The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis

The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis Yichao Han, Yue Chen, Xujun Xuan, Hongyu Guan, Cheng Luo, Daohu Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5023932/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Objective Diabetes mellitus (DM) has been confirmed as a common risk factor for postoperative complications. This study aims to elucidate the impact of DM on postoperative complications following radical prostatectomy. Methods Using data from a national inpatient sample from 2016 to 2020, patients aged ≥ 18 years who were diagnosed with prostate cancer (PCa) and underwent radical prostatectomy were identified and divided into a DM group and a non-DM group. We further divided the DM group into uncomplicated DM and advanced DM groups. We compared the outcome variables between the three groups through univariate analysis and adjusted multivariate logistic regression. Results Seventeen thousand five hundred eighty-eight records were undergoing radical prostatectomy included in the present study, among which 2683 records (9.43%) had a diagnosis of DM. The DM group will incur higher costs (53,775 [38,286 − 65,482] vs. 51,546 [37,195 − 61,815] p < 0.001). After adjusting the variables with baseline differences in the multivariate regression models, DM was identified as an independent risk factor for unfavorable discharge (aOR = 1.20, 95%CI [1.02–1.42], P = 0.31), genitourinary complication (aOR = 1.40, 95%CI [1.13–1.73], P = 0.002), cardiac complication (aOR = 1.29, 95%CI [1.04–1.6], P = 0.019), and ventilatory support (aOR = 1.55, 95%CI [1.05–2.29], P = 0.028). After subgrouping the DM group by DM-related complications, the advanced DM group has more than double the risks of blood transfusion, genitourinary, and respiratory complications, compared to the non-DM group. Conclusion The findings suggest that DM is more likely to face adverse clinical outcomes and higher incidences of postoperative complications. It found that DM is an independent risk factor for adverse clinical outcomes after radical prostatectomy for cancer. prostatectomy prostate cancer diabetes mellitus postoperative complications Introduction Prostate cancer (PCa) is the most prevalent malignancy among men in the United States (US) and the second leading cause of cancer-related mortality[ 1 ]. Prostate cancer and diabetes mellitus (DM) are the two most common public health concerns within the aging male demographic[ 2 ]. Radical prostatectomy (RP), conducted via open retropubic resection (ORP) or robot-assisted radical prostatectomy (RARP), is the reference standard for the treatment of prostate cancer. Several studies have investigated various risk factors associated with adverse outcomes following RP[ 3 – 6 ]. These studies reveal a significant correlation between adverse outcomes and factors such as patient age, family history, race, weight, dietary habits, smoking, hospital capacity, hospital bed size, and hospital teaching status. The impact of DM on postoperative outcomes in patients undergoing RP remains debated. A meta-analysis included 17 cohort studies with 274,677 male patients concluded that pre-existing DM is associated with increased prostate cancer-specific mortality and all-cause mortality[ 7 ]. However, a Swedish cohort study reached the opposite conclusion, reporting no correlation between DM and prostate cancer after adjusting for confounding risk factors[ 8 ]. Jayachandran et al. studied diabetic patients undergoing RP and found a significant link between DM and higher postoperative complication rates, with obesity and race as crucial contributing factors.[ 9 ]. Considering these inconsistent research findings, this study aims to assess the impact of DM on postoperative complications following RP using a largest publicly accessible hospital discharge database. Materials and Methods Data Source All patient data were extracted from the National Inpatient Sample (NIS) database between 2016 to 2020. The NIS, the largest publicly accessible hospital discharge database encompassing all payers in the US, is a component of the Healthcare Cost and Utilization Project supported by the Agency for Healthcare Research and Quality (AHRQ)[ 10 ]. It comprises approximately 20% of discharge summaries from community hospitals across the US, encompassing public hospitals and academic medical centers, thus enabling the derivation of national estimates. The NIS database contains various data elements, including primary and secondary diagnoses, primary and secondary procedures, admission type, patient demographics, expected payment source, length of hospital stay, and hospital characteristics. Since 2016, the NIS has utilized the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) codes. Study Design ICD-10-CM program codes (0VT00ZZ, 0VT04ZZ, 0VT07ZZ, 0VT08ZZ, 0VB00ZZ, 0VB04ZZ) were used to identify patients underwent prostatectomy. We excluded subjects without a diagnosis of prostate malignancy (C61) and patients aged ≤ 18 years. Records missing critical data were excluded, while missing values for the race/ethnicity variable, exceeding 5%, were combined into the "Other" category. According to the presence or absence of diabetes diagnosis codes, patients included were divided into the DM group and the non-DM group. Additionally, patients in the DM group were further categorized as uncomplicated and advanced DM based on the presence of chronic DM-related complications. Details of the ICD-10-CM/PCS codes used are summarised in Table 1 . Table 1 ICD-10 codes for defining . Variable ICD-10 Codes Diabetes Mellitus Advanced diabetes mellitus E08.2, E08.3, E08.4, E08.5, E08.6, E08.8, E09.2, E09.3, E09.4, E09.5, E09.6, E09.8, E10.2, E10.3, E10.4, E10.5, E10.6, E10.8, E11.2, E11.3, E11.4, E11.5, E11.6, E11.8, E13.2, E13.3, E13.4, E13.5, E13.6, E13.8 Uncomplicated diabetes mellitus E08.0, E08.1, E08.9, E09.0, E09.1, E09.9, E10.1, E10.9, E11.0, E11.1, E11.9, E13.0, E13.1, E13.9, O24.0, O24.1, O24.3, O24.4, O24.8, O24.9 Prostate Malignancy C61 Radical Prostatectomy 0VT00ZZ, 0VT04ZZ, 0VT07ZZ, 0VT08ZZ, 0VB00ZZ, 0VB04ZZ The baseline data included patient demographics and hospital characteristics. Patient demographics encompassed age, race, admission type, insurance status, primary expected payer, income quartile by zip code, admission type, and comorbidities. The burden of comorbidities was measured using the Elixhauser comorbidity index (ECI) and categorized as 0, 1, and ≥ 2[ 11 , 12 ]. Since DM is the primary variable of interest in this study, we excluded the two DM-related categories when calculating the ECI. Hospital characteristics included hospital size, location, and teaching status. Age was continuously assessed. The primary clinical outcomes of this study were length of stay (LOS), unfavorable discharge status, total hospital charges, and postoperative complications. Postoperative complications included ventilatory support, blood transfusion, postoperative pain, infection, deep vein thrombosis (DVT)/pulmonary embolism (PE), genitourinary, respiratory, cardiac, and gastrointestinal issues. Details of the ICD-10 codes used can be found in Supplementary Table 1 . Transfer to a short-term hospital, home health care, or other transfers, including a skilled nursing facility, intermediate care, and another type of facility, was defined as unfavorable discharge[ 13 , 14 ]. LOS and total hospital charges were calculated as continuous variables. Statistical analysis Continuous variables are presenting as medians and interquartile ranges owing to skewed data. Categorical variables are presented as proportions. The Mann-Whitney U test was utilized for comparing continuous variables, while categorical variables were analyzed with Pearson's chi-square test (with or without Yates' continuity correction). Fisher's exact test was applied when the chi-square test was inappropriate. To examine the impact of DM on clinical outcomes, both univariate and multivariate comparisons were performed between the two groups. Univariate comparisons were conducted as previously described. For subset analysis, categorical variables were compared using the same methods. Kruskal–Wallis test was applied to compare continuous variables among the non-DM, uncomplicated DM, and advanced DM groups. Subsequently, unadjusted and adjusted multivariable logistic regression models were established. All baseline variables with significant differences were incorporated into the adjusted models, including age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region, and ECI. Finally, the same multivariable logistic regression models were performed to compare the clinical outcomes among the non-DM, uncomplicated DM, and advanced DM groups. Patient selection and all statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC) and R software (version 4.3.3, R Foundation for Statistical Computing, Vienna, Austria). A p-value of < 0.05 was considered statistically significant. Results Table 2 presents the baseline demographic and clinical feature data of the 17,588 patients included in the analysis, of which 2,683 (15.25%) were divided into the DM group. Patients with DM are older (65 [60–69] vs. 63 [58–67]) and have a higher proportion of black individuals (20.8% vs. 11.7%). They also have lower income level, with higher proportions in the first (23.1% vs. 17.2%) or second (25.3% vs. 22.9%) income level quartiles. Additionally, a lower proportion of these patients pay with private insurance (49.3% vs. 58.9%), and they generally have higher ECI scores (ECI ≥ 3: 10.5% vs. 5.2%). Table 2 Characteristics of Hospitals and patients in DM or non-DM group undergoing radical prostectomy for prostate cancer, National Inpatient Sample 2016–2020. Demographic Characteristics Non-DM group n = 14905 (%) DM group n = 2683 (%) P-value Uncomplicated DM group n = 2129 (%) Advanced DM group n = 554 (%) P-value Between two groups c Between three groups d Age (y, median, IQR) 63 [58–67] 65 [60–69] < 0.001 64 [60–69] 66 [61–69] 0.009 < 0.001 Race/Ethnicity < 0.001 < 0.001 < 0.001 White 70.8 56.6 57.7 52.5 Black 11.7 20.8 18.9 28.2 Hispanic 5.6 8.7 9.1 7.4 Other a 11.9 13.8 14.3 11.9 Income Quartile by Zip Code < 0.001 0.254 < 0.001 1st 17.2 23.1 23.3 22.0 2nd 22.9 25.3 25.0 26.5 3rd 26.5 26.6 26.0 29.1 4th 33.4 24.9 25.6 22.4 Primary Expected Payer < 0.001 < 0.001 < 0.001 Medicare 33.8 41.3 39.5 48.4 Medicaid 3.6 5.0 4.7 5.8 Private 58.9 49.3 51.6 40.4 Other b 3.8 4.4 4.2 5.4 Admission Type 0.566 0.414 0.618 Elective 96.5 96.8 3.1 3.8 Non-elective 3.5 3.2 96.9 96.2 Hospital Bed Size 0.411 0.948 0.757 Small 15.7 15.3 15.4 15.2 Medium 25.3 24.3 24.4 23.8 Large 59.1 60.4 60.3 61.0 Hospital Location/Teaching Status 0.185 0.687 0.383 Rural 2.6 2.8 3.0 2.3 Urban Non-teaching 11.1 12.2 12.3 11.7 Urban Teaching 86.3 85.0 84.8 85.9 Hospital Region < 0.001 < 0.001 < 0.001 Northeast 26.0 24.5 25.5 20.8 Midwest 25.5 23.3 21.7 29.1 South 29.9 35.1 36.2 30.9 West 18.6 17.1 16.5 19.3 Elixhauser Comorbidity Index < 0.001 < 0.001 < 0.001 0 36.1 11.9 13.5 6.0 1 41.5 47.3 49.0 40.4 2 17.2 30.3 28.9 35.6 ≥3 5.2 10.5 8.6 18.1 a Includes Asian or Pacific Islander, Native American, other and missing . b Includes self−pay, no charge and others . Mann−Whitney U test was performed to compare age between three groups. Pearson’s chi−square tests with or without Yates’ continuity correction and Fisher’s exact tests were performed for categorical variables . c Between uncomplicated DM group and advanced DM group . d Among non−DM group, uncomplicated DM group and advanced DM group . After further categorization within the DM group, 2,129 patients (79.35%) were classified as having uncomplicated DM and 554 patients (20.65%) as having advanced DM. Similar baseline differences were observed between the uncomplicated DM and advanced DM groups, as well as among the three groups (Table 2 ). Clinical outcomes are shown in Table 3 . Longer LOS (1 [ 1 – 2 ] days vs. 1 [ 1 – 2 ] days, P < 0.001) and higher adjusted hospital charges ( $ 53,775 [38,286 − 65,482] vs. $ 51,546 [37,195 − 61,815], P < 0.001) were observed in the DM group. Higher rates of unfavorable discharge (8.2% vs. 5.6% P < 0.001) and postoperative complications were also noted, including ventilatory support (1.4% vs. 0.7% p < 0.001), blood transfusion (1.1% vs. 0.6% P < 0.009), genitourinary (4.7% vs. 2.4% P < 0.001), respiratory (1.2% vs. 0.8% P = 0.015), cardiac (4.5% vs. 2.8% P < 0.001), and gastrointestinal (3.4% vs. 2.3% P < 0.001) complications. The unadjusted logistic regression results were consistent with these findings (Table 4 ). Further analysis within the DM group revealed significant differences between the uncomplicated DM and advanced DM subgroups. Advanced DM patients had higher hospital charges ( $ 63,945 [44,808 − 77,453] vs. $ 52,129 [37,389 − 62,367], P < 0.001) and higher incidence of unfavorable discharge (11.4% vs. 7.4%, P = 0.002). They also experienced higher incidences of complications such as genitourinary (11.0% vs. 3.0%, P < 0.001), respiratory (2.3% vs. 0.9%, P = 0.007), cardiac (7.4% vs. 3.8%, P < 0.001), and gastrointestinal complications (5.8% vs. 2.8%, P < 0.001). Table 3 Clinical outcomes of patients in DM or non-DM group undergoing radical prostatecotmy for prostate cancer, National Inpatient Sample 2016–2020. Clinical Outcomes Non-DM group n = 14905 (%) DM group n = 2683 (%) P-value Uncomplicated DM group n = 2129 (%) Advanced DM group n = 554 (%) P-value Between two groups a Between three groups b Length of Stay (d, median, IQR) 1 [1–2] 1 [1–2] < 0.001 1 [1–2] 1 [1–2] < 0.001 < 0.001 Adjusted Hospital Charges ( $ , median, IQR) 51,546 [37,195 − 61,815] 53,775 [38,286 − 65,482] < 0.001 52,129 [37,389 − 62,367] 63,945 [44,808 − 77,453] < 0.001 < 0.001 Unfavorable Discharge 5.6 8.2 < 0.001 7.4 11.4 0.002 < 0.001 Ventilatory Support 0.7 1.4 < 0.001 1.2 2.0 0.169 0.001 Blood Transfusion 0.6 1.1 0.009 0.9 1.8 0.064 0.005 Postoperative Pain 1.3 1.7 0.115 1.7 1.4 0.631 0.250 Infection 0.2 0.1 1.000 0.1 0.4 0.191 0.277 DVT/PE 0.1 0.1 0.532 0.1 0.2 1.000 0.538 Genitourinary 2.4 4.7 < 0.001 3.0 11.0 < 0.001 < 0.001 Respiratory 0.8 1.2 0.015 0.9 2.3 0.007 0.002 Cardiac 2.8 4.5 < 0.001 3.8 7.4 < 0.001 < 0.001 Gastrointestinal 2.3 3.4 < 0.001 2.8 5.8 < 0.001 < 0.001 Mann−Whitney U tests and Kruskal–Wallis test were performed for length of stay and adjusted hospital charges. Pearson’s chi−square tests with or without Yates’ continuity correction and Fisher’s exact tests were performed for postoperative complications . a Between uncomplicated DM group and advanced DM group . b Among non−DM group, uncomplicated DM group and advanced DM group . Table 4 Logistic Regression Analysis of Morbidity in Patients in DM group vs non-DM group undergoing radical prostatectomy for prostate cancer, National Inpatient Sample 2016–2020. Unadjusted Adjusted a Odds Ratio 95%CI P-value Odds Ratio 95%CI P-value Unfavorable Discharge 1.50 1.29–1.75 < 0.001 1.20 1.02–1.42 0.031 Ventilatory Support 1.93 1.33–2.82 0.001 1.55 1.05–2.29 0.028 Blood Transfusion 1.74 1.14–2.65 0.010 1.48 0.95–2.28 0.081 Postoperative Pain 1.30 0.94–1.80 0.116 1.17 0.83–1.64 0.364 Infection 0.97 0.33–2.80 0.949 0.67 0.22–1.98 0.464 DVT/PE 1.39 0.46–4.16 0.557 1.19 0.38–3.67 0.766 Genitourinary 2.02 1.64–2.49 < 0.001 1.40 1.13–1.73 0.002 Respiratory 1.62 1.09–2.39 0.016 1.22 0.82–1.83 0.329 Cardiac 1.66 1.35–2.04 < 0.001 1.29 1.04–1.60 0.019 Gastrointestinal 1.49 1.18–1.88 0.001 1.14 0.90–1.46 0.282 a Adjusted for age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region and Elixhauser comorbidity index . After adjusting with baseline variables in the multivariable regression models, DM was identified as an independent risk factor for clinical outcomes, including unfavorable discharge (aOR = 1.20, 95%CI [1.02–1.42], P = 0.031), ventilatory support (aOR = 1.55, 95%CI [1.05–2.29], P = 0.028), genitourinary (aOR = 1.40, 95%CI [1.13–1.73], P = 0.002) and cardiac complications (aOR = 1.29, 95%CI [1.04–1.6], P = 0.019). (Table 4 ) In the subgroup analysis, the non-DM group served as a reference for comparison. As shown in Table 5 , though not statistically significant, higher incidences and odds were also observed in the uncomplicated DM group compared to the non-DM group. Patients in the advanced DM group undergoing RP exhibited significantly higher odds of several adverse outcomes compared to the non-DM group. These outcomes included unfavorable discharge (aOR 1.65, 95% CI [1.24–2.21], P = 0.001), blood transfusion (aOR 2.33, 95% CI [1.18–4.62], P = 0.015), genitourinary (aOR 2.96, 95% CI [2.19-4.00], P < 0.001), cardiac (aOR 1.94, 95% CI [1.37–2.74], P < 0.001), and gastrointestinal complications (aOR 1.67, 95% CI [1.13–2.45], P = 0.009). Table 5 Logistic Regression Analysis of Morbidity in Patients in non-DM group, uncomlicated DM group or DM with chronic complications group undergoing radical prostatecotmy for prostate cancer, National Inpatient Sample 2016–2020. DM Subgroups a Unadjusted Adjusted b Odds Ratio 95%CI P-value Odds Ratio 95%CI P-value Unfavorable Discharge Uncomplicated DM group 1.34 1.12–1.60 0.001 1.09 0.90–1.31 0.389 Advanced DM group 2.16 1.65–2.83 < 0.001 1.65 1.24–2.21 0.001 Ventilatory Support Uncomplicated DM group 1.71 1.11–2.63 0.015 1.46 0.94–2.27 0.095 Advanced DM group 2.80 1.50–5.24 0.001 1.83 0.93–3.50 0.067 Blood Transfusion Uncomplicated DM group 1.43 0.87–2.35 0.154 1.25 0.75–2.07 0.396 Advanced DM group 2.93 1.52–5.65 0.001 2.33 1.18–4.62 0.015 Postoperative Pain Uncomplicated DM group 1.35 0.95–1.92 0.099 1.23 0.85–1.77 0.272 Advanced DM group 1.12 0.55–2.28 0.761 0.96 0.46–1.98 0.907 Infection Uncomplicated DM group 0.61 0.14–2.58 0.500 0.45 0.10–1.93 0.282 Advanced DM group 2.34 0.55–9.97 0.249 1.33 0.30–5.92 0.705 DVT/PE Uncomplicated DM group 1.23 0.76–1.98 0.395 1.15 0.33–4.07 0.825 Advanced DM group 3.12 1.75–5.57 < 0.001 1.30 0.17–10.24 0.800 Genitourinary Uncomplicated DM group 1.28 0.98–1.68 0.072 0.95 0.72–1.25 0.689 Advanced DM group 5.12 3.84–6.81 < 0.001 2.96 2.19-4.00 < 0.001 Respiratory Uncomplicated DM group 1.31 0.38–4.51 0.665 0.99 0.61–1.60 0.955 Advanced DM group 1.68 0.22–12.71 0.614 2.00 1.09–3.65 0.024 Cardiac Uncomplicated DM group 1.31 0.38–4.51 0.665 1.11 0.87–1.43 0.409 Advanced DM group 1.68 0.22–12.71 0.614 1.94 1.37–2.74 < 0.001 Gastrointestinal Uncomplicated DM group 1.21 0.92–1.60 0.173 0.98 0.74–1.31 0.915 Advanced DM group 2.56 1.77–3.72 < 0.001 1.67 1.13–2.45 0.009 a Non−DM group was used as a reference to compare with . b Adjusted for age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region and Elixhauser comorbidity index . Discussion DM has long been a global health challenge. This study elucidates the impact of DM, particularly cases with DM-related complications, on postoperative outcomes after RP, including LOS, total hospital charges, discharge status, and postoperative complications. From 2015 to 2020, 18,057 patients in the NIS database were diagnosed with prostate cancer and received RP. After dividing these patients into DM and non-DM groups, we examined their demographic and hospital characteristics, total hospital charges, LOS, discharge status, and postoperative complication rates. Although DM is considered an independent predictor of poor prognosis in some studies on urinary surgery[ 15 – 17 ], few studies examine its impact on postoperative clinical outcomes, specifically in RP. DM plays an essential role in the complications of most surgical operations: Tan et al. and Zhang et al. indicate that DM is a risk factor for postoperative complications such as infection, hematoma, and reoperation in various non-cardiac surgeries. Several studies have assessed the impact of DM on patients undergoing RP. Teber et al. found that type 2 diabetes mellitus patients need a longer time to recover urinary control ability than non-diabetes patients after LRP, which is more evident in patients with DM for more than five years[ 10 ]. Multiple studies have shown that DM is unrelated to the clinicopathological features and biochemical recurrence in patients with PCa treated with RP[ 9 , 18 , 19 ]. Among these, Jayakrishnan et al. analyzed data from 1,262 patients with PCa and suggested that diabetes significantly increased the risk of biochemical recurrence in obese white males. Lee et al. analyzed 2,716 subjects and found that poor preoperative glycemic control worsened tumor prognosis and urinary incontinence recovery. However, most of these studies were limited by small sample size, while others focused on the relationship between preoperative glycemic control and postoperative recurrence risk or survival outcomes[ 7 , 20 ]. To our knowledge, few studies have independently reported the impact of DM on clinical outcomes after RP. This study is by far the first large-scale research to explore the relationship between DM and clinical outcomes after RP using the NIS database, incorporating over 17,000 patients with PCa. Our results found that PCa patients with DM tend to be younger and have lower income levels. Hill-Briggs et al. also reported that patients with DM generally have lower incomes[ 21 ]. At the same time, the study by Jayakrishnan et al. did not find significant age differences between PCa patients with and without DM[ 9 ]. It is confirmed that white and non-Hispanic black individuals constitute a large portion of the diabetic population, a finding consistent with the conclusions of this study[ 22 ]. Compared to non-diabetic patients, those with DM incur higher costs for RP, likely due to the combined need for postoperative care and diabetes management[ 23 ]. In this study, the incidences of postoperative complications in the DM group were significantly higher, including unfavorable discharge, ventilatory support, genitourinary, respiratory, cardiac, and gastrointestinal complications. After adjusting for potential confounding factors, DM as an independent risk factor increased the risks of unfavorable discharge after RP by 20%, ventilatory support by 55%, genitourinary by 40% and cardiac by 29%. Zhang et al. also reached similar conclusions in their meta-analysis of postoperative complications after non-cardiac surgery[ 24 ]. After subgrouping the DM group by DM-related complications, the advanced DM group has more than double the risks of blood transfusion, genitourinary, and respiratory complications, compared to the non-DM group. Wong et al. found that blood glucose control affects the clinical outcomes of abdominal surgeries ( including RP ): preoperative glycated hemoglobin (HbA1c) levels between 6% and 7% are associated with a higher risk of certain complications. These complications include anastomotic leak, wound infection, significant complications, and an increase in overall postoperative complications. This further supports the hypothesis that DM is a potential risk factor for early complications after RP. This study benefits from using a well-designed and comprehensive NIS database system. It includes substantial data, ensuring sufficient statistical power and producing convincing results. We recognize that our research has some limitations. This study possesses all the disadvantages of retrospective studies—selection bias, temporal variations in disease and treatment modalities, and unknown confounding factors. The design of the NIS database lacks definitions for diabetes control, so we cannot assess the effect of diabetes control on the outcome of postoperative complications. In addition, the NIS database lacks information on cancer's severity or pathological findings, which will help measure surgical indications, structural factors, case combinations, and disease attributes. Manual diagnostic coding may lead to inaccuracies and omissions in diagnostic information. The non-longitudinal data structure design prevents us from obtaining patients' baseline conditions upon admission. We also lack information on changes in health status during hospitalization and follow-up data. Conclusion For patients undergoing RP for PCa, those with DM are more likely to face adverse clinical outcomes and have higher incidences of postoperative complications. These differences are more pronounced in the population with DM-related complications. Our results highlight the association between diabetes and adverse clinical outcomes following RP, providing valuable insights into the perioperative management of prostate cancer patients and guidance for improved management strategies and better overall outcomes for this high-risk group. Declarations Author Contribution Yichao Han and Yue Chen wrote the main manuscript text and Hongyu Guan prepared table 1-5. Xujun Xuan and Cheng Luo prepared supplemental table 1. Daohu Wang is responsible for reviewing and revising manuscript. All authors reviewed the manuscript. Conflict of Interest: The authors declare no conflicts of interest in this study. References Siegel, R.L., A.N. Giaquinto, and A. Jemal, Cancer statistics, 2024. 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Rieken, M., et al., Association of diabetes mellitus and metformin use with biochemical recurrence in patients treated with radical prostatectomy for prostate cancer. World J Urol, 2014. 32 (4): p. 999-1005. Lee, H., et al., Impact of poor glycemic control upon clinical outcomes after radical prostatectomy in localized prostate cancer. Sci Rep, 2021. 11 (1): p. 12002. Hirata, Y., et al., Prognostic significance of diabetes mellitus and dyslipidemia in men receiving androgen-deprivation therapy for metastatic prostate cancer. Prostate Int, 2019. 7 (4): p. 166-170. Hill-Briggs, F., et al., Social Determinants of Health and Diabetes: A Scientific Review. Diabetes Care, 2020. 44 (1): p. 258-79. Zhu, Y., et al., Racial/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U.S. Diabetes Care, 2019. 42 (12): p. 2211-2219. Bommer, C., et al., The global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study. Lancet Diabetes Endocrinol, 2017. 5 (6): p. 423-430. Zhang, X., et al., Association of Diabetes Mellitus With Postoperative Complications and Mortality After Non-Cardiac Surgery: A Meta-Analysis and Systematic Review. Front Endocrinol (Lausanne), 2022. 13 : p. 841256. Additional Declarations No competing interests reported. Supplementary Files SupplementalTable1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 04 Sep, 2024 Submission checks completed at journal 04 Sep, 2024 First submitted to journal 03 Sep, 2024 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5023932","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":349736612,"identity":"2b937473-2f20-49e3-9b84-c0c3e2156ca7","order_by":0,"name":"Yichao Han","email":"","orcid":"","institution":"The First Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yichao","middleName":"","lastName":"Han","suffix":""},{"id":349736613,"identity":"48e808a9-d5eb-4f06-9f04-691ff9e553b4","order_by":1,"name":"Yue Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yue","middleName":"","lastName":"Chen","suffix":""},{"id":349736614,"identity":"0b636b38-5866-4349-9c09-237f63a47811","order_by":2,"name":"Xujun Xuan","email":"","orcid":"","institution":"The Seventh Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Xujun","middleName":"","lastName":"Xuan","suffix":""},{"id":349736615,"identity":"c36f27c3-ea29-45ee-93fe-27a1cb202e4e","order_by":3,"name":"Hongyu Guan","email":"","orcid":"","institution":"The First Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Hongyu","middleName":"","lastName":"Guan","suffix":""},{"id":349736616,"identity":"05866b93-59e1-4892-b7fe-dde49dd83bda","order_by":4,"name":"Cheng Luo","email":"","orcid":"","institution":"The First Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Cheng","middleName":"","lastName":"Luo","suffix":""},{"id":349736617,"identity":"d3233518-6997-41be-8fcc-8c699711955a","order_by":5,"name":"Daohu Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYLACHgaGBH4gfeABkghhLZINQC0JJGkxOABkEKXF4PjZwy/e1NjkGV87/BBoS13i/BkJjA/etjHIm+PSciYvzXLOsbRis9tpBkAthxM33EhgNpzbxmC4swG7FrMDOWbGPGyHE7fdTgBpOZC4QSKBTZq3DepUbFrOvwFq+Xc4cfPs9A8wh7H/xqvlRo7xY942oHukc0C2MCc23EhgY8anxf7GGzPGuX1piTNu5xQcSDA4bLzhzMNmyTnnJAw34NAi2Z9j/OHNN5vE/tnpmz98qKiTnd+efPDDmzIbeVy2AAGbBIJtwODYwMDYAGRJ4FIOAswfUFyKT+koGAWjYBSMTAAAAdRl/4cISI4AAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":true,"prefix":"","firstName":"Daohu","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2024-09-03 09:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5023932/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5023932/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65948596,"identity":"0cf309a9-5353-4aee-b1ac-9fa0320214f0","added_by":"auto","created_at":"2024-10-04 18:37:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1073700,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5023932/v1/2d1b514c-7cb0-427f-8ea3-bb9a8fe28b44.pdf"},{"id":65948457,"identity":"83c898ff-e0c3-4e96-ba6f-d94a4a2b8c3e","added_by":"auto","created_at":"2024-10-04 18:29:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15457,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalTable1.docx","url":"https://assets-eu.researchsquare.com/files/rs-5023932/v1/61919512504e24a78d112c87.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eProstate cancer (PCa) is the most prevalent malignancy among men in the United States (US) and the second leading cause of cancer-related mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Prostate cancer and diabetes mellitus (DM) are the two most common public health concerns within the aging male demographic[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Radical prostatectomy (RP), conducted via open retropubic resection (ORP) or robot-assisted radical prostatectomy (RARP), is the reference standard for the treatment of prostate cancer. Several studies have investigated various risk factors associated with adverse outcomes following RP[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. These studies reveal a significant correlation between adverse outcomes and factors such as patient age, family history, race, weight, dietary habits, smoking, hospital capacity, hospital bed size, and hospital teaching status.\u003c/p\u003e \u003cp\u003eThe impact of DM on postoperative outcomes in patients undergoing RP remains debated. A meta-analysis included 17 cohort studies with 274,677 male patients concluded that pre-existing DM is associated with increased prostate cancer-specific mortality and all-cause mortality[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, a Swedish cohort study reached the opposite conclusion, reporting no correlation between DM and prostate cancer after adjusting for confounding risk factors[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Jayachandran et al. studied diabetic patients undergoing RP and found a significant link between DM and higher postoperative complication rates, with obesity and race as crucial contributing factors.[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Considering these inconsistent research findings, this study aims to assess the impact of DM on postoperative complications following RP using a largest publicly accessible hospital discharge database.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Source\u003c/h2\u003e \u003cp\u003eAll patient data were extracted from the National Inpatient Sample (NIS) database between 2016 to 2020. The NIS, the largest publicly accessible hospital discharge database encompassing all payers in the US, is a component of the Healthcare Cost and Utilization Project supported by the Agency for Healthcare Research and Quality (AHRQ)[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. It comprises approximately 20% of discharge summaries from community hospitals across the US, encompassing public hospitals and academic medical centers, thus enabling the derivation of national estimates. The NIS database contains various data elements, including primary and secondary diagnoses, primary and secondary procedures, admission type, patient demographics, expected payment source, length of hospital stay, and hospital characteristics. Since 2016, the NIS has utilized the International Classification of Diseases, Tenth Revision, Clinical Modification/Procedure Coding System (ICD-10-CM/PCS) codes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eICD-10-CM program codes (0VT00ZZ, 0VT04ZZ, 0VT07ZZ, 0VT08ZZ, 0VB00ZZ, 0VB04ZZ) were used to identify patients underwent prostatectomy. We excluded subjects without a diagnosis of prostate malignancy (C61) and patients aged\u0026thinsp;\u0026le;\u0026thinsp;18 years. Records missing critical data were excluded, while missing values for the race/ethnicity variable, exceeding 5%, were combined into the \"Other\" category. According to the presence or absence of diabetes diagnosis codes, patients included were divided into the DM group and the non-DM group. Additionally, patients in the DM group were further categorized as uncomplicated and advanced DM based on the presence of chronic DM-related complications. Details of the ICD-10-CM/PCS codes used are summarised in 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\u003eICD-10 codes for defining .\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICD-10 Codes\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\u003eDiabetes Mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdvanced diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE08.2, E08.3, E08.4, E08.5, E08.6, E08.8, E09.2, E09.3, E09.4, E09.5, E09.6, E09.8, E10.2, E10.3, E10.4, E10.5, E10.6, E10.8, E11.2, E11.3, E11.4, E11.5, E11.6, E11.8, E13.2, E13.3, E13.4, E13.5, E13.6, E13.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUncomplicated diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE08.0, E08.1, E08.9, E09.0, E09.1, E09.9, E10.1, E10.9, E11.0, E11.1, E11.9, E13.0, E13.1, E13.9, O24.0, O24.1, O24.3, O24.4, O24.8, O24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProstate Malignancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadical Prostatectomy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0VT00ZZ, 0VT04ZZ, 0VT07ZZ, 0VT08ZZ, 0VB00ZZ, 0VB04ZZ\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe baseline data included patient demographics and hospital characteristics. Patient demographics encompassed age, race, admission type, insurance status, primary expected payer, income quartile by zip code, admission type, and comorbidities. The burden of comorbidities was measured using the Elixhauser comorbidity index (ECI) and categorized as 0, 1, and \u0026ge;\u0026thinsp;2[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Since DM is the primary variable of interest in this study, we excluded the two DM-related categories when calculating the ECI. Hospital characteristics included hospital size, location, and teaching status. Age was continuously assessed.\u003c/p\u003e \u003cp\u003eThe primary clinical outcomes of this study were length of stay (LOS), unfavorable discharge status, total hospital charges, and postoperative complications. Postoperative complications included ventilatory support, blood transfusion, postoperative pain, infection, deep vein thrombosis (DVT)/pulmonary embolism (PE), genitourinary, respiratory, cardiac, and gastrointestinal issues. Details of the ICD-10 codes used can be found in \u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e. Transfer to a short-term hospital, home health care, or other transfers, including a skilled nursing facility, intermediate care, and another type of facility, was defined as unfavorable discharge[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. LOS and total hospital charges were calculated as continuous variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables are presenting as medians and interquartile ranges owing to skewed data. Categorical variables are presented as proportions. The Mann-Whitney U test was utilized for comparing continuous variables, while categorical variables were analyzed with Pearson's chi-square test (with or without Yates' continuity correction). Fisher's exact test was applied when the chi-square test was inappropriate.\u003c/p\u003e \u003cp\u003eTo examine the impact of DM on clinical outcomes, both univariate and multivariate comparisons were performed between the two groups. Univariate comparisons were conducted as previously described. For subset analysis, categorical variables were compared using the same methods. Kruskal\u0026ndash;Wallis test was applied to compare continuous variables among the non-DM, uncomplicated DM, and advanced DM groups. Subsequently, unadjusted and adjusted multivariable logistic regression models were established. All baseline variables with significant differences were incorporated into the adjusted models, including age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region, and ECI. Finally, the same multivariable logistic regression models were performed to compare the clinical outcomes among the non-DM, uncomplicated DM, and advanced DM groups.\u003c/p\u003e \u003cp\u003ePatient selection and all statistical analyses were conducted using SAS 9.4 (SAS Institute, Cary, NC) and R software (version 4.3.3, R Foundation for Statistical Computing, Vienna, Austria). A p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e presents the baseline demographic and clinical feature data of the 17,588 patients included in the analysis, of which 2,683 (15.25%) were divided into the DM group. Patients with DM are older (65 [60\u0026ndash;69] vs. 63 [58\u0026ndash;67]) and have a higher proportion of black individuals (20.8% vs. 11.7%). They also have lower income level, with higher proportions in the first (23.1% vs. 17.2%) or second (25.3% vs. 22.9%) income level quartiles. Additionally, a lower proportion of these patients pay with private insurance (49.3% vs. 58.9%), and they generally have higher ECI scores (ECI\u0026thinsp;\u0026ge;\u0026thinsp;3: 10.5% vs. 5.2%).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCharacteristics of Hospitals and patients in DM or non-DM group undergoing radical prostectomy for prostate cancer, National Inpatient Sample 2016\u0026ndash;2020.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDemographic Characteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNon-DM group n\u0026thinsp;=\u0026thinsp;14905\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDM group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;2683\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;2129 (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAdvanced\u003c/p\u003e\n \u003cp\u003eDM group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;554 (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBetween two groups\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBetween three groups\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (y, median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 [58\u0026ndash;67]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 [60\u0026ndash;69]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 [60\u0026ndash;69]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 [61\u0026ndash;69]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome Quartile by Zip Code\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.254\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1st\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2nd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3rd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4th\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary Expected Payer\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdmission Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.566\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-elective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Bed Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.411\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.948\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Location/Teaching Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.687\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.383\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban Non-teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUrban Teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e85.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital Region\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMidwest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eElixhauser Comorbidity Index\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e\u003csup\u003ea Includes Asian or Pacific Islander, Native American, other and missing\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb Includes self\u0026minus;pay, no charge and others\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eMann\u0026minus;Whitney U test was performed to compare age between three groups. Pearson\u0026rsquo;s chi\u0026minus;square tests with or without Yates\u0026rsquo; continuity correction and Fisher\u0026rsquo;s exact tests were performed for categorical variables\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ec Between uncomplicated DM group and advanced DM group\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ed Among non\u0026minus;DM group, uncomplicated DM group and advanced DM group\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAfter further categorization within the DM group, 2,129 patients (79.35%) were classified as having uncomplicated DM and 554 patients (20.65%) as having advanced DM. Similar baseline differences were observed between the uncomplicated DM and advanced DM groups, as well as among the three groups (Table\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eClinical outcomes are shown in Table\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e. Longer LOS (1 [\u003cspan\u003e1\u003c/span\u003e\u0026ndash;\u003cspan\u003e2\u003c/span\u003e] days vs. 1 [\u003cspan\u003e1\u003c/span\u003e\u0026ndash;\u003cspan\u003e2\u003c/span\u003e] days, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher adjusted hospital charges (\u003cspan\u003e$\u003c/span\u003e53,775 [38,286\u0026thinsp;\u0026minus;\u0026thinsp;65,482] vs. \u003cspan\u003e$\u003c/span\u003e51,546 [37,195\u0026thinsp;\u0026minus;\u0026thinsp;61,815], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were observed in the DM group. Higher rates of unfavorable discharge (8.2% vs. 5.6% P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and postoperative complications were also noted, including ventilatory support (1.4% vs. 0.7% p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), blood transfusion (1.1% vs. 0.6% P\u0026thinsp;\u0026lt;\u0026thinsp;0.009), genitourinary (4.7% vs. 2.4% P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respiratory (1.2% vs. 0.8% P\u0026thinsp;=\u0026thinsp;0.015), cardiac (4.5% vs. 2.8% P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and gastrointestinal (3.4% vs. 2.3% P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) complications. The unadjusted logistic regression results were consistent with these findings (Table\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e). Further analysis within the DM group revealed significant differences between the uncomplicated DM and advanced DM subgroups. Advanced DM patients had higher hospital charges (\u003cspan\u003e$\u003c/span\u003e63,945 [44,808\u0026thinsp;\u0026minus;\u0026thinsp;77,453] vs. \u003cspan\u003e$\u003c/span\u003e52,129 [37,389\u0026thinsp;\u0026minus;\u0026thinsp;62,367], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher incidence of unfavorable discharge (11.4% vs. 7.4%, P\u0026thinsp;=\u0026thinsp;0.002). They also experienced higher incidences of complications such as genitourinary (11.0% vs. 3.0%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), respiratory (2.3% vs. 0.9%, P\u0026thinsp;=\u0026thinsp;0.007), cardiac (7.4% vs. 3.8%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and gastrointestinal complications (5.8% vs. 2.8%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eClinical outcomes of patients in DM or non-DM group undergoing radical prostatecotmy for prostate cancer, National Inpatient Sample 2016\u0026ndash;2020.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eClinical Outcomes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eNon-DM group n\u0026thinsp;=\u0026thinsp;14905\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDM group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;2683\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;2129 (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eAdvanced\u003c/p\u003e\n \u003cp\u003eDM group\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;554 (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBetween two groups\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eBetween three groups\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLength of Stay (d, median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 [1\u0026ndash;2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 [1\u0026ndash;2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 [1\u0026ndash;2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 [1\u0026ndash;2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdjusted Hospital Charges (\u003cspan\u003e$\u003c/span\u003e, median, IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51,546 [37,195\u0026thinsp;\u0026minus;\u0026thinsp;61,815]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e53,775 [38,286\u0026thinsp;\u0026minus;\u0026thinsp;65,482]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e52,129 [37,389\u0026thinsp;\u0026minus;\u0026thinsp;62,367]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63,945 [44,808\u0026thinsp;\u0026minus;\u0026thinsp;77,453]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnfavorable Discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVentilatory Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood Transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.005\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.115\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInfection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDVT/PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.532\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenitourinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.007\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastrointestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e\u003csup\u003eMann\u0026minus;Whitney U tests and Kruskal\u0026ndash;Wallis test were performed for length of stay and adjusted hospital charges. Pearson\u0026rsquo;s chi\u0026minus;square tests with or without Yates\u0026rsquo; continuity correction and Fisher\u0026rsquo;s exact tests were performed for postoperative complications\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003ea Between uncomplicated DM group and advanced DM group\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb Among non\u0026minus;DM group, uncomplicated DM group and advanced DM group\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 4\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eLogistic Regression Analysis of Morbidity in Patients in DM group vs non-DM group undergoing radical prostatectomy for prostate cancer, National Inpatient Sample 2016\u0026ndash;2020.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"7\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eAdjusted\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnfavorable Discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29\u0026ndash;1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.02\u0026ndash;1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.031\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVentilatory Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.33\u0026ndash;2.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.05\u0026ndash;2.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.028\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood Transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u0026ndash;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u0026ndash;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePostoperative Pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u0026ndash;1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.83\u0026ndash;1.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInfection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u0026ndash;2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u0026ndash;1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDVT/PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u0026ndash;4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.557\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u0026ndash;3.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGenitourinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.64\u0026ndash;2.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u0026ndash;1.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRespiratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026ndash;2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.016\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.82\u0026ndash;1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.329\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCardiac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35\u0026ndash;2.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.04\u0026ndash;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGastrointestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18\u0026ndash;1.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u0026ndash;1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003e\u003csup\u003ea Adjusted for age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region and Elixhauser comorbidity index\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAfter adjusting with baseline variables in the multivariable regression models, DM was identified as an independent risk factor for clinical outcomes, including unfavorable discharge (aOR\u0026thinsp;=\u0026thinsp;1.20, 95%CI [1.02\u0026ndash;1.42], P\u0026thinsp;=\u0026thinsp;0.031), ventilatory support (aOR\u0026thinsp;=\u0026thinsp;1.55, 95%CI [1.05\u0026ndash;2.29], P\u0026thinsp;=\u0026thinsp;0.028), genitourinary (aOR\u0026thinsp;=\u0026thinsp;1.40, 95%CI [1.13\u0026ndash;1.73], P\u0026thinsp;=\u0026thinsp;0.002) and cardiac complications (aOR\u0026thinsp;=\u0026thinsp;1.29, 95%CI [1.04\u0026ndash;1.6], P\u0026thinsp;=\u0026thinsp;0.019). (Table\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e)\u003c/p\u003e\n\u003cp\u003eIn the subgroup analysis, the non-DM group served as a reference for comparison. As shown in Table\u0026nbsp;\u003cspan\u003e5\u003c/span\u003e, though not statistically significant, higher incidences and odds were also observed in the uncomplicated DM group compared to the non-DM group. Patients in the advanced DM group undergoing RP exhibited significantly higher odds of several adverse outcomes compared to the non-DM group. These outcomes included unfavorable discharge (aOR 1.65, 95% CI [1.24\u0026ndash;2.21], P\u0026thinsp;=\u0026thinsp;0.001), blood transfusion (aOR 2.33, 95% CI [1.18\u0026ndash;4.62], P\u0026thinsp;=\u0026thinsp;0.015), genitourinary (aOR 2.96, 95% CI [2.19-4.00], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), cardiac (aOR 1.94, 95% CI [1.37\u0026ndash;2.74], P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and gastrointestinal complications (aOR 1.67, 95% CI [1.13\u0026ndash;2.45], P\u0026thinsp;=\u0026thinsp;0.009).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eLogistic Regression Analysis of Morbidity in Patients in non-DM group, uncomlicated DM group or DM with chronic complications group undergoing radical prostatecotmy for prostate cancer, National Inpatient Sample 2016\u0026ndash;2020.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDM Subgroups\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eUnadjusted\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eAdjusted\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOdds Ratio\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eUnfavorable Discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u0026ndash;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.90\u0026ndash;1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.389\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u0026ndash;2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.24\u0026ndash;2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVentilatory Support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11\u0026ndash;2.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.94\u0026ndash;2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.50\u0026ndash;5.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.93\u0026ndash;3.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eBlood Transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u0026ndash;2.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.75\u0026ndash;2.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.396\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.52\u0026ndash;5.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.18\u0026ndash;4.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.015\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePostoperative Pain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u0026ndash;1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.85\u0026ndash;1.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u0026ndash;2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.761\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.46\u0026ndash;1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.907\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eInfection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.14\u0026ndash;2.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.10\u0026ndash;1.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.282\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.55\u0026ndash;9.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.249\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.30\u0026ndash;5.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.705\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eDVT/PE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.76\u0026ndash;1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.395\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.33\u0026ndash;4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.825\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.75\u0026ndash;5.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.17\u0026ndash;10.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.800\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGenitourinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u0026ndash;1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.72\u0026ndash;1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.84\u0026ndash;6.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.19-4.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eRespiratory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u0026ndash;4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.61\u0026ndash;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.955\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u0026ndash;12.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.09\u0026ndash;3.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.024\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eCardiac\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.38\u0026ndash;4.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.87\u0026ndash;1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.409\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.22\u0026ndash;12.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.614\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.37\u0026ndash;2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGastrointestinal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUncomplicated DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.92\u0026ndash;1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.74\u0026ndash;1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced DM group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.77\u0026ndash;3.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.13\u0026ndash;2.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.009\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"8\"\u003e\n \u003cp\u003e\u003csup\u003ea Non\u0026minus;DM group was used as a reference to compare with\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003e\u003csup\u003eb Adjusted for age, race/ethnicity, income quartile by zip code, primary expected payer, hospital region and Elixhauser comorbidity index\u003c/sup\u003e.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eDM has long been a global health challenge. This study elucidates the impact of DM, particularly cases with DM-related complications, on postoperative outcomes after RP, including LOS, total hospital charges, discharge status, and postoperative complications. From 2015 to 2020, 18,057 patients in the NIS database were diagnosed with prostate cancer and received RP. After dividing these patients into DM and non-DM groups, we examined their demographic and hospital characteristics, total hospital charges, LOS, discharge status, and postoperative complication rates. Although DM is considered an independent predictor of poor prognosis in some studies on urinary surgery[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], few studies examine its impact on postoperative clinical outcomes, specifically in RP.\u003c/p\u003e \u003cp\u003eDM plays an essential role in the complications of most surgical operations: Tan et al. and Zhang et al. indicate that DM is a risk factor for postoperative complications such as infection, hematoma, and reoperation in various non-cardiac surgeries. Several studies have assessed the impact of DM on patients undergoing RP. Teber et al. found that type 2 diabetes mellitus patients need a longer time to recover urinary control ability than non-diabetes patients after LRP, which is more evident in patients with DM for more than five years[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Multiple studies have shown that DM is unrelated to the clinicopathological features and biochemical recurrence in patients with PCa treated with RP[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Among these, Jayakrishnan et al. analyzed data from 1,262 patients with PCa and suggested that diabetes significantly increased the risk of biochemical recurrence in obese white males. Lee et al. analyzed 2,716 subjects and found that poor preoperative glycemic control worsened tumor prognosis and urinary incontinence recovery. However, most of these studies were limited by small sample size, while others focused on the relationship between preoperative glycemic control and postoperative recurrence risk or survival outcomes[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To our knowledge, few studies have independently reported the impact of DM on clinical outcomes after RP. This study is by far the first large-scale research to explore the relationship between DM and clinical outcomes after RP using the NIS database, incorporating over 17,000 patients with PCa.\u003c/p\u003e \u003cp\u003eOur results found that PCa patients with DM tend to be younger and have lower income levels. Hill-Briggs et al. also reported that patients with DM generally have lower incomes[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. At the same time, the study by Jayakrishnan et al. did not find significant age differences between PCa patients with and without DM[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. It is confirmed that white and non-Hispanic black individuals constitute a large portion of the diabetic population, a finding consistent with the conclusions of this study[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Compared to non-diabetic patients, those with DM incur higher costs for RP, likely due to the combined need for postoperative care and diabetes management[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, the incidences of postoperative complications in the DM group were significantly higher, including unfavorable discharge, ventilatory support, genitourinary, respiratory, cardiac, and gastrointestinal complications. After adjusting for potential confounding factors, DM as an independent risk factor increased the risks of unfavorable discharge after RP by 20%, ventilatory support by 55%, genitourinary by 40% and cardiac by 29%. Zhang et al. also reached similar conclusions in their meta-analysis of postoperative complications after non-cardiac surgery[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. After subgrouping the DM group by DM-related complications, the advanced DM group has more than double the risks of blood transfusion, genitourinary, and respiratory complications, compared to the non-DM group. Wong et al. found that blood glucose control affects the clinical outcomes of abdominal surgeries ( including RP ): preoperative glycated hemoglobin (HbA1c) levels between 6% and 7% are associated with a higher risk of certain complications. These complications include anastomotic leak, wound infection, significant complications, and an increase in overall postoperative complications. This further supports the hypothesis that DM is a potential risk factor for early complications after RP.\u003c/p\u003e \u003cp\u003eThis study benefits from using a well-designed and comprehensive NIS database system. It includes substantial data, ensuring sufficient statistical power and producing convincing results. We recognize that our research has some limitations. This study possesses all the disadvantages of retrospective studies\u0026mdash;selection bias, temporal variations in disease and treatment modalities, and unknown confounding factors. The design of the NIS database lacks definitions for diabetes control, so we cannot assess the effect of diabetes control on the outcome of postoperative complications. In addition, the NIS database lacks information on cancer's severity or pathological findings, which will help measure surgical indications, structural factors, case combinations, and disease attributes. Manual diagnostic coding may lead to inaccuracies and omissions in diagnostic information. The non-longitudinal data structure design prevents us from obtaining patients' baseline conditions upon admission. We also lack information on changes in health status during hospitalization and follow-up data.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eFor patients undergoing RP for PCa, those with DM are more likely to face adverse clinical outcomes and have higher incidences of postoperative complications. These differences are more pronounced in the population with DM-related complications. Our results highlight the association between diabetes and adverse clinical outcomes following RP, providing valuable insights into the perioperative management of prostate cancer patients and guidance for improved management strategies and better overall outcomes for this high-risk group.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eYichao Han and Yue Chen wrote the main manuscript text and Hongyu Guan prepared table 1-5. Xujun Xuan and Cheng Luo prepared supplemental table 1. Daohu Wang is responsible for reviewing and revising manuscript. All authors reviewed the manuscript.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflict of Interest:\u003c/strong\u003e The authors declare no conflicts of interest in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSiegel, R.L., A.N. Giaquinto, and A. 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\u003cstrong\u003e44\u003c/strong\u003e(1): p. 258-79.\u003c/li\u003e\n\u003cli\u003eZhu, Y., et al., \u003cem\u003eRacial/Ethnic Disparities in the Prevalence of Diabetes and Prediabetes by BMI: Patient Outcomes Research To Advance Learning (PORTAL) Multisite Cohort of Adults in the U.S.\u003c/em\u003e Diabetes Care, 2019. \u003cstrong\u003e42\u003c/strong\u003e(12): p. 2211-2219.\u003c/li\u003e\n\u003cli\u003eBommer, C., et al., \u003cem\u003eThe global economic burden of diabetes in adults aged 20-79 years: a cost-of-illness study.\u003c/em\u003e Lancet Diabetes Endocrinol, 2017. \u003cstrong\u003e5\u003c/strong\u003e(6): p. 423-430.\u003c/li\u003e\n\u003cli\u003eZhang, X., et al., \u003cem\u003eAssociation of Diabetes Mellitus With Postoperative Complications and Mortality After Non-Cardiac Surgery: A Meta-Analysis and Systematic Review.\u003c/em\u003e Front Endocrinol (Lausanne), 2022. \u003cstrong\u003e13\u003c/strong\u003e: p. 841256.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"hereditary-cancer-in-clinical-practice","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hccp","sideBox":"Learn more about [Hereditary Cancer in Clinical Practice](http://jhoonline.biomedcentral.com)","snPcode":"13053","submissionUrl":"https://submission.nature.com/new-submission/13053/3","title":"Hereditary Cancer in Clinical Practice","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"snapp","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"prostatectomy, prostate cancer, diabetes mellitus, postoperative complications","lastPublishedDoi":"10.21203/rs.3.rs-5023932/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5023932/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eDiabetes mellitus (DM) has been confirmed as a common risk factor for postoperative complications. This study aims to elucidate the impact of DM on postoperative complications following radical prostatectomy.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing data from a national inpatient sample from 2016 to 2020, patients aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years who were diagnosed with prostate cancer (PCa) and underwent radical prostatectomy were identified and divided into a DM group and a non-DM group. We further divided the DM group into uncomplicated DM and advanced DM groups. We compared the outcome variables between the three groups through univariate analysis and adjusted multivariate logistic regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eSeventeen thousand five hundred eighty-eight records were undergoing radical prostatectomy included in the present study, among which 2683 records (9.43%) had a diagnosis of DM. The DM group will incur higher costs (53,775 [38,286\u0026thinsp;\u0026minus;\u0026thinsp;65,482] vs. 51,546 [37,195\u0026thinsp;\u0026minus;\u0026thinsp;61,815] p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After adjusting the variables with baseline differences in the multivariate regression models, DM was identified as an independent risk factor for unfavorable discharge (aOR\u0026thinsp;=\u0026thinsp;1.20, 95%CI [1.02\u0026ndash;1.42], P\u0026thinsp;=\u0026thinsp;0.31), genitourinary complication (aOR\u0026thinsp;=\u0026thinsp;1.40, 95%CI [1.13\u0026ndash;1.73], P\u0026thinsp;=\u0026thinsp;0.002), cardiac complication (aOR\u0026thinsp;=\u0026thinsp;1.29, 95%CI [1.04\u0026ndash;1.6], P\u0026thinsp;=\u0026thinsp;0.019), and ventilatory support (aOR\u0026thinsp;=\u0026thinsp;1.55, 95%CI [1.05\u0026ndash;2.29], P\u0026thinsp;=\u0026thinsp;0.028). After subgrouping the DM group by DM-related complications, the advanced DM group has more than double the risks of blood transfusion, genitourinary, and respiratory complications, compared to the non-DM group.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe findings suggest that DM is more likely to face adverse clinical outcomes and higher incidences of postoperative complications. It found that DM is an independent risk factor for adverse clinical outcomes after radical prostatectomy for cancer.\u003c/p\u003e","manuscriptTitle":"The impact of diabetes mellitus on postoperative outcomes following radical prostatectomy: a 5-year retrospective analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-04 18:29:46","doi":"10.21203/rs.3.rs-5023932/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorAssigned","content":"","date":"2024-09-05T01:28:15+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-09-04T05:00:02+00:00","index":"","fulltext":""},{"type":"submitted","content":"Hereditary Cancer in Clinical Practice","date":"2024-09-03T09:50:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"hereditary-cancer-in-clinical-practice","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hccp","sideBox":"Learn more about [Hereditary Cancer in Clinical Practice](http://jhoonline.biomedcentral.com)","snPcode":"13053","submissionUrl":"https://submission.nature.com/new-submission/13053/3","title":"Hereditary Cancer in Clinical Practice","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"snapp","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e0f973aa-e578-4454-b168-ed30d952ffdc","owner":[],"postedDate":"October 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2024-10-04T18:29:46+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-04 18:29:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5023932","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5023932","identity":"rs-5023932","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}