The Impact of Obesity on Postoperative Pulmonary Complications in Patients Undergoing Aortic Surgery

The Impact of Obesity on Postoperative Pulmonary Complications in Patients Undergoing Aortic Surgery | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Impact of Obesity on Postoperative Pulmonary Complications in Patients Undergoing Aortic Surgery Hui Wang, Chun Chen, Yun-Tai Yao, the Evidence in Cardiovascular Anesthesia (EICA) Group the Evidence in Cardiovascular Anesthesia (EICA) Group This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7240021/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 Background Postoperative pulmonary complications (PPCs) are common following total aortic arch replacement with frozen elephant trunk (TAR + FET) in patients with acute type A aortic dissection (ATAAD). This study aimed to evaluate the incidence and risk factors for PPCs in ATAAD patients undergoing TAR + FET. Methods This single-center retrospective study included 203 patients with ATAAD who underwent TAR + FET between January 2023 and August 2024. Patients were divided into PPC and non-PPC groups. The incidence and types of PPCs were recorded, and risk factors were analyzed using multivariate logistic regression. Postoperative outcomes were compared between groups. Results The incidence of PPCs was 17.7%, with respiratory infections being the most common (9.9%), followed by respiratory failure (3.9%), acute respiratory distress syndrome (2.0%), pleural effusion (1.0%), pneumothorax (0.5%), and pulmonary embolism (0.5%). Multivariate analysis identified body mass index (BMI) as an independent risk factor for PPCs [odds ratio (OR): 1.144; 95% confidence interval (CI): 1.048–1.250; P = 0.003]. Conclusions Higher BMI is independently associated with an increased risk of PPCs following TAR + FET in ATAAD patients. These findings highlight the importance of preoperative BMI assessment in optimizing perioperative management. Aortic arch surgery body mass index postoperative pulmonary complications aortic dissection frozen elephant trunk Figures Figure 1 Figure 2 Introduction Aortic intimal rupture or intramural bleeding can cause separation of the aortic wall layer, leading to the formation of true and false lumens in the artery, resulting in aortic dissection. The anatomy involving the ascending aorta is called type A aortic dissection. Type A aortic dissection is a life-threatening disease that occurs rapidly and can affect important branches of the aorta, such as the brachiocephalic artery, subclavian artery, coronary artery, etc. Surgery is the preferred treatment method. Under the conditions of moderate to low temperature circulatory arrest combined with selective cerebral perfusion, total arch replacement surgery and stent graft implantation have become standard surgical procedures for treating aortic dissection. The International Aortic Arch Surgery Research Group emphasizes that early hospitalization related adverse events include in-hospital mortality, gastrointestinal bleeding, amputation related paralysis, acute renal failure, low cardiac output syndrome, and cerebrovascular disease [ 1 ]. Despite continuous advancements in surgical techniques, the perioperative mortality rate and incidence of pulmonary complications remain high. A study showed that the incidence of pulmonary complications was 29.2% [ 2 ]. Another study revealed that the incidence of hypoxemia was 27.4%, and the incidence of pulmonary infection was 17.7% [ 3 ]. Obesity increases the risk of cardiovascular disease [ 4 ], and obesity also increases in-hospital mortality in patients with dissection [ 5 ]. However, data on the role of obesity in PPCs among ATAAD patients is limited. This study investigates the impact of body mass index (BMI) on PPCs following TAR + FET in ATAAD patients, aiming to improve perioperative strategies and outcomes. Methods Ethical approval This retrospective cohort study was approved by the Institutional Review Boards of Fuwai Hospital (2019-1301), with informed consent waived. The study followed the Declaration of Helsinki and adhered to STROBE guidelines. Data Collection A total of 203 consecutive patients with ATAAD who underwent at a single center between January 2023 and August 2024 were included. Inclusion criteria were confirmed , age ≥18 years, no pre-existing pulmonary disease, and surgery within 2 weeks of symptom onset. The following was used as exclusion criteria: accompanied by severe cardiovascular diseases, malignant tumors, genetic or endocrine disorders, postoperative cerebrovascular events, as well as intraoperative death or death occurring within 24 hours after surgery. Data were collected from medical records, including age, sex, body mass index, history of smoking, history of diabetes, history of hypertension, history of hyperlipidemia, history of renal dysfunction, history of cerebrovascular events, history of coronary heart disease, preoperative labs, preoperative HR, preoperative SpO2, preoperative SBP, preoperative DBP, intraoperative variables (CPB time, DHCA duration, ACC duration, minimum nasopharyngeal temperature, operation duration ), and PPCs. PPCs were diagnosed based on standardized criteria[6], including infection, respiratory failure, ARDS, pleural effusion, pneumothorax, and pulmonary embolism. Statistical analysis SPSS 26.0 was used for statistical analyses. Continuous variables were analyzed using t-tests or Mann–Whitney U-tests. Categorical data were compared using chi-square tests. Significant variables from univariate analysis were entered into multivariate logistic regression to identify independent risk factors. Use ROC to evaluate the predictive efficacy of relevant indicators for PPCs in ATAAD patients. Results Baseline characteristics A total of 226 patients who underwent surgery for acute type A aortic dissection were identified from the medical record system. Among these patients, 20 were excluded because the time from surgery to onset of symptoms exceeded 2 weeks. 3 were excluded because they died intraoperatively or within 24 hours postoperatively. Finally, 203 patients were included in the analysis (Figure 1). The preoperative and intraoperative variables of patients are reported in Table 1. There were 36 patients in the PPCs group and 167 in the non-PPCs group, with an incidence rate of 17.7%. The body mass index of the PPCs group was higher than that of the non-PPCs group (30.9 ± 6.7 vs 26.8 ± 4.0, P = 0.001). Preoperative oxygen saturation in the PPCs group was lower than in the non-PPCs group (93.5 ± 4.8 vs 96.2 ± 3.5, P = 0.002). Systolic blood pressure upon entering the room was higher in the PPCs group compared to the non-PPCs group (132.5 ± 22.3 vs 124.4 ± 19.5, P = 0.03). The duration of surgery in the PPCs group was longer than in the non-PPCs group (7.3 ± 1.6 vs 6.6 ± 1.9, P = 0.042). Additionally, the number of neutrophils in the PPCs group was greater than in the non-PPCs group (11.4 ± 4.3 vs 9.9 ± 4.1, P = 0.048). Incidence of PPCs PPCs occurred in 17.7% of patients. Respiratory infection (9.9%) was the most frequent complication, followed by respiratory failure (3.9%), ARDS (2.0%), pleural effusion (1.0%), pneumothorax (0.5%), and pulmonary embolism (0.5%). Risk Factors All clinically significant covariates were included in a multi-variable logistic regression model (Table 2). Multivariate logistic regression revealed higher BMI ( OR 1.144, 95% CI : 1.048–1.250, P = 0.003), lower SpO2, and higher SBP as independent risk factors. ROC curve analysis showed an AUC of 0.693 for BMI in predicting PPCs in Figure 2. Table1 Preoperative and intraoperative variables. PPCs(n=36) Non-PPCs(n=167) P value Age, yr 49.8±11.0 52.2±12.1 0.272 Male sex, % 30(83.3) 123(73.7) 0.221 BMI 30.9±6.7 26.8±4.0 0.001 Smoking, % 4(11.1) 12(7.2) 0.651 Diabetes, % 5(13.9) 9(5.4) 0.144 Hypertension, % 31(86.1) 129(77.2) 0.382 Hyperlipidemia,% 7(19.4) 20(12.0) 0.354 Renal diseases ,% 2(5.6) 1(0.6) 0.140 Cerebrovascular events, % 5(13.9) 12（(7.2) 0.325 Coronary heart disease, % 4(11.1) 12(7.2) 0.651 Preoperative HR (bpm) 82.7±15.5 78.4±12.5 0.081 Preoperative SpO2 93.5±4.8 96.2±3.5 0.002 Preoperative SBP 132.5±22.3 124.4±19.5 0.030 Preoperative DBP 63.7±12.7 63.9±13.9 0.932 Operation duration (h) 7.3±1.6 6.6±1.9 0.042 CPB duration (min) 215.4±65.4 203.0±73.8 0.351 ACC duration (min) 149.3±51.2 140.3±53.4 0.357 DHCA duration (min) 19.9±4.8 20.0±6.4 0.902 Blood loss (mL) 772.2±167.9 739.6±143.4 0.285 Tmin, ℃ 25.9±1.3 26.0±1.1 0.560 Red blood cell (mL) 394.3±291.1 337.4±282.3 0.277 Platelet concentrates (unit) 1.1±0.5 1.0±0.5 0.677 Haemoglobin (g L -1) 34.5±19.5 132.4±16.1 0.502 White cell count (cells 109 L-1) 13.0±4.8 11.8±4.2 0.118 Neutrophil count (cells 109 L -1) 11.4±4.3 9.9±4.1 0.048 Monocyte count (cells 109 L- 1) 0.8±0.3 0.7±0.7 0.908 Platelets (cells 109 L-1) 188.9±60.6 183.8±67.8 0.680 NLR 11.0±5.5 10.8±8.2 0.849 MLR 0.7±0.4 0.7±0.6 0.939 PLR 182.7±68.8 184.9±104.0 0.903 ACC = aortic cross clamping, BMI = body mass index, CPB = cardiopulmonary bypass, DBP = diastolic blood pressure, DHCA = deep hypothermic circulatory arrest, HR = heart rate, PPCs = postoperative pulmonary complications, SBP=systolic blood pressure, NLR= the neutrophil-lymphocyte ratio, MLR=the monocyte-lymphocyte ratio, PLR= the platelet-lymphocyte ratio Table2 PPCs risk factors. Variables Multivariable Analysis OR (95% CI) P Value BMI 1.144(1.048-1.250) 0.003 Preoperative SpO2 0.879(0.798-0.969) 0.009 Preoperative SBP 1.025(1.005-1.044) 0.012 Operation duration (h) 1.144(0.933-1.402) 0.195 Neutrophil count (cells 109 L -1 ) 1.028 (0.928-1.139) 0.596 Discussion PPCs are common postoperative complications in ATAAD patients. It has been reported that the frequency of respiratory events following ATAAD is 24.24% in previous research, which is similar to the 17.7% incidence observed in our research[7]. In this cohort study of 203 patients who underwent TAR+FET for ATAAD, we found that BMI was correlated with PPCs. At present, the potential mechanism of PPCs after acute Stanford A dissection is still unclear. Thus, further understanding of the risk factors and mechanism of PPCs after acute Stanford type A dissection surgery is crucial to the design of preventative strategies. Among the numerous factors influencing postoperative outcomes, obesity has emerged as one of the more prominent indicators in recent years. A research has demonstrated that high preoperative bradykinin levels and increased BMI are independent predictors of severe postoperative hypoxaemia in patients with acute Stanford type A aortic dissection[8]. Body mass index was an independent predictor of acute kidney injury after urgent aortic total arch replacement surgery with a frozen elephant trunk implant[9].There exists a certain causal relationship between obesity and various perioperative indicators among surgical patients, often resulting in an unfavorable prognosis[10]. With changes in lifestyle, the incidence of obesity gradually increases. This study shows that The incidence of obesity in ATAAD patients is relatively high (29.75%). This study also shows elevated BMI was a independent risk factor of PPCs after acute Stanford type A dissection surgery. Some Chinese scholars found that Obesity was independent risk factors for postoperative severe hypoxemia in patients with acute type A aortic dissection[11]. A study showed a higher body mass index may be closely correlated with prolonged intubation for patients undergoing aortic dissection surgery[12]. Another study showed that association was found for both PPCs and mortality in relation to increased BMI[13]. Obesity has many adverse effects on the body. Obesity is independent of cardiovascular disease Risk factors. Obesity patients are often accompanied by atherosclerosis and coronary artery disease heart disease, congestive heart failure, arrhythmia, cardiomyopathy, etc. The risk of cardiovascular accidents has significantly increased. Its mechanism and obesity patients often accompanied by hypertension, dyslipidemia, inflammatory response, and insulin Resistance and related obesity can lead to Type 2 diabetes, hypertension, kidney disease, obstructive sleep apnea syndrome. The relationship between obesity and increased pulmonary complications after dissection surgery is a complex, multifactorial process involving respiratory mechanics, lung function, inflammatory response, fluid management, and immune regulation. The increased weight of abdominal and thoracic adipose tissue exacerbates the compressive forces transmitted by the chest wall to the lung and exaggerates the cephalad displacement of the diaphragm. These produce a rightward shift of the respiratory system pressure–volume curve, higher pleural pressure, lower respiratory system compliance and lower functional residual capacity (FRC) before and after induction of general anesthesia.The combined effect of compression of the dorso-caudal lung and the gas absorption in lung units exposed to small airway closure results in greater risk of perioperative pulmonary atelectasis in obese than nonobese patients[14, 15]. The adipose tissue of obese patients secretes a large amount of inflammatory factors (such as IL-6 and TNF-a), which have caused a chronic inflammatory state throughout the body before surgery [16, 17]. Obese patients had a higher level of NE and CRP, suggesting a more severe inflammatory response[18]. Many of the factors involved in the CPB create multiple inflammatory responses[19]. Due to the surgical trauma, the inflammatory response further intensifies after surgery, leading to increased pulmonary capillary permeability, causing pulmonary edema and acute respiratory distress syndrome (ARDS). Surgical dissection involves significant trauma and is prone to trigger systemic inflammatory response syndrome (SIRS). Obese patients have a more severe inflammatory response and a significantly increased risk of lung injury. Large amounts of blood transfusion and infusion are often required in total arch replacement combined with frozen elephant trunk implantation(TAR with FET). Inflammatory response leads to increased capillary permeability, fluid leakage into the interstitial and alveolar spaces of the lungs, further exacerbating pulmonary edema and hypoxemi. The inflammatory factors secreted by the adipose tissue of obese patients, such as IL-6 and TNF-a, suppress immune function and increase the risk of postoperative infection[20]. obesity may cause obstructive sleep apnea (OSA) and Obstructive sleep hypopnea (OSH)[21]. Increased fat deposition in the pharynx resulting in decreased patency of the pharynx increases the likelihood that relaxation of the upper airway muscles will cause collapse of the soft-walled oropharynx between the uvula and epiglottis[21]. Increased cervical adipose tissue leads to decreased upper respiratory tract patency. Furthermore, obese patients are susceptible to PPCs after a prolonged surgical procedure due to the anesthetic drug accumulating in fat cells, which slows metabolism, resulting in delayed recovery of bodily functions. The study still has some limitations. First, as mentioned in the Methods, our study was based on the Chinese population, reducing the generalizability of the findings, and it is unclear whether it is applicable to other ethnicities. Second, our findings are derived from single-center observational data, and further multi-center studies and a high-quality meta-analysis should be carried out to provide more evidence. Simultaneously, limited by the sample size, we were unable to assess the interaction of stratified root procedure and concomitant surgery with multivariate adjustment, which will be addressed in our future studies. Finally, this study did not explore the effect of obesity degree and BMI on in-hospital mortality, as the Chinese criteria do not subdivide the obesity degree. The continuous grouping of BMI, linear or non-linear relationships, and optimal cutoff values for prediction were also not further explored, which may be addressed in our future studies. Abbreviations PPCs Postoperative Pulmonary Complications ATAAD Acute Type A Aortic Dissection BMI Body Mass Index OR Odds Ratio CI Confidence Interval TAR + FET Total Aortic Arch Replacement with Frozen Elephant Trunk CPB Cardiopulmonary Bypass ACC Aortic Cross Clamping SBP Systolic Blood Pressure DBP:Diastolic Blood Pressure DHCA Deep Hypothermic Circulatory Arrest HR Heart Rate NLR Neutrophil-lymphocyte Ratio MLR Monocyte-lymphocyte Ratio PLR Platelet-lymphocyte Ratio ARDS Acute Respiratory Distress Syndrome FRC Functional Residual Capacity SIRS Systemic Inflammatory Response Syndrome OSA Obstructive Sleep Apnea Syndrome OSH Obstructive Sleep Hypopnea Declarations Acknowledgements Not applicable. Authors’ contributions Data collection was done by Hui Wang. Conceptualization was done by Hui Wang and Yun-Tai Yao. Research, manuscript writing, Manuscript outline, data quality assessment and manuscript revision were done by Hui Wang and Chun Chen. The final manuscript was read and approved by all authors. Funding This work was supported by the Youth Teacher Training Program of Peking Union Medical College (2014) and CAMS Innovation Fund for Medical Sciences (CIFMS)-2021-I2M-C&T-B-038. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate The study protocol was approved by the Institutional Review Boards of Fuwai Hospital (2019-1301). Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details 1 Department of Anesthesiology, Yichang Central People’s Hospital, Yichang, Hubei, China. 2 Department of Anesthesiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China. 3 Center of Outcomes Research, Department of Anesthesiology, Critical Care and Pain Medicine, University of Texas, Houston 77030, Texas, United States. 4 Outcomes research Consortium, Houston 77030, Texas, United States. References Jammer I, Wickboldt N, Sander M, et al. Standards for definitions and use of outcome measures for clinical effectiveness research in perioperative medicine: European Perioperative Clinical Outcome (EPCO) definitions: a statement from the ESA-ESICM joint taskforce on perioperative outcome measures. Eur J Anaesthesiol, 2015, 32(2): 88-105. doi:10.1097/EJA.0000000000000118 Yan Y, Zhang X, Yao Y. Evidence in Cardiovascular Anesthesia (EICA) Group. Postoperative pulmonary complications in patients undergoing aortic surgery: A single-center retrospective study. Medicine (Baltimore), 2023, 102(39): e34668. Bai L, Ge L, Zhang Y, Li M, et al. Experience of the Postoperative Intensive Care Treatment of Stanford Type A Aortic Dissection. Int J Clin Pract. 2023, 2023: 4191277. Published 2023 Jan 10. Kim MS, Kim WJ, Khera AV, et al. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J, 2021, 42(34): 3388-3403. Pan X, Xing Z, Yang G, Ding N, Zhou Y, Chai X. Obesity Increases In-Hospital Mortality of Acute Type A Aortic Dissection Patients Undergoing Open Surgical Repair: A Retrospective Study in the Chinese Population. Front Cardiovasc Med, 2022, 9:899050. Abbott TEF, Fowler AJ, Pelosi P, et al. A systematic review and consensus definitions for standardised end-points in perioperative medicine: pulmonary complications. Br J Anaesth，2018, 120(5): 1066-1079. Liu G, Wang H, Luo Q, et al. Low postoperative blood platelet count may be a risk factor for 3-year mortality in patients with acute type A aortic dissection. J Cardiothorac Surg, 2021, 16(1): 274. Guan X, Li L, Li J, et al. High preoperative bradykinin level is a risk factor for severe postoperative hypoxaemia in acute aortic dissection surgery. Exp Physiol, 2023, 108(5): 683-691. Liu T, Fu Y, Liu J, et al. Body mass index is an independent predictor of acute kidney injury after urgent aortic arch surgery for acute DeBakey Type I aortic dissection. J Cardiothorac Surg, 2021, 16(1): 145. Guan X, Li L, Li J, et al. High preoperative bradykinin level is a risk factor for severe postoperative hypoxaemia in acute aortic dissection surgery. Exp Physiol, 2023, 108(5): 683-691. Gong M, Wu Z, Xu S, et al. Increased risk for the development of postoperative severe hypoxemia in obese women with acute type a aortic dissection. J Cardiothorac Surg, 2019, 14(1): 81. Li Y, Jiang H, Xu H, et al. Impact of a Higher Body Mass Index on Prolonged Intubation in Patients Undergoing Surgery for Acute Thoracic Aortic Dissection. Heart Lung Circ, 2020, 29: 1725-1732. Covarrubias J, Grigorian A, Schubl S, et al. Obesity associated with increased postoperative pulmonary complications and mortality after trauma laparotomy. Eur J Trauma Emerg Surg, 2021, 47(5): 1561-1568. Lagier D, Zeng C, Fernandez-Bustamante A, Vidal Melo MF. Perioperative Pulmonary Atelectasis: Part II. Clinical Implications. Anesthesiology, 2022,1 36(1): 206-236. Covarrubias J, Grigorian A, Schubl S, et al. Obesity associated with increased postoperative pulmonary complications and mortality after trauma laparotomy. Eur J Trauma Emerg Surg, 2021, 47(5): 1561-1568. Ellulu MS, Patimah I, Khaza'ai H, Rahmat A, Abed Y. Obesity and inflammation: the linking mechanism and the complications. Arch Med Sci, 2017, 13(4): 851-863. Boutari C, Hill MA, Procaccini C, et al. The key role of inflammation in the pathogenesis and management of obesity and CVD. Metabolism, 2023, 145: 155627. Zhang C, Shi R, Zhang G, et al. The association between body mass index and risk of preoperative oxygenation impairment in patients with the acute aortic syndrome. Front Endocrinol (Lausanne),2022, 13: 1018369. Nteliopoulos G, Nikolakopoulou Z, Chow BHN,et al. Lung injury following cardiopulmonary bypass: a clinical update. Expert Rev Cardiovasc Ther. 2022, 20(11): 871-880. Mărginean CO, Meliţ LE, Huțanu A, et al. The adipokines and inflammatory status in the era of pediatric obesity. Cytokine, 2020, 126: 154925. Benumof JL. Obesity, sleep apnea, the airway and anesthesia. Curr Opin Anaesthesiol, 2004, 17(1): 21-30. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7240021","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":509843547,"identity":"8826c8a5-8865-4494-b477-c9c25d95ed15","order_by":0,"name":"Hui Wang","email":"","orcid":"","institution":"Yichang Central People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hui","middleName":"","lastName":"Wang","suffix":""},{"id":509843549,"identity":"8d8023e8-ce01-4ae7-bf3e-3506b7120734","order_by":1,"name":"Chun Chen","email":"","orcid":"","institution":"Yichang Central People’s Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chun","middleName":"","lastName":"Chen","suffix":""},{"id":509843550,"identity":"6633ae5f-1b87-4080-a0f2-e7719c6d3743","order_by":2,"name":"Yun-Tai Yao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYNACAyBmb2x88IFI9YwNYC08h5sNZxCvBQQk0tukOYhy0o3c4w9+FByW55d82CDNwGAnp9tAUEteYmOPwWHDmbMTG4wLGJKNzQ4Q1JJj2MBjcJhxw+3EhuQZDAcStxGjpfGPwWH7DTcPNhzmIVZLM9CWxA03GBubidIieeaN4WwZg/TkmT2JzYwzDIjwC9/xHIOPb/5Y2/azH3/+40OFnRxBLQoQBc0wdxJQDgLyDWCqjgilo2AUjIJRMGIBAA+mSbZYtX2SAAAAAElFTkSuQmCC","orcid":"","institution":"Chinese Academy of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Yun-Tai","middleName":"","lastName":"Yao","suffix":""},{"id":509843551,"identity":"63fabd48-7c11-4014-a278-fdf4f0dead54","order_by":3,"name":"the Evidence in Cardiovascular Anesthesia (EICA) Group the Evidence in Cardiovascular Anesthesia (EICA) Group","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences and Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"the","middleName":"Evidence in Cardiovascular Anesthesia (EICA) Group the Evidence in Cardiovascular Anesthesia (EICA)","lastName":"Group","suffix":""}],"badges":[],"createdAt":"2025-07-29 07:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7240021/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7240021/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90882558,"identity":"624f0041-82b7-455b-92b6-d863a5081d09","added_by":"auto","created_at":"2025-09-09 09:52:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":46181,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of the screening and enrollment of study patients\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7240021/v1/361a1e0b976f85a44f8aab5a.png"},{"id":90882560,"identity":"8cdacb1b-5e36-42b6-a7c0-285642a12124","added_by":"auto","created_at":"2025-09-09 09:52:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":112341,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve of BMI for prediction of PPCs occurred in ATAAD patients\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7240021/v1/888b3d0e9173c6cd364ae33d.png"},{"id":103507838,"identity":"5e563528-78cd-4aac-a092-a51014ef1aec","added_by":"auto","created_at":"2026-02-26 13:45:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":695195,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7240021/v1/d6de76f8-a8aa-425f-9b71-14cc202c5ad4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Obesity on Postoperative Pulmonary Complications in Patients Undergoing Aortic Surgery","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAortic intimal rupture or intramural bleeding can cause separation of the aortic wall layer, leading to the formation of true and false lumens in the artery, resulting in aortic dissection. The anatomy involving the ascending aorta is called type A aortic dissection. Type A aortic dissection is a life-threatening disease that occurs rapidly and can affect important branches of the aorta, such as the brachiocephalic artery, subclavian artery, coronary artery, etc. Surgery is the preferred treatment method. Under the conditions of moderate to low temperature circulatory arrest combined with selective cerebral perfusion, total arch replacement surgery and stent graft implantation have become standard surgical procedures for treating aortic dissection. The International Aortic Arch Surgery Research Group emphasizes that early hospitalization related adverse events include in-hospital mortality, gastrointestinal bleeding, amputation related paralysis, acute renal failure, low cardiac output syndrome, and cerebrovascular disease [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite continuous advancements in surgical techniques, the perioperative mortality rate and incidence of pulmonary complications remain high. A study showed that the incidence of pulmonary complications was 29.2% [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Another study revealed that the incidence of hypoxemia was 27.4%, and the incidence of pulmonary infection was 17.7% [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Obesity increases the risk of cardiovascular disease [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and obesity also increases in-hospital mortality in patients with dissection [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, data on the role of obesity in PPCs among ATAAD patients is limited. This study investigates the impact of body mass index (BMI) on PPCs following TAR\u0026thinsp;+\u0026thinsp;FET in ATAAD patients, aiming to improve perioperative strategies and outcomes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective cohort study was approved by\u0026nbsp;the Institutional Review Boards of\u003c/p\u003e\n\u003cp\u003eFuwai Hospital (2019-1301), with informed consent waived. The study followed the Declaration of Helsinki and adhered to STROBE guidelines.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 203 consecutive patients with ATAAD who underwent at a single center between January 2023 and August 2024 were included. Inclusion criteria were confirmed , age\u0026nbsp;\u0026ge;18 years, no pre-existing pulmonary disease, and surgery within 2 weeks of symptom onset. The following was used as exclusion criteria: accompanied by severe cardiovascular diseases, malignant tumors, genetic or endocrine disorders, postoperative cerebrovascular events, as well as intraoperative death or death occurring within 24 hours after surgery. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eData were collected from medical records, including age, sex, body mass index, history of smoking, history of diabetes, history of hypertension, history of hyperlipidemia, history of renal dysfunction, history of cerebrovascular events, history of coronary heart disease, preoperative labs, preoperative HR, preoperative SpO2, preoperative SBP, preoperative DBP, intraoperative variables (CPB time, DHCA duration, ACC duration, minimum nasopharyngeal temperature, operation duration ), and PPCs. PPCs were diagnosed based on standardized criteria[6], including infection, respiratory failure, ARDS, pleural effusion, pneumothorax, and pulmonary embolism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSPSS 26.0 was used for statistical analyses. Continuous variables were analyzed using t-tests or Mann\u0026ndash;Whitney U-tests. Categorical data were compared using chi-square tests. Significant variables from univariate analysis were entered into multivariate logistic regression to identify independent risk factors. Use ROC to evaluate the predictive efficacy of relevant indicators for PPCs in ATAAD patients.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 226 patients who underwent surgery for acute type A aortic dissection were identified from the medical record system. Among these patients, 20 were excluded because the time from surgery to onset of symptoms exceeded 2 weeks. 3 were excluded because they died intraoperatively or within 24 hours postoperatively. Finally, 203 patients were included in the analysis (Figure 1).\u003c/p\u003e\n\u003cp\u003eThe preoperative and intraoperative variables of patients are reported in Table 1. There were 36 patients in the PPCs group and 167 in the non-PPCs group, with an incidence rate of 17.7%. The body mass index of the PPCs group was higher than that of the non-PPCs group (30.9 \u0026plusmn; 6.7 vs 26.8 \u0026plusmn; 4.0,\u003cem\u003e\u0026nbsp;P\u0026nbsp;\u003c/em\u003e= 0.001). Preoperative oxygen saturation in the PPCs group was lower than in the non-PPCs group (93.5 \u0026plusmn; 4.8 vs 96.2 \u0026plusmn; 3.5,\u003cem\u003e\u0026nbsp;P\u003c/em\u003e = 0.002). Systolic blood pressure upon entering the room was higher in the PPCs group compared to the non-PPCs group (132.5 \u0026plusmn; 22.3 vs 124.4 \u0026plusmn; 19.5, \u003cem\u003eP\u003c/em\u003e = 0.03). The duration of surgery in the PPCs group was longer than in the non-PPCs group (7.3 \u0026plusmn; 1.6 vs 6.6 \u0026plusmn; 1.9, \u003cem\u003eP\u003c/em\u003e = 0.042). Additionally, the number of neutrophils in the PPCs group was greater than in the non-PPCs group (11.4 \u0026plusmn; 4.3 vs 9.9 \u0026plusmn; 4.1, \u003cem\u003eP\u003c/em\u003e = 0.048).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIncidence of PPCs\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePPCs occurred in 17.7% of patients. Respiratory infection (9.9%) was the most frequent complication, followed by respiratory failure (3.9%), ARDS (2.0%), pleural effusion (1.0%), pneumothorax (0.5%), and pulmonary embolism (0.5%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRisk Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll clinically significant covariates were included in a multi-variable logistic regression model (Table 2). Multivariate logistic regression revealed higher BMI (\u003cem\u003eOR\u003c/em\u003e 1.144, 95%\u003cem\u003e\u0026nbsp;CI\u003c/em\u003e: 1.048\u0026ndash;1.250, P = 0.003), lower SpO2, and higher SBP as independent risk factors. ROC curve analysis showed an AUC of 0.693 for BMI in predicting PPCs in Figure 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable1\u003c/strong\u003e Preoperative and intraoperative variables.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003ePPCs(n=36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003eNon-PPCs(n=167)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003evalue\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eAge, yr\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e49.8\u0026plusmn;11.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e52.2\u0026plusmn;12.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eMale sex, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e30(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e123(73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.221\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e30.9\u0026plusmn;6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e26.8\u0026plusmn;4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\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: 39.8946%;\"\u003e\n \u003cp\u003eSmoking, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e4(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e12(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eDiabetes, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e5(13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e9(5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.144\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eHypertension, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e31(86.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e129(77.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.382\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eHyperlipidemia,%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e7(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e20(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.354\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eRenal diseases ,%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e2(5.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e1(0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eCerebrovascular events, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e5(13.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e12（(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eCoronary heart disease, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e4(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e12(7.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePreoperative HR (bpm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e82.7\u0026plusmn;15.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e78.4\u0026plusmn;12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePreoperative SpO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e93.5\u0026plusmn;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e96.2\u0026plusmn;3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePreoperative SBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e132.5\u0026plusmn;22.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e124.4\u0026plusmn;19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePreoperative DBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e63.7\u0026plusmn;12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e63.9\u0026plusmn;13.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.932\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eOperation duration\u0026nbsp;(h)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e7.3\u0026plusmn;1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e6.6\u0026plusmn;1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eCPB duration (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e215.4\u0026plusmn;65.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e203.0\u0026plusmn;73.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eACC duration\u0026nbsp;(min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e149.3\u0026plusmn;51.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e140.3\u0026plusmn;53.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eDHCA duration (min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e19.9\u0026plusmn;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e20.0\u0026plusmn;6.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eBlood loss (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e772.2\u0026plusmn;167.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e739.6\u0026plusmn;143.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eTmin, ℃\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e25.9\u0026plusmn;1.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e26.0\u0026plusmn;1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eRed blood cell (mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e394.3\u0026plusmn;291.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e337.4\u0026plusmn;282.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePlatelet concentrates (unit)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e1.1\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e1.0\u0026plusmn;0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.677\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eHaemoglobin (g L -1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e34.5\u0026plusmn;19.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e132.4\u0026plusmn;16.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eWhite cell count (cells 109 L-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e13.0\u0026plusmn;4.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e11.8\u0026plusmn;4.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eNeutrophil count (cells 109 L -1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e11.4\u0026plusmn;4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e9.9\u0026plusmn;4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eMonocyte count (cells 109 L- 1)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.8\u0026plusmn;0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.908\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePlatelets (cells 109 L-1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e188.9\u0026plusmn;60.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e183.8\u0026plusmn;67.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.680\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e11.0\u0026plusmn;5.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e10.8\u0026plusmn;8.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.849\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003eMLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.7\u0026plusmn;0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.939\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 39.8946%;\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e182.7\u0026plusmn;68.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e184.9\u0026plusmn;104.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.0351%;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eACC = aortic cross clamping, BMI = body mass index, CPB = cardiopulmonary bypass, DBP = diastolic blood pressure, DHCA = deep hypothermic circulatory arrest, HR = heart rate, PPCs = postoperative pulmonary complications, SBP=systolic blood pressure, NLR= the neutrophil-lymphocyte ratio, MLR=the monocyte-lymphocyte ratio, PLR= the platelet-lymphocyte ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable2\u003c/strong\u003e\u0026nbsp; PPCs risk factors.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 332px;\"\u003e\n \u003cp\u003eMultivariable Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.144(1.048-1.250)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePreoperative SpO2\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.879(0.798-0.969)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003ePreoperative SBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.025(1.005-1.044)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eOperation duration (h)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.144(0.933-1.402)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 236px;\"\u003e\n \u003cp\u003eNeutrophil count (cells 109 L\u003csup\u003e\u0026nbsp;-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e1.028 (0.928-1.139)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.596\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion ","content":"\u003cp\u003ePPCs are common postoperative complications in ATAAD patients. It has been reported that the frequency of respiratory events following ATAAD is 24.24% in previous research, which is similar to the 17.7% incidence observed in our research[7]. In this cohort study of 203 patients \u0026nbsp;who underwent \u0026nbsp; TAR+FET for ATAAD, we found that BMI was correlated with PPCs. At present, the potential mechanism of PPCs after acute Stanford A dissection is still unclear. Thus, further understanding of the risk factors and mechanism of PPCs after acute Stanford type A dissection surgery is crucial to the design of preventative strategies. Among the numerous factors influencing postoperative outcomes, obesity has emerged as one of the more prominent indicators in recent years. A research has demonstrated that high preoperative bradykinin levels and increased BMI are independent predictors of severe postoperative hypoxaemia in patients with acute Stanford type A aortic dissection[8]. Body mass index was an independent predictor of acute kidney injury after urgent aortic total arch replacement surgery with a frozen elephant trunk implant[9].There exists a certain causal relationship between obesity and various perioperative indicators among surgical patients, often resulting in an unfavorable prognosis[10].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWith changes in lifestyle, the incidence of obesity gradually increases. This study shows that The incidence of obesity in ATAAD patients is relatively high (29.75%). This study also shows elevated BMI was a independent risk factor of PPCs after acute Stanford type A dissection surgery. Some Chinese scholars found that Obesity was independent risk factors for postoperative severe hypoxemia in patients with acute type A aortic dissection[11]. A study showed a higher body mass index may be closely correlated with prolonged intubation for patients undergoing aortic dissection surgery[12]. Another study showed that association was found for both PPCs and mortality in relation to increased BMI[13]. Obesity has many adverse effects on the body. Obesity is independent of cardiovascular disease Risk factors. Obesity patients are often accompanied by atherosclerosis and coronary artery disease heart disease, congestive heart failure, arrhythmia, cardiomyopathy, etc. The risk of cardiovascular accidents has significantly increased. Its mechanism and obesity patients often accompanied by hypertension, dyslipidemia, inflammatory response, and insulin Resistance and related obesity can lead to Type 2 diabetes, hypertension, kidney disease, obstructive sleep apnea syndrome.\u003c/p\u003e\n\u003cp\u003eThe relationship between obesity and increased pulmonary complications after dissection surgery is a complex, multifactorial process involving respiratory mechanics, lung function, inflammatory response, fluid management, and immune regulation. The increased weight of abdominal and thoracic adipose tissue exacerbates the compressive forces transmitted by the chest wall to the lung and exaggerates the cephalad displacement of the diaphragm. These produce a rightward shift of the respiratory system pressure\u0026ndash;volume curve, higher pleural pressure, lower respiratory system compliance and lower functional residual capacity (FRC) before and after induction of general anesthesia.The combined effect of compression of the dorso-caudal lung and the gas absorption in lung units exposed to small airway closure results in greater risk of perioperative pulmonary atelectasis in obese than nonobese patients[14, 15]. The adipose tissue of obese patients secretes a large amount of inflammatory factors (such as IL-6 and TNF-a), which have caused a chronic inflammatory state throughout the body before surgery [16, 17]. Obese patients had a higher level of NE and CRP, suggesting a more severe inflammatory response[18]. Many of the factors involved in the CPB create multiple inflammatory responses[19]. Due to the surgical trauma, the inflammatory response further intensifies after surgery, leading to increased pulmonary capillary permeability, causing pulmonary edema and acute respiratory distress syndrome (ARDS). Surgical dissection involves significant trauma and is prone to trigger systemic inflammatory response syndrome (SIRS). Obese patients have a more severe inflammatory response and a significantly increased risk of lung injury. Large amounts of blood transfusion and infusion are often required in total arch replacement combined with frozen elephant trunk implantation(TAR with FET). Inflammatory response leads to increased capillary permeability, fluid leakage into the interstitial and alveolar spaces of the lungs, further exacerbating pulmonary edema and hypoxemi. The inflammatory factors secreted by the adipose tissue of obese patients, such as IL-6 and TNF-a, suppress immune function and increase the risk of postoperative infection[20].\u003c/p\u003e\n\u003cp\u003eobesity may cause obstructive sleep apnea (OSA) and Obstructive sleep hypopnea (OSH)[21]. Increased fat deposition in the pharynx resulting in decreased patency of the pharynx increases the likelihood that relaxation of the upper airway muscles will cause collapse of the soft-walled oropharynx between the uvula and epiglottis[21]. Increased cervical adipose tissue leads to decreased upper respiratory tract patency.\u003c/p\u003e\n\u003cp\u003eFurthermore, obese patients are susceptible to PPCs after a prolonged surgical procedure due to the anesthetic drug accumulating in fat cells, which slows metabolism, resulting in delayed recovery of bodily functions.\u003c/p\u003e\n\u003cp\u003eThe study still has some limitations. First, as mentioned in the Methods, our study was based on the Chinese population, reducing the generalizability of the findings, and it is unclear whether it is applicable to other ethnicities. Second, our findings are derived from single-center observational data, and further multi-center studies and a high-quality meta-analysis should be carried out to provide more evidence. Simultaneously, limited by the sample size, we were unable to assess the interaction of stratified root procedure and concomitant surgery with multivariate adjustment, which will be addressed in our future studies. Finally, this study did not explore the effect of obesity degree and BMI on in-hospital mortality, as the Chinese criteria do not subdivide the obesity degree. The continuous grouping of BMI, linear or non-linear relationships, and optimal cutoff values for prediction were also not further explored, which may be addressed in our future studies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePPCs\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePostoperative Pulmonary Complications\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eATAAD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute Type A Aortic Dissection\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eBMI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBody Mass Index\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Interval\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eTAR\u0026thinsp;+\u0026thinsp;FET\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTotal Aortic Arch Replacement with Frozen Elephant Trunk\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCPB\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eCardiopulmonary Bypass\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eACC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAortic Cross Clamping\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSBP\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSystolic Blood Pressure DBP:Diastolic Blood Pressure\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eDHCA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eDeep Hypothermic Circulatory Arrest\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eHR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHeart Rate\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eNeutrophil-lymphocyte Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eMLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eMonocyte-lymphocyte Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003ePLR\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ePlatelet-lymphocyte Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eARDS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eAcute Respiratory Distress Syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eFRC\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eFunctional Residual Capacity\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eSIRS\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eSystemic Inflammatory Response Syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOSA\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eObstructive Sleep Apnea Syndrome\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eOSH\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eObstructive Sleep Hypopnea\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection was done by Hui Wang. \u0026nbsp;Conceptualization was done by Hui Wang and Yun-Tai Yao. Research, manuscript writing, Manuscript outline, data quality assessment and manuscript revision were done by Hui Wang and Chun Chen. The final manuscript was read and approved by all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Youth Teacher Training Program of Peking Union Medical College (2014) and CAMS Innovation Fund for Medical Sciences (CIFMS)-2021-I2M-C\u0026amp;T-B-038.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was approved by the Institutional Review Boards of Fuwai Hospital (2019-1301).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Anesthesiology, Yichang Central People\u0026rsquo;s Hospital, Yichang, Hubei, China. \u003csup\u003e2\u003c/sup\u003eDepartment of Anesthesiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China. \u003csup\u003e3\u003c/sup\u003eCenter of Outcomes Research, Department of Anesthesiology, Critical Care and Pain Medicine, University of Texas, Houston 77030, Texas, United States. \u003csup\u003e4\u003c/sup\u003eOutcomes research Consortium, Houston 77030, Texas, United States.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eJammer I, Wickboldt N, Sander M, et al. Standards for definitions and use of outcome measures for clinical effectiveness research in perioperative medicine: European Perioperative Clinical Outcome (EPCO) definitions: a statement from the ESA-ESICM joint taskforce on perioperative outcome measures. Eur J Anaesthesiol, 2015, 32(2): 88-105. doi:10.1097/EJA.0000000000000118\u003c/li\u003e\n\u003cli\u003eYan Y, Zhang X, Yao Y. Evidence in Cardiovascular Anesthesia (EICA) Group. Postoperative pulmonary complications in patients undergoing aortic surgery: A single-center retrospective study. Medicine (Baltimore), 2023, 102(39): e34668.\u003c/li\u003e\n\u003cli\u003eBai L, Ge L, Zhang Y, Li M, et al. Experience of the Postoperative Intensive Care Treatment of Stanford Type A Aortic Dissection. Int J Clin Pract. 2023, 2023: 4191277. Published 2023 Jan 10. \u003c/li\u003e\n\u003cli\u003eKim MS, Kim WJ, Khera AV, et al. Association between adiposity and cardiovascular outcomes: an umbrella review and meta-analysis of observational and Mendelian randomization studies. Eur Heart J, 2021, 42(34): 3388-3403.\u003c/li\u003e\n\u003cli\u003ePan X, Xing Z, Yang G, Ding N, Zhou Y, Chai X. Obesity Increases In-Hospital Mortality of Acute Type A Aortic Dissection Patients Undergoing Open Surgical Repair: A Retrospective Study in the Chinese Population. Front Cardiovasc Med, 2022, 9:899050.\u003c/li\u003e\n\u003cli\u003eAbbott TEF, Fowler AJ, Pelosi P, et al. A systematic review and consensus definitions for standardised end-points in perioperative medicine: pulmonary complications. Br J Anaesth，2018, 120(5): 1066-1079.\u003c/li\u003e\n\u003cli\u003eLiu G, Wang H, Luo Q, et al. Low postoperative blood platelet count may be a risk factor for 3-year mortality in patients with acute type A aortic dissection. J Cardiothorac Surg, 2021, 16(1): 274. \u003c/li\u003e\n\u003cli\u003eGuan X, Li L, Li J, et al. High preoperative bradykinin level is a risk factor for severe postoperative hypoxaemia in acute aortic dissection surgery. Exp Physiol, 2023, 108(5): 683-691.\u003c/li\u003e\n\u003cli\u003eLiu T, Fu Y, Liu J, et al. Body mass index is an independent predictor of acute kidney injury after urgent aortic arch surgery for acute DeBakey Type I aortic dissection. J Cardiothorac Surg, 2021, 16(1): 145. \u003c/li\u003e\n\u003cli\u003eGuan X, Li L, Li J, et al. High preoperative bradykinin level is a risk factor for severe postoperative hypoxaemia in acute aortic dissection surgery. Exp Physiol, 2023, 108(5): 683-691. \u003c/li\u003e\n\u003cli\u003eGong M, Wu Z, Xu S, et al. Increased risk for the development of postoperative severe hypoxemia in obese women with acute type a aortic dissection. J Cardiothorac Surg, 2019, 14(1): 81. \u003c/li\u003e\n\u003cli\u003eLi Y, Jiang H, Xu H, et al. Impact of a Higher Body Mass Index on Prolonged Intubation in Patients Undergoing Surgery for Acute Thoracic Aortic Dissection. Heart Lung Circ, 2020, 29: 1725-1732. \u003c/li\u003e\n\u003cli\u003eCovarrubias J, Grigorian A, Schubl S, et al. Obesity associated with increased postoperative pulmonary complications and mortality after trauma laparotomy. Eur J Trauma Emerg Surg, 2021, 47(5): 1561-1568.\u003c/li\u003e\n\u003cli\u003eLagier D, Zeng C, Fernandez-Bustamante A, Vidal Melo MF. Perioperative Pulmonary Atelectasis: Part II. Clinical Implications. Anesthesiology, 2022,1 36(1): 206-236.\u003c/li\u003e\n\u003cli\u003eCovarrubias J, Grigorian A, Schubl S, et al. Obesity associated with increased postoperative pulmonary complications and mortality after trauma laparotomy. Eur J Trauma Emerg Surg, 2021, 47(5): 1561-1568.\u003c/li\u003e\n\u003cli\u003eEllulu MS, Patimah I, Khaza\u0026apos;ai H, Rahmat A, Abed Y. Obesity and inflammation: the linking mechanism and the complications. Arch Med Sci, 2017, 13(4): 851-863.\u003c/li\u003e\n\u003cli\u003eBoutari C, Hill MA, Procaccini C, et al. The key role of inflammation in the pathogenesis and management of obesity and CVD. Metabolism, 2023, 145: 155627.\u003c/li\u003e\n\u003cli\u003eZhang C, Shi R, Zhang G, et al. The association between body mass index and risk of preoperative oxygenation impairment in patients with the acute aortic syndrome. Front Endocrinol (Lausanne),2022, 13: 1018369.\u003c/li\u003e\n\u003cli\u003eNteliopoulos G, Nikolakopoulou Z, Chow BHN,et al. Lung injury following cardiopulmonary bypass: a clinical update. Expert Rev Cardiovasc Ther. 2022, 20(11): 871-880.\u003c/li\u003e\n\u003cli\u003eMărginean CO, Meliţ LE, Huțanu A, et al. The adipokines and inflammatory status in the era of pediatric obesity. Cytokine, 2020, 126: 154925.\u003c/li\u003e\n\u003cli\u003eBenumof JL. Obesity, sleep apnea, the airway and anesthesia. Curr Opin Anaesthesiol, 2004, 17(1): 21-30.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Aortic arch surgery, body mass index, postoperative pulmonary complications, aortic dissection, frozen elephant trunk","lastPublishedDoi":"10.21203/rs.3.rs-7240021/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7240021/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e Postoperative pulmonary complications (PPCs) are common following total aortic arch replacement with frozen elephant trunk (TAR\u0026thinsp;+\u0026thinsp;FET) in patients with acute type A aortic dissection (ATAAD). This study aimed to evaluate the incidence and risk factors for PPCs in ATAAD patients undergoing TAR\u0026thinsp;+\u0026thinsp;FET.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e This single-center retrospective study included 203 patients with ATAAD who underwent TAR\u0026thinsp;+\u0026thinsp;FET between January 2023 and August 2024. Patients were divided into PPC and non-PPC groups. The incidence and types of PPCs were recorded, and risk factors were analyzed using multivariate logistic regression. Postoperative outcomes were compared between groups.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e The incidence of PPCs was 17.7%, with respiratory infections being the most common (9.9%), followed by respiratory failure (3.9%), acute respiratory distress syndrome (2.0%), pleural effusion (1.0%), pneumothorax (0.5%), and pulmonary embolism (0.5%). Multivariate analysis identified body mass index (BMI) as an independent risk factor for PPCs [odds ratio (OR): 1.144; 95% confidence interval (CI): 1.048\u0026ndash;1.250; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003].\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusions\u003c/b\u003e Higher BMI is independently associated with an increased risk of PPCs following TAR\u0026thinsp;+\u0026thinsp;FET in ATAAD patients. These findings highlight the importance of preoperative BMI assessment in optimizing perioperative management.\u003c/p\u003e","manuscriptTitle":"The Impact of Obesity on Postoperative Pulmonary Complications in Patients Undergoing Aortic Surgery","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-09 09:52:31","doi":"10.21203/rs.3.rs-7240021/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":"ee84455b-8998-4cce-a852-fa2513d27634","owner":[],"postedDate":"September 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-26T05:25:13+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-09 09:52:31","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7240021","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7240021","identity":"rs-7240021","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}