint Surg Am. 2015;97(23):1952\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEun SS, Lee KY, Lee SH, Kim JS. Delayed thromboembolic occlusion of common femoral artery following posterior lumbar decompressive surgery in a patient with chronic atrial fibrillation. J Orthop Sci. 2011;16(5):661\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang TJ, Larson MG, Levy D, Vasan RS, Leip EP, Wolf PA, et al. Temporal relations of atrial fibrillation and congestive heart failure and their joint influence on mortality: the Framingham Heart Study. Circulation. 2003;107(23):2920\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eConen D, Alonso-Coello P, Douketis J, Chan MTV, Kurz A, Sigamani A, et al. Risk of stroke and other adverse outcomes in patients with perioperative atrial fibrillation 1 year after non-cardiac surgery. Eur Heart J. 2020;41(5):645\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShaw JR, Kaplovitch E, Douketis J. Periprocedural Management of Oral Anticoagulation. Med Clin North Am. 2020;104(4):709\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLong G, Suqin S, Li G, Weihong Y, Zhenhu W. Impact of atrial fibrillation on postoperative outcomes after total knee arthroplasty-A retrospective study. J Orthop Sci. 2016;21(5):652\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasado Naranjo I, Portilla-Cuenca JC, Jim\u0026eacute;nez Caballero PE, Calle Escobar ML, Romero Sevilla RM. Fatal intracerebral hemorrhage associated with administration of recombinant tissue plasminogen activator in a stroke patient on treatment with dabigatran. Cerebrovasc Dis. 2011;32(6):614\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLegrand M, Mateo J, Aribaud A, Ginisty S, Eftekhari P, Huy PT, et al. The use of dabigatran in elderly patients. Arch Intern Med. 2011;171(14):1285\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMoore CH, Snashall J, Boniface K, Scott J. Spontaneous splenic hemorrhage after initiation of dabigatran (Pradaxa) for atrial fibrillation. Am J Emerg Med. 2012;30(9):2082.e1-2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSavelieva I, Bajpai A, Camm AJ. Stroke in atrial fibrillation: update on pathophysiology, new antithrombotic therapies, and evolution of procedures and devices. Ann Med. 2007;39(5):371\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang CC, Lin CL, Wang GJ, Chang CT, Sung FC, Kao CH. Atrial fibrillation associated with increased risk of venous thromboembolism. A population-based cohort study. Thromb Haemost. 2015;113(1):185\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKillu AM, Granger CB, Gersh BJ. Risk stratification for stroke in atrial fibrillation: a critique. Eur Heart J. 2019;40(16):1294\u0026ndash;302.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFriberg L, Svennberg E. A diagnosis of atrial fibrillation is not a predictor for pulmonary embolism. Thromb Res. 2020;195:238\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFukunaga N, Takahashi N, Hagiwara S, Kume O, Fukui A, Teshima Y, et al. Establishment of a model of atrial fibrillation associated with chronic kidney disease in rats and the role of oxidative stress. Heart Rhythm. 2012;9(12):2023\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoliman EZ, Prineas RJ, Go AS, Xie D, Lash JP, Rahman M, et al. Chronic kidney disease and prevalent atrial fibrillation: the Chronic Renal Insufficiency Cohort (CRIC). Am Heart J. 2010;159(6):1102\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVillgran VD, Lyons C, Nasrullah A, Clarisse Abalos C, Bihler E, Alhajhusain A. Acute Respiratory Failure. Crit Care Nurs Q. 2022;45(3):233\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWatanabe H, Watanabe T, Sasaki S, Nagai K, Roden DM, Aizawa Y. Close bidirectional relationship between chronic kidney disease and atrial fibrillation: the Niigata preventive medicine study. Am Heart J. 2009;158(4):629\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eStamellou E, Floege J. Erratum to: Novel oral anticoagulants in patients with chronic kidney disease and atrial fibrillation. Nephrol Dial Transplant. 2021;36(5):952.\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"perioperative-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"peri","sideBox":"Learn more about [Perioperative Medicine](http://perioperativemedicinejournal.biomedcentral.com)","snPcode":"13741","submissionUrl":"https://submission.nature.com/new-submission/13741/3","title":"Perioperative Medicine","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Atrial fibrillation, Lumbar surgery, Complications","lastPublishedDoi":"10.21203/rs.3.rs-7693596/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7693596/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWith aging population and high prevalence rate of atrial fibrillation (AF) in old individuals, more elderly patients with AF receive lumbar operations. Nevertheless, there has been little study discussing the perioperative outcomes of AF in lumbar surgery, especially using a national database.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA population-based, retrospective cohort survey was conducted on adults receiving lumbar surgery who were divided into 2 cohorts based on the diagnosis of AF or not using the 2016\u0026ndash;2019 Nationwide Inpatient Sample database. Propensity score matching was applied to eliminate founding bias. Univariate and multivariate analyses were performed to explore the impact of AF on postoperative complications following AF.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOverall, 222,557 lumbar surgical patients were finally involved in the present study, 10,929 (4.9%) of whom had AF. Irrespective of potential confounders, the in-hospital death risk of patients undergoing lumbar surgery with AF was 1.75-fold compared to those without AF. Additionally, AF was an apparently independent risk factor for cardiac arrest, postoperative delirium, pneumonia, pulmonary embolism, acute respiratory failure, continuous trauma ventilation, acute renal failure, urinary tract infection, gastrointestinal bleeding, blood transfusion, pyemia, septicemia, death, wound infection, and hemorrhage/hematoma/seroma.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eAF seems to be associated with increased perioperative mortality and complications. Orthopedists should be cognizant of the adverse impact in patients with AF.\u003c/p\u003e","manuscriptTitle":"Atrial Fibrillation Versus Non-Atrial Fibrillation in Postoperative Complications Following Lumbar Surgery: A retrospective case-control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-19 13:41:36","doi":"10.21203/rs.3.rs-7693596/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-17T01:35:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-16T08:29:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65236328755712675353064675573309464962","date":"2026-02-13T23:22:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-09T17:10:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"215249510222269250328529534138636402390","date":"2026-02-09T16:57:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"248214339127719680062644203397835453587","date":"2026-02-09T13:24:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1008067069565350649775142703661925973","date":"2026-01-27T21:47:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-14T15:26:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-24T06:27:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-24T06:25:55+00:00","index":"","fulltext":""},{"type":"submitted","content":"Perioperative Medicine","date":"2025-09-23T10:55:28+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"perioperative-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"peri","sideBox":"Learn more about [Perioperative Medicine](http://perioperativemedicinejournal.biomedcentral.com)","snPcode":"13741","submissionUrl":"https://submission.nature.com/new-submission/13741/3","title":"Perioperative Medicine","twitterHandle":"@EMSurgeryBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"409d1469-f828-4ca9-87c0-7a49325c93dd","owner":[],"postedDate":"January 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-04-13T16:06:14+00:00","versionOfRecord":{"articleIdentity":"rs-7693596","link":"https://doi.org/10.1186/s13741-026-00678-1","journal":{"identity":"perioperative-medicine","isVorOnly":false,"title":"Perioperative Medicine"},"publishedOn":"2026-04-06 15:58:22","publishedOnDateReadable":"April 6th, 2026"},"versionCreatedAt":"2026-01-19 13:41:36","video":"","vorDoi":"10.1186/s13741-026-00678-1","vorDoiUrl":"https://doi.org/10.1186/s13741-026-00678-1","workflowStages":[]},"version":"v1","identity":"rs-7693596","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7693596","identity":"rs-7693596","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}