Incidence and risk factors associated of blood transfusion after colorectal cancer surgery：A retrospective nationwide inpatient sample database study

Incidence and risk factors associated of blood transfusion after colorectal cancer surgery：A retrospective nationwide inpatient sample database study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Incidence and risk factors associated of blood transfusion after colorectal cancer surgery：A retrospective nationwide inpatient sample database study Na LI, Enhui SU, Lili YANG, Yan DU, Kai SONG, Ranjun XU, Yongheng WANG, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6921855/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract AIMS. This research aimed to determine the prevalence of blood transfusions and to identify preoperative variables associated with the need for blood transfusion after colorectal cancer surgery. METHODS. We analyzed 163,881 patients who had colorectal cancer surgery between 2010 and 2019 using the Nationwide Inpatient Sample. We also explored the relationship between blood transfusions and specific factors including length of stay (LOS), overall charges, and payer status. RESULTS During the study period, there was no significant change in the transfusion rate. Logistic regression analysis showed significant associations with chronic blood loss anemia, thrombocytopenia, deep vein thrombosis, peptic ulcer disease excluding bleeding, deficiency anemia, rheumatoid arthritis/collagen vascular diseases, chronic pulmonary disease, congestive heart failure, coagulopathy, depression, renal failure, diabetes, uncomplicated, hypertension, peripheral vascular disorders, liver disease, fluid and electrolyte disorders, other neurological disorders, paralysis, metastatic cancer, psychoses, pulmonary circulation disorders, valvular disease, weight loss and acquired immune deficiency syndrome. Patients who received blood transfusions had higher overall costs, longer hospital stays, and a greater likelihood of Medicare coverage compared to those who did not receive transfusions. CONCLUSIONS. Our study identified seven key risk factors for blood transfusions during colorectal cancer surgery: fluid and electrolyte disorders, paralysis, chronic blood loss anemia, peptic ulcer disease excluding bleeding, coagulopathy, deep vein thrombosis as well as thrombocytopenia. Patients with these risk factors are at increased risk of needing a blood transfusion after surgery and should receive appropriate health guidance. IMPACT. The main contribution of this study is to highlight the many risk factors present in patients undergoing surgical transfusion for colorectal cancer. This study recommends that clinical priority should be given to improving blood transfusion techniques, as well as fostering patients' awareness of disease risk factors and effective preventive. colorectal neoplasms blood transfusion national inpatient sample nursing Figures Figure 1 Figure 2 Figure 3 Figure 4 What is the necessity of this research? This paper's findings can be directly applied to clinical practice, enhancing patient care and treatment. It offers doctors more effective treatment plans or strategies, enhancing efficacy and reducing costs. It has improved the public's profound understanding of colorectal cancer, promoted the change of health behaviors, and also helped to improve global health literacy and promote the development of global health cause INTRODUCTION Colorectal cancer surgery is a well-established and effective treatment, showing positive clinical results and growing acceptance (Bailey & George, 2022 ; Qu et al., 2022 ; Sharma et al., 2022 ). Among the various surgical types, Endoscopic submucosal dissection (ESD), initially used for primary gastric cancer, is now a reliable and safe option for treating superficial colorectal cancer. Clinical reports indicate that ESD can achieve high en bloc resection rates, even in challenging cases involving larger or anatomically difficult lesions(Mayo et al., 2021 ). Nevertheless, intraoperative blood loss remains a concern for a subset of patients undergoing colorectal cancer surgery. As the volume of such surgeries continues to rise, it becomes increasingly important to identify the incidence and predictors of perioperative blood transfusions. Despite the clinical relevance, research on perioperative blood conservation in colorectal surgery remains limited, underscoring the need for evidence-based management strategies (Imai et al., 2017 ; Suzuki, 2014 ). additionally, they carry potential severe adverse reactions such as urticaria, allergic responses, fever, hemodynamic overload, and hemolytic reactions (Sharma et al., 2022 ). However, comprehensive national data and standardized guidelines for postoperative transfusions in colorectal cancer remain lacking (Sharma et al., 2022 ). Although several single-center studies have identified potential risk factors, large-scale multicenter analyses are still insufficient to guide clinical decision-making. This study leverages a large national database to evaluate trends in postoperative blood transfusions among colorectal cancer patients. It further aims to identify independent preoperative risk factors and provide insights to inform patient counseling and surgical planning. Additionally, the study will examine associations between postoperative transfusions and indicators of healthcare burden, including hospital length of stay, total cost, and payer status. Adverse outcomes from blood transfusions during colorectal cancer surgery have been documented. However, current evidence-based guidance on blood transfusions for colorectal cancer surgery patients is inadequate. This study aims to determine the prevalence of blood transfusions after colorectal cancer surgery and identify pre- and post-operative variables independently linked to the need for transfusion. In-depth analysis of these factors will enable us to offer more precise blood transfusion guidance for clinical use. This will help reduce unnecessary transfusions, mitigate transfusion risks, and enhance postoperative rehabilitation quality.Specifically, we will analyze in detail the occurrence of blood transfusion rates during colorectal cancer surgery against a database. Simultaneously, we will also conduct in-depth studies on patient comorbidities, complications and other variables to identify risk factors closely associated with postoperative transfusions. Furthermore, we aim for this study to offer a scientific foundation for blood transfusion strategy development, streamline procedures, minimize resource waste, and enhance service quality and efficiency. Ultimately, we seek to deliver a highly personalized and accurate transfusion plan via scientific approaches and thorough data analysis, thereby improving patient outcomes and quality of life. THE STUDY 2.1 DESIGN SPSS version 27.0 was used for statistical analysis. Continuous data were analyzed using the Wilcoxon rank test, and categorical data with the chi-square test to identify significant differences between the two groups(Schober & Vetter, 2019 ). Logistic regression models, both univariate and multivariate, were constructed to assess the correlation between blood transfusion and surgical and medical perioperative complications. A stepwise binary logistic regression was employed to identify independent risk factors for postoperative blood transfusion. All variables provided from NIS, including demographic data, hospital attributes, and preoperative comorbidities, were incorporated into the regression analysis (Table 1 )(Kelley & Tsikitis, 2019 ). Statistical significance was set at α level P ≤ 0.001, which is considered a large sample size as used in other NIS studies.(Rubin, 1997 )(Batista Rodríguez et al., 2018 ) 2.2 DATA COLLECTION The study participants were selected from the National Inpatient Sample (NIS) of the Healthcare Cost and Utilization Program (HCUP) in the United States. All information regarding patients who underwent colorectal cancer surgery was extracted from the NIS database(Batista Rodríguez et al., 2018 ). Within this group, individuals who passed away during their hospital stay were pinpointed. The NIS database encompasses a wide array of data points, including patient demographics (comprising associated comorbidities and complications), hospitalization specifics (like duration of stay, type of medical insurance, and overall hospitalization costs), as well as perioperative complications or adverse events (AEs). As the data in the NIS database is publicly accessible and identifiable, our research did not require Institutional Review Board (IRB) approval. Patients who had colorectal cancer surgery were identified using the International Classification of Diseases (ICD-10) 10th Revised Clinical Modification Procedure (ICD-10 CMP) code. We made use of the International Classification of Diseases 9th edition (ICD-9), diagnostic codes 153.0-153.4, 153.6, 153.8, 153.9, 154.0-154.3, 154.8, 209.10, 209.12-209.17 for colorectal cancer resection. ICD-9 robot-assisted resection codes 17.41–17.45, 17.49 were used to identify robotic colorectal cancer resections. Meanwhile, ICD-9 laparoscopic surgery codes 17.31–17.36, 17.39, and 45.81–45.83 were employed to discern instances of pure laparoscopic radical colectomy devoid of robot-assisted modifications. ICD-9 open surgery codes 45.71–45.76, 45.79, and 457.1-457.2 were used to identify open colectomies and other resections. Excluding patients under 18 years old (n = 49) and those with missing information (n = 4,576), a total of valid cases were obtained (n = 163,881). For every surgical operation, we scrutinized patient and hospital level factors that could potentially impact the outcome. Patient characteristics included age, gender, and race. In addition, detailed information related to admission was obtained for all included patients, including outcome indicators such as LOS, total hospitalization expenses, and hospitalization mortality rate( Comorbidity software, v.3.7). The database was searched for medical and surgical postoperative complications prior to discharge using the ICD-9-CM diagnostic code. Postoperative medical complications were specifically recognized as peptic ulcer disease without bleeding, diabetes with chronic complications, deep vein thrombosis, thrombocytopenia, and peripheral vascular diseases. Surgical complications during the postoperative period include bleeding(Kwaan et al., 2022 ; Li et al., 2024 ). 2.3 DATA ANALYSIS 2.3.1 The incidence of postoperative blood transfusion in colorectal cancer The study analyzed blood transfusion rates among colorectal cancer surgery patients from 2010 through 2019, analyzing data from 163,881 cases in the NIS database. Among these cases, 27,513 patients needed blood transfusions, with an incidence rate of 16.80%. The incidence of postoperative blood transfusions increased slightly from 2010 to 2011 (from 22.80–23.60%) (Fig. 1 ), while from 2011 to 2019 it showed a downward trend year by year (from 23.60–10.80%) (Fig. 1 ). 2.3.2 Patient demographics between two surgical groups A notable contrast in postoperative blood transfusion frequency exists between the two surgical groups, especially regarding demographic factors. A higher proportion of females and a lower proportion of males received blood transfusions (P < 0.001) (Table 2 )(Shah et al., 2023 ). Additionally, there's a significant age disparity among these groups. The rate of patients over 75 years is 47.20% higher (47.20% vs 31.30%, P < 0.001), and those aged 18–44 are less common (3.60% vs 5.20%, P < 0.001) (Table 2 ). Moreover, the postoperative blood transfusion group exhibited a significantly higher percentage of individuals of white race (67.50%, P < 0.001) (Table 2 ).(Oladunjoye et al., 2022 )(Fig. 2 ). 2.3.3 The characteristics of two groups of hospitals In line with expectations, compared with patients without these complications, patients who underwent blood transfusion after colorectal cancer surgery had a 31.60% lower likelihood of elective admission (40.60% compared to 72.20%, P < 0.001) (Table 2 ). It is not surprising that compared to patients without these complications, patients with postoperative blood transfusion in colorectal cancer are less likely to be admitted on a scheduled basis (P < 0.001) (Table 2 ). In addition, the rate of postoperative blood transfusion in urban and teaching hospitals for colorectal cancer is close to that of no transfusion (P < 0.001). From the perspective of hospital areas, blood transfusions tend to occur in the south, while in the west, northeast, central and western regions, or central and northern regions, there are fewer and closer occurrences (P < 0.001) (Table 2 ). The group of patients who did not receive transfusions showed a notably greater percentage of individuals with larger bed sizes in comparison to the group that did receive transfusions (57.6% vs 15.5%, P < 0.001)(Fig. 2 ). 2.3.4 Adverse outcomes following blood transfusion in colorectal cancer surgery It is not surprising that colorectal cancer patients with multiple comorbidities (n ≥ 3) before surgery have a greater chance of blood transfusion (77.80%, P < 0.001) (Table 2 ). As expected, the hospitalization mortality rate for patients who received transfusions was markedly higher compared to those who did not receive transfusions (4.80% vs 1.60%, P < 0.001) (Table 2 ). Transfusion patients had a median survival time that was 5 days longer than non-transfusion patients (10 days vs 5 days, P < 0.001) (Table 2 ). Consequently, the transfusion group incurred higher medical expenses, leading to a total increase in hospitalization costs of $ 32,478.5 ( $ 94,200 to $ 61,721.50, P < 0.001) (Table 2 ). In terms of payer types, the blood transfusion group had a higher proportion of Medicare recipients by 12.20% (68.00% vs 55.80%), while the proportion of Private Insurance holders was 13.10% lower (19.80% vs 32.90%) (P < 0.001) (Table 2 )(Fig. 2 ). 2.3.5 Risk factors associated with postoperative blood transfusion in colorectal cancer patients Through logistic regression analysis, the risk factors related to blood transfusion were confirmed (Table 3 ), and the following indexes were determined: teaching hospital (odds ratio [OR] = 1.44, CI = 1.40–1.49), elective admission (OR = 2.91, CI = 2.83–2.99), the Hispanic (OR = 1.15, CI = 1.08–1.23, P < 0.001), the Asian or Pacific Islander (OR = 1.09, CI = 1.01–1.17, P = 0.020), hospitals with a medium (OR = 1.08, CI = 1.04–1.13, P < 0.001) or large bed size (OR = 1.05, CI = 1.02–1.08, P = 0.003), alcohol abuse (OR = 1.09, CI = 1.00-1.19), deficiency anemia (OR = 2.78, CI = 2.70–2.87), rheumatoid arthritis/collagen vascular diseases (OR = 1.06, CI = 0.95–1.17), chronic blood loss anemia (OR = 4.42, CI = 4.23–4.63), congestive heart failure (OR = 1.68, CI = 1.61–1.76), chronic pulmonary disease(OR = 1.06, CI = 1.02–1.10), coagulopathy (OR = 2.12, CI = 2.00–2.25), depression (OR = 1.06, CI = 1.01–1.12), diabetes, uncomplicated (OR = 1.22, CI = 1.18–1.27), hypertension (OR = 1.08, CI = 1.05–1.11), hypothyroidism (OR = 1.04, CI = 1.00–1.09),liver disease (OR = 1.13, CI = 1.06–1.22), lymphoma (OR = 1.17, CI = 0.99–1.39), fluid and electrolyte disorders (OR = 1.89, CI = 1.83–1.95), metastatic cancer (OR = 1.20, CI = 1.17–1.24), other neurological disorders (OR = 1.31, CI = 1.23–1.39), obesity (OR = 0.84, CI = 0.80–0.87), paralysis (OR = 1.71, CI = 1.52–1.92), peripheral vascular disorders(OR = 1.14, CI = 1.08–1.21), psychoses (OR = 1.25, CI = 1.14–1.36), pulmonary circulation disorders (OR = 1.44, CI = 1.34–1.55), renal failure (OR = 1.39, CI = 1.33–1.46), valvular disease (OR = 1.33, CI = 1.26–1.41) and weight loss (OR = 1.74, CI = 1.67–1.80). Unexpectedly, there were various factors that provided protection against the need for blood transfusion, such as patients between the ages of 45 and 64 (OR = 0.68, CI = 0.62–0.74), and patients aged 65 to 74 years (OR = 0.62, CI = 0.59–0.65), patients older than 75 years (OR = 0.70, CI = 0.68–0.73), female (OR = 0.84, CI = 0.82–0.87), number of comorbidity = 1 (OR = 0.23, CI = 0.20–0.25, P < 0.001), number of comorbidity = 2 (OR = 0.36, CI = 0.34–0.38, P < 0.001), number of comorbidity ≥ 3 (OR = 0.53, CI = 0.50–0.55, P < 0.001), hospital in the Midwest or North Central (OR = 0.72, CI = 0.69–0.75, P < 0.001), hospital in the West (OR = 0.93, CI = 0.89–0.97, P = 0.001), the Black (OR = 0.84, CI = 0.80–0.89, P < 0.001), self-pay (OR = 0.82, CI = 0.73–0.91, P < 0.001), and solid tumor without metastasis (OR = 0.75, CI = 0.73–0.78), diabetes with chronic complications (OR = 0.99, CI = 0.93–1.05)(Fig. 3 ). 2.3.6 The association between blood transfusion and other postoperative complications The probabilities of peptic ulcer disease excluding bleeding (1.00%), diabetes with chronic complications (7.20%), deep vein thrombosis (4.20%), thrombocytopenia (4.80%), peripheral vascular disease (5.80%) and hemorrhage (3.50%) were no lower than those in patients without transfusion (P < 0.001). (Table 5 and Fig. 6). Logistic regression analysis found that peptic ulcer disease excluding bleeding (OR = 2.03, CI = 1.72–2.39), deep vein thrombosis (OR = 3.13, CI = 2.90–3.38), thrombocytopenia (OR = 2.55, CI = 2.38–2.73), peripheral vascular disease (OR = 1.50, CI = 1.42–1.60), hemorrhage (OR = 3.92, CI = 3.59–4.27) (Fig. 4 ). 3 Ethical consideration In our study, ethical review was not required. 4.Rigour and reflexivity In our research, we insist on rigor to ensure that the data is accurate and well-demonstrated. At the same time, we also focus on reflexivity, reflecting deeply on the impact of research methods and personal biases on results. This dual approach enhances the objectivity and comprehensiveness of our research, thereby enhancing academic quality. DISCUSSION We utilized the NIS database to study the occurrence and risk factors associated with receiving a blood transfusion after colorectal cancer surgery, and to explore how transfusions relate to variables like LOS, overall cost, and insurance status. From 2010 to 2011, the blood transfusion rate increased annually from 22.80–23.60%. This trend reversed, with the rate dropping to 10.80% by 2019(Hussan et al., 2020 ) (Fig. 1 ). Remarkably, this decline was not previously reported in the literature(Jenkins & Lowenfels, 2015 ; Lim et al., 2022 ). The total postoperative blood transfusion rate for colorectal cancer is 16.80%. A possible explanation is the ongoing advancements in medical technology and socio-economic development, which may lead to a decrease in the transfusion rate due to enhanced blood management strategies(Anthony et al., 2023 ; Lim et al., 2022 ; Nanji et al., 2021 ; Shin et al., 2022 ; Tamini et al., 2021 ). Notably, a greater proportion of White patients received postoperative blood transfusions. This aligns with previous findings suggesting that White patients undergoing general or orthopedic surgery are more prone to needing postoperative blood transfusions(Lee et al., 2025 ). Furthermore, logistic regression analysis revealed that Hispanics were at a higher risk for postoperative blood transfusions compared to Whites, suggesting that racial or genetic factors could influence the likelihood of needing a blood transfusion(Lu et al., 2024 ). Yet, the precise link between racial disparities and postoperative blood transfusions remains unclear and calls for further investigation(Anthony et al., 2023 ; Lim et al., 2022 ; Weng et al., 2022 ). Another demographic feature is that postoperative patients requiring blood transfusions are older than those who do not. Logistic regression analysis revealed age as a protective factor for transfusion (Table 3 ). While the study identifies age as a related factor, it does not suggest that older age provides greater protection(Half et al., 2024 ). Surgical patients who receive blood transfusions postoperatively have been shown to experience prolonged hospital stays, increased medical expenses, and higher mortality rates(Logie et al., 2024 ). Our research supports these findings, as shown in Table 2 . Patients who received postoperative blood transfusions had a median LOS that was 5 days longer and incurred an additional $ 32,478.5 in total hospital charges per admission. This could be attributed to the fact that individuals who undergo postoperative blood transfusions often experience cognitive impairment or altered perception, which may hinder their ability to adhere to nursing and rehabilitation instructions. Additionally, postoperative blood transfusions have been linked to conditions such as peptic ulcer disease without bleeding, diabetes with chronic complications, deep vein thrombosis, thrombocytopenia, peripheral vascular disease, and hemorrhage (as shown in Table 5 ), which frequently lead to delayed discharge and prolonged hospitalization. Significantly, patients receiving blood transfusions were more likely to have their costs covered by Medicare than those who did not receive transfusions. Furthermore, self-payment emerged as a protective factor against postoperative blood transfusions, underscoring the significant role of Medicare as a primary payer source(Lim et al., 2022 ; Sharma et al., 2022 ). Consequently, the in-hospital mortality rate among patients who received blood transfusions was more than three times higher than that of those who did not receive transfusions(Hayama et al., 2022 ). In this investigation, our logistic regression analysis revealed 31 significant OR risk factors linked to the occurrence of postoperative blood transfusion in patients with colorectal cancer. Among these 31 statistically significant risk factors, variables like Hispanic ethnicity, Asian or Pacific Islander descent, hospital size (medium and large), hospital teaching status, comorbidities including acquired immune deficiency syndrome, congestive heart failure, chronic pulmonary disease, depression, diabetes, uncomplicated hypertension, liver disease, metastatic cancer, other neurological disorders, paralysis, peripheral vascular disorders, psychoses, pulmonary circulation disorders, renal failure, valvular disease, weight loss, and peripheral vascular disease were found to have minimal associations with increased transfusion rate. Conversely, the remaining 9 risk factors were deemed both statistically and clinically significant in relation to blood transfusions following colorectal cancer surgery: elective admission, deficiency anemia, chronic blood loss anemia, coagulopathy, fluid and electrolyte disorders, peptic ulcer disease excluding bleeding, deep vein thrombosis, thrombocytopenia, and hemorrhage(Bauer et al., 2023 ). Numerous research investigations focusing on postoperative blood transfusion subsequent to colorectal cancer surgery have indicated the significance of pre-screening, risk assessment, and proper intervention to enhance patient outcomes. Hence, a thorough comprehension of the predisposing factors prior to surgery is crucial in preventing the need for postoperative blood transfusion. Notably, chronic blood loss anemia exhibited the highest OR (4.42) for requiring blood transfusion(Table 4 ),underscoring the paramount importance of addressing preoperative comorbidities that exhibit the strongest correlation with the likelihood of postoperative blood transfusion, warranting preoperative attention. Hemorrhage had a considerably high OR (3.92). Patients with a history of the other disorders such as thrombocytopenia (OR = 2.55), deep vein thrombosis (OR = 3.13), peptic ulcer disease excluding bleeding (OR = 2.03), deficiency anemia (OR = 2.78), rheumatoid arthritis/collagen vascular diseases (OR = 1.06), congestive heart failure (OR = 1.68), chronic pulmonary disease (OR = 1.06), coagulopathy (OR = 2.12), depression (OR = 1.06), diabetes, uncomplicated (OR = 1.22), hypertension (OR = 1.08), liver disease (OR = 1.13), fluid and electrolyte disorders (OR = 1.89), metastatic cancer (OR = 1.20), other neurological disorders (OR = 1.31), paralysis (OR = 1.71), peripheral vascular disorders (OR = 1.14), psychoses (OR = 1.25), pulmonary circulation disorders (OR = 1.44), renal failure (OR = 1.39), valvular disease (OR = 1.33), weight loss (OR = 1.74) and acquired immune deficiency syndrome (OR = 1.67) had a higher likelihood of needing a blood transfusion after surgery. Notably, being female (OR = 0.84) and having obesity (OR = 0.84) were identified as protective factors. The underlying reasons for this phenomenon are not fully understood but are likely to be influenced by multiple factors. Previous research findings may offer insights that are pertinent and warrant further examination. Because women typically have higher hemoglobin levels, while obese individuals typically have higher blood volume. These factors all contribute to reducing the risk of negative effects after blood transfusion. The complex relationship between women, obesity, and postoperative blood transfusion needs further research(Kommuru et al., 2022 ). Although there are some risk factors that cannot be changed before surgery, such as race, depression, and neurological disorders, consulting patients with surgeons during the informed consent stage and managing postoperative blood transfusions more cautiously during the perioperative period can effectively prevent or reduce the occurrence of postoperative blood transfusions(Moghadamyeghaneh et al., 2014 ), thereby having a positive impact on patients. Other risk factors of postoperative blood transfusion include peptic ulcer disease excluding bleeding, diabetes with chronic complications, weight loss, deficiency anemia, coagulation, hypertension, congestive heart failure, valvular disease, chronic pulmonary disease, pulmonary circulation disorders, and peripheral vascular disorders, which can be changed to a certain extent. Because patients with one or more of these complications can better perform selective colorectal cancer surgery through appropriate optimization, such as blood glucose regulation in patients with diabetes, blood transfusion in patients with anemia or coagulation dysfunction, and blood pressure control in patients with hypertension. Therefore, these findings have important and beneficial implications for the management of postoperative blood transfusion in colorectal cancer(Storch et al., 2019 ). Strengths and Limitations of the Work The utilization of the NIS database is subject to certain constraints. It is important to note that the data within the NIS may not be fully representative of the entire surgical population. One key limitation is that patient information is solely captured up to the point of discharge, thus any complications arising post-discharge are not reflected in the database. This restriction may lead to a potential underestimation of postoperative blood transfusion occurrences, as only early medical records are considered for analysis. Furthermore, the analysis is restricted to variables documented within the NIS, thereby excluding other pertinent risk factors such as anesthesia type, surgical duration, commonly administered perioperative medications, conditions during anesthesia recovery, vascular complications, functional impairments, among others. Moreover, the database does not encompass preventive measures like preoperative anesthesia consultations, optimization of chronic disease management preoperatively, and postoperative follow-up care by specialized healthcare providers for vulnerable patient groups. Additionally, as with any extensive database, discrepancies or inaccuracies in coding and documentation may exist. Consequently, administrative data typically exhibit high specificity (low false positive rate) but low sensitivity (high false negative rate) in detecting adverse events, potentially leading to an underestimation of postoperative blood transfusion incidents in colorectal cancer cases(McSorley et al., 2020 ; Wu et al., 2018 ). CONCLUSION This study documented the national incidence of postoperative blood transfusions in colorectal cancer patients in the NIS database over the past decade, revealing a decline in overall transfusion rates over time. In addition, this research regarded many preoperative risk indexes, including race, history of neurological and mental diseases, acquired immune deficiency syndrome, deficiency anemia, weight loss, coagulation, diabetes, hypertension, congestive heart failure, valve disease, pulmonary circulation disorders, etc. Both gender and obesity were identified as protective factors. In colorectal cancer patients, the occurrence of postoperative blood transfusions correlates with prolonged LOS, elevated total hospitalization expenses, heightened hospital mortality rates, and an increased risk of perioperative complications ( peptic ulcer disease excluding bleeding, deep vein thrombosis, thrombocytopenia, hemorrage, and peripheral vascular disease ). Declarations Consent for publication All authors approved the publication of the manuscript. Competing interests The authors declare no competing interests. Clinical trial number not applicable Funding Declaration No. Author Contribution Na LI.Enhui SU. wrote the main manuscript text and Hao XIE.Lili YANG and Yan DU. prepared figures 1-3. Kai SONG.Ranjun XU and Yongheng WANG. prepared figures 4-5.Kai SONG.Na LI and Enhui SU. prepared Tables 1-3.Ranjun XU and Yongheng WANG. prepared Tables 4-7.All authors reviewed the manuscript.Ruifang ZHU.Hao XIE. is responsible for format review and supervision Data Availability This study is based on data provided by Nationwide Inpatient Sample (NIS) database, part of the Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. The NIS database is a large publicly available all-payer inpatient care database in the United States. Therefore, in dividual or grouped data cannot be shared by the authors. References Batista Rodríguez G, Balla A, Corradetti S, Martinez C, Hernández P, Bollo J, Targarona EM. What have we learned in minimally invasive colorectal surgery from NSQIP and NIS large databases? A systematic review. Int J Colorectal Dis. 2018;33(6):663–81. https://doi.org/10.1007/s00384-018-3036-4 . Bauer TM, Santoro A, Lin CC, Garrido-Laguna I, Joerger M, Greil R, Spreafico A, Yau T, Goebeler ME, Hütter-Krönke ML, Perotti A, Juif PE, Lu D, Barys L, Cremasco V, Pelletier M, Evans H, Fabre C, Doi T. Phase I/Ib, open-label, multicenter, dose-escalation study of the anti-TGF-β monoclonal antibody, NIS793, in combination with spartalizumab in adult patients with advanced tumors. J Immunother Cancer. 2023;11(11). https://doi.org/10.1136/jitc-2023-007353 . Half EE, Levi Z, Mannalithara A, Leshno M, Ben-Aharon I, Abu-Freha N, Silverman B, Ladabaum U. Colorectal cancer screening at age 45 years in Israel: Cost-effectiveness and global implications. Cancer. 2024;130(6):901–12. https://doi.org/10.1002/cncr.35097 . Hayama T, Ozawa T, Tsukamoto M, Fukushima Y, Shimada R, Nozawa K, Matsuda K, Fujii S, Fukagawa T, Hashiguchi Y. (2022). Predicting Overall Survival Using Preoperative Nutritional and Inflammation Status for Colorectal Cancer. In Vivo, 36(1), 450–457. https://doi.org/10.21873/invivo.12724 Hussan H, Patel A, Le Roux M, Cruz-Monserrate Z, Porter K, Clinton SK, Carethers JM, Courneya KS. Rising Incidence of Colorectal Cancer in Young Adults Corresponds With Increasing Surgical Resections in Obese Patients. Clin Transl Gastroenterol. 2020;11(4):e00160. https://doi.org/10.14309/ctg.0000000000000160 . Kelley KA, Tsikitis VL. Clinical Research Using the National Inpatient Sample: A Brief Review of Colorectal Studies Utilizing the NIS Database. Clin Colon Rectal Surg. 2019;32(1):33–40. https://doi.org/10.1055/s-0038-1673352 . Kommuru S, Aziz SN, Sagireddy S, Kaur G, Rijal S, Loh CC, Ibrahim Y, Patel V. Risk Factors for Colorectal Cancer in Inpatients With Ulcerative Colitis: A Nationwide Cross-Sectional Analysis. Cureus. 2022;14(7):e27114. https://doi.org/10.7759/cureus.27114 . Kwaan MR, Wu Y, Ren Y, Xirasagar S. Prompt intervention in large bowel obstruction management: A Nationwide Inpatient Sample analysis. Am J Surg. 2022;224(5):1262–6. https://doi.org/10.1016/j.amjsurg.2022.07.002 . Lee KC, Su YL, Wu KL, Cheng KC, Song LC, Tang CE, Chen HH, Chung KC. Impact of iron-deficiency anemia on short-term outcomes after resection of colorectal cancer liver metastasis: a US National (Nationwide) Inpatient Sample (NIS) analysis. Ann Coloproctol. 2025;41(2):119–26. https://doi.org/10.3393/ac.2024.00591.0084 . Li X, Xie H, Liu S, Wang J, Shi Z, Yao Q, Yang Q, Li Q, Bao L. Analysis of the incidence and risk factors of blood transfusion in total knee revision: a retrospective nationwide inpatient sample database study. BMC Musculoskelet Disord. 2024;25(1):225. https://doi.org/10.1186/s12891-024-07331-2 . Logie K, McKechnie T, Talwar G, Lee Y, Parpia S, Amin N, Doumouras A, Hong D, Eskicioglu C. The impact of operative approach for obese colorectal cancer patients: analysis of the National Inpatient Sample 2015–2019. Colorectal Dis. 2024;26(1):34–44. https://doi.org/10.1111/codi.16808 . Lu CC, Lu CT, Chang KY, Chun-Li W, Wu CY. Robot-assisted vs. laparoscopic right hemicolectomy in octogenarians and nonagenarians: an analysis of the US nationwide inpatient sample 2005–2018. Aging Clin Exp Res. 2024;36(1):193. https://doi.org/10.1007/s40520-024-02833-4 . Mayo JS, Brazer ML, Bogenberger KJ, Tavares KB, Conrad RJ, Lustik MB, Gillern SM, Park CW, Richards CR. Ureteral injuries in colorectal surgery and the impact of laparoscopic and robotic-assisted approaches. Surg Endosc. 2021;35(6):2805–16. https://doi.org/10.1007/s00464-020-07714-1 . Moghadamyeghaneh Z, Mills SD, Pigazzi A, Carmichael JC, Stamos MJ. Risk factors of postoperative upper gastrointestinal bleeding following colorectal resections. J Gastrointest Surg. 2014;18(7):1327–33. https://doi.org/10.1007/s11605-014-2540-2 . Oladunjoye AF, Kaleem SZ, Suresh A, Sahni V, Thoonkuzhy MJ, Anugwom G, Oladunjoye O, Otuada D, Ikekwere J, Espiridion ED. Cannabis use and medication nonadherence in bipolar disorder: A nationwide inpatient sample database analysis. J Affect Disord. 2022;299:174–9. https://doi.org/10.1016/j.jad.2021.11.067 . Shah RM, Patel S, Sandhu LK, Patel S, Chand B. Outcomes and Characteristics of Hospitalized Colorectal Cancer Patients ≤ 45 Years Old. J Gastrointest Cancer. 2023;54(4):1380–2. https://doi.org/10.1007/s12029-023-00928-1 . Anthony P, Wu M, Shanmugalingam A, Ng CH, Wright D. Preoperative iron infusion does not reduce the requirement for blood transfusion in colorectal cancer surgery. Minerva Surg. 2023. https://doi.org/10.23736/s2724-5691.23.09975-6 . Bailey CR, George ML. Colorectal cancer surgery: is further research necessary? Anaesthesia. 2022;77(7):748–50. https://doi.org/10.1111/anae.15706 . Comorbidity software., v.3.7 . Agency for Healthcare Research and Quality. Retrieved Updated October 2011 from http://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp Imai K, Hotta K, Yamaguchi Y, Ito S, Ono H. Endoscopic submucosal dissection for large colorectal neoplasms. Dig Endoscopy. 2017;29(S2):53–7. https://doi.org/10.1111/den.12850 . Jenkins C, Lowenfels AB. Blood transfusion and colorectal cancer outcome. Ann Surg. 2015;261(3):e80. https://doi.org/10.1097/sla.0000000000000615 . Lim AR, Kim JH, Hyun MH, Chang WJ, Lee S, Kim YH, Park KH, Park JH. Blood transfusion has an adverse impact on the prognosis of patients receiving chemotherapy for advanced colorectal cancer: experience from a single institution with a patient blood management program. Support Care Cancer. 2022;30(6):5289–97. https://doi.org/10.1007/s00520-022-06949-z . McSorley ST, Tham A, Dolan RD, Steele CW, Ramsingh J, Roxburgh C, Horgan PG, McMillan DC. Perioperative Blood Transfusion is Associated with Postoperative Systemic Inflammatory Response and Poorer Outcomes Following Surgery for Colorectal Cancer. Ann Surg Oncol. 2020;27(3):833–43. https://doi.org/10.1245/s10434-019-07984-7 . Mueller MM, Van Remoortel H, Meybohm P, Aranko K, Aubron C, Burger R, Carson JL, Cichutek K, De Buck E, Devine D, Fergusson D, Folléa G, French C, Frey KP, Gammon R, Levy JH, Murphy MF, Ozier Y, Pavenski K, Seifried E. (2019). Patient Blood Management: Recommendations From the 2018 Frankfurt Consensus Conference. Jama , 321 (10), 983–997. https://doi.org/10.1001/jama.2019.0554 Nanji S, Mir ZM, Karim S, Brennan KE, Patel SV, Merchant SJ, Booth CM. Perioperative blood transfusion and resection of colorectal cancer liver metastases: outcomes in routine clinical practice. HPB (Oxford). 2021;23(3):404–12. https://doi.org/10.1016/j.hpb.2020.06.014 . Qu R, Ma Y, Zhang Z, Fu W. Increasing burden of colorectal cancer in China. Lancet Gastroenterol Hepatol. 2022;7(8):700. https://doi.org/10.1016/s2468-1253(22)00156-x . Rubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med. 1997;127(8 Pt 2):757–63. https://doi.org/10.7326/0003-4819-127-8_part_2-199710151-00064 . Schober P, Vetter TR. Chi-square Tests in Medical Research. Anesth Analg. 2019;129(5):1193. https://doi.org/10.1213/ane.0000000000004410 . Sharma R, Abbasi-Kangevari M, Abd-Rabu R, Abidi H, Abu-Gharbieh E, Acuna JM, Adhikari S, Advani SM, Afzal MS, Meybodi A, Ahinkorah M, Ahmad BO, Ahmadi S, Ahmadi A, Ahmed S, Ahmed H, Ahmed LA, Hamad MBA, Alahdab H, Zoladl F, M. Global, regional, and national burden of colorectal cancer and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Gastroenterol Hepatol. 2022;7(7):627–47. https://doi.org/https://doi.org/10.1016/S2468-1253(22)00044-9 . Shin SH, Piozzi GN, Kwak JM, Baek SJ, Kim J, Kim SH. Effect of a Patient Blood Management system on perioperative transfusion practice and short-term outcomes of colorectal cancer surgery. Blood Transfus. 2022;20(6):475–82. https://doi.org/10.2450/2022.0328-21 . Storch EK, Custer BS, Jacobs MR, Menitove JE, Mintz PD. Review of current transfusion therapy and blood banking practices. Blood Rev. 2019;38:100593. https://doi.org/10.1016/j.blre.2019.100593 . Suzuki S. Risk factors for bleeding after endoscopic submucosal dissection of colorectal neoplasms. World J Gastroenterol. 2014;20(7). https://doi.org/10.3748/wjg.v20.i7.1839 . Tamini N, Deghi G, Gianotti L, Braga M, Nespoli L. Colon Cancer Surgery: Does Preoperative Blood Transfusion Influence Short-Term Postoperative Outcomes? J Invest Surg. 2021;34(9):974–8. https://doi.org/10.1080/08941939.2020.1731634 . Weng M, Guo M, Li T, Zhou C, Sun C, Yue Y, Liao Q, Cai S, Lu X, Zhou D, Miao C. Anemia tolerance versus blood transfusion on long-term outcomes after colorectal cancer surgery: A retrospective propensity-score-matched analysis. Front Oncol. 2022;12:940428. https://doi.org/10.3389/fonc.2022.940428 . Wu HL, Tai YH, Lin SP, Chan MY, Chen HH, Chang KY. The Impact of Blood Transfusion on Recurrence and Mortality Following Colorectal Cancer Resection: A Propensity Score Analysis of 4,030 Patients. Sci Rep. 2018;8(1):13345. https://doi.org/10.1038/s41598-018-31662-5 . Tables Table 1 Variables used in binary logistic regression analysis Variables Categories Specific Variables Patient demographics Age (18-44 years, 45-64 years, 65-74 years and ≥75 years), sex (male and female), race (White, Black, Hispanic, Asian or Pacific Islander, Native American and Other) Hospital characteristics Type of admission (non-elective, elective), bed size of hospital (small, medium, large), teaching status of hospital (nonteaching, teaching), location of hospital (rural, urban), type of insurance (Medicare, Medicaid, private insurance, self-pay, no charge, other), location of the hospital (northeast, Midwest or north central, south, west) Comorbidities AIDS, alcohol abuse, deficiency anemia, rheumatoid diseases, chronic blood loss anemia, congestive heart failure, chronic pulmonar disease, coagulopathy, depression, diabetes (uncomplicated), drug abuse, hypertension, hypothyroidism, liver disease, lymphoma, fluid and electrolyte disorders, metastatic cancer, neurological disorders, obesity, paralysis, peripheral vascular disorders, psychoses, pulmonary circulation disorders, renal failure, solid tumor without metastasis, valvular disease and weight loss AIDS: Acquired immunodeficiency syndrome Table 2 Patient characteristics and outcomes after colorectal cancer surgery (2010-2019) Characteristics Transfusion No Transfusion P Total (n=count) 27,513 136,368 Total incidence (%) 16.80 Age (median, years) 73.00 (62.20,82.00) 67.00 (57.00, 77.00) <0.001 Age group (%) 18-44 3.60 5.20 <0.001 45-64 24.90 35.90 65-74 24.30 27.60 ≥75 47.20 31.30 Gender (%) Male 45.20 51.40 <0.001 Female 54.80 48.60 Race (%) White 67.50 71.80 <0.001 Black 13.30 10.10 Hispanic 8.30 6.90 Asian or Pacific Islander 3.00 3.00 Native American 0.50 0.40 Other 7.50 7.90 Number of Comorbidity (%) 0 1.50 7.10 <0.001 1 6.80 18.10 2 13.90 22.60 ≥3 77.80 52.30 LOS (median, d) 10 (7-15) 5 (4-9) <0.001 TOTCHG (median, $) 94,200 (57,349-156,677) 61,721.50 (40,214-99,261.50) <0.001 Type of insure (%) Medicare 68.00 55.80 <0.001 Medicaid 7.20 6.90 Private insurance 19.80 32.90 Self-pay 2.90 2.30 No charge 0.30 0.20 Other 1.80 1.90 Bed size of hospital (%) Small 15.90 15.50 <0.001 Medium 28.60 27.00 Large 15.50 57.60 Elective admission (%) 40.60 72.20 <0.001 Type of hospital (teaching %) 52.30 62.80 <0.001 Continue Characteristics Transfusion No Transfusion P Location of hospital (urban, %) 88.50 90.30 <0.001 Region of hospital (%) Northeast 19.70 18.80 <0.001 Midwest or North Central 19.20 24.10 South 42.50 39.00 West 18.60 18.10 Died (%) 4.80 1.60 <0.001 LOS: Length of stay, TOTCHE: Total charge Table 3 Risk factors associated with blood transfusion after colorectal cancer surgery Variable Multivariate Logistic Regression OR 95% CI P Age 18-44 Ref —— —— 45-64 0.68 0.62-0.74 ＜0.001 65-74 0.62 0.59-0.65 ＜0.001 ≥75 0.70 0.68-0.73 ＜0.001 Female 0.84 0.82-0.87 ＜0.001 Race White Ref —— —— Black 0.84 0.80-0.89 ＜0.001 Hispanic 1.15 1.08-1.23 ＜0.001 Asian or Pacific Islander 1.09 1.01-1.17 0.020 Native American 1.04 0.95-1.15 0.407 Other 0.97 0.78-1.19 0.744 Number of Comorbidity 0 Ref —— —— 1 0.23 0.20-0.25 ＜0.001 2 0.36 0.34-0.38 ＜0.001 ≥3 0.53 0.50-0.55 ＜0.001 Type of insurance Medicare Ref —— —— Medicaid 0.92 0.83-1.03 0.141 Private insurance 0.98 0.88-1.10 0.742 Self-pay 0.82 0.73-0.91 ＜0.001 No charge 1.07 0.94-1.22 0.296 Other 1.08 0.81-1.43 0.605 Bed size of hospital Small Ref —— —— Medium 1.08 1.04-1.13 ＜0.001 Large 1.05 1.02-1.08 0.003 Elective admission 2.91 2.83-2.99 ＜0.001 Teaching hospital 1.44 1.40-1.49 ＜0.001 Urban hospital 1.03 0.99-1.09 0.169 Region of hospital Northeast Ref —— —— Midwest or North Central 0.72 0.69-0.75 ＜0.001 South 0.97 0.94-1.01 0.154 West 0.93 0.89-0.97 0.001 AIDS: Acquired immunodeficiency syndrome, OR: Odds ratio, CI: Confidence interval Table 4 Relationship between blood transfusion and preoperative comorbidities Comorbidities Univariate Analysis Multivariate Logistic Regression No transfusion Transfusion P OR 95% CI P Preoperative comorbidities Acquired immune deficiency syndrome 218 (0.20%) 58 (0.20%) 0.060 1.67 1.22-2.27 0.001 Alcohol abuse 2,843 (2.10%) 803 (2.90%) ＜0.001 1.09 1.00-1.19 0.062 Deficiency anemia 22,580 (16.60%) 10,431 (37.90%) ＜0.001 2.78 2.70-2.87 ＜0.001 Rheumatoid arthritis/collagen vascular diseases 2,069 (1.50%) 530 (1.90%) ＜0.001 1.06 0.95-1.17 ＜0.001 Chronic blood loss anemia 5,734 (4.20%) 4,299 (15.60%) ＜0.001 4.42 4.23-4.63 ＜0.001 Congestive heart failure 9,475 (6.90%) 4,586 (16.70%) ＜0.001 1.68 1.61-1.76 ＜0.001 Chronic pulmonary disease 20,321 (14.90%) 5,150 (18.70%) ＜0.001 1.06 1.02-1.10 0.001 Coagulopathy 3,699 (2.70%) 2,154 (7.80%) ＜0.001 2.12 2.00-2.25 ＜0.001 Depression 10,284 (7.50%) 2,457 (8.90%) ＜0.001 1.06 1.01-1.12 0.022 Diabetes, uncomplicated 23,733 (17.40%) 5,932 (21.60%) ＜0.001 1.22 1.18-1.27 ＜0.001 Drug abuse 1,040 (0.80%) 240 (0.90%) 0.059 0.90 0.77-1.04 0.159 Hypertension 78,093 (57.30%) 17,802 (64.70%) ＜0.001 1.08 1.05-1.11 ＜0.001 Hypothyroidism 14,545 (10.70%) 3,504 (12.70%) ＜0.001 1.04 1.00-1.09 0.069 Liver disease 4,829 (3.50%) 1,241 (4.50%) ＜0.001 1.13 1.06-1.22 ＜0.001 Lymphoma 724 (0.50%) 201 (0.70%) ＜0.001 1.17 0.99-1.39 0.072 Fluid and electrolyte disorders 28,935 (21.20%) 11,854 (43.10%) ＜0.001 1.89 1.83-1.95 ＜0.001 Metastatic cancer 36,674 (26.90%) 9,315 (33.90%) ＜0.001 1.20 1.17-1.24 ＜0.001 Other neurological disorders 4,692 (3.40%) 1,851 (6.70%) ＜0.001 1.31 1.23-1.39 ＜0.001 Obesity 19,637 (14.4%) 3,607 (13.1%) ＜0.001 0.84 0.80-0.87 ＜0.001 Paralysis 1,041 (0.8%) 515 (1.9%) ＜0.001 1.71 1.52-1.92 ＜0.001 Peripheral vascular disorders 6,125 (4.50%) 1,997 (7.30%) ＜0.001 1.14 1.08-1.21 ＜0.001 Psychoses 2,484 (1.80%) 795 (2.90%) ＜0.001 1.25 1.14-1.36 ＜0.001 Pulmonary circulation disorders 2,700 (2.00%) 1,455 (5.30%) ＜0.001 1.44 1.34-1.55 ＜0.001 Renal failure 9,962 (7.30%) 4,037 (14.70%) ＜0.001 1.39 1.33-1.46 ＜0.001 Solid tumor without metastasis 56,265 (41.30%) 8,822 (32.10%) ＜0.001 0.75 0.73-0.78 ＜0.001 Valvular disease 5,808 (4.30%) 2,343 (8.50%) ＜0.001 1.33 1.26-1.41 ＜0.001 Weight loss 13,260 (9.70%) 6,135 (22.30%) ＜0.001 1.74 1.67-1.80 ＜0.001 OR: Odds ratio, CI: Confidence interval Table 5 Relationship between blood transfusion and postoperative complications Complications Univariate Analysis Multivariate Logistic Regression No transfusion Transfusion P OR 95% CI P Medical complications Peptic ulcer disease excluding bleeding 489 (0.40%) 270 (1.00%) ＜0.001 2.03 1.72-2.39 ＜0.001 Diabetes with chronic complications 7,538 (5.50%) 1,975(7.20%) ＜0.001 0.99 0.93-1.05 0.779 Deep vein thrombosis 1,731 (1.30%) 1,154 (4.20%) ＜0.001 3.13 2.90-3.38 ＜0.001 Thrombocytopenia 2,503 (1.80%) 1,333 (4.80%) ＜0.001 2.55 2.38-2.73 ＜0.001 Peripheral vascular disease 5,103 (3.70%) 1,599 (5.80%) ＜0.001 1.50 1.42-1.60 ＜0.001 Surgical complications Hemorrhage 1,193 (0.90%) 964 (3.50%) ＜0.001 3.92 3.59-4.27 ＜0.001 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6921855","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":483480750,"identity":"1f9734bc-d058-4a43-98a7-524c7c7e9c88","order_by":0,"name":"Na LI","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Na","middleName":"","lastName":"LI","suffix":""},{"id":483480751,"identity":"6d29f96b-56c3-44c8-865a-faa5efb8ad95","order_by":1,"name":"Enhui SU","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Enhui","middleName":"","lastName":"SU","suffix":""},{"id":483480752,"identity":"f1b35dd1-5f8e-4026-85c4-c8c6deecd413","order_by":2,"name":"Lili YANG","email":"","orcid":"","institution":"Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"YANG","suffix":""},{"id":483480753,"identity":"81e0ce7e-bcf7-4778-a08d-52a3ef118d3f","order_by":3,"name":"Yan DU","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"DU","suffix":""},{"id":483480754,"identity":"080e7861-2904-460e-9d96-4639d20c1ee4","order_by":4,"name":"Kai SONG","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"SONG","suffix":""},{"id":483480755,"identity":"3d38851d-cf10-4dce-8824-1d06e08524de","order_by":5,"name":"Ranjun XU","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ranjun","middleName":"","lastName":"XU","suffix":""},{"id":483480756,"identity":"08356672-bdd0-4495-a6ed-88fb660305eb","order_by":6,"name":"Yongheng WANG","email":"","orcid":"","institution":"Shanxi Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yongheng","middleName":"","lastName":"WANG","suffix":""},{"id":483480757,"identity":"f2ea2280-2951-41fd-b615-f99c57d0770e","order_by":7,"name":"Hao XIE","email":"","orcid":"","institution":"Nanfang Hospital, S outhern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Hao","middleName":"","lastName":"XIE","suffix":""},{"id":483480758,"identity":"108fb90d-1158-4b5a-a384-725d7b2fb8c2","order_by":8,"name":"Ruifang ZHU","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYFACxoYPYFqCgfEBVMiAkJbGGVAtzDClhLQwMMK0sEkQpcV8RnJjw88dtQzys3vMKn+2bUtsYG/eJsFQcwenFpkbiY2NvWeOMzDOOWN2m+fM7cQGnmNlEgzHnuHUIiGR2P6At+0YA7NEjtlthgqgFiBDgrHhMD4tjY1/gVrYgCoLfxgAtci/IaylmbethoEHqIWBB2wLDwEtPA8bm2XbDvBISKQVSwP9YtzGk1ZskXAMjxb29IeNb9vq5ORnJG/8+LPttmw/++GNNz7U4NYCBYd54Ew2EJFASAMDQx1hJaNgFIyCUTByAQDs51L5x2DS5QAAAABJRU5ErkJggg==","orcid":"","institution":"First Hospital of Shanxi Medical University","correspondingAuthor":true,"prefix":"","firstName":"Ruifang","middleName":"","lastName":"ZHU","suffix":""}],"badges":[],"createdAt":"2025-06-18 10:08:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6921855/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6921855/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86764684,"identity":"311b7e81-0d11-459f-a110-84e0f3f9c762","added_by":"auto","created_at":"2025-07-15 10:55:33","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21407,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"figure51.png","url":"https://assets-eu.researchsquare.com/files/rs-6921855/v1/c7d31cc32b8ac94f9d6dffef.png"},{"id":86764686,"identity":"18f7b7e9-0428-4ce9-95b3-52e414749917","added_by":"auto","created_at":"2025-07-15 10:55:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":177747,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"figure52.png","url":"https://assets-eu.researchsquare.com/files/rs-6921855/v1/549421b8b3a5908401c6f9e1.png"},{"id":86765903,"identity":"1d64a73a-4cd3-4fc5-a6ac-98810c1f6901","added_by":"auto","created_at":"2025-07-15 11:03:33","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":87070,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"figure54.png","url":"https://assets-eu.researchsquare.com/files/rs-6921855/v1/63ff379c0a5cb0bba52dbd4b.png"},{"id":86765900,"identity":"f85072f2-b5f1-479e-a1e4-94a0ccd15b9d","added_by":"auto","created_at":"2025-07-15 11:03:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":32127,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"figure55.png","url":"https://assets-eu.researchsquare.com/files/rs-6921855/v1/7d9c0c5e4bf215cdf6c6f586.png"},{"id":90644461,"identity":"1982b499-ba22-4ab7-b0b3-151677d5c2b9","added_by":"auto","created_at":"2025-09-05 07:32:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1924744,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6921855/v1/fcfd87d4-4622-46e3-921d-78fad312a659.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Incidence and risk factors associated of blood transfusion after colorectal cancer surgery：A retrospective nationwide inpatient sample database study","fulltext":[{"header":"What is the necessity of this research?","content":"\u003cul start=\"\"\u003e\n \u003cli\u003eThis paper\u0026apos;s findings can be directly applied to clinical practice, enhancing patient care and treatment.\u003c/li\u003e\n \u003cli\u003eIt offers doctors more effective treatment plans or strategies, enhancing efficacy and reducing costs.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eIt has improved the public\u0026apos;s profound understanding of colorectal cancer, promoted the change of health behaviors, and also helped to improve global health literacy and promote the development of global health cause\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"INTRODUCTION","content":"\u003cp\u003eColorectal cancer surgery is a well-established and effective treatment, showing positive clinical results and growing acceptance (Bailey \u0026amp; George, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Qu et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sharma et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Among the various surgical types, Endoscopic submucosal dissection (ESD), initially used for primary gastric cancer, is now a reliable and safe option for treating superficial colorectal cancer. Clinical reports indicate that ESD can achieve high en bloc resection rates, even in challenging cases involving larger or anatomically difficult lesions(Mayo et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Nevertheless, intraoperative blood loss remains a concern for a subset of patients undergoing colorectal cancer surgery. As the volume of such surgeries continues to rise, it becomes increasingly important to identify the incidence and predictors of perioperative blood transfusions. Despite the clinical relevance, research on perioperative blood conservation in colorectal surgery remains limited, underscoring the need for evidence-based management strategies (Imai et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Suzuki, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). additionally, they carry potential severe adverse reactions such as urticaria, allergic responses, fever, hemodynamic overload, and hemolytic reactions (Sharma et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, comprehensive national data and standardized guidelines for postoperative transfusions in colorectal cancer remain lacking (Sharma et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although several single-center studies have identified potential risk factors, large-scale multicenter analyses are still insufficient to guide clinical decision-making. This study leverages a large national database to evaluate trends in postoperative blood transfusions among colorectal cancer patients. It further aims to identify independent preoperative risk factors and provide insights to inform patient counseling and surgical planning. Additionally, the study will examine associations between postoperative transfusions and indicators of healthcare burden, including hospital length of stay, total cost, and payer status. Adverse outcomes from blood transfusions during colorectal cancer surgery have been documented. However, current evidence-based guidance on blood transfusions for colorectal cancer surgery patients is inadequate. This study aims to determine the prevalence of blood transfusions after colorectal cancer surgery and identify pre- and post-operative variables independently linked to the need for transfusion. In-depth analysis of these factors will enable us to offer more precise blood transfusion guidance for clinical use. This will help reduce unnecessary transfusions, mitigate transfusion risks, and enhance postoperative rehabilitation quality.Specifically, we will analyze in detail the occurrence of blood transfusion rates during colorectal cancer surgery against a database. Simultaneously, we will also conduct in-depth studies on patient comorbidities, complications and other variables to identify risk factors closely associated with postoperative transfusions.\u003c/p\u003e\u003cp\u003eFurthermore, we aim for this study to offer a scientific foundation for blood transfusion strategy development, streamline procedures, minimize resource waste, and enhance service quality and efficiency. Ultimately, we seek to deliver a highly personalized and accurate transfusion plan via scientific approaches and thorough data analysis, thereby improving patient outcomes and quality of life.\u003c/p\u003e"},{"header":"THE STUDY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 DESIGN\u003c/h2\u003e\u003cp\u003eSPSS version 27.0 was used for statistical analysis. Continuous data were analyzed using the Wilcoxon rank test, and categorical data with the chi-square test to identify significant differences between the two groups(Schober \u0026amp; Vetter, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Logistic regression models, both univariate and multivariate, were constructed to assess the correlation between blood transfusion and surgical and medical perioperative complications. A stepwise binary logistic regression was employed to identify independent risk factors for postoperative blood transfusion. All variables provided from NIS, including demographic data, hospital attributes, and preoperative comorbidities, were incorporated into the regression analysis (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)(Kelley \u0026amp; Tsikitis, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Statistical significance was set at α level P\u0026thinsp;\u0026le;\u0026thinsp;0.001, which is considered a large sample size as used in other NIS studies.(Rubin, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1997\u003c/span\u003e)(Batista Rodr\u0026iacute;guez et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 DATA COLLECTION\u003c/h2\u003e\u003cp\u003eThe study participants were selected from the National Inpatient Sample (NIS) of the Healthcare Cost and Utilization Program (HCUP) in the United States. All information regarding patients who underwent colorectal cancer surgery was extracted from the NIS database(Batista Rodr\u0026iacute;guez et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Within this group, individuals who passed away during their hospital stay were pinpointed. The NIS database encompasses a wide array of data points, including patient demographics (comprising associated comorbidities and complications), hospitalization specifics (like duration of stay, type of medical insurance, and overall hospitalization costs), as well as perioperative complications or adverse events (AEs).\u003c/p\u003e\u003cp\u003eAs the data in the NIS database is publicly accessible and identifiable, our research did not require Institutional Review Board (IRB) approval. Patients who had colorectal cancer surgery were identified using the International Classification of Diseases (ICD-10) 10th Revised Clinical Modification Procedure (ICD-10 CMP) code. We made use of the International Classification of Diseases 9th edition (ICD-9), diagnostic codes 153.0-153.4, 153.6, 153.8, 153.9, 154.0-154.3, 154.8, 209.10, 209.12-209.17 for colorectal cancer resection. ICD-9 robot-assisted resection codes 17.41\u0026ndash;17.45, 17.49 were used to identify robotic colorectal cancer resections. Meanwhile, ICD-9 laparoscopic surgery codes 17.31\u0026ndash;17.36, 17.39, and 45.81\u0026ndash;45.83 were employed to discern instances of pure laparoscopic radical colectomy devoid of robot-assisted modifications. ICD-9 open surgery codes 45.71\u0026ndash;45.76, 45.79, and 457.1-457.2 were used to identify open colectomies and other resections. Excluding patients under 18 years old (n\u0026thinsp;=\u0026thinsp;49) and those with missing information (n\u0026thinsp;=\u0026thinsp;4,576), a total of valid cases were obtained (n\u0026thinsp;=\u0026thinsp;163,881). For every surgical operation, we scrutinized patient and hospital level factors that could potentially impact the outcome. Patient characteristics included age, gender, and race. In addition, detailed information related to admission was obtained for all included patients, including outcome indicators such as LOS, total hospitalization expenses, and hospitalization mortality rate( Comorbidity software, v.3.7). The database was searched for medical and surgical postoperative complications prior to discharge using the ICD-9-CM diagnostic code. Postoperative medical complications were specifically recognized as peptic ulcer disease without bleeding, diabetes with chronic complications, deep vein thrombosis, thrombocytopenia, and peripheral vascular diseases. Surgical complications during the postoperative period include bleeding(Kwaan et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3 DATA ANALYSIS\u003c/h2\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.3.1 The incidence of postoperative blood transfusion in colorectal cancer\u003c/h2\u003e\u003cp\u003eThe study analyzed blood transfusion rates among colorectal cancer surgery patients from 2010 through 2019, analyzing data from 163,881 cases in the NIS database. Among these cases, 27,513 patients needed blood transfusions, with an incidence rate of 16.80%. The incidence of postoperative blood transfusions increased slightly from 2010 to 2011 (from 22.80\u0026ndash;23.60%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e), while from 2011 to 2019 it showed a downward trend year by year (from 23.60\u0026ndash;10.80%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.3.2 Patient demographics between two surgical groups\u003c/h2\u003e\u003cp\u003eA notable contrast in postoperative blood transfusion frequency exists between the two surgical groups, especially regarding demographic factors. A higher proportion of females and a lower proportion of males received blood transfusions (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)(Shah et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Additionally, there's a significant age disparity among these groups. The rate of patients over 75 years is 47.20% higher (47.20% vs 31.30%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and those aged 18\u0026ndash;44 are less common (3.60% vs 5.20%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, the postoperative blood transfusion group exhibited a significantly higher percentage of individuals of white race (67.50%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).(Oladunjoye et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2022\u003c/span\u003e)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section3\"\u003e\u003ch2\u003e2.3.3 The characteristics of two groups of hospitals\u003c/h2\u003e\u003cp\u003eIn line with expectations, compared with patients without these complications, patients who underwent blood transfusion after colorectal cancer surgery had a 31.60% lower likelihood of elective admission (40.60% compared to 72.20%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). It is not surprising that compared to patients without these complications, patients with postoperative blood transfusion in colorectal cancer are less likely to be admitted on a scheduled basis (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In addition, the rate of postoperative blood transfusion in urban and teaching hospitals for colorectal cancer is close to that of no transfusion (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). From the perspective of hospital areas, blood transfusions tend to occur in the south, while in the west, northeast, central and western regions, or central and northern regions, there are fewer and closer occurrences (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The group of patients who did not receive transfusions showed a notably greater percentage of individuals with larger bed sizes in comparison to the group that did receive transfusions (57.6% vs 15.5%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e\u003ch2\u003e2.3.4 Adverse outcomes following blood transfusion in colorectal cancer surgery\u003c/h2\u003e\u003cp\u003eIt is not surprising that colorectal cancer patients with multiple comorbidities (n\u0026thinsp;\u0026ge;\u0026thinsp;3) before surgery have a greater chance of blood transfusion (77.80%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). As expected, the hospitalization mortality rate for patients who received transfusions was markedly higher compared to those who did not receive transfusions (4.80% vs 1.60%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Transfusion patients had a median survival time that was 5 days longer than non-transfusion patients (10 days vs 5 days, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Consequently, the transfusion group incurred higher medical expenses, leading to a total increase in hospitalization costs of \u003cspan\u003e$\u003c/span\u003e32,478.5 (\u003cspan\u003e$\u003c/span\u003e94,200 to \u003cspan\u003e$\u003c/span\u003e61,721.50, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In terms of payer types, the blood transfusion group had a higher proportion of Medicare recipients by 12.20% (68.00% vs 55.80%), while the proportion of Private Insurance holders was 13.10% lower (19.80% vs 32.90%) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section3\"\u003e\u003ch2\u003e2.3.5 Risk factors associated with postoperative blood transfusion in colorectal cancer patients\u003c/h2\u003e\u003cp\u003eThrough logistic regression analysis, the risk factors related to blood transfusion were confirmed (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and the following indexes were determined: teaching hospital (odds ratio [OR]\u0026thinsp;=\u0026thinsp;1.44, CI\u0026thinsp;=\u0026thinsp;1.40\u0026ndash;1.49), elective admission (OR\u0026thinsp;=\u0026thinsp;2.91, CI\u0026thinsp;=\u0026thinsp;2.83\u0026ndash;2.99), the Hispanic (OR\u0026thinsp;=\u0026thinsp;1.15, CI\u0026thinsp;=\u0026thinsp;1.08\u0026ndash;1.23, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), the Asian or Pacific Islander (OR\u0026thinsp;=\u0026thinsp;1.09, CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.17, P\u0026thinsp;=\u0026thinsp;0.020), hospitals with a medium (OR\u0026thinsp;=\u0026thinsp;1.08, CI\u0026thinsp;=\u0026thinsp;1.04\u0026ndash;1.13, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) or large bed size (OR\u0026thinsp;=\u0026thinsp;1.05, CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;1.08, P\u0026thinsp;=\u0026thinsp;0.003), alcohol abuse (OR\u0026thinsp;=\u0026thinsp;1.09, CI\u0026thinsp;=\u0026thinsp;1.00-1.19), deficiency anemia (OR\u0026thinsp;=\u0026thinsp;2.78, CI\u0026thinsp;=\u0026thinsp;2.70\u0026ndash;2.87), rheumatoid arthritis/collagen vascular diseases (OR\u0026thinsp;=\u0026thinsp;1.06, CI\u0026thinsp;=\u0026thinsp;0.95\u0026ndash;1.17), chronic blood loss anemia (OR\u0026thinsp;=\u0026thinsp;4.42, CI\u0026thinsp;=\u0026thinsp;4.23\u0026ndash;4.63), congestive heart failure (OR\u0026thinsp;=\u0026thinsp;1.68, CI\u0026thinsp;=\u0026thinsp;1.61\u0026ndash;1.76), chronic pulmonary disease(OR\u0026thinsp;=\u0026thinsp;1.06, CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;1.10), coagulopathy (OR\u0026thinsp;=\u0026thinsp;2.12, CI\u0026thinsp;=\u0026thinsp;2.00\u0026ndash;2.25), depression (OR\u0026thinsp;=\u0026thinsp;1.06, CI\u0026thinsp;=\u0026thinsp;1.01\u0026ndash;1.12), diabetes, uncomplicated (OR\u0026thinsp;=\u0026thinsp;1.22, CI\u0026thinsp;=\u0026thinsp;1.18\u0026ndash;1.27), hypertension (OR\u0026thinsp;=\u0026thinsp;1.08, CI\u0026thinsp;=\u0026thinsp;1.05\u0026ndash;1.11), hypothyroidism (OR\u0026thinsp;=\u0026thinsp;1.04, CI\u0026thinsp;=\u0026thinsp;1.00\u0026ndash;1.09),liver disease (OR\u0026thinsp;=\u0026thinsp;1.13, CI\u0026thinsp;=\u0026thinsp;1.06\u0026ndash;1.22), lymphoma (OR\u0026thinsp;=\u0026thinsp;1.17, CI\u0026thinsp;=\u0026thinsp;0.99\u0026ndash;1.39), fluid and electrolyte disorders (OR\u0026thinsp;=\u0026thinsp;1.89, CI\u0026thinsp;=\u0026thinsp;1.83\u0026ndash;1.95), metastatic cancer (OR\u0026thinsp;=\u0026thinsp;1.20, CI\u0026thinsp;=\u0026thinsp;1.17\u0026ndash;1.24), other neurological disorders (OR\u0026thinsp;=\u0026thinsp;1.31, CI\u0026thinsp;=\u0026thinsp;1.23\u0026ndash;1.39), obesity (OR\u0026thinsp;=\u0026thinsp;0.84, CI\u0026thinsp;=\u0026thinsp;0.80\u0026ndash;0.87), paralysis (OR\u0026thinsp;=\u0026thinsp;1.71, CI\u0026thinsp;=\u0026thinsp;1.52\u0026ndash;1.92), peripheral vascular disorders(OR\u0026thinsp;=\u0026thinsp;1.14, CI\u0026thinsp;=\u0026thinsp;1.08\u0026ndash;1.21), psychoses (OR\u0026thinsp;=\u0026thinsp;1.25, CI\u0026thinsp;=\u0026thinsp;1.14\u0026ndash;1.36), pulmonary circulation disorders (OR\u0026thinsp;=\u0026thinsp;1.44, CI\u0026thinsp;=\u0026thinsp;1.34\u0026ndash;1.55), renal failure (OR\u0026thinsp;=\u0026thinsp;1.39, CI\u0026thinsp;=\u0026thinsp;1.33\u0026ndash;1.46), valvular disease (OR\u0026thinsp;=\u0026thinsp;1.33, CI\u0026thinsp;=\u0026thinsp;1.26\u0026ndash;1.41) and weight loss (OR\u0026thinsp;=\u0026thinsp;1.74, CI\u0026thinsp;=\u0026thinsp;1.67\u0026ndash;1.80). Unexpectedly, there were various factors that provided protection against the need for blood transfusion, such as patients between the ages of 45 and 64 (OR\u0026thinsp;=\u0026thinsp;0.68, CI\u0026thinsp;=\u0026thinsp;0.62\u0026ndash;0.74), and patients aged 65 to 74 years (OR\u0026thinsp;=\u0026thinsp;0.62, CI\u0026thinsp;=\u0026thinsp;0.59\u0026ndash;0.65), patients older than 75 years (OR\u0026thinsp;=\u0026thinsp;0.70, CI\u0026thinsp;=\u0026thinsp;0.68\u0026ndash;0.73), female (OR\u0026thinsp;=\u0026thinsp;0.84, CI\u0026thinsp;=\u0026thinsp;0.82\u0026ndash;0.87), number of comorbidity\u0026thinsp;=\u0026thinsp;1 (OR\u0026thinsp;=\u0026thinsp;0.23, CI\u0026thinsp;=\u0026thinsp;0.20\u0026ndash;0.25, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), number of comorbidity\u0026thinsp;=\u0026thinsp;2 (OR\u0026thinsp;=\u0026thinsp;0.36, CI\u0026thinsp;=\u0026thinsp;0.34\u0026ndash;0.38, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), number of comorbidity\u0026thinsp;\u0026ge;\u0026thinsp;3 (OR\u0026thinsp;=\u0026thinsp;0.53, CI\u0026thinsp;=\u0026thinsp;0.50\u0026ndash;0.55, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hospital in the Midwest or North Central (OR\u0026thinsp;=\u0026thinsp;0.72, CI\u0026thinsp;=\u0026thinsp;0.69\u0026ndash;0.75, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), hospital in the West (OR\u0026thinsp;=\u0026thinsp;0.93, CI\u0026thinsp;=\u0026thinsp;0.89\u0026ndash;0.97, P\u0026thinsp;=\u0026thinsp;0.001), the Black (OR\u0026thinsp;=\u0026thinsp;0.84, CI\u0026thinsp;=\u0026thinsp;0.80\u0026ndash;0.89, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), self-pay (OR\u0026thinsp;=\u0026thinsp;0.82, CI\u0026thinsp;=\u0026thinsp;0.73\u0026ndash;0.91, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and solid tumor without metastasis (OR\u0026thinsp;=\u0026thinsp;0.75, CI\u0026thinsp;=\u0026thinsp;0.73\u0026ndash;0.78), diabetes with chronic complications (OR\u0026thinsp;=\u0026thinsp;0.99, CI\u0026thinsp;=\u0026thinsp;0.93\u0026ndash;1.05)(Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section3\"\u003e\u003ch2\u003e2.3.6 The association between blood transfusion and other postoperative complications\u003c/h2\u003e\u003cp\u003eThe probabilities of peptic ulcer disease excluding bleeding (1.00%), diabetes with chronic complications (7.20%), deep vein thrombosis (4.20%), thrombocytopenia (4.80%), peripheral vascular disease (5.80%) and hemorrhage (3.50%) were no lower than those in patients without transfusion (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e and Fig.\u0026nbsp;6). Logistic regression analysis found that peptic ulcer disease excluding bleeding (OR\u0026thinsp;=\u0026thinsp;2.03, CI\u0026thinsp;=\u0026thinsp;1.72\u0026ndash;2.39), deep vein thrombosis (OR\u0026thinsp;=\u0026thinsp;3.13, CI\u0026thinsp;=\u0026thinsp;2.90\u0026ndash;3.38), thrombocytopenia (OR\u0026thinsp;=\u0026thinsp;2.55, CI\u0026thinsp;=\u0026thinsp;2.38\u0026ndash;2.73), peripheral vascular disease (OR\u0026thinsp;=\u0026thinsp;1.50, CI\u0026thinsp;=\u0026thinsp;1.42\u0026ndash;1.60), hemorrhage (OR\u0026thinsp;=\u0026thinsp;3.92, CI\u0026thinsp;=\u0026thinsp;3.59\u0026ndash;4.27) (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\n\u003ch3\u003e3 Ethical consideration\u003c/h3\u003e\n\u003cp\u003eIn our study, ethical review was not required.\u003c/p\u003e\n\u003ch3\u003e4.Rigour and reflexivity\u003c/h3\u003e\n\u003cp\u003eIn our research, we insist on rigor to ensure that the data is accurate and well-demonstrated. At the same time, we also focus on reflexivity, reflecting deeply on the impact of research methods and personal biases on results. This dual approach enhances the objectivity and comprehensiveness of our research, thereby enhancing academic quality.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe utilized the NIS database to study the occurrence and risk factors associated with receiving a blood transfusion after colorectal cancer surgery, and to explore how transfusions relate to variables like LOS, overall cost, and insurance status. From 2010 to 2011, the blood transfusion rate increased annually from 22.80\u0026ndash;23.60%. This trend reversed, with the rate dropping to 10.80% by 2019(Hussan et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Remarkably, this decline was not previously reported in the literature(Jenkins \u0026amp; Lowenfels, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lim et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The total postoperative blood transfusion rate for colorectal cancer is 16.80%. A possible explanation is the ongoing advancements in medical technology and socio-economic development, which may lead to a decrease in the transfusion rate due to enhanced blood management strategies(Anthony et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lim et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nanji et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Shin et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Tamini et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNotably, a greater proportion of White patients received postoperative blood transfusions. This aligns with previous findings suggesting that White patients undergoing general or orthopedic surgery are more prone to needing postoperative blood transfusions(Lee et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Furthermore, logistic regression analysis revealed that Hispanics were at a higher risk for postoperative blood transfusions compared to Whites, suggesting that racial or genetic factors could influence the likelihood of needing a blood transfusion(Lu et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Yet, the precise link between racial disparities and postoperative blood transfusions remains unclear and calls for further investigation(Anthony et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Lim et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Weng et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAnother demographic feature is that postoperative patients requiring blood transfusions are older than those who do not. Logistic regression analysis revealed age as a protective factor for transfusion (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). While the study identifies age as a related factor, it does not suggest that older age provides greater protection(Half et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2024\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eSurgical patients who receive blood transfusions postoperatively have been shown to experience prolonged hospital stays, increased medical expenses, and higher mortality rates(Logie et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Our research supports these findings, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Patients who received postoperative blood transfusions had a median LOS that was 5 days longer and incurred an additional \u003cspan\u003e$\u003c/span\u003e32,478.5 in total hospital charges per admission. This could be attributed to the fact that individuals who undergo postoperative blood transfusions often experience cognitive impairment or altered perception, which may hinder their ability to adhere to nursing and rehabilitation instructions. Additionally, postoperative blood transfusions have been linked to conditions such as peptic ulcer disease without bleeding, diabetes with chronic complications, deep vein thrombosis, thrombocytopenia, peripheral vascular disease, and hemorrhage (as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), which frequently lead to delayed discharge and prolonged hospitalization. Significantly, patients receiving blood transfusions were more likely to have their costs covered by Medicare than those who did not receive transfusions. Furthermore, self-payment emerged as a protective factor against postoperative blood transfusions, underscoring the significant role of Medicare as a primary payer source(Lim et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Sharma et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Consequently, the in-hospital mortality rate among patients who received blood transfusions was more than three times higher than that of those who did not receive transfusions(Hayama et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this investigation, our logistic regression analysis revealed 31 significant OR risk factors linked to the occurrence of postoperative blood transfusion in patients with colorectal cancer. Among these 31 statistically significant risk factors, variables like Hispanic ethnicity, Asian or Pacific Islander descent, hospital size (medium and large), hospital teaching status, comorbidities including acquired immune deficiency syndrome, congestive heart failure, chronic pulmonary disease, depression, diabetes, uncomplicated hypertension, liver disease, metastatic cancer, other neurological disorders, paralysis, peripheral vascular disorders, psychoses, pulmonary circulation disorders, renal failure, valvular disease, weight loss, and peripheral vascular disease were found to have minimal associations with increased transfusion rate. Conversely, the remaining 9 risk factors were deemed both statistically and clinically significant in relation to blood transfusions following colorectal cancer surgery: elective admission, deficiency anemia, chronic blood loss anemia, coagulopathy, fluid and electrolyte disorders, peptic ulcer disease excluding bleeding, deep vein thrombosis, thrombocytopenia, and hemorrhage(Bauer et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eNumerous research investigations focusing on postoperative blood transfusion subsequent to colorectal cancer surgery have indicated the significance of pre-screening, risk assessment, and proper intervention to enhance patient outcomes. Hence, a thorough comprehension of the predisposing factors prior to surgery is crucial in preventing the need for postoperative blood transfusion. Notably, chronic blood loss anemia exhibited the highest OR (4.42) for requiring blood transfusion(Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e),underscoring the paramount importance of addressing preoperative comorbidities that exhibit the strongest correlation with the likelihood of postoperative blood transfusion, warranting preoperative attention. Hemorrhage had a considerably high OR (3.92). Patients with a history of the other disorders such as thrombocytopenia (OR\u0026thinsp;=\u0026thinsp;2.55), deep vein thrombosis (OR\u0026thinsp;=\u0026thinsp;3.13), peptic ulcer disease excluding bleeding (OR\u0026thinsp;=\u0026thinsp;2.03), deficiency anemia (OR\u0026thinsp;=\u0026thinsp;2.78), rheumatoid arthritis/collagen vascular diseases (OR\u0026thinsp;=\u0026thinsp;1.06), congestive heart failure (OR\u0026thinsp;=\u0026thinsp;1.68), chronic pulmonary disease (OR\u0026thinsp;=\u0026thinsp;1.06), coagulopathy (OR\u0026thinsp;=\u0026thinsp;2.12), depression (OR\u0026thinsp;=\u0026thinsp;1.06), diabetes, uncomplicated (OR\u0026thinsp;=\u0026thinsp;1.22), hypertension (OR\u0026thinsp;=\u0026thinsp;1.08), liver disease (OR\u0026thinsp;=\u0026thinsp;1.13), fluid and electrolyte disorders (OR\u0026thinsp;=\u0026thinsp;1.89), metastatic cancer (OR\u0026thinsp;=\u0026thinsp;1.20), other neurological disorders (OR\u0026thinsp;=\u0026thinsp;1.31), paralysis (OR\u0026thinsp;=\u0026thinsp;1.71), peripheral vascular disorders (OR\u0026thinsp;=\u0026thinsp;1.14), psychoses (OR\u0026thinsp;=\u0026thinsp;1.25), pulmonary circulation disorders (OR\u0026thinsp;=\u0026thinsp;1.44), renal failure (OR\u0026thinsp;=\u0026thinsp;1.39), valvular disease (OR\u0026thinsp;=\u0026thinsp;1.33), weight loss (OR\u0026thinsp;=\u0026thinsp;1.74) and acquired immune deficiency syndrome (OR\u0026thinsp;=\u0026thinsp;1.67) had a higher likelihood of needing a blood transfusion after surgery.\u003c/p\u003e\u003cp\u003eNotably, being female (OR\u0026thinsp;=\u0026thinsp;0.84) and having obesity (OR\u0026thinsp;=\u0026thinsp;0.84) were identified as protective factors. The underlying reasons for this phenomenon are not fully understood but are likely to be influenced by multiple factors. Previous research findings may offer insights that are pertinent and warrant further examination. Because women typically have higher hemoglobin levels, while obese individuals typically have higher blood volume. These factors all contribute to reducing the risk of negative effects after blood transfusion. The complex relationship between women, obesity, and postoperative blood transfusion needs further research(Kommuru et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough there are some risk factors that cannot be changed before surgery, such as race, depression, and neurological disorders, consulting patients with surgeons during the informed consent stage and managing postoperative blood transfusions more cautiously during the perioperative period can effectively prevent or reduce the occurrence of postoperative blood transfusions(Moghadamyeghaneh et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), thereby having a positive impact on patients. Other risk factors of postoperative blood transfusion include peptic ulcer disease excluding bleeding, diabetes with chronic complications, weight loss, deficiency anemia, coagulation, hypertension, congestive heart failure, valvular disease, chronic pulmonary disease, pulmonary circulation disorders, and peripheral vascular disorders, which can be changed to a certain extent. Because patients with one or more of these complications can better perform selective colorectal cancer surgery through appropriate optimization, such as blood glucose regulation in patients with diabetes, blood transfusion in patients with anemia or coagulation dysfunction, and blood pressure control in patients with hypertension. Therefore, these findings have important and beneficial implications for the management of postoperative blood transfusion in colorectal cancer(Storch et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eStrengths and Limitations of the Work\u003c/p\u003e\u003cp\u003eThe utilization of the NIS database is subject to certain constraints. It is important to note that the data within the NIS may not be fully representative of the entire surgical population. One key limitation is that patient information is solely captured up to the point of discharge, thus any complications arising post-discharge are not reflected in the database. This restriction may lead to a potential underestimation of postoperative blood transfusion occurrences, as only early medical records are considered for analysis. Furthermore, the analysis is restricted to variables documented within the NIS, thereby excluding other pertinent risk factors such as anesthesia type, surgical duration, commonly administered perioperative medications, conditions during anesthesia recovery, vascular complications, functional impairments, among others. Moreover, the database does not encompass preventive measures like preoperative anesthesia consultations, optimization of chronic disease management preoperatively, and postoperative follow-up care by specialized healthcare providers for vulnerable patient groups. Additionally, as with any extensive database, discrepancies or inaccuracies in coding and documentation may exist. Consequently, administrative data typically exhibit high specificity (low false positive rate) but low sensitivity (high false negative rate) in detecting adverse events, potentially leading to an underestimation of postoperative blood transfusion incidents in colorectal cancer cases(McSorley et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Wu et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study documented the national incidence of postoperative blood transfusions in colorectal cancer patients in the NIS database over the past decade, revealing a decline in overall transfusion rates over time. In addition, this research regarded many preoperative risk indexes, including race, history of neurological and mental diseases, acquired immune deficiency syndrome, deficiency anemia, weight loss, coagulation, diabetes, hypertension, congestive heart failure, valve disease, pulmonary circulation disorders, etc. Both gender and obesity were identified as protective factors. In colorectal cancer patients, the occurrence of postoperative blood transfusions correlates with prolonged LOS, elevated total hospitalization expenses, heightened hospital mortality rates, and an increased risk of perioperative complications ( peptic ulcer disease excluding bleeding, deep vein thrombosis, thrombocytopenia, hemorrage, and peripheral vascular disease ).\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eAll authors approved the publication of the manuscript.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003ch2\u003eClinical trial number\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003enot applicable\u003c/p\u003e\n\u003ch2\u003eFunding Declaration\u003c/h2\u003e\n\u003cp\u003e No.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eNa LI.Enhui SU. wrote the main manuscript text and Hao XIE.Lili YANG and Yan DU. prepared figures 1-3. Kai SONG.Ranjun XU and Yongheng WANG. prepared figures 4-5.Kai SONG.Na LI and Enhui SU. prepared Tables 1-3.Ranjun XU and Yongheng WANG. prepared Tables 4-7.All authors reviewed the manuscript.Ruifang ZHU.Hao XIE. is responsible for format review and supervision\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThis study is based on data provided by Nationwide Inpatient Sample (NIS) database, part of the Healthcare Cost and Utilization Project, Agency for Healthcare Research and Quality. The NIS database is a large publicly available all-payer inpatient care database in the United States. Therefore, in dividual or grouped data cannot be shared by the authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBatista Rodr\u0026iacute;guez G, Balla A, Corradetti S, Martinez C, Hern\u0026aacute;ndez P, Bollo J, Targarona EM. What have we learned in minimally invasive colorectal surgery from NSQIP and NIS large databases? A systematic review. Int J Colorectal Dis. 2018;33(6):663\u0026ndash;81. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00384-018-3036-4\u003c/span\u003e\u003cspan address=\"10.1007/s00384-018-3036-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBauer TM, Santoro A, Lin CC, Garrido-Laguna I, Joerger M, Greil R, Spreafico A, Yau T, Goebeler ME, H\u0026uuml;tter-Kr\u0026ouml;nke ML, Perotti A, Juif PE, Lu D, Barys L, Cremasco V, Pelletier M, Evans H, Fabre C, Doi T. Phase I/Ib, open-label, multicenter, dose-escalation study of the anti-TGF-β monoclonal antibody, NIS793, in combination with spartalizumab in adult patients with advanced tumors. J Immunother Cancer. 2023;11(11). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/jitc-2023-007353\u003c/span\u003e\u003cspan address=\"10.1136/jitc-2023-007353\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHalf EE, Levi Z, Mannalithara A, Leshno M, Ben-Aharon I, Abu-Freha N, Silverman B, Ladabaum U. Colorectal cancer screening at age 45 years in Israel: Cost-effectiveness and global implications. Cancer. 2024;130(6):901\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/cncr.35097\u003c/span\u003e\u003cspan address=\"10.1002/cncr.35097\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHayama T, Ozawa T, Tsukamoto M, Fukushima Y, Shimada R, Nozawa K, Matsuda K, Fujii S, Fukagawa T, Hashiguchi Y. (2022). Predicting Overall Survival Using Preoperative Nutritional and Inflammation Status for Colorectal Cancer. In Vivo, 36(1), 450\u0026ndash;457. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.21873/invivo.12724\u003c/span\u003e\u003cspan address=\"10.21873/invivo.12724\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHussan H, Patel A, Le Roux M, Cruz-Monserrate Z, Porter K, Clinton SK, Carethers JM, Courneya KS. Rising Incidence of Colorectal Cancer in Young Adults Corresponds With Increasing Surgical Resections in Obese Patients. Clin Transl Gastroenterol. 2020;11(4):e00160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14309/ctg.0000000000000160\u003c/span\u003e\u003cspan address=\"10.14309/ctg.0000000000000160\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKelley KA, Tsikitis VL. Clinical Research Using the National Inpatient Sample: A Brief Review of Colorectal Studies Utilizing the NIS Database. Clin Colon Rectal Surg. 2019;32(1):33\u0026ndash;40. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1055/s-0038-1673352\u003c/span\u003e\u003cspan address=\"10.1055/s-0038-1673352\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKommuru S, Aziz SN, Sagireddy S, Kaur G, Rijal S, Loh CC, Ibrahim Y, Patel V. Risk Factors for Colorectal Cancer in Inpatients With Ulcerative Colitis: A Nationwide Cross-Sectional Analysis. Cureus. 2022;14(7):e27114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7759/cureus.27114\u003c/span\u003e\u003cspan address=\"10.7759/cureus.27114\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eKwaan MR, Wu Y, Ren Y, Xirasagar S. Prompt intervention in large bowel obstruction management: A Nationwide Inpatient Sample analysis. Am J Surg. 2022;224(5):1262\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.amjsurg.2022.07.002\u003c/span\u003e\u003cspan address=\"10.1016/j.amjsurg.2022.07.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLee KC, Su YL, Wu KL, Cheng KC, Song LC, Tang CE, Chen HH, Chung KC. Impact of iron-deficiency anemia on short-term outcomes after resection of colorectal cancer liver metastasis: a US National (Nationwide) Inpatient Sample (NIS) analysis. Ann Coloproctol. 2025;41(2):119\u0026ndash;26. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3393/ac.2024.00591.0084\u003c/span\u003e\u003cspan address=\"10.3393/ac.2024.00591.0084\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLi X, Xie H, Liu S, Wang J, Shi Z, Yao Q, Yang Q, Li Q, Bao L. Analysis of the incidence and risk factors of blood transfusion in total knee revision: a retrospective nationwide inpatient sample database study. BMC Musculoskelet Disord. 2024;25(1):225. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12891-024-07331-2\u003c/span\u003e\u003cspan address=\"10.1186/s12891-024-07331-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLogie K, McKechnie T, Talwar G, Lee Y, Parpia S, Amin N, Doumouras A, Hong D, Eskicioglu C. The impact of operative approach for obese colorectal cancer patients: analysis of the National Inpatient Sample 2015\u0026ndash;2019. Colorectal Dis. 2024;26(1):34\u0026ndash;44. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/codi.16808\u003c/span\u003e\u003cspan address=\"10.1111/codi.16808\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLu CC, Lu CT, Chang KY, Chun-Li W, Wu CY. Robot-assisted vs. laparoscopic right hemicolectomy in octogenarians and nonagenarians: an analysis of the US nationwide inpatient sample 2005\u0026ndash;2018. Aging Clin Exp Res. 2024;36(1):193. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40520-024-02833-4\u003c/span\u003e\u003cspan address=\"10.1007/s40520-024-02833-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMayo JS, Brazer ML, Bogenberger KJ, Tavares KB, Conrad RJ, Lustik MB, Gillern SM, Park CW, Richards CR. Ureteral injuries in colorectal surgery and the impact of laparoscopic and robotic-assisted approaches. Surg Endosc. 2021;35(6):2805\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00464-020-07714-1\u003c/span\u003e\u003cspan address=\"10.1007/s00464-020-07714-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMoghadamyeghaneh Z, Mills SD, Pigazzi A, Carmichael JC, Stamos MJ. Risk factors of postoperative upper gastrointestinal bleeding following colorectal resections. J Gastrointest Surg. 2014;18(7):1327\u0026ndash;33. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11605-014-2540-2\u003c/span\u003e\u003cspan address=\"10.1007/s11605-014-2540-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOladunjoye AF, Kaleem SZ, Suresh A, Sahni V, Thoonkuzhy MJ, Anugwom G, Oladunjoye O, Otuada D, Ikekwere J, Espiridion ED. Cannabis use and medication nonadherence in bipolar disorder: A nationwide inpatient sample database analysis. J Affect Disord. 2022;299:174\u0026ndash;9. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jad.2021.11.067\u003c/span\u003e\u003cspan address=\"10.1016/j.jad.2021.11.067\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShah RM, Patel S, Sandhu LK, Patel S, Chand B. Outcomes and Characteristics of Hospitalized Colorectal Cancer Patients\u0026thinsp;\u0026le;\u0026thinsp;45 Years Old. J Gastrointest Cancer. 2023;54(4):1380\u0026ndash;2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s12029-023-00928-1\u003c/span\u003e\u003cspan address=\"10.1007/s12029-023-00928-1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAnthony P, Wu M, Shanmugalingam A, Ng CH, Wright D. Preoperative iron infusion does not reduce the requirement for blood transfusion in colorectal cancer surgery. Minerva Surg. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.23736/s2724-5691.23.09975-6\u003c/span\u003e\u003cspan address=\"10.23736/s2724-5691.23.09975-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBailey CR, George ML. Colorectal cancer surgery: is further research necessary? Anaesthesia. 2022;77(7):748\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/anae.15706\u003c/span\u003e\u003cspan address=\"10.1111/anae.15706\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eComorbidity software., \u003cem\u003ev.3.7\u003c/em\u003e. Agency for Healthcare Research and Quality. Retrieved Updated October 2011 from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp\u003c/span\u003e\u003cspan address=\"http://www.hcup-us.ahrq.gov/toolssoftware/comorbidity/comorbidity.jsp\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eImai K, Hotta K, Yamaguchi Y, Ito S, Ono H. Endoscopic submucosal dissection for large colorectal neoplasms. Dig Endoscopy. 2017;29(S2):53\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/den.12850\u003c/span\u003e\u003cspan address=\"10.1111/den.12850\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJenkins C, Lowenfels AB. Blood transfusion and colorectal cancer outcome. Ann Surg. 2015;261(3):e80. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/sla.0000000000000615\u003c/span\u003e\u003cspan address=\"10.1097/sla.0000000000000615\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLim AR, Kim JH, Hyun MH, Chang WJ, Lee S, Kim YH, Park KH, Park JH. Blood transfusion has an adverse impact on the prognosis of patients receiving chemotherapy for advanced colorectal cancer: experience from a single institution with a patient blood management program. Support Care Cancer. 2022;30(6):5289\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s00520-022-06949-z\u003c/span\u003e\u003cspan address=\"10.1007/s00520-022-06949-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMcSorley ST, Tham A, Dolan RD, Steele CW, Ramsingh J, Roxburgh C, Horgan PG, McMillan DC. Perioperative Blood Transfusion is Associated with Postoperative Systemic Inflammatory Response and Poorer Outcomes Following Surgery for Colorectal Cancer. Ann Surg Oncol. 2020;27(3):833\u0026ndash;43. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1245/s10434-019-07984-7\u003c/span\u003e\u003cspan address=\"10.1245/s10434-019-07984-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMueller MM, Van Remoortel H, Meybohm P, Aranko K, Aubron C, Burger R, Carson JL, Cichutek K, De Buck E, Devine D, Fergusson D, Foll\u0026eacute;a G, French C, Frey KP, Gammon R, Levy JH, Murphy MF, Ozier Y, Pavenski K, Seifried E. (2019). Patient Blood Management: Recommendations From the 2018 Frankfurt Consensus Conference. \u003cem\u003eJama\u003c/em\u003e, \u003cem\u003e321\u003c/em\u003e(10), 983\u0026ndash;997. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1001/jama.2019.0554\u003c/span\u003e\u003cspan address=\"10.1001/jama.2019.0554\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNanji S, Mir ZM, Karim S, Brennan KE, Patel SV, Merchant SJ, Booth CM. Perioperative blood transfusion and resection of colorectal cancer liver metastases: outcomes in routine clinical practice. HPB (Oxford). 2021;23(3):404\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.hpb.2020.06.014\u003c/span\u003e\u003cspan address=\"10.1016/j.hpb.2020.06.014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eQu R, Ma Y, Zhang Z, Fu W. Increasing burden of colorectal cancer in China. Lancet Gastroenterol Hepatol. 2022;7(8):700. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/s2468-1253(22)00156-x\u003c/span\u003e\u003cspan address=\"10.1016/s2468-1253(22)00156-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRubin DB. Estimating causal effects from large data sets using propensity scores. Ann Intern Med. 1997;127(8 Pt 2):757\u0026ndash;63. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7326/0003-4819-127-8_part_2-199710151-00064\u003c/span\u003e\u003cspan address=\"10.7326/0003-4819-127-8_part_2-199710151-00064\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSchober P, Vetter TR. Chi-square Tests in Medical Research. Anesth Analg. 2019;129(5):1193. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1213/ane.0000000000004410\u003c/span\u003e\u003cspan address=\"10.1213/ane.0000000000004410\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSharma R, Abbasi-Kangevari M, Abd-Rabu R, Abidi H, Abu-Gharbieh E, Acuna JM, Adhikari S, Advani SM, Afzal MS, Meybodi A, Ahinkorah M, Ahmad BO, Ahmadi S, Ahmadi A, Ahmed S, Ahmed H, Ahmed LA, Hamad MBA, Alahdab H, Zoladl F, M. Global, regional, and national burden of colorectal cancer and its risk factors, 1990\u0026ndash;2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet Gastroenterol Hepatol. 2022;7(7):627\u0026ndash;47. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/https://doi.org/10.1016/S2468-1253(22)00044-9\u003c/span\u003e\u003cspan address=\"10.1016/S2468-1253(22)00044-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eShin SH, Piozzi GN, Kwak JM, Baek SJ, Kim J, Kim SH. Effect of a Patient Blood Management system on perioperative transfusion practice and short-term outcomes of colorectal cancer surgery. Blood Transfus. 2022;20(6):475\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2450/2022.0328-21\u003c/span\u003e\u003cspan address=\"10.2450/2022.0328-21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eStorch EK, Custer BS, Jacobs MR, Menitove JE, Mintz PD. Review of current transfusion therapy and blood banking practices. Blood Rev. 2019;38:100593. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.blre.2019.100593\u003c/span\u003e\u003cspan address=\"10.1016/j.blre.2019.100593\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSuzuki S. Risk factors for bleeding after endoscopic submucosal dissection of colorectal neoplasms. World J Gastroenterol. 2014;20(7). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3748/wjg.v20.i7.1839\u003c/span\u003e\u003cspan address=\"10.3748/wjg.v20.i7.1839\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTamini N, Deghi G, Gianotti L, Braga M, Nespoli L. Colon Cancer Surgery: Does Preoperative Blood Transfusion Influence Short-Term Postoperative Outcomes? J Invest Surg. 2021;34(9):974\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/08941939.2020.1731634\u003c/span\u003e\u003cspan address=\"10.1080/08941939.2020.1731634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWeng M, Guo M, Li T, Zhou C, Sun C, Yue Y, Liao Q, Cai S, Lu X, Zhou D, Miao C. Anemia tolerance versus blood transfusion on long-term outcomes after colorectal cancer surgery: A retrospective propensity-score-matched analysis. Front Oncol. 2022;12:940428. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fonc.2022.940428\u003c/span\u003e\u003cspan address=\"10.3389/fonc.2022.940428\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWu HL, Tai YH, Lin SP, Chan MY, Chen HH, Chang KY. The Impact of Blood Transfusion on Recurrence and Mortality Following Colorectal Cancer Resection: A Propensity Score Analysis of 4,030 Patients. Sci Rep. 2018;8(1):13345. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-018-31662-5\u003c/span\u003e\u003cspan address=\"10.1038/s41598-018-31662-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Variables used in binary logistic regression analysis\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables Categories\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecific Variables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient demographics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eAge (18-44 years, 45-64 years, 65-74 years and \u0026ge;75 years), sex (male and female), race (White, Black, Hispanic, Asian or Pacific Islander, Native American and Other)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital characteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eType of admission (non-elective, elective), bed size of hospital (small, medium, large), teaching status of hospital (nonteaching, teaching), location of hospital (rural, urban), type of insurance (Medicare, Medicaid, private insurance, self-pay, no charge, other), location of the hospital (northeast, Midwest or north central, south, west)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 404px;\"\u003e\n \u003cp\u003eAIDS, alcohol abuse, deficiency anemia, rheumatoid diseases, chronic blood loss anemia, congestive heart failure, chronic pulmonar disease, coagulopathy, depression, diabetes (uncomplicated), drug abuse, hypertension, hypothyroidism, liver disease, lymphoma, fluid and electrolyte disorders, metastatic cancer, neurological disorders, obesity, paralysis, peripheral vascular disorders, psychoses, pulmonary circulation disorders, renal failure, solid tumor without metastasis, valvular disease and weight loss\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAIDS: Acquired immunodeficiency syndrome\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003ePatient characteristics and outcomes after colorectal cancer surgery (2010-2019)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 127px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Transfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=count)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e27,513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e136,368\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal incidence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 246px;\"\u003e\n \u003cp\u003e16.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (median, years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e73.00 (62.20,82.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e67.00\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(57.00, 77.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge group (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e18-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e3.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e5.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e45-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e24.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e35.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e65-74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e24.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e27.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026ge;75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e47.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e31.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e45.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e51.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e54.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e48.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e67.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e71.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e13.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e10.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e8.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e3.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e7.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e7.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Comorbidity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e7.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e6.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e18.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e13.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e22.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e77.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e52.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (median, d)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e10 (7-15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e5 (4-9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTOTCHG (median, $)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e94,200\u003c/p\u003e\n \u003cp\u003e(57,349-156,677)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e61,721.50\u003c/p\u003e\n \u003cp\u003e(40,214-99,261.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of insure (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e68.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e55.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"6\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e7.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e6.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e19.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e32.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e2.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e2.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eNo charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed size of hospital\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e15.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e15.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e28.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e27.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e15.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e57.60\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElective admission (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e40.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e72.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of hospital (teaching %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 127px;\"\u003e\n \u003cp\u003e52.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e62.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eContinue\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 119px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo Transfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation of hospital (urban, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e88.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e90.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion of hospital (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e19.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e18.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eMidwest or North Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e19.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e24.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e42.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e39.00\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 180px;\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e18.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e18.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDied (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 113px;\"\u003e\n \u003cp\u003e4.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 119px;\"\u003e\n \u003cp\u003e1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eLOS: Length of stay, TOTCHE: Total charge\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003eRisk factors associated with blood transfusion after colorectal cancer surgery\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"554\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 349px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 156px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e18-44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e45-64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.62-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e65-74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.59-0.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026ge;75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.68-0.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.82-0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.80-0.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.08-1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eAsian or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.01-1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eNative American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.95-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.407\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.78-1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Comorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.20-0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.34-0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.50-0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMedicare\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMedicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.83-1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.141\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.88-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eSelf-pay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.73-0.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eNo charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.94-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.81-1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBed size of hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eSmall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMedium\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.04-1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.02-1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eElective admission\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e2.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e2.83-2.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTeaching hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e1.40-1.49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.99-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.169\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRegion of hospital\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eNortheast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026mdash;\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eMidwest or North Central\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.69-0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eSouth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.94-1.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 17px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 188px;\"\u003e\n \u003cp\u003eWest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 107px;\"\u003e\n \u003cp\u003e0.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 156px;\"\u003e\n \u003cp\u003e0.89-0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 86px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAIDS: Acquired immunodeficiency syndrome, OR: Odds ratio, CI: Confidence interval\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u0026nbsp;\u003c/strong\u003eRelationship between blood transfusion and preoperative\u0026nbsp;comorbidities\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"749\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 298px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 262px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo transfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"bottom\" style=\"width: 188px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePreoperative comorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eAcquired immune deficiency syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e218 (0.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e58 (0.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.67\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.22-2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eAlcohol abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e2,843 (2.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e803 (2.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00-1.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDeficiency anemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e22,580 (16.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e10,431 (37.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e2.70-2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eRheumatoid arthritis/collagen vascular diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e2,069 (1.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e530 (1.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.95-1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eChronic blood loss anemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e5,734 (4.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e4,299 (15.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e4.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e4.23-4.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eCongestive heart failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e9,475 (6.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e4,586 (16.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.61-1.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\u0026nbsp;\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eChronic pulmonary disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e20,321 (14.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5,150 (18.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.02-1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eCoagulopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e3,699 (2.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2,154 (7.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e2.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e2.00-2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e10,284 (7.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e2,457 (8.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.01-1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDiabetes, uncomplicated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e23,733 (17.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e5,932 (21.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.18-1.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eDrug abuse\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e1,040 (0.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e240 (0.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.77-1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e78,093 (57.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e17,802 (64.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.05-1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eHypothyroidism\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e14,545 (10.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e3,504 (12.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.00-1.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eLiver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e4,829 (3.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,241 (4.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.06-1.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eLymphoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e724 (0.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e201 (0.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.99-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eFluid and electrolyte disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e28,935 (21.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e11,854 (43.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.83-1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eMetastatic cancer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e36,674 (26.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e9,315 (33.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.17-1.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eOther neurological disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e4,692 (3.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,851 (6.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.23-1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eObesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e19,637 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e3,607 (13.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e0.80-0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003eParalysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e1,041 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e515 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.52-1.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003ePeripheral vascular disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e6,125 (4.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,997 (7.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.08-1.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003ePsychoses\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e2,484 (1.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e795 (2.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.14-1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\n \u003cp\u003ePulmonary circulation disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e2,700 (2.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,455 (5.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\n \u003cp\u003e1.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\n \u003cp\u003e1.34-1.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eRenal failure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e9,962 (7.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e4,037 (14.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.33-1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eSolid tumor without metastasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e56,265 (41.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e8,822 (32.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e0.73-0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eValvular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e5,808 (4.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e2,343 (8.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.26-1.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 167px;\"\u003e\n \u003cp\u003eWeight loss\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e13,260 (9.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e6,135 (22.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 66px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e1.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e1.67-1.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 115px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 21px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 167px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 47px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 54px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 115px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eOR: Odds ratio, CI: Confidence interval\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u0026nbsp;\u003c/strong\u003eRelationship between blood transfusion and postoperative complications\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"749\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 320px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate Analysis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 242px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate Logistic Regression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo transfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTransfusion\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedical complications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003ePeptic ulcer disease excluding bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e489 (0.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e270 (1.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1.72-2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eDiabetes with chronic complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e7,538 (5.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,975(7.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e0.93-1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eDeep vein thrombosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e1,731 (1.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,154 (4.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e3.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2.90-3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eThrombocytopenia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e2,503 (1.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,333 (4.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e2.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e2.38-2.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003ePeripheral vascular disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e5,103 (3.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e1,599 (5.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e1.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e1.42-1.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 187px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurgical complications\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 135px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 116px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 69px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 109px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 23px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eHemorrhage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 135px;\"\u003e\n \u003cp\u003e1,193 (0.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 116px;\"\u003e\n \u003cp\u003e964 (3.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 69px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 52px;\"\u003e\n \u003cp\u003e3.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 81px;\"\u003e\n \u003cp\u003e3.59-4.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 109px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"colorectal neoplasms, blood transfusion, national inpatient sample, nursing","lastPublishedDoi":"10.21203/rs.3.rs-6921855/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6921855/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eAIMS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research aimed to determine the prevalence of blood transfusions and to identify preoperative variables associated with the need for blood transfusion after colorectal cancer surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMETHODS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe analyzed 163,881 patients who had colorectal cancer surgery between 2010 and 2019 using the Nationwide Inpatient Sample. We also explored the relationship between blood transfusions and specific factors including length of stay (LOS), overall charges, and payer status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRESULTS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the study period, there was no significant change in the transfusion rate. Logistic regression analysis showed significant associations with chronic blood loss anemia, thrombocytopenia, deep vein thrombosis, peptic ulcer disease excluding bleeding, deficiency anemia, rheumatoid arthritis/collagen vascular diseases, chronic pulmonary disease, congestive heart failure, coagulopathy, depression, renal failure, diabetes, uncomplicated, hypertension, peripheral vascular disorders, liver disease, fluid and electrolyte disorders, other neurological disorders, paralysis, metastatic cancer, psychoses, pulmonary circulation disorders, valvular disease, weight loss and acquired immune deficiency syndrome. Patients who received blood transfusions had higher overall costs, longer hospital stays, and a greater likelihood of Medicare coverage compared to those who did not receive transfusions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONCLUSIONS.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur study identified seven key risk factors for blood transfusions during colorectal cancer surgery: fluid and electrolyte disorders, paralysis, chronic blood loss anemia, peptic ulcer disease excluding bleeding, coagulopathy, deep vein thrombosis as well as thrombocytopenia. Patients with these risk factors are at increased risk of needing a blood transfusion after surgery and should receive appropriate health guidance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIMPACT.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main contribution of this study is to highlight the many risk factors present in patients undergoing surgical transfusion for colorectal cancer. This study recommends that clinical priority should be given to improving blood transfusion techniques, as well as fostering patients' awareness of disease risk factors and effective preventive.\u003c/p\u003e","manuscriptTitle":"Incidence and risk factors associated of blood transfusion after colorectal cancer surgery：A retrospective nationwide inpatient sample database study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-15 10:55:28","doi":"10.21203/rs.3.rs-6921855/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b1a8df5b-bb91-44dd-9b25-5159bfe3b007","owner":[],"postedDate":"July 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-05T07:24:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-15 10:55:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6921855","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6921855","identity":"rs-6921855","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}