Preoperative Transthoracic Echocardiography in Laparoscopic Colorectal Surgery: Impact on Postoperative Cardiac Outcomes

Preoperative Transthoracic Echocardiography in Laparoscopic Colorectal Surgery: Impact on Postoperative Cardiac Outcomes | 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 Preoperative Transthoracic Echocardiography in Laparoscopic Colorectal Surgery: Impact on Postoperative Cardiac Outcomes Yuanming Liu, Ting Yan, Liangcheng Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5653634/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 Objective: This study aimed to assess the clinical utility of preoperative transthoracic echocardiography (TTE) in predicting postoperative major adverse cardiac events (MACEs) in patients undergoing laparoscopic colorectal surgery. Methods: A retrospective cohort study was conducted involving 1049 patients who underwent laparoscopic colorectal surgery between January 1st, 2018, and December 31st, 2018. Among these, 967 patients completed preoperative TTE, while 82 did not. Data collection encompassed basic patient information, medical history, ASA classification, and surgical details. The primary outcome was the occurrence of postoperative MACEs, which were defined based on myocardial enzyme levels, ECG results, and clinical events. Results: A total of 44 MACEs were identified, with congestive heart failure and new arrhythmias being the most prevalent. Univariate and multivariate regression analyses revealed that interventricular septal thickening (IVST) and left ventricular hypertrophy (LVH) were independent risk factors for MACEs, whereas the overall presence of TTE abnormalities was not significantly associated with postoperative MACEs. The study also highlighted that postoperative MACEs were significantly associated with increased hospitalization days and costs. Conclusion: Preoperative TTE abnormalities, specifically IVST and LVH, were found to be independent risk factors for postoperative MACEs. However, the routine use of TTE as a predictive tool for MACEs in this patient population may not be warranted based on the overall findings. laparoscopic colorectal surgery transthoracic echocardiography preoperative assessment postoperative major adverse cardiac events Figures Figure 1 Introduction Echocardiography is pivotal in assessing and managing cardiac conditions, providing critical morphological and physiological insights into the myocardium, valves, pericardium, coronary arteries, and great vessels. It is particularly valuable in evaluating cardiac function, detecting conditions like cardiac tamponade, and assessing perioperative risks in non-cardiac surgery patients, where cardiovascular events are the leading cause of mortality[ 1 ]. Transthoracic echocardiography (TTE), a non-invasive tool, is increasingly used by anesthesiologists for preoperative cardiac evaluation[ 2 , 3 ]. Despite low anesthesia-related mortality, cardiac complications occur in 2.0-3.5% of patients, contributing to one-third of postoperative deaths (0.5–1.5%)[ 4 ]. The American Heart Association emphasizes the importance of preoperative cardiac evaluation in managing cardiac conditions and improving outcomes[ 5 ]. Key risk factors for adverse cardiac outcomes include left ventricular dysfunction, ischemic heart disease, aortic stenosis, and pulmonary hypertension. However, clinical evaluation alone is often unreliable, necessitating TTE for accurate diagnosis[ 6 ]. While TTE is recommended before elective non-cardiac surgery, its indiscriminate use raises concerns due to its high cost, accounting for 11% of medical insurance fees, or over $ 1.1 billion[ 7 ]. The 2011 Appropriate Use Criteria (AUC) for TTE revealed that while 91.8% of uses were appropriate, 4.3% were inappropriate, and 3.9% uncertain, with no significant difference in medical management outcomes[ 8 ]. This underscores the need for judicious use of TTE. Preoperative echocardiography has been associated with longer pre-surgery waiting times and higher costs, estimated at $ 47 million annually[ 9 ]. Although routine TTE may optimize medical plans and reduce surgical delays, balancing early surgery with thorough pre-anesthesia evaluation remains challenging[ 10 ]. The role of preoperative TTE in risk stratification for non-cardiac surgeries is unclear, particularly in elderly patients with high comorbidity and financial constraints, where reducing unnecessary tests is essential[ 11 ]. Anesthesiologists must balance rapid preoperative assessments with patient safety and hospital efficiency. Current evidence suggests TTE's role in preoperative risk assessment is limited, as a large retrospective cohort study found no association between preoperative echocardiography and improved survival or reduced hospital stays[ 12 ]. This study aims to analyze the clinical value of preoperative TTE in elective laparoscopic colorectal surgery to promote cost-effective medical resource utilization. 1. Materials and Methods 1.1 General Information This retrospective study included patients who underwent laparoscopic colorectal surgery at our hospital from January 1st 2018 to December 31st 2018. These data were accessed for study purposes from July 1st 2019 to July 15th 2019. The inclusion criteria were patients aged > 18 years, while the exclusion criteria were patients with poor-quality echocardiographic images. This study followed the Declaration of Helsinki and received approval from the hospital’s ethics committee(201704342). Since this was a retrospective study, all data were fully anonymized, and the ethics committee waived the requirement for informed consent. Clinical information, including each patient’s basic information (gender, age, BMI etc), medical history, ASA classification, and surgery type, was obtained by carefully reviewing their medical records. Surgical risk assessment was based on surgical type and related risk factors in accordance with the ESC/ESA guidelines for non-cardiac surgeries. All cardiac-related adverse events occurring within 30 days postoperatively were recorded for all patients included in the study. If a patient’s electrocardiogram(ECG) exhibited at least one of the following conditions, he or she was considered to have abnormal ECG findings: sinus bradycardia (heart rate < 50 beats per minute), arrhythmias (supraventricular tachycardia, atrial fibrillation/flutter, pacing, or ventricular rhythm), premature beats, atrioventricular blocks (Mobitz II second degree or third degree), left or right bundle branch block, ventricular hypertrophy, ischemic Q waves/ST-segment/T-wave changes, or abnormal QT interval. 1.2 Echocardiographic Parameters This study used the Philips iE33 color Doppler ultrasound diagnostic device, equipped with an S5-1 adult cardiac transducer and an S7-2 multiplane transesophageal transducer, with frequencies of 2–5 MHz and 2–7 MHz, respectively. The device has the functions of two-dimensional echocardiography (2DE), color Doppler flow imaging (CDFI), pulse Doppler, and continuous Doppler. Before laparoscopic colorectal surgery, all patients were examined in the left lateral decubitus position by a trained echocardiography specialist using a 3.5 MHz transducer (Vivid-E9, GE Healthcare, Horten, Norway, or iE-33, Philips, Netherlands). Measurements of left ventricular mass index (LVMI), left ventricular ejection fraction (LVEF), and left atrial volume index (LAVI) were conducted according to ASE recommendations. Left ventricular hypertrophy (LVH) was defined as an LVMI > 115 g/m² for men and > 95 g/m² for women. LAVI was calculated using the formula (A1*A2/l)*8/3π, where l is the average LA length in both four-chamber and two-chamber views. Mitral valve blood flow measurements included early (E) and late (A) peak velocities and the E/A ratio. Pulse velocities of tissue Doppler imaging, including systolic (s') and early diastolic (e') peak velocities, were obtained at the interventricular septum and the lateral mitral annulus. The ratio of mitral annulus early diastolic flow velocity (E/e') was calculated using the average of septal and lateral e' values (average E/e' = E/[ (septal e' + lateral e') /2 ]). In the E/A ratio, the E peak occurs during the rapid filling phase of the left ventricle, reflecting the early diastolic LA-LV pressure gradient; the A peak occurs in late diastole, reflecting the late diastolic LA-LV pressure gradient. The average E peak flow velocity was 73 cm/s, the average A peak flow velocity was 40 cm/s, and the E/A ratio was 1.26 ± 0.32 (range 1-1.5). E-wave deceleration time (EDT) was influenced by left ventricular relaxation, left ventricular diastolic pressure after mitral valve opening, and left ventricular compliance. EDT ranged from 160 to 240 ms [(197 ± 27) ms]. Two-dimensional grayscale images were obtained in three standard views: apical two-chamber, apical four-chamber, and apical long-axis. All images were continuously collected over three cardiac cycles and digitally stored at a rate of 50–90 frames per second for offline analysis. 1.3 TTE major abnormalities All TTE examinations and reports were completed by specialists in cardiology. TTE findings were considered abnormal if any indicator exceeded the normal range [ 13 ]. Clinically significant abnormalities were defined as (1) LVEF < 45%; (2) regional wall motion abnormalities involving at least two segments; (3) grade III diastolic dysfunction; (4) right ventricular (RV) dysfunction; (5) RV enlargement; (6) the presence of intracardiac shunt; (7) presence of cardiac implant or cardiac mass; (8) moderate or greater valvular regurgitation; (9) aortic stenosis with an aortic valve area right atrial pressure > above 40 mm Hg; (11) aortic dilation; (12) aortic coarctation; (13) moderate or larger pericardial effusion; (14) the presence of pericardial disease; (15) significant valvular heart disease was defined as at least moderate valvular disease; (16) Interventricular septal thickness with > 11 mm indicating septal thickening. 1.4 Postoperative Major Adverse Cardiac Events Major adverse cardiac events (MACEs) are primarily defined by myocardial enzyme levels, ECG results, and clinical events [ 6 ]. MACEs include acute coronary syndromes, congestive heart failure, newly developed severe arrhythmias, non-fatal cardiac arrest, and cardiac death. A. Acute coronary syndromes include acute myocardial infarction and unstable angina. The diagnosis of acute myocardial infarction requires elevated creatine kinase-MB (CK-MB) levels (> 0.83 umol/L/s, equivalent to 50U/L) along with at least one of the following criteria: formation of new Q waves (as defined by the Minnesota Code 1.1 or 1.2), persistent ST-T changes, imaging evidence of myocardial motion abnormalities, angiographic abnormalities, or autopsy confirmation of an acute infarction. Unstable angina is defined as severe chest pain in the precordial area, unrelated to the surgical incision, lasting for no less than 30 minutes, with negative cardiac troponin I, unresponsive to standard treatment (rest and nitroglycerin), accompanied by transient ST-segment and T-wave changes, without Q-wave formation or enzyme elevation. B. Congestive heart failure diagnosis requires a. symptoms or signs of pulmonary edema (dyspnea, orthopnea); b. new signs of left or right ventricular failure (cardiomegaly, lung rales, engorgement of the jugular veins and/or positive hepatojugular reflux, peripheral edema); c. diagnostic findings of pulmonary hypertension or right ventricular overload (pulmonary capillary wedge pressure ≥ 18 mmHg, central venous pressure ≥ 12 mmHg) and Nt-proBNP levels: for patients under 50 years old, levels > 450 pg/ml suggest possible heart failure; for patients aged 50 to 75 years, levels > 900 pg/ml suggest possible heart failure; for patients over 75 years old, levels > 1800 pg/ml suggest possible heart failure; d. cTnI: 0-0.029, with values more than twice the normal range considered significant. C. Newly developed severe arrhythmias refer to postoperative arrhythmias requiring intervention with drugs or electrical cardioversion/defibrillation and include sustained and rapid atrial flutter and fibrillation, Type II or higher atrioventricular block, ventricular tachycardia (defined as a rate of ≥ 100 beats/min with at least five consecutive ventricular ectopic beats on continuous two-lead Holter monitoring), and ventricular fibrillation. 1.5 Follow-Up All patients included were followed for 30 days postoperatively. Previous studies on MACEs after non-cardiac surgeries have shown that most of these events occur within the first month after surgery [ 14 ]. Throughout the follow-up period, patients’ medical records were carefully reviewed. The primary endpoint was the occurrence of a postoperative MACE defined as cardiovascular death, acute coronary syndromes, hospitalization for heart failure, or ventricular tachycardia. The diagnoses of acute coronary syndrome and ventricular tachycardia were confirmed by cardiology specialists. There was no loss-to-up patient in this study, as all medical records were well documented. 1.6 Statistical Analysis All statistical analyses were performed using SPSS 27.0. Continuous data were presented as mean ± standard deviation or median (interquartile range). Categorical data were presented as numbers and percentages. Between-group comparisons of normally or non-normally distributed continuous variables were performed using the t-test or Mann-Whitney U-test, respectively. Categorical variables were compared between groups using the chi-square test or Fisher’s exact test. A two-sided p-value less than 0.05 was considered statistically significant. Risk factors other than TTE-related ones were first identified using univariate analysis. Variables with a p-value smaller than 0.10 according to the univariate analysis were included in the multivariate logistic regression model to assess the effects of the overall preoperative TTE abnormalities and the variables with statistical significance in the univariate analysis on the outcome indicators. Second, each major TTE abnormality and the statistically significant variables in the univariate analysis were included in the multivariate logistic regression model to observe the effects of the above risk factors on the outcome indicators. This approach allowed for a comprehensive assessment of the impact of various factors on the occurrence of postoperative MACEs. 2 Results 2.1 Patient Basic Information This study included 1,049 patients who underwent laparoscopic colorectal surgery at our hospital between January 2018 to December 2018. Among them, 967 patients completed preoperative TTE, while 82 patients did not. The patients in the TTE and non-TTE groups were comparable in terms of gender, age, body mass index (BMI), previous hypertension, previous ischemic heart disease, previous cerebrovascular disease, previous diabetes, ASA Classification, serum level of Hemoglobin (Hb), albumin (ALB), Creatinine clearance rate (Ccr), hospitalization days and hospitalization expenses with no statistically significant differences between these two groups (Supplement Information Table 1 ). In addition, all surgeries were performed within the specified time window. Only one patient experienced a prolonged waiting time for surgery, while three patients had minor delays; the remaining patients underwent elective surgery as scheduled. Table 1 Analysis of factors associated with postoperative MACEs With MACEs Without MACEs χ 2 /t P-value Gender Male 27 640 Female 17 365 0.191 0.754 Age( years) 66.16 ± 13.693 58.87 ± 11.604 8.854 0.000 BMI 23.00 ± 3.206 22.99 ± 3.437 0.132 0.763 Previous hypertension No 28 752 Yes 16 253 3.543 0.096 Previous ischemic heart disease No 37 984 Yes 7 18 9.784 0.000 Previous cerebrovascular disease No 39 988 Yes 5 17 7.547 0.000 Previous diabetes No 38 889 Yes 6 116 0.323 0.671 ASA classification 1 1 96 2 34 836 3 9 73 4.536 0.003 Hb (g/L) 125.05 ± 23.100 130.27 ± 20.678 1.242 0.132 ALB (g/L) 40.232 ± 4.309 41.750 ± 4.045 3.764 0.012 Ccr (mL/min) 74.68 ± 15.40 72.85 ± 23.022 0.879 0.239 Normal ECG No 28 481 Yes 15 524 3.463 0.027 Hospitalization days 31.89 ± 15.997 22.43 ± 9.282 9.568 0.000 Hospitalization expenses (RMB, in thousands) 42.58 ± 4.67 33.65 ± 2.31 13.889 0.000 2.2 Prevalence of TTE Abnormalities Among the 967 patients who underwent TTE, the overall incidence of TTE abnormalities was 67.3% (664/967). The three most common abnormalities were left ventricular diastolic dysfunction (27%), mild tricuspid regurgitation (24%), and left atrial enlargement (17%) (Fig. 1 ). 2.3 Independent Risk Factors for Postoperative MACEs The multivariate regression analysis showed that interventricular septal thickening (IVST, OR = 0.152, 95% CI 0.030–0.768, P = 0.023) and left ventricular hypertrophy (LVH, OR = 5.477, 95% CI 1.196–25.082, P = 0.028) were independent risk factors for postoperative MACEs (Table 1 ). However, ROC curve analysis revealed that the area under the curve was 0.497 for IVST and 0.536 for LVH, indicating a relatively low predictive value. Table 1 Association between the abnormality of each indicator and postoperative MACEs B SE Wals df P LVDD 0.558 0.442 1.591 1 0.207 MTR 0.536 0.443 1.467 1 0.226 LAE -0.083 0.541 0.023 1 0.879 MAR -0.592 0.589 1.011 1 0.315 IVST -1.883 0.826 5.195 1 0.023 LVH 1.701 0.776 4.799 1 0.028 AAD 0.295 0.531 0.310 1 0.578 MMR -0.251 0.618 0.615 1 0.685 AS -0.012 0.603 0.000 1 0.984 In our study, a total of 1049 patients who underwent laparoscopic colorectal surgery were analyzed for factors associated with postoperative major adverse cardiac events (MACEs). The results showed that factors significantly associated with the occurrence of MACEs included age (P = 0.000), history of ischemic heart disease (P = 0.000), history of cerebrovascular disease (P = 0.000), ASA classification (P = 0.003), albumin (ALB) levels (P = 0.012), electrocardiogram (ECG) status (P = 0.027), hospitalization days (P = 0.000), and hospitalization costs (P = 0.000). Additionally, gender (P = 0.754), body mass index (BMI) (P = 0.763), history of hypertension (P = 0.096), history of diabetes (P = 0.671), hemoglobin (Hb) levels (P = 0.132), and creatinine clearance rate (Ccr) (P = 0.239) were not significantly associated with the occurrence of MACEs. (Table 2 )These findings emphasize the importance of identifying high-risk patients in preoperative assessments and may aid in guiding clinical decision-making and the development of preventive strategies. Table 2 Analysis of factors associated with postoperative MACEs With MACEs Without MACEs χ 2 /t P-value Gender Male 27 640 Female 17 365 0.191 0.754 Age( years) 66.16 ± 13.693 58.87 ± 11.604 8.854 0.000 BMI 23.00 ± 3.206 22.99 ± 3.437 0.132 0.763 Previous hypertension No 28 752 Yes 16 253 3.543 0.096 Previous ischemic heart disease No 37 984 Yes 7 18 9.784 0.000 Previous cerebrovascular disease No 39 988 Yes 5 17 7.547 0.000 Previous diabetes No 38 889 Yes 6 116 0.323 0.671 ASA classification 1 1 96 2 34 836 3 9 73 4.536 0.003 Hb (g/L) 125.05 ± 23.100 130.27 ± 20.678 1.242 0.132 ALB (g/L) 40.232 ± 4.309 41.750 ± 4.045 3.764 0.012 Ccr (mL/min) 74.68 ± 15.40 72.85 ± 23.022 0.879 0.239 Normal ECG No 28 481 Yes 15 524 3.463 0.027 Hospitalization days 31.89 ± 15.997 22.43 ± 9.282 9.568 0.000 Hospitalization expenses (RMB, in thousands) 42.58 ± 4.67 33.65 ± 2.31 13.889 0.000 2.4 The association between preoperative TTE abnormalities for postoperative MACEs The multivariate regression analysis including overall TTE abnormalities and other risk factors identified from univariate analysis revealed that among the 10 factors, hospitalization days (OR = 1.061, 95% CI 1.032–1.090, P = 0.000), hospitalization expensesand (OR = 1.043, 95% CI 1.023–1.083, P = 0.003) and previous ischemic heart disease (OR = 7.378, 95% CI 2.105–25.864, P = 0.02) were statistically significant predictors for postoperative MACEs, whereas overall TTE abnormalities were not significantly associated with postoperative MACEs (OR = 0.80, 95% CI 0.318–2.030, P = 0.644) (Table 3 ). Table 3 Association between overall preoperative TTE abnormalities and postoperative MACEs B SE Wals df P Age, years 0.027 0.019 2.110 1 0.146 Hospitalization days 0.061 0.012 25.515 1 0.000 Hospitalization expenses 0.066 0.013 17.739 1 0.003 ASA classification 0.070 0.438 0.026 1 0.873 Previous Hypertension 0.037 0.383 0.009 1 0.923 Previous ischemic heart disease 1.639 0.590 7.723 1 0.005 Previous cerebrovascular disease 0.612 0.700 0.765 1 0.382 ALB -0.048 0.041 1.380 1 0.240 Normal ECG -0.132 0.368 0.129 1 0.719 Overall TTE abnormalities -0.218 0.473 0.214 1 0.644 Discussion The primary objective of preoperative evaluation is to assess the risk of perioperative complications, optimize patients' preoperative conditions, and mitigate surgery- or anesthesia-related morbidity and mortality. This process aims to expedite recovery to an ideal state with consideration for healthcare cost efficiency [ 15 ]. Preoperative risk assessment and optimization rely on previous treatment data and health status to provide a baseline for evaluation [ 16 ]. Consultation is a common method used in preoperative evaluation. If additional examinations prompt changes in anesthetic management or necessitate other interventions, postoperative outcomes may be influenced. Conversely, if preoperative management or anesthetic plans remain unchanged, further evaluations may lead to unnecessary and potentially harmful testing, as well as delays in surgery [ 17 ]. Our findings indicate that among preoperative TTE abnormalities, IVST and LVH are independent risk factors for postoperative MACEs, aligning with other studies' findings [ 18 ]. In the TTE group, the overall incidence of TTE abnormalities was 67.3% (664/967), with IVST occurring in 13% and LVH in 12%, which is comparable to other studies' reports (12.7–17.9%) [ 19 ]. IVST and LVH typically suggest a high left ventricular workload, serving as a compensatory mechanism for hypertension [ 20 ]. Studies have linked moderate to severe LVH with postoperative MACE [ 14 ]. Possible reasons include myocardial fibrosis, interstitial cell proliferation, and capillary rarefaction associated with LVH and IVH, which may precipitate ischemic processes leading to myocardial ischemia [ 21 ] and pathological LVH due to interstitial and compensatory fibrosis, leading to progressive left ventricular diastolic dysfunction and heart failure [ 22 ]. Other research has identified preoperative diastolic dysfunction as an independent risk factor for postoperative mortality and MACE [ 23 ]. In our study, left ventricular diastolic dysfunction was the most prevalent TTE abnormality but was not significantly correlated with postoperative MACE. LVH, however, is associated with a reduced phosphocreatine/adenosine triphosphate ratio (PCr/ATP), indicating impaired myocardial energy metabolism, potentially leading to heart failure [ 24 ]. Furthermore, patients with LVH are more susceptible to transmural myocardial repolarization and refractory period dispersion across the ventricular wall, resulting in prolonged action potential duration and an increased risk of arrhythmias [ 25 ]. However, in this study, we found no statistically significant difference in the outcome of interest, major postoperative cardiac events (MACEs), between patients who completed TTE and those who did not, similar to other related studies [ 17 , 18 ]. An increasing number of surgeons and anesthesiologists frequently request preoperative echocardiography to assess cardiac function, particularly LVEF, a key indicator of left ventricular systolic function. A prospective study focusing on 339 males who underwent non-cardiac surgery, all with known or suspected coronary artery disease, revealed that an LVEF lower than 40% was correlated with all postoperative ischemic cardiac events. Multivariate analysis suggested that an LVEF below 40% remained a significant predictor after adjusting for known clinical risk factors [ 13 ]. Relevant studies have also reported a significantly positive correlation between impaired left ventricular systolic function and perioperative complications, suggesting that preoperative assessment of left ventricular systolic function may help predict perioperative outcomes and long-term mortality in non-cardiac surgery patients, especially those undergoing high-risk surgery [ 26 , 27 ]. However, some studies have shown no significant correlation between LVEF and postoperative MACEs [ 28 , 29 ], and LVEF only suggested the possibility of left ventricular dysfunction after surgery [ 30 ]. A prospective cohort study identified six independent predictors for postoperative cardiac complications in non-cardiac surgery patients: high-risk surgery type, history of ischemic heart disease, history of congestive heart failure, history of cerebrovascular disease, preoperative insulin treatment, and preoperative serum creatinine (Cr) > 2.0 mg/dL [ 31 ]. Cr > 2 has been proven the most significant clinical variable associated with MACEs, and a univariate analysis conducted has indicated a significant correlation between both coronary artery disease (CAD) and heart failure (HF) included in the Lee index and MACEs [ 26 ]. Preoperative advanced chronic kidney disease (CKD) has been reported as an independent predictor of an increased incidence of perioperative MACEs (myocardial infarction, stroke, or heart failure), mortality, and healthcare costs [ 32 ]. However, our study found no relationship between renal function, LVEF, and postoperative MACE. This could be due to the small number of cases with reduced LVEF, and renal function assessment was limited to serum creatinine levels. More renal function indicators are needed to further evaluate their impact on postoperative MACEs. Evidence has demonstrated TTE's ability to improve clinical evaluation and alter major treatment plans in approximately 50% of cases across various medical settings, including intensive care units (ICU), emergency departments, and perioperative settings at risk of sustained hemodynamic instability, as well as the outpatient preoperative stage [ 33 ]. In one prospective observational study, 100 patients scheduled for non-cardiac surgery underwent preoperative TTE, which confirmed moderate to severe ventricular or valvular dysfunction in 36% of high-risk patients and 10% of low-risk patients (who accounted for 32% of the total), leading to a change in treatment plans in 54% of cases [ 34 ]. TTE affects decisions regarding whether to proceed with or delay surgery, leads to changes in the type of anesthesia (local or general), and increases the use of invasive hemodynamic monitoring and treatment and postoperative high-dependency care. For anesthesiologists, clinically significant hemodynamic or valvular abnormalities detected by TTE alert them to the potential increase in cardiac risk, requiring enhanced medical care; on the other hand, normal or clinically insignificant TTE findings provide reassurance, reducing the need for further investigations, invasive monitoring, and high-dependency postoperative care. These findings support the feasibility of routine TTE screening as an aid in determining a patient's suitability for surgery and planning anesthesia and postoperative care to reduce adverse outcomes. However, the study did not assess TTE's effects on postoperative outcomes. Our study filled this gap and found that TTE abnormalities had low predictive value for postoperative MACEs and were not able to serve as independent risk factors. Patients often undergo preoperative TTE due to coexisting conditions, such as coronary artery disease, hypertension, cerebrovascular disease, and arrhythmias, which are the true independent risk factors for postoperative MACEs [ 17 ]. Meanwhile, common TTE abnormalities such as left ventricular diastolic dysfunction, mild tricuspid regurgitation, and left atrial enlargement were not significantly associated with surgical outcomes. Conclusion In conclusion, our study suggests that overall preoperative TTE abnormalities do not have significant predictive value for postoperative MACEs. However, preoperative findings of interventricular septal thickening and left ventricular hypertrophy are independent risk factors for MACEs. Additionally, postoperative MACEs significantly increase patient hospitalization time and costs. To address the unresolved debate over routine preoperative TTE, large-sample, multicenter studies are needed. Shortcomings Admittedly, our study has some limitations. First, our study only includes patients who underwent laparoscopic colorectal surgery in our hospital in 2018, introducing potential selection bias. As a result, it may not fully represent the broader population undergoing non-cardiac surgery from other hospitals. Second, the retrospective nature of the study inevitably leads to some inaccurate data, since there was no blinding or quality control during the data collecting process. Third, the outcome indicator—MACEs—was treated as a dichotomous outcome, leading to the failure to further analyze the association between some risk factors and certain individual adverse cardiac events. Lastly, the sample size was relatively small, and the study design needs to be improved as it did not consider factors like surgical type, duration, and urgency. Declarations Ethics Approval and Consent to Participate The study was approved by the Ethics Committee of the Fujian Longyan Second Hospital, with the approval number[201704342]. It was conducted in compliance with the ethical standards of the committee and the Declaration of Helsinki. Informed consent was obtained from all participants involved in the study. The consent procedure was reviewed and approved by the Ethics Committee, ensuring participants were fully informed about the study's objectives, methods, risks, and benefits before consenting. Written consent was provided by participants or their legal guardians. Consent for Publication Written informed consent for publication of clinical details and/or clinical images was obtained from all patients or participants involved in the study. This consent explicitly includes the use of their data for scientific publication purposes. A copy of the consent form is available for review by the editorial board of this journal. All personal identifiers have been removed or anonymized in order to protect the privacy of the individuals involved. The consent obtained ensures that the publication does not infringe on the rights of the participants, and the data presented are in compliance with the ethical standards for publication in medical journals. All data generated or analysed during this study are included in this published article and its supplementary information files. All data generated or analysed during this study are included in this published article and its supplementary information files. Data availability The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. Competing Interests Statements The Authors declare no Competing Financial or Non-Financial Interests. No Fundings Authors' Contributions Liu Yuanming: Conducted the experiments, collected and analyzed the data, and contributed to the writing of the manuscript.Yan Ting: Participated in the study design, interpreted the results, and provided critical revisions to the manuscript.Zhang Liangcheng: Principal investigator of the study, conceived the study, secured funding, and provided final approval of the version to be published.All authors have read and approved the final manuscript. References Perez J V, Warwick D J, Case C P, et al. Death after proximal femoral fracture--an autopsy study[J]. Injury, 1995, 26(4): 237-40. Poldermans D, Bax J J, Boersma E, et al. Guidelines for pre-operative cardiac risk assessment and perioperative cardiac management in non-cardiac surgery[J]. Eur Heart J, 2009, 30(22): 2769-812. Poldermans D, Bax J J, Boersma E, et al. 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Beyond type 2 diabetes, obesity and hypertension: an axis including sleep apnea, left ventricular hypertrophy, endothelial dysfunction, and aortic stiffness among Mexican Americans in Starr County, Texas[J]. Cardiovasc Diabetol, 2016, 15: 86. Kosiolova N A, Shatunova I M. Clinical Value of Left Ventricular Hypertrophy in Arterial Hypertension[J]. Kardiologiia, 2015, 55(8): 62-7. Stanton T, Dunn F G. Hypertension, Left Ventricular Hypertrophy, and Myocardial Ischemia[J]. Medical Clinics of North America, 2017, 101(1): 29-41. Lazzeroni D, Rimoldi O, Camici P G. From Left Ventricular Hypertrophy to Dysfunction and Failure[J]. Circ J, 2016, 80(3): 555-64. Kaw R, Hernandez A V, Pasupuleti V, et al. Effect of diastolic dysfunction on postoperative outcomes after cardiovascular surgery: A systematic review and meta-analysis[J]. J Thorac Cardiovasc Surg, 2016, 152(4): 1142-53. Jameel M N, Zhang J. Myocardial energetics in left ventricular hypertrophy[J]. Curr Cardiol Rev, 2009, 5(3): 243-50. Gao C, Yang D. Electrical inhomogeneity in left ventricular hypertrophy[J]. Cell Biochem Biophys, 2014, 69(3): 399-404. Takagi H, Umemoto T. Systematic review and meta-analysis of the early and late outcomes of open and endovascular repair of abdominal aortic aneurysm [J]. Br J Surg, 2013, 100(10): 1397. Healy K O, Waksmonski C A, Altman R K, et al. Perioperative outcome and long-term mortality for heart failure patients undergoing intermediate- and high-risk noncardiac surgery: impact of left ventricular ejection fraction[J]. Congest Heart Fail, 2010, 16(2): 45-9. Saito S, Takagi A, Kurokawa F, et al. Usefulness of tissue Doppler echocardiography to predict perioperative cardiac events in patients undergoing noncardiac surgery[J]. Heart Vessels, 2012, 27(6): 594-602. Cho D H, Park S M, Kim M N, et al. Presence of preoperative diastolic dysfunction predicts postoperative pulmonary edema and cardiovascular complications in patients undergoing noncardiac surgery[J]. Echocardiography, 2014, 31(1): 42-9. Rossi E, Citterio F, Vescio M F, et al. Risk stratification of patients undergoing peripheral vascular revascularization by combined resting and dipyridamole echocardiography[J]. Am J Cardiol, 1998, 82(3): 306-10. Lee T H, Marcantonio E R, Mangione C M, et al. Derivation and prospective validation of a simple index for prediction of cardiac risk of major noncardiac surgery[J]. Circulation, 1999, 100(10): 1043-9. Lavery L A, Hunt N A, Ndip A, et al. Impact of chronic kidney disease on survival after amputation in individuals with diabetes[J]. Diabetes Care, 2010, 33(11): 2365-9. Canty D J, Royse C F, Kilpatrick D, et al. The impact on cardiac diagnosis and mortality of focused transthoracic echocardiography in hip fracture surgery patients with increased risk of cardiac disease: a retrospective cohort study[J]. Anaesthesia, 2012, 67(11): 1202-9. Canty D J, Royse C F, Kilpatrick D, et al. The impact of pre-operative focused transthoracic echocardiography in emergency non-cardiac surgery patients with known or risk of cardiac disease[J]. Anaesthesia, 2012, 67(7): 714-20. Additional Declarations No competing interests reported. Supplementary Files SupplementInformationTable1Characteristicsof.docx 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-5653634","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":396233748,"identity":"604a2c27-a20b-4442-8c0e-d603ac886ffe","order_by":0,"name":"Yuanming Liu","email":"","orcid":"","institution":"longyan second hospital","correspondingAuthor":false,"prefix":"","firstName":"Yuanming","middleName":"","lastName":"Liu","suffix":""},{"id":396233749,"identity":"d589005e-22d6-44ca-99ae-d6e578b13896","order_by":1,"name":"Ting Yan","email":"","orcid":"","institution":"fujian medical university union hospital","correspondingAuthor":false,"prefix":"","firstName":"Ting","middleName":"","lastName":"Yan","suffix":""},{"id":396233750,"identity":"f0ba495b-5855-4508-b9ba-b33d298e1670","order_by":2,"name":"Liangcheng Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2UlEQVRIiWNgGAWjYDACdgY2EMXDz9584MCHH8RoYYZokZHsOZZ4cGYPCVpsDG7kGB/mYCNCh3wz87MHH3fU8hicOfPhMAMPgzy/2AH8Whib2cwNZ545ziN5vHfD4QILBsOZsxMIuIuZh02at+0YD9+ZsxsOz+BhSDC4TUALG0jLX6AWhhs5Dw7zsBGhhQekhbGthkfgRg4DcVokmNnMJHvbDvAAA9kAGMgShP0i3978TOJnW509MCoff/jww0aeX5qAFig4DLeVKOUgUEe0ylEwCkbBKBiBAABWy0Kf5A71xAAAAABJRU5ErkJggg==","orcid":"","institution":"fujian medical university union hospital","correspondingAuthor":true,"prefix":"","firstName":"Liangcheng","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-12-16 12:08:40","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5653634/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5653634/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":72739511,"identity":"1e02c3a2-22fd-494b-9dbc-62b61ae8c355","added_by":"auto","created_at":"2025-01-01 09:24:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19590,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of various TTE abnormalities among 1,049 patients\u003c/p\u003e\n\u003cp\u003eLeft-ventricular Diastolic Dysfunction, LVDD; Mild tricuspid regurgitation, MTR; Left atrial enlargement, LAE; Mild aortic regurgitation, MAR; Interventricular septal thickening, IVST; Left ventricular hypertrophy, LVH; Ascending aortic dilatation, AAD; Mild mitral regurgitation, MMR;Mild pulmonary hypertension, MPH; Aortic sclerosis, AS; Basal septal hypertrophy, BSH; Mild and moderate aortic regurgitation, MmAR;Mild and moderate tricuspid regurgitation, MmTR; Pericardial effusion, PE; Mild and moderate mitral regurgitation, MmMR; Right atrium enlargement RAE; Left ventricular enlargement LVE, mAR; Right ventricular enlargement, RVE; Patent foramen ovale, PFO; Moderate pulmonary hypertension, mPH; Moderate tricuspid regurgitation, mTR; Mild aortic stenosis, MAS; other abnormalities with an incidence of ≤3 included left ventricular systolic dysfunction and atrial septal defect.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5653634/v1/c00c33e043e2b0e6e30677a7.png"},{"id":80796919,"identity":"ac3549db-504c-485e-aa8f-ad7e317c9ce3","added_by":"auto","created_at":"2025-04-17 07:47:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":840731,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5653634/v1/530dddaa-ed80-44c6-b168-962a9077340f.pdf"},{"id":72740561,"identity":"da3ebae0-bfc6-4925-bd1d-990ecd1137d5","added_by":"auto","created_at":"2025-01-01 09:32:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":16195,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementInformationTable1Characteristicsof.docx","url":"https://assets-eu.researchsquare.com/files/rs-5653634/v1/2024c16237e4d6ea52b474d4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Preoperative Transthoracic Echocardiography in Laparoscopic Colorectal Surgery: Impact on Postoperative Cardiac Outcomes","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEchocardiography is pivotal in assessing and managing cardiac conditions, providing critical morphological and physiological insights into the myocardium, valves, pericardium, coronary arteries, and great vessels. It is particularly valuable in evaluating cardiac function, detecting conditions like cardiac tamponade, and assessing perioperative risks in non-cardiac surgery patients, where cardiovascular events are the leading cause of mortality[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Transthoracic echocardiography (TTE), a non-invasive tool, is increasingly used by anesthesiologists for preoperative cardiac evaluation[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite low anesthesia-related mortality, cardiac complications occur in 2.0-3.5% of patients, contributing to one-third of postoperative deaths (0.5\u0026ndash;1.5%)[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The American Heart Association emphasizes the importance of preoperative cardiac evaluation in managing cardiac conditions and improving outcomes[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Key risk factors for adverse cardiac outcomes include left ventricular dysfunction, ischemic heart disease, aortic stenosis, and pulmonary hypertension. However, clinical evaluation alone is often unreliable, necessitating TTE for accurate diagnosis[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. While TTE is recommended before elective non-cardiac surgery, its indiscriminate use raises concerns due to its high cost, accounting for 11% of medical insurance fees, or over \u003cspan\u003e$\u003c/span\u003e1.1 billion[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The 2011 Appropriate Use Criteria (AUC) for TTE revealed that while 91.8% of uses were appropriate, 4.3% were inappropriate, and 3.9% uncertain, with no significant difference in medical management outcomes[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. This underscores the need for judicious use of TTE. Preoperative echocardiography has been associated with longer pre-surgery waiting times and higher costs, estimated at \u003cspan\u003e$\u003c/span\u003e47\u0026nbsp;million annually[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although routine TTE may optimize medical plans and reduce surgical delays, balancing early surgery with thorough pre-anesthesia evaluation remains challenging[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The role of preoperative TTE in risk stratification for non-cardiac surgeries is unclear, particularly in elderly patients with high comorbidity and financial constraints, where reducing unnecessary tests is essential[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Anesthesiologists must balance rapid preoperative assessments with patient safety and hospital efficiency. Current evidence suggests TTE's role in preoperative risk assessment is limited, as a large retrospective cohort study found no association between preoperative echocardiography and improved survival or reduced hospital stays[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This study aims to analyze the clinical value of preoperative TTE in elective laparoscopic colorectal surgery to promote cost-effective medical resource utilization.\u003c/p\u003e"},{"header":"1. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e1.1 General Information\u003c/h2\u003e \u003cp\u003eThis retrospective study included patients who underwent laparoscopic colorectal surgery at our hospital from January 1st 2018 to December 31st 2018. These data were accessed for study purposes from July 1st 2019 to July 15th 2019. The inclusion criteria were patients aged\u0026thinsp;\u0026gt;\u0026thinsp;18 years, while the exclusion criteria were patients with poor-quality echocardiographic images. This study followed the Declaration of Helsinki and received approval from the hospital\u0026rsquo;s ethics committee(201704342). Since this was a retrospective study, all data were fully anonymized, and the ethics committee waived the requirement for informed consent. Clinical information, including each patient\u0026rsquo;s basic information (gender, age, BMI etc), medical history, ASA classification, and surgery type, was obtained by carefully reviewing their medical records. Surgical risk assessment was based on surgical type and related risk factors in accordance with the ESC/ESA guidelines for non-cardiac surgeries. All cardiac-related adverse events occurring within 30 days postoperatively were recorded for all patients included in the study. If a patient\u0026rsquo;s electrocardiogram(ECG) exhibited at least one of the following conditions, he or she was considered to have abnormal ECG findings: sinus bradycardia (heart rate\u0026thinsp;\u0026lt;\u0026thinsp;50 beats per minute), arrhythmias (supraventricular tachycardia, atrial fibrillation/flutter, pacing, or ventricular rhythm), premature beats, atrioventricular blocks (Mobitz II second degree or third degree), left or right bundle branch block, ventricular hypertrophy, ischemic Q waves/ST-segment/T-wave changes, or abnormal QT interval.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e1.2 Echocardiographic Parameters\u003c/h3\u003e\n\u003cp\u003eThis study used the Philips iE33 color Doppler ultrasound diagnostic device, equipped with an S5-1 adult cardiac transducer and an S7-2 multiplane transesophageal transducer, with frequencies of 2\u0026ndash;5 MHz and 2\u0026ndash;7 MHz, respectively. The device has the functions of two-dimensional echocardiography (2DE), color Doppler flow imaging (CDFI), pulse Doppler, and continuous Doppler. Before laparoscopic colorectal surgery, all patients were examined in the left lateral decubitus position by a trained echocardiography specialist using a 3.5 MHz transducer (Vivid-E9, GE Healthcare, Horten, Norway, or iE-33, Philips, Netherlands). Measurements of left ventricular mass index (LVMI), left ventricular ejection fraction (LVEF), and left atrial volume index (LAVI) were conducted according to ASE recommendations. Left ventricular hypertrophy (LVH) was defined as an LVMI\u0026thinsp;\u0026gt;\u0026thinsp;115 g/m\u0026sup2; for men and \u0026gt;\u0026thinsp;95 g/m\u0026sup2; for women. LAVI was calculated using the formula (A1*A2/l)*8/3π, where l is the average LA length in both four-chamber and two-chamber views. Mitral valve blood flow measurements included early (E) and late (A) peak velocities and the E/A ratio. Pulse velocities of tissue Doppler imaging, including systolic (s') and early diastolic (e') peak velocities, were obtained at the interventricular septum and the lateral mitral annulus. The ratio of mitral annulus early diastolic flow velocity (E/e') was calculated using the average of septal and lateral e' values (average E/e' = E/[ (septal e' + lateral e') /2 ]). In the E/A ratio, the E peak occurs during the rapid filling phase of the left ventricle, reflecting the early diastolic LA-LV pressure gradient; the A peak occurs in late diastole, reflecting the late diastolic LA-LV pressure gradient. The average E peak flow velocity was 73 cm/s, the average A peak flow velocity was 40 cm/s, and the E/A ratio was 1.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.32 (range 1-1.5). E-wave deceleration time (EDT) was influenced by left ventricular relaxation, left ventricular diastolic pressure after mitral valve opening, and left ventricular compliance. EDT ranged from 160 to 240 ms [(197\u0026thinsp;\u0026plusmn;\u0026thinsp;27) ms]. Two-dimensional grayscale images were obtained in three standard views: apical two-chamber, apical four-chamber, and apical long-axis. All images were continuously collected over three cardiac cycles and digitally stored at a rate of 50\u0026ndash;90 frames per second for offline analysis.\u003c/p\u003e\n\u003ch3\u003e1.3 TTE major abnormalities\u003c/h3\u003e\n\u003cp\u003eAll TTE examinations and reports were completed by specialists in cardiology. TTE findings were considered abnormal if any indicator exceeded the normal range [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Clinically significant abnormalities were defined as (1) LVEF\u0026thinsp;\u0026lt;\u0026thinsp;45%; (2) regional wall motion abnormalities involving at least two segments; (3) grade III diastolic dysfunction; (4) right ventricular (RV) dysfunction; (5) RV enlargement; (6) the presence of intracardiac shunt; (7) presence of cardiac implant or cardiac mass; (8) moderate or greater valvular regurgitation; (9) aortic stenosis with an aortic valve area\u0026thinsp;\u0026lt;\u0026thinsp;1.5 cm\u0026sup2;; (10) RV systolic pressure\u0026thinsp;\u0026gt;\u0026thinsp;right atrial pressure\u0026thinsp;\u0026gt;\u0026thinsp;above 40 mm Hg; (11) aortic dilation; (12) aortic coarctation; (13) moderate or larger pericardial effusion; (14) the presence of pericardial disease; (15) significant valvular heart disease was defined as at least moderate valvular disease; (16) Interventricular septal thickness with \u0026gt;\u0026thinsp;11 mm indicating septal thickening.\u003c/p\u003e\n\u003ch3\u003e1.4 Postoperative Major Adverse Cardiac Events\u003c/h3\u003e\n\u003cp\u003eMajor adverse cardiac events (MACEs) are primarily defined by myocardial enzyme levels, ECG results, and clinical events [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. MACEs include acute coronary syndromes, congestive heart failure, newly developed severe arrhythmias, non-fatal cardiac arrest, and cardiac death. A. Acute coronary syndromes include acute myocardial infarction and unstable angina. The diagnosis of acute myocardial infarction requires elevated creatine kinase-MB (CK-MB) levels (\u0026gt;\u0026thinsp;0.83 umol/L/s, equivalent to 50U/L) along with at least one of the following criteria: formation of new Q waves (as defined by the Minnesota Code 1.1 or 1.2), persistent ST-T changes, imaging evidence of myocardial motion abnormalities, angiographic abnormalities, or autopsy confirmation of an acute infarction. Unstable angina is defined as severe chest pain in the precordial area, unrelated to the surgical incision, lasting for no less than 30 minutes, with negative cardiac troponin I, unresponsive to standard treatment (rest and nitroglycerin), accompanied by transient ST-segment and T-wave changes, without Q-wave formation or enzyme elevation. B. Congestive heart failure diagnosis requires a. symptoms or signs of pulmonary edema (dyspnea, orthopnea); b. new signs of left or right ventricular failure (cardiomegaly, lung rales, engorgement of the jugular veins and/or positive hepatojugular reflux, peripheral edema); c. diagnostic findings of pulmonary hypertension or right ventricular overload (pulmonary capillary wedge pressure\u0026thinsp;\u0026ge;\u0026thinsp;18 mmHg, central venous pressure\u0026thinsp;\u0026ge;\u0026thinsp;12 mmHg) and Nt-proBNP levels: for patients under 50 years old, levels\u0026thinsp;\u0026gt;\u0026thinsp;450 pg/ml suggest possible heart failure; for patients aged 50 to 75 years, levels\u0026thinsp;\u0026gt;\u0026thinsp;900 pg/ml suggest possible heart failure; for patients over 75 years old, levels\u0026thinsp;\u0026gt;\u0026thinsp;1800 pg/ml suggest possible heart failure; d. cTnI: 0-0.029, with values more than twice the normal range considered significant. C. Newly developed severe arrhythmias refer to postoperative arrhythmias requiring intervention with drugs or electrical cardioversion/defibrillation and include sustained and rapid atrial flutter and fibrillation, Type II or higher atrioventricular block, ventricular tachycardia (defined as a rate of \u0026ge;\u0026thinsp;100 beats/min with at least five consecutive ventricular ectopic beats on continuous two-lead Holter monitoring), and ventricular fibrillation.\u003c/p\u003e\n\u003ch3\u003e1.5 Follow-Up\u003c/h3\u003e\n\u003cp\u003eAll patients included were followed for 30 days postoperatively. Previous studies on MACEs after non-cardiac surgeries have shown that most of these events occur within the first month after surgery [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Throughout the follow-up period, patients\u0026rsquo; medical records were carefully reviewed. The primary endpoint was the occurrence of a postoperative MACE defined as cardiovascular death, acute coronary syndromes, hospitalization for heart failure, or ventricular tachycardia. The diagnoses of acute coronary syndrome and ventricular tachycardia were confirmed by cardiology specialists. There was no loss-to-up patient in this study, as all medical records were well documented.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e1.6 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using SPSS 27.0. Continuous data were presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range). Categorical data were presented as numbers and percentages. Between-group comparisons of normally or non-normally distributed continuous variables were performed using the t-test or Mann-Whitney U-test, respectively. Categorical variables were compared between groups using the chi-square test or Fisher\u0026rsquo;s exact test. A two-sided p-value less than 0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eRisk factors other than TTE-related ones were first identified using univariate analysis. Variables with a p-value smaller than 0.10 according to the univariate analysis were included in the multivariate logistic regression model to assess the effects of the overall preoperative TTE abnormalities and the variables with statistical significance in the univariate analysis on the outcome indicators. Second, each major TTE abnormality and the statistically significant variables in the univariate analysis were included in the multivariate logistic regression model to observe the effects of the above risk factors on the outcome indicators. This approach allowed for a comprehensive assessment of the impact of various factors on the occurrence of postoperative MACEs.\u003c/p\u003e \u003c/div\u003e"},{"header":"2 Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patient Basic Information\u003c/h2\u003e \u003cp\u003eThis study included 1,049 patients who underwent laparoscopic colorectal surgery at our hospital between January 2018 to December 2018. Among them, 967 patients completed preoperative TTE, while 82 patients did not. The patients in the TTE and non-TTE groups were comparable in terms of gender, age, body mass index (BMI), previous hypertension, previous ischemic heart disease, previous cerebrovascular disease, previous diabetes, ASA Classification, serum level of Hemoglobin (Hb), albumin (ALB), Creatinine clearance rate (Ccr), hospitalization days and hospitalization expenses with no statistically significant differences between these two groups (Supplement Information Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In addition, all surgeries were performed within the specified time window. Only one patient experienced a prolonged waiting time for surgery, while three patients had minor delays; the remaining patients underwent elective surgery as scheduled.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of factors associated with postoperative MACEs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith MACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWithout MACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e/t\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge( years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.16\u0026thinsp;\u0026plusmn;\u0026thinsp;13.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.87\u0026thinsp;\u0026plusmn;\u0026thinsp;11.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious ischemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious cerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125.05\u0026thinsp;\u0026plusmn;\u0026thinsp;23.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.27\u0026thinsp;\u0026plusmn;\u0026thinsp;20.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.232\u0026thinsp;\u0026plusmn;\u0026thinsp;4.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.750\u0026thinsp;\u0026plusmn;\u0026thinsp;4.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCcr (mL/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.68\u0026thinsp;\u0026plusmn;\u0026thinsp;15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.85\u0026thinsp;\u0026plusmn;\u0026thinsp;23.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal ECG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.89\u0026thinsp;\u0026plusmn;\u0026thinsp;15.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.43\u0026thinsp;\u0026plusmn;\u0026thinsp;9.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization expenses (RMB, in thousands)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.58\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Prevalence of TTE Abnormalities\u003c/h2\u003e \u003cp\u003eAmong the 967 patients who underwent TTE, the overall incidence of TTE abnormalities was 67.3% (664/967). The three most common abnormalities were left ventricular diastolic dysfunction (27%), mild tricuspid regurgitation (24%), and left atrial enlargement (17%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Independent Risk Factors for Postoperative MACEs\u003c/h2\u003e \u003cp\u003eThe multivariate regression analysis showed that interventricular septal thickening (IVST, OR\u0026thinsp;=\u0026thinsp;0.152, 95% CI 0.030\u0026ndash;0.768, P\u0026thinsp;=\u0026thinsp;0.023) and left ventricular hypertrophy (LVH, OR\u0026thinsp;=\u0026thinsp;5.477, 95% CI 1.196\u0026ndash;25.082, P\u0026thinsp;=\u0026thinsp;0.028) were independent risk factors for postoperative MACEs (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). However, ROC curve analysis revealed that the area under the curve was 0.497 for IVST and 0.536 for LVH, indicating a relatively low predictive value.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between the abnormality of each indicator and postoperative MACEs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.591\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.207\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMTR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAE\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.315\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIVST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-1.883\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.826\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.701\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.799\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.295\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.578\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.685\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.984\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn our study, a total of 1049 patients who underwent laparoscopic colorectal surgery were analyzed for factors associated with postoperative major adverse cardiac events (MACEs). The results showed that factors significantly associated with the occurrence of MACEs included age (P\u0026thinsp;=\u0026thinsp;0.000), history of ischemic heart disease (P\u0026thinsp;=\u0026thinsp;0.000), history of cerebrovascular disease (P\u0026thinsp;=\u0026thinsp;0.000), ASA classification (P\u0026thinsp;=\u0026thinsp;0.003), albumin (ALB) levels (P\u0026thinsp;=\u0026thinsp;0.012), electrocardiogram (ECG) status (P\u0026thinsp;=\u0026thinsp;0.027), hospitalization days (P\u0026thinsp;=\u0026thinsp;0.000), and hospitalization costs (P\u0026thinsp;=\u0026thinsp;0.000). Additionally, gender (P\u0026thinsp;=\u0026thinsp;0.754), body mass index (BMI) (P\u0026thinsp;=\u0026thinsp;0.763), history of hypertension (P\u0026thinsp;=\u0026thinsp;0.096), history of diabetes (P\u0026thinsp;=\u0026thinsp;0.671), hemoglobin (Hb) levels (P\u0026thinsp;=\u0026thinsp;0.132), and creatinine clearance rate (Ccr) (P\u0026thinsp;=\u0026thinsp;0.239) were not significantly associated with the occurrence of MACEs. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e)These findings emphasize the importance of identifying high-risk patients in preoperative assessments and may aid in guiding clinical decision-making and the development of preventive strategies.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAnalysis of factors associated with postoperative MACEs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWith MACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWithout MACEs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e/t\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e640\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.191\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.754\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge( years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e66.16\u0026thinsp;\u0026plusmn;\u0026thinsp;13.693\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58.87\u0026thinsp;\u0026plusmn;\u0026thinsp;11.604\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.00\u0026thinsp;\u0026plusmn;\u0026thinsp;3.206\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.99\u0026thinsp;\u0026plusmn;\u0026thinsp;3.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e752\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.543\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.096\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious ischemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e984\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious cerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.547\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.323\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e836\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4.536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHb (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125.05\u0026thinsp;\u0026plusmn;\u0026thinsp;23.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130.27\u0026thinsp;\u0026plusmn;\u0026thinsp;20.678\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40.232\u0026thinsp;\u0026plusmn;\u0026thinsp;4.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41.750\u0026thinsp;\u0026plusmn;\u0026thinsp;4.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCcr (mL/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74.68\u0026thinsp;\u0026plusmn;\u0026thinsp;15.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72.85\u0026thinsp;\u0026plusmn;\u0026thinsp;23.022\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal ECG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e481\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.463\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31.89\u0026thinsp;\u0026plusmn;\u0026thinsp;15.997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.43\u0026thinsp;\u0026plusmn;\u0026thinsp;9.282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e9.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization expenses (RMB, in thousands)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42.58\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.65\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13.889\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.4 The association between preoperative TTE abnormalities for postoperative MACEs\u003c/h2\u003e \u003cp\u003eThe multivariate regression analysis including overall TTE abnormalities and other risk factors identified from univariate analysis revealed that among the 10 factors, hospitalization days (OR\u0026thinsp;=\u0026thinsp;1.061, 95% CI 1.032\u0026ndash;1.090, P\u0026thinsp;=\u0026thinsp;0.000), hospitalization expensesand (OR\u0026thinsp;=\u0026thinsp;1.043, 95% CI 1.023\u0026ndash;1.083, P\u0026thinsp;=\u0026thinsp;0.003) and previous ischemic heart disease (OR\u0026thinsp;=\u0026thinsp;7.378, 95% CI 2.105\u0026ndash;25.864, P\u0026thinsp;=\u0026thinsp;0.02) were statistically significant predictors for postoperative MACEs, whereas overall TTE abnormalities were not significantly associated with postoperative MACEs (OR\u0026thinsp;=\u0026thinsp;0.80, 95% CI 0.318\u0026ndash;2.030, P\u0026thinsp;=\u0026thinsp;0.644) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between overall preoperative TTE abnormalities and postoperative MACEs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e25.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHospitalization expenses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17.739\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eASA classification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.070\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious Hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.037\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious ischemic heart disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.639\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.590\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7.723\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious cerebrovascular disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.612\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.700\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.382\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal ECG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.368\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.719\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOverall TTE abnormalities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.218\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.473\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary objective of preoperative evaluation is to assess the risk of perioperative complications, optimize patients' preoperative conditions, and mitigate surgery- or anesthesia-related morbidity and mortality. This process aims to expedite recovery to an ideal state with consideration for healthcare cost efficiency [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Preoperative risk assessment and optimization rely on previous treatment data and health status to provide a baseline for evaluation [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Consultation is a common method used in preoperative evaluation. If additional examinations prompt changes in anesthetic management or necessitate other interventions, postoperative outcomes may be influenced. Conversely, if preoperative management or anesthetic plans remain unchanged, further evaluations may lead to unnecessary and potentially harmful testing, as well as delays in surgery [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our findings indicate that among preoperative TTE abnormalities, IVST and LVH are independent risk factors for postoperative MACEs, aligning with other studies' findings [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In the TTE group, the overall incidence of TTE abnormalities was 67.3% (664/967), with IVST occurring in 13% and LVH in 12%, which is comparable to other studies' reports (12.7\u0026ndash;17.9%) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. IVST and LVH typically suggest a high left ventricular workload, serving as a compensatory mechanism for hypertension [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Studies have linked moderate to severe LVH with postoperative MACE [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Possible reasons include myocardial fibrosis, interstitial cell proliferation, and capillary rarefaction associated with LVH and IVH, which may precipitate ischemic processes leading to myocardial ischemia [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and pathological LVH due to interstitial and compensatory fibrosis, leading to progressive left ventricular diastolic dysfunction and heart failure [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Other research has identified preoperative diastolic dysfunction as an independent risk factor for postoperative mortality and MACE [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In our study, left ventricular diastolic dysfunction was the most prevalent TTE abnormality but was not significantly correlated with postoperative MACE. LVH, however, is associated with a reduced phosphocreatine/adenosine triphosphate ratio (PCr/ATP), indicating impaired myocardial energy metabolism, potentially leading to heart failure [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Furthermore, patients with LVH are more susceptible to transmural myocardial repolarization and refractory period dispersion across the ventricular wall, resulting in prolonged action potential duration and an increased risk of arrhythmias [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, in this study, we found no statistically significant difference in the outcome of interest, major postoperative cardiac events (MACEs), between patients who completed TTE and those who did not, similar to other related studies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAn increasing number of surgeons and anesthesiologists frequently request preoperative echocardiography to assess cardiac function, particularly LVEF, a key indicator of left ventricular systolic function. A prospective study focusing on 339 males who underwent non-cardiac surgery, all with known or suspected coronary artery disease, revealed that an LVEF lower than 40% was correlated with all postoperative ischemic cardiac events. Multivariate analysis suggested that an LVEF below 40% remained a significant predictor after adjusting for known clinical risk factors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Relevant studies have also reported a significantly positive correlation between impaired left ventricular systolic function and perioperative complications, suggesting that preoperative assessment of left ventricular systolic function may help predict perioperative outcomes and long-term mortality in non-cardiac surgery patients, especially those undergoing high-risk surgery [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, some studies have shown no significant correlation between LVEF and postoperative MACEs [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], and LVEF only suggested the possibility of left ventricular dysfunction after surgery [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. A prospective cohort study identified six independent predictors for postoperative cardiac complications in non-cardiac surgery patients: high-risk surgery type, history of ischemic heart disease, history of congestive heart failure, history of cerebrovascular disease, preoperative insulin treatment, and preoperative serum creatinine (Cr)\u0026thinsp;\u0026gt;\u0026thinsp;2.0 mg/dL [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Cr\u0026thinsp;\u0026gt;\u0026thinsp;2 has been proven the most significant clinical variable associated with MACEs, and a univariate analysis conducted has indicated a significant correlation between both coronary artery disease (CAD) and heart failure (HF) included in the Lee index and MACEs [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Preoperative advanced chronic kidney disease (CKD) has been reported as an independent predictor of an increased incidence of perioperative MACEs (myocardial infarction, stroke, or heart failure), mortality, and healthcare costs [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. However, our study found no relationship between renal function, LVEF, and postoperative MACE. This could be due to the small number of cases with reduced LVEF, and renal function assessment was limited to serum creatinine levels. More renal function indicators are needed to further evaluate their impact on postoperative MACEs.\u003c/p\u003e \u003cp\u003eEvidence has demonstrated TTE's ability to improve clinical evaluation and alter major treatment plans in approximately 50% of cases across various medical settings, including intensive care units (ICU), emergency departments, and perioperative settings at risk of sustained hemodynamic instability, as well as the outpatient preoperative stage [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In one prospective observational study, 100 patients scheduled for non-cardiac surgery underwent preoperative TTE, which confirmed moderate to severe ventricular or valvular dysfunction in 36% of high-risk patients and 10% of low-risk patients (who accounted for 32% of the total), leading to a change in treatment plans in 54% of cases [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. TTE affects decisions regarding whether to proceed with or delay surgery, leads to changes in the type of anesthesia (local or general), and increases the use of invasive hemodynamic monitoring and treatment and postoperative high-dependency care. For anesthesiologists, clinically significant hemodynamic or valvular abnormalities detected by TTE alert them to the potential increase in cardiac risk, requiring enhanced medical care; on the other hand, normal or clinically insignificant TTE findings provide reassurance, reducing the need for further investigations, invasive monitoring, and high-dependency postoperative care. These findings support the feasibility of routine TTE screening as an aid in determining a patient's suitability for surgery and planning anesthesia and postoperative care to reduce adverse outcomes. However, the study did not assess TTE's effects on postoperative outcomes. Our study filled this gap and found that TTE abnormalities had low predictive value for postoperative MACEs and were not able to serve as independent risk factors. Patients often undergo preoperative TTE due to coexisting conditions, such as coronary artery disease, hypertension, cerebrovascular disease, and arrhythmias, which are the true independent risk factors for postoperative MACEs [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Meanwhile, common TTE abnormalities such as left ventricular diastolic dysfunction, mild tricuspid regurgitation, and left atrial enlargement were not significantly associated with surgical outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, our study suggests that overall preoperative TTE abnormalities do not have significant predictive value for postoperative MACEs. However, preoperative findings of interventricular septal thickening and left ventricular hypertrophy are independent risk factors for MACEs. Additionally, postoperative MACEs significantly increase patient hospitalization time and costs. To address the unresolved debate over routine preoperative TTE, large-sample, multicenter studies are needed.\u003c/p\u003e "},{"header":"Shortcomings","content":"\u003cp\u003eAdmittedly, our study has some limitations. First, our study only includes patients who underwent laparoscopic colorectal surgery in our hospital in 2018, introducing potential selection bias. As a result, it may not fully represent the broader population undergoing non-cardiac surgery from other hospitals. Second, the retrospective nature of the study inevitably leads to some inaccurate data, since there was no blinding or quality control during the data collecting process. Third, the outcome indicator—MACEs—was treated as a dichotomous outcome, leading to the failure to further analyze the association between some risk factors and certain individual adverse cardiac events. Lastly, the sample size was relatively small, and the study design needs to be improved as it did not consider factors like surgical type, duration, and urgency.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics Approval and Consent to Participate\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of the Fujian Longyan Second Hospital, with the approval number[201704342]. It was conducted in compliance with the ethical standards of the committee and the Declaration of Helsinki. Informed consent was obtained from all participants involved in the study. The consent procedure was reviewed and approved by the Ethics Committee, ensuring participants were fully informed about the study's objectives, methods, risks, and benefits before consenting. Written consent was provided by participants or their legal guardians.\u003c/p\u003e\n\u003cp\u003eConsent for Publication\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication of clinical details and/or clinical images was obtained from all patients or participants involved in the study. This consent explicitly includes the use of their data for scientific publication purposes. A copy of the consent form is available for review by the editorial board of this journal. All personal identifiers have been removed or anonymized in order to protect the privacy of the individuals involved. The consent obtained ensures that the publication does not infringe on the rights of the participants, and the data presented are in compliance with the ethical standards for publication in medical journals. All data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003eAll data generated or analysed during this study are included in this published article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003eData availability\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003eCompeting Interests Statements\u003c/p\u003e\n\u003cp\u003eThe Authors declare no Competing Financial or Non-Financial Interests.\u003c/p\u003e\n\u003cp\u003eNo Fundings\u003c/p\u003e\n\u003cp\u003eAuthors' Contributions\u003c/p\u003e\n\u003cp\u003eLiu Yuanming: Conducted the experiments, collected and analyzed the data, and contributed to the writing of the manuscript.Yan Ting: Participated in the study design, interpreted the results, and provided critical revisions to the manuscript.Zhang Liangcheng: Principal investigator of the study, conceived the study, secured funding, and provided final approval of the version to be published.All authors have read and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePerez J V, Warwick D J, Case C P, et al. 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The impact on cardiac diagnosis and mortality of focused transthoracic echocardiography in hip fracture surgery patients with increased risk of cardiac disease: a retrospective cohort study[J]. Anaesthesia, 2012, 67(11): 1202-9.\u003c/li\u003e\n\u003cli\u003eCanty D J, Royse C F, Kilpatrick D, et al. The impact of pre-operative focused transthoracic echocardiography in emergency non-cardiac surgery patients with known or risk of cardiac disease[J]. Anaesthesia, 2012, 67(7): 714-20.\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":"laparoscopic colorectal surgery, transthoracic echocardiography, preoperative assessment, postoperative major adverse cardiac events","lastPublishedDoi":"10.21203/rs.3.rs-5653634/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5653634/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThis study aimed to assess the clinical utility of preoperative transthoracic echocardiography (TTE) in predicting postoperative major adverse cardiac events (MACEs) in patients undergoing laparoscopic colorectal surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA retrospective cohort study was conducted involving 1049 patients who underwent laparoscopic colorectal surgery between January 1st, 2018, and December 31st, 2018. Among these, 967 patients completed preoperative TTE, while 82 did not. Data collection encompassed basic patient information, medical history, ASA classification, and surgical details. The primary outcome was the occurrence of postoperative MACEs, which were defined based on myocardial enzyme levels, ECG results, and clinical events.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eA total of 44 MACEs were identified, with congestive heart failure and new arrhythmias being the most prevalent. Univariate and multivariate regression analyses revealed that interventricular septal thickening (IVST) and left ventricular hypertrophy (LVH) were independent risk factors for MACEs, whereas the overall presence of TTE abnormalities was not significantly associated with postoperative MACEs. The study also highlighted that postoperative MACEs were significantly associated with increased hospitalization days and costs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003ePreoperative TTE abnormalities, specifically IVST and LVH, were found to be independent risk factors for postoperative MACEs. However, the routine use of TTE as a predictive tool for MACEs in this patient population may not be warranted based on the overall findings.\u003c/p\u003e","manuscriptTitle":"Preoperative Transthoracic Echocardiography in Laparoscopic Colorectal Surgery: Impact on Postoperative Cardiac Outcomes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-01 09:24:25","doi":"10.21203/rs.3.rs-5653634/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":"244818e3-7272-4c09-a9b7-c811707ac9a4","owner":[],"postedDate":"January 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-17T07:39:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-01 09:24:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5653634","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5653634","identity":"rs-5653634","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}