Analysis of risk factors for postoperative lower extremity deep vein thrombosis in liver transplant patients

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However, various postoperative complications seriously affect the patient's prognosis, among which deep vein thrombosis of the lower limbs is one of the more common and dangerous ones. Objective To investigate the high-risk factors for the development of lower extremity deep vein thrombosis in liver transplant recipients after surgery and to establish a relevant prediction model. Methods A total of 425 patients were collected in this study, out of which 110 patients developed lower limb deep vein thrombosis after liver transplantation; The past medical history and relevant information during hospitalisation of the patients enrolled in this study were collected separately to study the correlation factors affecting the emergence of lower limb deep vein thrombosis in patients after surgery, and to establish a prediction model. Results Possibly relevant factors were included in a one-way logistic regression, and after analysing the results: age, history of alcohol consumption, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were the potential risk factors for the development of lower limb deep vein thrombosis after liver transplantation, P < 0.2. The data obtained were further included in a multifactorial review and age, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were independent risk factors for the development of lower extremity deep vein thrombosis after liver transplantation (P < 0.05). Conclusion This finding suggests that clinicians should focus on high-risk individuals with these factors when dealing with liver transplant patients. By strengthening monitoring and adopting targeted preventive measures to reduce the incidence of lower limb DVT and improve the quality of postoperative rehabilitation and long-term prognosis of patients. Liver transplant Deep vein thrombosis of the lower limbs Hepatic encephalopathy Risk factor Predictive model Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Liver transplantation is an effective treatment for end-stage liver disease and significantly improves patient survival and quality of life [ 1 – 3 ] . However, various types of postoperative complications have a serious impact on the prognosis of patients, among which deep vein thrombosis (DVT) of the lower limbs is one of the more common and dangerous ones, which has many adverse effects on the prognosis of patients [ 4 ] . A large retrospective study in the United States involving multiple centres, which included nearly 1,000 liver transplant patients, showed that the incidence of postoperative DVT was approximately 10% − 15% [ 5 ] . Studies have pointed out that patients' own factors, such as advanced age, obesity, and comorbid diabetes mellitus, increase blood viscosity and alter haemodynamics, which are important risk factors for the development of DVT [ 4 – 6 ] . In addition, surgery-related factors, such as long surgery times and large intraoperative blood transfusions, can cause damage to the vascular endothelium, activate the coagulation system, and contribute to thrombus formation. Related studies in Europe have similarly shown that prolonged extracorporeal circulation diversion disrupts the coagulation-anticoagulation balance and is one of the key factors in the high incidence of postoperative DVT [ 6 ] . Due to the differences in the etiology of end-stage liver disease in China and abroad, hepatitis B cirrhosis leads to a higher percentage of liver transplant patients [ 7 , 8 ] . It has been shown that hepatitis B virus infection may affect immunomodulation and coagulation, increasing the risk of postoperative DVT in these patients [ 9 ] . In addition, national studies have focused on the impact of the patient's postoperative rehabilitation environment and level of care on the occurrence of DVT. Due to the differences in medical resources and nursing concepts in different regions, the implementation of preventive measures such as early postoperative activity guidance and stress treatment for patients is uneven, which also affects the incidence of DVT to a certain extent [ 5 , 6 ] . In conclusion, despite the progress of research on the risk factors of DVT after liver transplantation both at home and abroad, in view of the differences in the disease spectrum and medical environment of patients in different regions, in-depth analysis of the relevant risk factors is of great significance in formulating preventive strategies suitable for China's national conditions, reducing the incidence of postoperative DVT in patients undergoing liver transplantation, and improving the prognosis of the patients. 2. Materials and methods 2.1 Research object : This study was conducted on 425 patients who underwent liver transplantation in the Third Hospital of Hebei Medical University from January 2021 to June 2024, including 300 males and 125 females. We obtained a waiver of informed consent from the Ethics Committee. The research was approved by the Ethics Committee of The Third Hospital of Hebei Medical University. And the Number is W2024-133-010. Clinical trial number: not applicable. 2.2 Research Methods : In this retrospective case-control study, 425 patients were collected, out of which 110 patients developed lower limb deep vein thrombosis after liver transplantation. Information about the patients' past medical history and hospitalisation period was collected separately to study the correlating factors affecting the development of lower limb deep vein thrombosis in liver transplant patients after surgery. 2.3 Collection of indicators : Gender, age, BMI, history of smoking, history of alcohol consumption, history of diabetes mellitus, history of hypertension, history of coronary artery disease, incidence of ascites, incidence of hepatic encephalopathy, duration of surgery, hypoproteinemia, and D-dimer were collected from the patients in this study. 2.4 Inclusion and exclusion criteria 2.4.1 Inclusion criteria : (1) all underwent allogeneic in situ liver transplantation; (2) age ≥ 18 years; (3) complete and complete clinical data; and (4) colour ultrasound of the deep veins of the lower limbs was feasible on day 7 after liver transplantation; 2.4.2 Exclusion criteria : (1) combined with other organ transplants; (2) preoperatively diagnosed with lower limb deep vein thrombosis; (3) loss of motor function of the lower limbs; (4) receiving anticoagulant therapy; (5) patients with other serious pre-existing illnesses or psychiatric abnormalities; and (6) undergoing other treatments or participating in other clinical studies. 2.5 Interpretation of relevant indicators mentioned in this study : Lower extremity deep vein thrombosis: This study investigated the factors associated with the development of lower extremity deep vein thrombosis in patients after liver transplantation, therefore routine lower extremity deep vein ultrasound was performed preoperatively to clarify the condition, and patients who developed lower extremity deep vein thrombosis preoperatively were excluded from this study. 2.6 Statistical method : SPSS 25.0 was used for data processing and statistical analysis in this study. Quantitative data conforming to normal distribution were expressed as mean ± standard deviation, and the differences between groups were analyzed by independent sample T test. Comparisons between groups that did not follow a normal distribution were performed using nonparametric tests. Data for qualitative data were expressed as number of cases and percentage, and chi-square tests were used to determine whether there were differences between groups. First, the patients were divided into the training set and the validation set in a 7:3 ratio by complete randomisation, and then the occurrence of lower limb deep vein thrombosis in the patients in the training set was analysed based on the factors such as the occurrence of lower limb deep vein thrombosis and various clinically relevant indexes, and then based on the one-way logistic regression analysis of the collected data, the potential risk factors for the occurrence of lower limb deep vein thrombosis in the patients with liver transplantation were determined. For the univariate analysis, exposure factors with P ≤ 0.2 were selected and included in the multivariate analysis [ 10 , 11 ] . Independent risk factors associated with the development of lower limb deep vein thrombosis in liver transplant recipients were derived, and P < 0.05 was considered a statistically significant difference. The model was then internally validated to further confirm the reliability of the predictive model derived from this study. 3. Results 3.1 Table of values assigned to the relevant indicators in this study See Table 1 for details. Table 1 Table of values assigned to the relevant indicators Name Variable assignment and description Deep vein thrombosis of the lower limbs No-0, Yes-1 Gender Female-0, Male-1 Age <60 years-0, ≥ 60 years-1 History of smoking No-0, Yes-1 History of hypertension No-0, Yes-1 Hepatic encephalopathy No-0, Yes-1 D-dimer Normal-0, Raise-1 3.2 Table of baseline characteristics of patients in both groups We randomly divided the patients included in this experimental study into a training set and a validation set in a ratio of 7:3. There were 297 patients in the training set and 128 patients in the validation set. The general information of the patients in both groups was included in the statistical study, P > 0.05, and the differences in the baseline characteristics of both groups were not statistically significant, as shown in Table 2 . Table 2 Comparison of baseline features between training and validation sets Variables Total (n = 425) test (n = 128) train (n = 297) Statistic P BMI 23.11 ± 2.80 23.23 ± 2.89 23.06 ± 2.76 t = 0.59 0.554 Surgical time 8.58 ± 1.60 8.53 ± 1.63 8.60 ± 1.59 t=-0.37 0.709 DVT, n(%) χ²=1.38 0.240 0 315 (74.12) 90 (70.31) 225 (75.76) 1 110 (25.88) 38 (29.69) 72 (24.24) Gender, n(%) χ²=1.02 0.312 0 125 (29.41) 42 (32.81) 83 (27.95) 1 300 (70.59) 86 (67.19) 214 (72.05) Age, n(%) χ²=0.07 0.795 0 190 (44.71) 56 (43.75) 134 (45.12) 1 235 (55.29) 72 (56.25) 163 (54.88) Smoking history, n(%) χ²=0.30 0.581 0 184 (43.29) 58 (45.31) 126 (42.42) 1 241 (56.71) 70 (54.69) 171 (57.58) Drinking history, n(%) χ²=0.14 0.706 0 235 (55.29) 69 (53.91) 166 (55.89) 1 190 (44.71) 59 (46.09) 131 (44.11) History of diabetes, n(%) χ²=1.09 0.296 0 348 (81.88) 101 (78.91) 247 (83.16) 1 77 (18.12) 27 (21.09) 50 (16.84) History of hypertension, n(%) χ²=2.49 0.114 0 276 (64.94) 76 (59.38) 200 (67.34) 1 149 (35.06) 52 (40.62) 97 (32.66) History of coronary heart disease, n(%) χ²=0.00 0.994 0 362 (85.18) 109 (85.16) 253 (85.19) 1 63 (14.82) 19 (14.84) 44 (14.81) Hydroperitoneum (, n(%) χ²=0.02 0.895 0 188 (44.24) 56 (43.75) 132 (44.44) 1 237 (55.76) 72 (56.25) 165 (55.56) Hepatic encephalopathy, n(%) χ²=0.62 0.433 0 313 (73.65) 91 (71.09) 222 (74.75) 1 112 (26.35) 37 (28.91) 75 (25.25) Low protein, n(%) χ²=0.63 0.428 0 185 (43.53) 52 (40.62) 133 (44.78) 1 240 (56.47) 76 (59.38) 164 (55.22) DD, n(%) χ²=0.66 0.417 0 144 (33.88) 47 (36.72) 97 (32.66) 1 281 (66.12) 81 (63.28) 200 (67.34) 3.3 One-way analysis of variance A training set of 297 patients were included in the statistical analysis, of which 72 patients developed lower limb deep vein thrombosis after liver transplantation. Possibly relevant factors were included in a one-way logistic regression, in which age, history of alcohol consumption, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were potential risk factors for patients to develop lower extremity DVT after liver transplantation, P < 0.2. See Table 3 for details. Table 3 One-Factor Logistic Regression Analysis Based on Training Set Variables β S.E Z P OR (95%CI) Gender 0 1.00 (Reference) 1 0.20 0.31 0.64 0.523 1.22 (0.66 ~ 2.23) Age 0 1.00 (Reference) 1 1.16 0.30 3.83 < .001 3.19 (1.76 ~ 5.78) Smoking history 0 1.00 (Reference) 1 0.27 0.28 0.97 0.332 1.31 (0.76 ~ 2.26) Drinking history 0 1.00 (Reference) 1 0.46 0.27 1.70 0.090 1.59 (0.93 ~ 2.70) History of diabetes 0 1.00 (Reference) 1 1.24 0.33 3.80 < .001 3.44 (1.82 ~ 6.52) History of hypertension 0 1.00 (Reference) 1 0.04 0.29 0.14 0.889 1.04 (0.59 ~ 1.83) History of coronary heart disease 0 1.00 (Reference) 1 0.19 0.37 0.51 0.612 1.21 (0.58 ~ 2.49) Hydroperitoneum 0 1.00 (Reference) 1 0.86 0.29 2.95 0.003 2.36 (1.34 ~ 4.19) Hepatic encephalopathy 0 1.00 (Reference) 1 1.22 0.29 4.18 < .001 3.39 (1.91 ~ 6.00) Low protein 0 1.00 (Reference) 1 0.24 0.27 0.88 0.378 1.27 (0.74 ~ 2.18) DD 0 1.00 (Reference) 1 1.36 0.37 3.71 < .001 3.91 (1.90 ~ 8.03) 3.4 Multifactorial analysis The eight risk factors derived from the univariate analysis of this study were further included in the multivariate analysis, which showed that age, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were independent risk factors for the development of lower limb deep vein thrombosis in postoperative liver transplant patients. See Table 4 for details. Table 4 Multifactor Logistic Regression Analysis Based on Training Set Variables β S.E Z P OR (95%CI) Intercept -4.15 0.54 -7.67 < .001 0.02 (0.01 ~ 0.05) Age 0 1.00 (Reference) 1 0.86 0.33 2.58 0.010 2.36 (1.23 ~ 4.53) History of diabetes 0 1.00 (Reference) 1 1.43 0.37 3.81 < .001 4.17 (2.00 ~ 8.69) Hydroperitoneum 0 1.00 (Reference) 1 0.88 0.34 2.61 0.009 2.40 (1.24 ~ 4.65) Hepatic encephalopathy 0 1.00 (Reference) 1 1.46 0.34 4.31 < .001 4.30 (2.21 ~ 8.35) DD 0 1.00 (Reference) 1 1.56 0.41 3.78 < .001 4.77 (2.12 ~ 10.73) 3.5 Plotting of nomograms A nomogram of the risk of developing lower limb deep vein thrombosis in liver transplant patients after surgery was constructed based on five independent predictors tested by multifactorial logistic regression analysis, as shown in Fig. 1 . Nomo score assigned to each independent risk factor. The total score is derived by summing the clinical characteristics of the patient based on that patient's clinical characteristics, positioned on the Total points axis, and the value on the Risk axis corresponding vertically downward is the probability that the patient will develop DVT in the lower extremities. The score for each independent predictor corresponds to the upper limit of the score for each independent predictor, and the total score for each subject is the sum of the scores for each independent predictor. The probability of developing lower-extremity DVT was determined by the total score on the axis of risk of developing lower-extremity DVT in liver transplant patients after surgery. The model was subsequently validated internally, and the internal validation was carried out by repeating the sampling of the nomograms 1000 times using the Bootstrap method in the R software. The calibration curve is close to the ideal curve, indicating that the nomogram predicts the incidence of lower limb deep vein thrombosis in liver transplant patients presenting after surgery with a high degree of agreement with the actual incidence, reflecting a good predictive performance, see Fig. 2 . The ROC curve for this nomogram training set, with an AUC of 0.818 (95% CI = 0.768–0.868), and for the validation set, with an AUC of 0.707 (95% CI = 0.614–0.801), is shown in Fig. 3 . This nomogram is shown to be a good discriminator between liver transplant recipients at high risk of developing lower extremity deep vein thrombosis after surgery. The decision curve (DCA) for this nomogram shows that the model provides more net benefits than the ‘all intervene’ or ‘none intervene’ strategies when the threshold probability of an individual is greater than 0.05 in this column. This finding suggests that the nomogram model has a good clinical application in predicting the development of lower limb deep vein thrombosis in liver transplant patients after surgery, see Fig. 4 for details. 4. Discussion Liver transplantation, as a key treatment for end-stage liver disease, significantly improves the survival rate of patients, but postoperative deep vein thrombosis (DVT) of the lower limbs is a complication that seriously affects the recovery process and long-term prognosis of patients [ 5 ] . Risk factors have been explored in previous studies; however, there is not yet a high degree of agreement on the conclusions due to differences in study samples, geographic location, and methodology. Some studies have focused on patients' own underlying conditions, such as age and comorbidities; some have focused on surgery-related factors, such as length of surgery and intraoperative blood loss; although these studies have their own findings, they still have limitations. In view of this, the present study is expected to systematically sort out the risk factors of postoperative lower extremity deep vein thrombosis in liver transplantation patients through in-depth analysis, aiming to accurately identify the key factors, and to provide a solid basis for the clinical development of scientific and effective preventive and interventional measures, so as to reduce the incidence of DVT and improve the prognosis of the patients. 4.1 Review of the Background and Purpose of the Study A number of large overseas studies have shown that the incidence of DVT after liver transplantation should not be underestimated. Several single-centre or regional collaborative studies have shown that the incidence of postoperative DVT in Chinese liver transplant recipients is similar to that reported abroad, and the actual number of cases should not be underestimated due to the large population base. This not only increases the length of hospitalisation and medical costs, but may also lead to long-term complications such as chronic thromboembolic pulmonary hypertension, placing a heavy burden on the patient's family and society [ 5 ] . This study focuses on risk factors in depth from multiple dimensions. In terms of the patient's own factors, in addition to basic factors such as age and gender, the focus is on the patient's preoperative hepatic function status and the degree of coagulation dysfunction. Patients with severely impaired preoperative liver function, such as those with high Child - Turcotte - Pugh scores, have an imbalance in the liver's ability to synthesise coagulation factors and anticoagulant proteins, which may increase the tendency to thrombosis [ 12 ] . At the same time, dynamic changes in coagulation indices such as D-dimer and fibrinogen levels may also be closely related to the occurrence of postoperative DVT. The length of surgery, the amount of intraoperative bleeding and blood transfusion may have an impact on the occurrence of postoperative DVT. Prolonged surgical manipulation can lead to slow venous blood flow in the patient's lower limbs, while intraoperative blood loss and transfusion may further disturb the balance of the coagulation system. In addition, the choice of liver transplantation procedure, such as classical in situ versus backpack liver transplantation, has a different degree of postoperative vascular endothelial injury, which in turn affects the risk of DVT. In addition, the type and dose of postoperative immunosuppressive agents used may affect the body's immune status and coagulation. For example, while inhibiting immune rejection, calcineurin phosphatase inhibitors may cause some damage to vascular endothelial cells and increase the risk of thrombosis. In addition, the postoperative activity status of the patient and whether or not early rehabilitation exercises are carried out are also closely related to the occurrence of DVT [ 12 , 13 ] . By comprehensively and thoroughly analysing these risk factors, this study expects to establish a more accurate risk assessment model to guide clinicians to stratify the management of post-liver transplantation patients and take targeted preventive measures to reduce the incidence of lower limb deep vein thrombosis and to improve the prognosis of patients. 4.2 In-depth analysis of the findings and comparison with previous studies IDENTIFICATION OF POTENTIAL RISK FACTORS: Univariate logistic regression analysis identified age, history of alcohol consumption, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer as potential risk factors for lower extremity DVT after liver transplantation, P < 0.2. This study confirms that age is an independent risk factor for DVT after liver transplantation. With age, the vessel wall gradually undergoes degenerative changes, elastic fibres are reduced, the function of vascular endothelial cells is impaired, and the secretion of vasodilatory substances such as nitric oxide is reduced, leading to vasoconstriction and slower blood flow [ 12 ] . At the same time, the elderly have relatively high coagulation factor activity, reduced fibrinolytic activity, and the blood is in a relatively hypercoagulable state, and all these factors work together to make elderly patients more prone to postoperative DVT. In addition, long-term hyperglycaemia in diabetic patients can trigger damage to the vascular endothelium, exposing subendothelial collagen, activating platelets and coagulation factors, and initiating the coagulation process [ 12 ] . In addition, high blood glucose can lead to decreased deformability of red blood cells and increased blood viscosity, further promoting thrombosis. In the post-liver transplantation period, when the body is under stress and blood glucose fluctuates more, this hypercoagulable tendency is more pronounced in diabetic patients, and the risk of DVT is significantly increased [ 14 ] . The presence of ascites increases intra-abdominal pressure, which compresses the inferior vena cava and lower limb veins, leading to obstruction of venous return to the lower limbs and stagnation of blood. At the same time, ascites contains a variety of biologically active substances that can affect the balance of the coagulation and fibrinolytic systems and promote thrombosis. Studies have shown that the incidence of postoperative DVT is significantly higher in patients with a large amount of ascites than in patients with less or no ascites [ 5 ] . In addition, studies have confirmed that liver detoxification is severely impaired in patients with hepatic encephalopathy, and toxic substances such as ammonia accumulate in the body, interfering with normal neuroendocrine regulation and coagulation-anticoagulation balance. Ammonia inhibits the aggregation and release function of platelets, as well as affecting the normal metabolism of vascular endothelial cells, which weakens their anticoagulant effect [ 5 ] . In addition, patients with hepatic encephalopathy often have impaired consciousness and reduced activity, further increasing the risk of DVT. In addition, elevated levels of D-dimer, a degradation product of cross-linked fibrin, reflect activation of the coagulation and fibrinolytic systems in vivo. After liver transplantation, due to surgical trauma and tissue damage, the coagulation system is activated, fibrin is formed and cross-linked, and subsequently the fibrinolytic system is activated to degrade fibrin, leading to elevated levels of D - dimer [ 14 ] . In this study, the risk of DVT was significantly increased in patients with high postoperative D-dimer levels, suggesting that clinical practice can detect signs of thrombosis and take appropriate preventive and therapeutic measures through dynamic monitoring of D-dimer levels. In addition to the above independent risk factors, this study further analysed the possible effects of chronic alcohol consumption on liver function and coagulation mechanisms. Although not an independent risk factor in the multifactorial analysis, there was a potential association in the unifactorial analysis. It is hypothesised that it may indirectly affect blood coagulation status by affecting hepatic metabolism. In the study of risk factors for postoperative deep vein thrombosis (DVT) formation in the lower extremities of liver transplant patients, there are significant similarities between this study and several previous studies. Most studies have consistently shown that advanced age is one of the important risk factors for the development of DVT after liver transplantation. With age, the endothelial function of the body's blood vessels gradually declines, the elasticity of the vessel wall decreases, and haemodynamic changes occur, while the balance between the coagulation and anticoagulation systems is more likely to be dysfunctional, leading to an increased risk of thrombosis. For example, in a study of nearly 100 patients with cirrhosis in Europe and the United States, the incidence of postoperative DVT was found to be significantly higher in elderly patients than in younger patients [ 15 ] . In addition, preoperative coagulation abnormalities have likewise been collectively identified as a risk factor in several studies. Preoperative liver transplant patients often suffer from impaired liver function, which leads to impaired synthesis of coagulation factors as well as disorders of the fibrinolytic system, leaving the body in a hypercoagulable state. In this study, the incidence of postoperative DVT was significantly higher in patients with abnormal coagulation indices such as prolonged preoperative prothrombin time and elevated fibrinogen levels. Similarly, by analysing a large number of liver transplantation cases, it was found that abnormal preoperative coagulation indices were strongly associated with the occurrence of postoperative DVT [ 5 ] . In terms of sample selection and research methodology, there are certain commonalities among these studies. In terms of sample selection, most of them selected the group of patients who underwent liver transplantation, covering patients with end-stage liver disease caused by different etiologies, which is a good representation. In terms of research methodology, most studies used retrospective analysis to analyse the occurrence of postoperative DVT and related risk factors by collecting clinical data from patients. This commonality makes the results of different studies corroborate each other and strengthens the reliability of the importance of factors such as ‘advanced age’ and ‘preoperative coagulation abnormalities’ in the development of DVT after liver transplantation. Despite the similarities, there are also differences between the results of this study and some of the previous studies. Some foreign studies have suggested that there are differences in the risk of DVT after liver transplantation by specific races, such as a higher risk for patients of African descent compared to other races, however, this study did not reach a similar conclusion [ 5 ] . This may stem from the racial differences between the different study samples, with the racial composition of the foreign study samples being more complex, whereas the present study sample was predominantly a mono-ethnic population in the country, with a relatively homogeneous distribution of the underlying diseases and genetic backgrounds, thus not reflecting race-related differences. Some large-scale multicentre studies with sample sizes of up to thousands of cases are more sensitive in detecting risk factors and are able to identify some relatively weak but statistically significant risk factors. In contrast, the relatively small sample size of this study may have missed some rare or less potent risk factors. In addition, differences in observational metrics and duration of follow-up can lead to differences. Based on the results of the study, the authors considered that factors such as patients' physical recovery and adjustment of treatment regimen in different time periods may affect the occurrence of DVT, which may lead to different study results. 4.3 What is the clinical significance of predictive modelling Identifying independent risk factors for postoperative lower extremity deep vein thrombosis (DVT) in liver transplant recipients is of great clinical significance. Doctors can accurately stratify the risk of patients accordingly, and tailor personalised prevention programmes for high-risk groups in advance to enhance the effectiveness of prevention. Based on these findings, postoperative care should be strengthened in elderly patients to encourage early activity, promote blood circulation, and reduce the risk of thrombosis; Patients with diabetes mellitus require strict control of blood glucose levels, as high blood glucose may affect vascular endothelial function and increase the risk of DVT; Patients with ascites and hepatic encephalopathy should be treated aggressively for primary disease, improve liver function, and correct coagulation abnormalities. At the same time, postoperative D-dimer levels should be closely monitored and the anticoagulation regimen should be adjusted accordingly. These risk factors also guide the treatment of DVT. Patients respond differently to drug therapy in the context of different risk factors. For example, patients with comorbidities of multiple underlying diseases may need to have their anticoagulant dose adjusted to balance efficacy with the risk of bleeding. Clinicians can refer to these factors to select appropriate therapeutic drugs, dosage and course of treatment to improve the therapeutic effect, reduce complications and improve the prognosis of liver transplant patients. 4.4 Research limitations and future research directions In this study of risk factors for postoperative lower extremity deep vein thrombosis in liver transplant recipients, certain limitations exist. The sample source for this study was relatively limited, focusing on selected medical centres in specific regions, which makes it difficult to represent all regions and ethnicities of liver transplant patients worldwide. Environmental factors and differences in medical care in different regions, as well as differences in genetic backgrounds of different races, may have an impact on the occurrence of postoperative lower extremity DVT, but were not adequately represented in this study. In addition, the sample size was relatively limited, and some risk factors with weak but possible associations were not identified due to insufficient sample size, affecting the comprehensiveness of the findings. This study used a retrospective study design, and although it was able to be analysed using the available clinical data, there is a risk of information bias. At the same time, there may be confounding factors not included in the analysis during the study that may interfere with the determination of the true relationship between risk factors and lower extremity DVT and reduce the accuracy of the results. Future research could be conducted in the following directions. Efforts should be made to expand the scope of the sample and collect data on a wide range of liver transplant recipients of different geographic and ethnic origins, so that the results of the study can be more generalised and provide a more reliable basis for prevention and treatment on a global scale. In addition, new potential risk factors should be actively explored, such as in-depth study of factors at the genetic level, mining the association between different gene polymorphisms and thrombosis, or searching for new biomarkers, to provide new ideas and targets for early diagnosis and prevention of DVT in the lower limbs. 5. Conclusions The present study has been analysed systematically and rigorously to show conclusively that age, history of diabetes mellitus, ascites, hepatic encephalopathy and postoperative D-dimer levels, are independent risk factors for lower limb deep vein thrombosis in patients after liver transplantation. This result is significant for clinical work and reminds physicians to focus their attention on high-risk patients who are accompanied by these factors. For example, in the case of elderly people with diabetes mellitus, blood glucose control is strengthened; in the case of people with ascites and hepatic encephalopathy, active treatment is given to improve their conditions; For all patients, postoperative D-dimer changes were closely followed. Through these targeted monitoring and preventive measures, it may be possible to reduce the incidence of lower extremity DVT, help patients recover better after surgery, improve long-term quality of life, and improve the overall prognosis. Declarations Ethics approval and consent to participate: We obtained a waiver of informed consent from the Ethics Committee. The research was approved by the Ethics Committee of The Third Hospital of Hebei Medical University. And the Number is W2024-133-010. Conflict of interest: The author declare that they have no conflicts of interest. Funding: Xiaoqing Zhang is funded by Medical Science Research Project of Hebei: Hebei Provincial Health Commission(Number:20242250). Author Contribution Xiaoqing Zhang and Ruisi Ma participated in case collection.Xiaoqing Zhang, Ruisi Ma and Yingying Wang wrote the manuscript and raised idea. Jinghui Yan, Jiaxing Zhu, Jie Wei and Yanmin Shi revised the manuscript and raised critical editing. The author have read and approved the manuscript. Acknowledgements: None. Data Availability The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.If you need to ask us for the data of this study, please contact Yingying Wang, [email protected] . References Bodzin AS, Baker TB. Liver Transplantation Today: Where We Are Now and Where We Are Going. Liver Transpl. 2018;24(10):1470–75. 10.1002/lt.25320 . Iacob S, Gheorghe L. Long Term Follow-up of Liver Transplant Recipients: Considerations for Non-transplant Specialists. J Gastrointestin Liver Dis. 2021;30(2):283–90. 10.15403/jgld-3616 . Martin Saborido C, Borobia AM, Cobas J, et al. Effectiveness of immunosuppression minimisation, conversion or withdrawal strategies in paediatric solid organ and haematopoietic stem cell transplantation: a protocol of a systematic review and meta-analysis. BMJ Open. 2020;10(12):e037721. 10.1136/bmjopen-2020-037721 . Annamalai A, Kim I, Sundaram V, et al. Incidence and risk factors of deep vein thrombosis after liver transplantation. Transpl Proc. 2014;46(10):3564–9. 10.1016/j.transproceed.2014.09.113 . Emuakhagbon V, Philips P, Agopian V, et al. Incidence and risk factors for deep venous thrombosis and pulmonary embolus after liver transplantation. Am J Surg. 2016;211(4):768–71. 10.1016/j.amjsurg.2015.11.028 . Balaceanu A. Deep vein thrombosis during long-term surveillance of patients with liver transplantation. Ir J Med Sci. 2019;188(4):1191–93. 10.1007/s11845-019-01998-6 . Lou TW, Yang RX, Fan JG. The global burden of fatty liver disease: the major impact of China. Hepatobiliary Surg Nutr. 2024;13(1):119–23. 10.21037/hbsn-23-556 . Wang FS, Fan JG, Zhang Z, et al. The global burden of liver disease: the major impact of China. Hepatology. 2014;60(6):2099–108. 10.1002/hep.27406 . Ghaziani T, Sendi H, Shahraz S, et al. Hepatitis B and liver transplantation: molecular and clinical features that influence recurrence and outcome. World J Gastroenterol. 2014;20(39):14142–55. 10.3748/wjg.v20.i39.14142 . Wang C, Zou Y, Pan C, et al. Prognostic significance of chemokines CCL11 and CCL5 modulated by low-density lipoprotein cholesterol in colon cancer patients with normal body mass index. Ann Transl Med. 2021;9(3):202. 10.21037/atm-20-1604 . Zhang Y, Chen L, Chen H. A meta-analysis of the correlation between non-steroidal anti-inflammatory drugs and recurrent colorectal adenomatous polyps. Am J Transl Res. 2021;13(4):2432–38. Salami A, Qureshi W, Kuriakose P, et al. Frequency and predictors of venous thromboembolism in orthotopic liver transplant recipients: a single-center retrospective review. Transpl Proc. 2013;45(1):315–9. 10.1016/j.transproceed.2012.06.060 . Mukerji AN, Karachristos A, Maloo M, et al. Do postliver transplant patients need thromboprophylactic anticoagulation? Clin Appl Thromb Hemost. 2014;20(7):673–7. 10.1177/1076029614538490 . Law Y, Chan YC, Cheng SWK. Epidemiological updates of venous thromboembolism in a Chinese population. Asian J Surg. 2018;41(2):176–82. 10.1016/j.asjsur.2016.11.005 . Khanna R, Sarin SK. Non-cirrhotic portal hypertension - diagnosis and management. J Hepatol. 2014;60(2):421–41. 10.1016/j.jhep.2013.08.013 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 10 Feb, 2026 Read the published version in BMC Surgery → Version 1 posted Editorial decision: Revision requested 29 Sep, 2025 Reviews received at journal 09 Sep, 2025 Reviews received at journal 08 Sep, 2025 Reviews received at journal 08 Sep, 2025 Reviewers agreed at journal 05 Sep, 2025 Reviews received at journal 04 Sep, 2025 Reviews received at journal 31 Aug, 2025 Reviewers agreed at journal 30 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 28 Aug, 2025 Reviewers agreed at journal 27 Aug, 2025 Reviewers invited by journal 27 Aug, 2025 Editor invited by journal 12 Jun, 2025 Editor assigned by journal 10 Jun, 2025 Submission checks completed at journal 10 Jun, 2025 First submitted to journal 31 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6790586","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":508539864,"identity":"b575a8b4-1630-4da6-be9d-19e3f3b33fcb","order_by":0,"name":"Xiaoqing Zhang","email":"","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqing","middleName":"","lastName":"Zhang","suffix":""},{"id":508539865,"identity":"56ff3207-94b9-4c2d-a240-166537be9ac9","order_by":1,"name":"Ruisi Ma","email":"","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ruisi","middleName":"","lastName":"Ma","suffix":""},{"id":508539866,"identity":"f034c64a-ad8d-4a72-b376-1daafe52e375","order_by":2,"name":"Jinghui Yan","email":"","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jinghui","middleName":"","lastName":"Yan","suffix":""},{"id":508539867,"identity":"8f9b456c-3011-45e3-842b-2a72392c8c07","order_by":3,"name":"Jiaxing Zhu","email":"","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiaxing","middleName":"","lastName":"Zhu","suffix":""},{"id":508539868,"identity":"a043733d-d64e-4084-8bde-3829dc994e62","order_by":4,"name":"Jie Wei","email":"","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Wei","suffix":""},{"id":508539869,"identity":"be58b48b-9567-4c99-8f60-e7e034865d98","order_by":5,"name":"Yanmin Shi","email":"","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yanmin","middleName":"","lastName":"Shi","suffix":""},{"id":508539870,"identity":"14646771-5ceb-4b3a-a03b-eb2359a99c15","order_by":6,"name":"Yingying Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA5klEQVRIiWNgGAWjYBACNvmDzQ8SDGzk+NkbGx8k/LAhrIVPgvmYwYeCNGPJnsPNBg970ghrkZNgS5Cc8eFwosGN9DbJB2yHiXCYdI+BMY9BWgLDgcS2igSewwz87d0J+LXInDF4zGNgk8fYcLDtRoJFOoPEmbMb8GthyAHbUszM2AjUwmPNYCCRS1iLNI/B4cQ2Zsa2ggQ2ZiK0SKQBvQ/U0sPG2MaQwOZMhBaew8BANkgzluBhbJZI7EnjIegX+fZGYFT+sZGzv//84ccfP4Bx2t6LXwsG4CFN+SgYBaNgFIwCrAAAvExKPg4uj+8AAAAASUVORK5CYII=","orcid":"","institution":"The Third Hospital of Hebei Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2025-05-31 11:08:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6790586/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6790586/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12893-025-03378-7","type":"published","date":"2026-02-10T15:58:41+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":90543648,"identity":"e3c65a0b-2a85-4194-96c4-47ee7ff8c10d","added_by":"auto","created_at":"2025-09-04 00:13:41","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43150,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6790586/v1/7082c78e7e0b2086d17b26e7.jpg"},{"id":90544856,"identity":"0c36a415-7797-4d4e-b6b4-3bed09d1d443","added_by":"auto","created_at":"2025-09-04 00:21:41","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":36354,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6790586/v1/5e25e7b50b3ba8b50559cb66.jpg"},{"id":90543654,"identity":"ea6afd4e-588e-4b9d-88e1-dd1e13943268","added_by":"auto","created_at":"2025-09-04 00:13:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":36892,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6790586/v1/ea7f2751fca117b1c440a180.jpg"},{"id":90544858,"identity":"ba41fa80-868a-48ea-85a8-a03ae3ad65cb","added_by":"auto","created_at":"2025-09-04 00:21:41","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":31447,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6790586/v1/88bd5731a8ad4032aa3803d5.jpg"},{"id":102785717,"identity":"616e29a2-b515-4ed8-a3db-b62912104307","added_by":"auto","created_at":"2026-02-16 16:09:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1302000,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6790586/v1/c983a9b9-de4d-49fd-9dbd-ab5e019579a3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Analysis of risk factors for postoperative lower extremity deep vein thrombosis in liver transplant patients","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eLiver transplantation is an effective treatment for end-stage liver disease and significantly improves patient survival and quality of life\u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. However, various types of postoperative complications have a serious impact on the prognosis of patients, among which deep vein thrombosis (DVT) of the lower limbs is one of the more common and dangerous ones, which has many adverse effects on the prognosis of patients\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e. A large retrospective study in the United States involving multiple centres, which included nearly 1,000 liver transplant patients, showed that the incidence of postoperative DVT was approximately 10% \u0026minus;\u0026thinsp;15%\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Studies have pointed out that patients' own factors, such as advanced age, obesity, and comorbid diabetes mellitus, increase blood viscosity and alter haemodynamics, which are important risk factors for the development of DVT\u003csup\u003e[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In addition, surgery-related factors, such as long surgery times and large intraoperative blood transfusions, can cause damage to the vascular endothelium, activate the coagulation system, and contribute to thrombus formation. Related studies in Europe have similarly shown that prolonged extracorporeal circulation diversion disrupts the coagulation-anticoagulation balance and is one of the key factors in the high incidence of postoperative DVT\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Due to the differences in the etiology of end-stage liver disease in China and abroad, hepatitis B cirrhosis leads to a higher percentage of liver transplant patients\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. It has been shown that hepatitis B virus infection may affect immunomodulation and coagulation, increasing the risk of postoperative DVT in these patients\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. In addition, national studies have focused on the impact of the patient's postoperative rehabilitation environment and level of care on the occurrence of DVT. Due to the differences in medical resources and nursing concepts in different regions, the implementation of preventive measures such as early postoperative activity guidance and stress treatment for patients is uneven, which also affects the incidence of DVT to a certain extent\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. In conclusion, despite the progress of research on the risk factors of DVT after liver transplantation both at home and abroad, in view of the differences in the disease spectrum and medical environment of patients in different regions, in-depth analysis of the relevant risk factors is of great significance in formulating preventive strategies suitable for China's national conditions, reducing the incidence of postoperative DVT in patients undergoing liver transplantation, and improving the prognosis of the patients.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e2.1 \u003cstrong\u003eResearch object\u003c/strong\u003e: This study was conducted on 425 patients who underwent liver transplantation in the Third Hospital of Hebei Medical University from January 2021 to June 2024, including 300 males and 125 females. We obtained a waiver of informed consent from the Ethics Committee. The research was approved by the Ethics Committee of The Third Hospital of Hebei Medical University. And the Number is W2024-133-010. Clinical trial number: not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003e2.2 \u003cstrong\u003eResearch Methods\u003c/strong\u003e: In this retrospective case-control study, 425 patients were collected, out of which 110 patients developed lower limb deep vein thrombosis after liver transplantation. Information about the patients\u0026apos; past medical history and hospitalisation period was collected separately to study the correlating factors affecting the development of lower limb deep vein thrombosis in liver transplant patients after surgery.\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003e2.3 \u003cstrong\u003eCollection of indicators\u003c/strong\u003e: Gender, age, BMI, history of smoking, history of alcohol consumption, history of diabetes mellitus, history of hypertension, history of coronary artery disease, incidence of ascites, incidence of hepatic encephalopathy, duration of surgery, hypoproteinemia, and D-dimer were collected from the patients in this study.\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e2.4 \u003cstrong\u003eInclusion and exclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e2.4.1 \u003cstrong\u003eInclusion criteria\u003c/strong\u003e: (1) all underwent allogeneic in situ liver transplantation; (2) age\u0026thinsp;\u0026ge;\u0026thinsp;18 years; (3) complete and complete clinical data; and (4) colour ultrasound of the deep veins of the lower limbs was feasible on day 7 after liver transplantation;\u003c/p\u003e\n\u003c/span\u003e\u003cspan\u003e\n \u003cp\u003e2.4.2 \u003cstrong\u003eExclusion criteria\u003c/strong\u003e: (1) combined with other organ transplants; (2) preoperatively diagnosed with lower limb deep vein thrombosis; (3) loss of motor function of the lower limbs; (4) receiving anticoagulant therapy; (5) patients with other serious pre-existing illnesses or psychiatric abnormalities; and (6) undergoing other treatments or participating in other clinical studies.\u003c/p\u003e\n\u003c/span\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 \u003cstrong\u003eInterpretation of relevant indicators mentioned in this study\u003c/strong\u003e:\u003c/h2\u003e\n \u003cp\u003eLower extremity deep vein thrombosis: This study investigated the factors associated with the development of lower extremity deep vein thrombosis in patients after liver transplantation, therefore routine lower extremity deep vein ultrasound was performed preoperatively to clarify the condition, and patients who developed lower extremity deep vein thrombosis preoperatively were excluded from this study.\u003c/p\u003e\n \u003cp\u003e2.6 \u003cstrong\u003eStatistical method\u003c/strong\u003e: SPSS 25.0 was used for data processing and statistical analysis in this study. Quantitative data conforming to normal distribution were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation, and the differences between groups were analyzed by independent sample T test. Comparisons between groups that did not follow a normal distribution were performed using nonparametric tests. Data for qualitative data were expressed as number of cases and percentage, and chi-square tests were used to determine whether there were differences between groups. First, the patients were divided into the training set and the validation set in a 7:3 ratio by complete randomisation, and then the occurrence of lower limb deep vein thrombosis in the patients in the training set was analysed based on the factors such as the occurrence of lower limb deep vein thrombosis and various clinically relevant indexes, and then based on the one-way logistic regression analysis of the collected data, the potential risk factors for the occurrence of lower limb deep vein thrombosis in the patients with liver transplantation were determined. For the univariate analysis, exposure factors with P\u0026thinsp;\u0026le;\u0026thinsp;0.2 were selected and included in the multivariate analysis\u003csup\u003e[\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. Independent risk factors associated with the development of lower limb deep vein thrombosis in liver transplant recipients were derived, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered a statistically significant difference. The model was then internally validated to further confirm the reliability of the predictive model derived from this study.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1 \u003cb\u003eTable of values assigned to the relevant indicators in this study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSee Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e for details.\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\u003eTable of values assigned to the relevant indicators\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eName\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eVariable assignment and description\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeep vein thrombosis of the lower limbs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo-0, Yes-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale-0, Male-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026lt;60 years-0, \u0026ge;\u0026thinsp;60 years-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of smoking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo-0, Yes-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of hypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo-0, Yes-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepatic encephalopathy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo-0, Yes-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eD-dimer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNormal-0, Raise-1\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\u003e3.2 \u003cb\u003eTable of baseline characteristics of patients in both groups\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe randomly divided the patients included in this experimental study into a training set and a validation set in a ratio of 7:3. There were 297 patients in the training set and 128 patients in the validation set. The general information of the patients in both groups was included in the statistical study, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05, and the differences in the baseline characteristics of both groups were not statistically significant, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of baseline features between training and validation sets\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=\"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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;425)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003etest (n\u0026thinsp;=\u0026thinsp;128)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003etrain (n\u0026thinsp;=\u0026thinsp;297)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.11\u0026thinsp;\u0026plusmn;\u0026thinsp;2.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.23\u0026thinsp;\u0026plusmn;\u0026thinsp;2.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u0026thinsp;=\u0026thinsp;0.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.554\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSurgical time\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.60\u0026thinsp;\u0026plusmn;\u0026thinsp;1.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.709\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDVT, n(%)\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\u003cp\u003eχ\u0026sup2;=1.38\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\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e315 (74.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e90 (70.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e225 (75.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e110 (25.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38 (29.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72 (24.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGender, n(%)\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\u003cp\u003eχ\u0026sup2;=1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.312\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e125 (29.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (32.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83 (27.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e300 (70.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (67.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e214 (72.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, n(%)\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\u003cp\u003eχ\u0026sup2;=0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.795\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e190 (44.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56 (43.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e134 (45.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e235 (55.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72 (56.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e163 (54.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking history, n(%)\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\u003cp\u003eχ\u0026sup2;=0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.581\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e184 (43.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (45.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e126 (42.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e241 (56.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (54.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e171 (57.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrinking history, n(%)\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\u003cp\u003eχ\u0026sup2;=0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.706\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e235 (55.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69 (53.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e166 (55.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e190 (44.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e59 (46.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e131 (44.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of diabetes, n(%)\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\u003cp\u003eχ\u0026sup2;=1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.296\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e348 (81.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101 (78.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e247 (83.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e77 (18.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (21.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e50 (16.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of hypertension, n(%)\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\u003cp\u003eχ\u0026sup2;=2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.114\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e276 (64.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 (59.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e200 (67.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e149 (35.06)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (40.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (32.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of coronary heart disease, n(%)\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\u003cp\u003eχ\u0026sup2;=0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.994\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e362 (85.18)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e109 (85.16)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e253 (85.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e63 (14.82)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (14.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44 (14.81)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHydroperitoneum (, n(%)\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\u003cp\u003eχ\u0026sup2;=0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.895\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e188 (44.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e56 (43.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132 (44.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e237 (55.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72 (56.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e165 (55.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepatic encephalopathy, n(%)\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\u003cp\u003eχ\u0026sup2;=0.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.433\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e313 (73.65)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (71.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e222 (74.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e112 (26.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37 (28.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75 (25.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow protein, n(%)\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\u003cp\u003eχ\u0026sup2;=0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.428\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e185 (43.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (40.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e133 (44.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e240 (56.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 (59.38)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e164 (55.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDD, n(%)\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\u003cp\u003eχ\u0026sup2;=0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.417\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e144 (33.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 (36.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (32.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\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\u003e281 (66.12)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 (63.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e200 (67.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e3.3 \u003cb\u003eOne-way analysis of variance\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eA training set of 297 patients were included in the statistical analysis, of which 72 patients developed lower limb deep vein thrombosis after liver transplantation. Possibly relevant factors were included in a one-way logistic regression, in which age, history of alcohol consumption, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were potential risk factors for patients to develop lower extremity DVT after liver transplantation, P\u0026thinsp;\u0026lt;\u0026thinsp;0.2. See Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e for details.\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 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eOne-Factor Logistic Regression Analysis Based on Training Set\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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR (95%CI)\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.523\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.22 (0.66\u0026thinsp;~\u0026thinsp;2.23)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.19 (1.76\u0026thinsp;~\u0026thinsp;5.78)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking history\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.31 (0.76\u0026thinsp;~\u0026thinsp;2.26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrinking history\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.090\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.59 (0.93\u0026thinsp;~\u0026thinsp;2.70)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of 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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.44 (1.82\u0026thinsp;~\u0026thinsp;6.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of 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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.04 (0.59\u0026thinsp;~\u0026thinsp;1.83)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of coronary 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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.21 (0.58\u0026thinsp;~\u0026thinsp;2.49)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHydroperitoneum\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.36 (1.34\u0026thinsp;~\u0026thinsp;4.19)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepatic encephalopathy\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.39 (1.91\u0026thinsp;~\u0026thinsp;6.00)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow protein\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.378\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.27 (0.74\u0026thinsp;~\u0026thinsp;2.18)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDD\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.91 (1.90\u0026thinsp;~\u0026thinsp;8.03)\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=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e3.4 \u003cb\u003eMultifactorial analysis\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eThe eight risk factors derived from the univariate analysis of this study were further included in the multivariate analysis, which showed that age, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were independent risk factors for the development of lower limb deep vein thrombosis in postoperative liver transplant patients. See Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e for details.\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 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultifactor Logistic Regression Analysis Based on Training Set\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=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR (95%CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIntercept\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-4.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-7.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.02 (0.01\u0026thinsp;~\u0026thinsp;0.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.36 (1.23\u0026thinsp;~\u0026thinsp;4.53)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHistory of 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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.17 (2.00\u0026thinsp;~\u0026thinsp;8.69)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHydroperitoneum\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e2.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.40 (1.24\u0026thinsp;~\u0026thinsp;4.65)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepatic encephalopathy\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.30 (2.21\u0026thinsp;~\u0026thinsp;8.35)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDD\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\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\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.00 (Reference)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e3.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.77 (2.12\u0026thinsp;~\u0026thinsp;10.73)\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=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e3.5 \u003cb\u003ePlotting of nomograms\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eA nomogram of the risk of developing lower limb deep vein thrombosis in liver transplant patients after surgery was constructed based on five independent predictors tested by multifactorial logistic regression analysis, as shown in \u003cb\u003eFig.\u0026nbsp;1\u003c/b\u003e. Nomo score assigned to each independent risk factor. The total score is derived by summing the clinical characteristics of the patient based on that patient's clinical characteristics, positioned on the Total points axis, and the value on the Risk axis corresponding vertically downward is the probability that the patient will develop DVT in the lower extremities. The score for each independent predictor corresponds to the upper limit of the score for each independent predictor, and the total score for each subject is the sum of the scores for each independent predictor. The probability of developing lower-extremity DVT was determined by the total score on the axis of risk of developing lower-extremity DVT in liver transplant patients after surgery. The model was subsequently validated internally, and the internal validation was carried out by repeating the sampling of the nomograms 1000 times using the Bootstrap method in the R software. The calibration curve is close to the ideal curve, indicating that the nomogram predicts the incidence of lower limb deep vein thrombosis in liver transplant patients presenting after surgery with a high degree of agreement with the actual incidence, reflecting a good predictive performance, see \u003cb\u003eFig.\u0026nbsp;2\u003c/b\u003e. The ROC curve for this nomogram training set, with an AUC of 0.818 (95% CI\u0026thinsp;=\u0026thinsp;0.768\u0026ndash;0.868), and for the validation set, with an AUC of 0.707 (95% CI\u0026thinsp;=\u0026thinsp;0.614\u0026ndash;0.801), is shown in \u003cb\u003eFig.\u0026nbsp;3\u003c/b\u003e. This nomogram is shown to be a good discriminator between liver transplant recipients at high risk of developing lower extremity deep vein thrombosis after surgery. The decision curve (DCA) for this nomogram shows that the model provides more net benefits than the \u0026lsquo;all intervene\u0026rsquo; or \u0026lsquo;none intervene\u0026rsquo; strategies when the threshold probability of an individual is greater than 0.05 in this column. This finding suggests that the nomogram model has a good clinical application in predicting the development of lower limb deep vein thrombosis in liver transplant patients after surgery, see \u003cb\u003eFig.\u0026nbsp;4\u003c/b\u003e for details.\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eLiver transplantation, as a key treatment for end-stage liver disease, significantly improves the survival rate of patients, but postoperative deep vein thrombosis (DVT) of the lower limbs is a complication that seriously affects the recovery process and long-term prognosis of patients\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Risk factors have been explored in previous studies; however, there is not yet a high degree of agreement on the conclusions due to differences in study samples, geographic location, and methodology. Some studies have focused on patients' own underlying conditions, such as age and comorbidities; some have focused on surgery-related factors, such as length of surgery and intraoperative blood loss; although these studies have their own findings, they still have limitations. In view of this, the present study is expected to systematically sort out the risk factors of postoperative lower extremity deep vein thrombosis in liver transplantation patients through in-depth analysis, aiming to accurately identify the key factors, and to provide a solid basis for the clinical development of scientific and effective preventive and interventional measures, so as to reduce the incidence of DVT and improve the prognosis of the patients.\u003c/p\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e4.1 \u003cb\u003eReview of the Background and Purpose of the Study\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eA number of large overseas studies have shown that the incidence of DVT after liver transplantation should not be underestimated. Several single-centre or regional collaborative studies have shown that the incidence of postoperative DVT in Chinese liver transplant recipients is similar to that reported abroad, and the actual number of cases should not be underestimated due to the large population base. This not only increases the length of hospitalisation and medical costs, but may also lead to long-term complications such as chronic thromboembolic pulmonary hypertension, placing a heavy burden on the patient's family and society\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. This study focuses on risk factors in depth from multiple dimensions. In terms of the patient's own factors, in addition to basic factors such as age and gender, the focus is on the patient's preoperative hepatic function status and the degree of coagulation dysfunction. Patients with severely impaired preoperative liver function, such as those with high Child - Turcotte - Pugh scores, have an imbalance in the liver's ability to synthesise coagulation factors and anticoagulant proteins, which may increase the tendency to thrombosis\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. At the same time, dynamic changes in coagulation indices such as D-dimer and fibrinogen levels may also be closely related to the occurrence of postoperative DVT. The length of surgery, the amount of intraoperative bleeding and blood transfusion may have an impact on the occurrence of postoperative DVT. Prolonged surgical manipulation can lead to slow venous blood flow in the patient's lower limbs, while intraoperative blood loss and transfusion may further disturb the balance of the coagulation system. In addition, the choice of liver transplantation procedure, such as classical in situ versus backpack liver transplantation, has a different degree of postoperative vascular endothelial injury, which in turn affects the risk of DVT. In addition, the type and dose of postoperative immunosuppressive agents used may affect the body's immune status and coagulation. For example, while inhibiting immune rejection, calcineurin phosphatase inhibitors may cause some damage to vascular endothelial cells and increase the risk of thrombosis. In addition, the postoperative activity status of the patient and whether or not early rehabilitation exercises are carried out are also closely related to the occurrence of DVT\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. By comprehensively and thoroughly analysing these risk factors, this study expects to establish a more accurate risk assessment model to guide clinicians to stratify the management of post-liver transplantation patients and take targeted preventive measures to reduce the incidence of lower limb deep vein thrombosis and to improve the prognosis of patients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e4.2 \u003cb\u003eIn-depth analysis of the findings and comparison with previous studies\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eIDENTIFICATION OF POTENTIAL RISK FACTORS: Univariate logistic regression analysis identified age, history of alcohol consumption, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer as potential risk factors for lower extremity DVT after liver transplantation, P\u0026thinsp;\u0026lt;\u0026thinsp;0.2.\u003c/p\u003e\u003cp\u003eThis study confirms that age is an independent risk factor for DVT after liver transplantation. With age, the vessel wall gradually undergoes degenerative changes, elastic fibres are reduced, the function of vascular endothelial cells is impaired, and the secretion of vasodilatory substances such as nitric oxide is reduced, leading to vasoconstriction and slower blood flow\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. At the same time, the elderly have relatively high coagulation factor activity, reduced fibrinolytic activity, and the blood is in a relatively hypercoagulable state, and all these factors work together to make elderly patients more prone to postoperative DVT. In addition, long-term hyperglycaemia in diabetic patients can trigger damage to the vascular endothelium, exposing subendothelial collagen, activating platelets and coagulation factors, and initiating the coagulation process\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. In addition, high blood glucose can lead to decreased deformability of red blood cells and increased blood viscosity, further promoting thrombosis. In the post-liver transplantation period, when the body is under stress and blood glucose fluctuates more, this hypercoagulable tendency is more pronounced in diabetic patients, and the risk of DVT is significantly increased\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. The presence of ascites increases intra-abdominal pressure, which compresses the inferior vena cava and lower limb veins, leading to obstruction of venous return to the lower limbs and stagnation of blood. At the same time, ascites contains a variety of biologically active substances that can affect the balance of the coagulation and fibrinolytic systems and promote thrombosis. Studies have shown that the incidence of postoperative DVT is significantly higher in patients with a large amount of ascites than in patients with less or no ascites\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. In addition, studies have confirmed that liver detoxification is severely impaired in patients with hepatic encephalopathy, and toxic substances such as ammonia accumulate in the body, interfering with normal neuroendocrine regulation and coagulation-anticoagulation balance. Ammonia inhibits the aggregation and release function of platelets, as well as affecting the normal metabolism of vascular endothelial cells, which weakens their anticoagulant effect\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. In addition, patients with hepatic encephalopathy often have impaired consciousness and reduced activity, further increasing the risk of DVT. In addition, elevated levels of D-dimer, a degradation product of cross-linked fibrin, reflect activation of the coagulation and fibrinolytic systems in vivo. After liver transplantation, due to surgical trauma and tissue damage, the coagulation system is activated, fibrin is formed and cross-linked, and subsequently the fibrinolytic system is activated to degrade fibrin, leading to elevated levels of D - dimer\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In this study, the risk of DVT was significantly increased in patients with high postoperative D-dimer levels, suggesting that clinical practice can detect signs of thrombosis and take appropriate preventive and therapeutic measures through dynamic monitoring of D-dimer levels.\u003c/p\u003e\u003cp\u003eIn addition to the above independent risk factors, this study further analysed the possible effects of chronic alcohol consumption on liver function and coagulation mechanisms. Although not an independent risk factor in the multifactorial analysis, there was a potential association in the unifactorial analysis. It is hypothesised that it may indirectly affect blood coagulation status by affecting hepatic metabolism.\u003c/p\u003e\u003cp\u003eIn the study of risk factors for postoperative deep vein thrombosis (DVT) formation in the lower extremities of liver transplant patients, there are significant similarities between this study and several previous studies. Most studies have consistently shown that advanced age is one of the important risk factors for the development of DVT after liver transplantation. With age, the endothelial function of the body's blood vessels gradually declines, the elasticity of the vessel wall decreases, and haemodynamic changes occur, while the balance between the coagulation and anticoagulation systems is more likely to be dysfunctional, leading to an increased risk of thrombosis. For example, in a study of nearly 100 patients with cirrhosis in Europe and the United States, the incidence of postoperative DVT was found to be significantly higher in elderly patients than in younger patients\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. In addition, preoperative coagulation abnormalities have likewise been collectively identified as a risk factor in several studies. Preoperative liver transplant patients often suffer from impaired liver function, which leads to impaired synthesis of coagulation factors as well as disorders of the fibrinolytic system, leaving the body in a hypercoagulable state. In this study, the incidence of postoperative DVT was significantly higher in patients with abnormal coagulation indices such as prolonged preoperative prothrombin time and elevated fibrinogen levels. Similarly, by analysing a large number of liver transplantation cases, it was found that abnormal preoperative coagulation indices were strongly associated with the occurrence of postoperative DVT\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn terms of sample selection and research methodology, there are certain commonalities among these studies. In terms of sample selection, most of them selected the group of patients who underwent liver transplantation, covering patients with end-stage liver disease caused by different etiologies, which is a good representation. In terms of research methodology, most studies used retrospective analysis to analyse the occurrence of postoperative DVT and related risk factors by collecting clinical data from patients. This commonality makes the results of different studies corroborate each other and strengthens the reliability of the importance of factors such as \u0026lsquo;advanced age\u0026rsquo; and \u0026lsquo;preoperative coagulation abnormalities\u0026rsquo; in the development of DVT after liver transplantation.\u003c/p\u003e\u003cp\u003eDespite the similarities, there are also differences between the results of this study and some of the previous studies. Some foreign studies have suggested that there are differences in the risk of DVT after liver transplantation by specific races, such as a higher risk for patients of African descent compared to other races, however, this study did not reach a similar conclusion\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. This may stem from the racial differences between the different study samples, with the racial composition of the foreign study samples being more complex, whereas the present study sample was predominantly a mono-ethnic population in the country, with a relatively homogeneous distribution of the underlying diseases and genetic backgrounds, thus not reflecting race-related differences. Some large-scale multicentre studies with sample sizes of up to thousands of cases are more sensitive in detecting risk factors and are able to identify some relatively weak but statistically significant risk factors. In contrast, the relatively small sample size of this study may have missed some rare or less potent risk factors. In addition, differences in observational metrics and duration of follow-up can lead to differences. Based on the results of the study, the authors considered that factors such as patients' physical recovery and adjustment of treatment regimen in different time periods may affect the occurrence of DVT, which may lead to different study results.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e4.3 \u003cb\u003eWhat is the clinical significance of predictive modelling\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eIdentifying independent risk factors for postoperative lower extremity deep vein thrombosis (DVT) in liver transplant recipients is of great clinical significance. Doctors can accurately stratify the risk of patients accordingly, and tailor personalised prevention programmes for high-risk groups in advance to enhance the effectiveness of prevention. Based on these findings, postoperative care should be strengthened in elderly patients to encourage early activity, promote blood circulation, and reduce the risk of thrombosis; Patients with diabetes mellitus require strict control of blood glucose levels, as high blood glucose may affect vascular endothelial function and increase the risk of DVT; Patients with ascites and hepatic encephalopathy should be treated aggressively for primary disease, improve liver function, and correct coagulation abnormalities. At the same time, postoperative D-dimer levels should be closely monitored and the anticoagulation regimen should be adjusted accordingly. These risk factors also guide the treatment of DVT. Patients respond differently to drug therapy in the context of different risk factors. For example, patients with comorbidities of multiple underlying diseases may need to have their anticoagulant dose adjusted to balance efficacy with the risk of bleeding. Clinicians can refer to these factors to select appropriate therapeutic drugs, dosage and course of treatment to improve the therapeutic effect, reduce complications and improve the prognosis of liver transplant patients.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e4.4 \u003cb\u003eResearch limitations and future research directions\u003c/b\u003e\u003c/h2\u003e\u003cp\u003eIn this study of risk factors for postoperative lower extremity deep vein thrombosis in liver transplant recipients, certain limitations exist. The sample source for this study was relatively limited, focusing on selected medical centres in specific regions, which makes it difficult to represent all regions and ethnicities of liver transplant patients worldwide. Environmental factors and differences in medical care in different regions, as well as differences in genetic backgrounds of different races, may have an impact on the occurrence of postoperative lower extremity DVT, but were not adequately represented in this study. In addition, the sample size was relatively limited, and some risk factors with weak but possible associations were not identified due to insufficient sample size, affecting the comprehensiveness of the findings. This study used a retrospective study design, and although it was able to be analysed using the available clinical data, there is a risk of information bias. At the same time, there may be confounding factors not included in the analysis during the study that may interfere with the determination of the true relationship between risk factors and lower extremity DVT and reduce the accuracy of the results. Future research could be conducted in the following directions. Efforts should be made to expand the scope of the sample and collect data on a wide range of liver transplant recipients of different geographic and ethnic origins, so that the results of the study can be more generalised and provide a more reliable basis for prevention and treatment on a global scale. In addition, new potential risk factors should be actively explored, such as in-depth study of factors at the genetic level, mining the association between different gene polymorphisms and thrombosis, or searching for new biomarkers, to provide new ideas and targets for early diagnosis and prevention of DVT in the lower limbs.\u003c/p\u003e\u003c/div\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eThe present study has been analysed systematically and rigorously to show conclusively that age, history of diabetes mellitus, ascites, hepatic encephalopathy and postoperative D-dimer levels, are independent risk factors for lower limb deep vein thrombosis in patients after liver transplantation. This result is significant for clinical work and reminds physicians to focus their attention on high-risk patients who are accompanied by these factors. For example, in the case of elderly people with diabetes mellitus, blood glucose control is strengthened; in the case of people with ascites and hepatic encephalopathy, active treatment is given to improve their conditions; For all patients, postoperative D-dimer changes were closely followed. Through these targeted monitoring and preventive measures, it may be possible to reduce the incidence of lower extremity DVT, help patients recover better after surgery, improve long-term quality of life, and improve the overall prognosis.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate:\u003c/h2\u003e\u003cp\u003eWe obtained a waiver of informed consent from the Ethics Committee. The research was approved by the Ethics Committee of The Third Hospital of Hebei Medical University. And the Number is W2024-133-010.\u003c/p\u003e\u003ch2\u003eConflict of interest:\u003c/h2\u003e\u003cp\u003eThe author declare that they have no conflicts of interest.\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eXiaoqing Zhang is funded by Medical Science Research Project of Hebei: Hebei Provincial Health Commission(Number:20242250).\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eXiaoqing Zhang and Ruisi Ma participated in case collection.Xiaoqing Zhang, Ruisi Ma and Yingying Wang wrote the manuscript and raised idea. Jinghui Yan, Jiaxing Zhu, Jie Wei and Yanmin Shi revised the manuscript and raised critical editing. The author have read and approved the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\u003cp\u003eNone.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.If you need to ask us for the data of this study, please contact Yingying Wang, [email protected].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBodzin AS, Baker TB. Liver Transplantation Today: Where We Are Now and Where We Are Going. Liver Transpl. 2018;24(10):1470\u0026ndash;75. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/lt.25320\u003c/span\u003e\u003cspan address=\"10.1002/lt.25320\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIacob S, Gheorghe L. 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J Hepatol. 2014;60(2):421\u0026ndash;41. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jhep.2013.08.013\u003c/span\u003e\u003cspan address=\"10.1016/j.jhep.2013.08.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bsur","sideBox":"Learn more about [BMC Surgery](http://bmcsurg.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bsur/default.aspx","title":"BMC Surgery","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Liver transplant, Deep vein thrombosis of the lower limbs, Hepatic encephalopathy, Risk factor, Predictive model","lastPublishedDoi":"10.21203/rs.3.rs-6790586/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6790586/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eLiver transplantation, as an effective treatment for end-stage liver disease, significantly improves the survival and quality of life of patients. However, various postoperative complications seriously affect the patient's prognosis, among which deep vein thrombosis of the lower limbs is one of the more common and dangerous ones.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo investigate the high-risk factors for the development of lower extremity deep vein thrombosis in liver transplant recipients after surgery and to establish a relevant prediction model.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eA total of 425 patients were collected in this study, out of which 110 patients developed lower limb deep vein thrombosis after liver transplantation; The past medical history and relevant information during hospitalisation of the patients enrolled in this study were collected separately to study the correlation factors affecting the emergence of lower limb deep vein thrombosis in patients after surgery, and to establish a prediction model.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePossibly relevant factors were included in a one-way logistic regression, and after analysing the results: age, history of alcohol consumption, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were the potential risk factors for the development of lower limb deep vein thrombosis after liver transplantation, P\u0026thinsp;\u0026lt;\u0026thinsp;0.2. The data obtained were further included in a multifactorial review and age, history of diabetes mellitus, ascites, hepatic encephalopathy, and postoperative D-dimer were independent risk factors for the development of lower extremity deep vein thrombosis after liver transplantation (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eThis finding suggests that clinicians should focus on high-risk individuals with these factors when dealing with liver transplant patients. By strengthening monitoring and adopting targeted preventive measures to reduce the incidence of lower limb DVT and improve the quality of postoperative rehabilitation and long-term prognosis of patients.\u003c/p\u003e","manuscriptTitle":"Analysis of risk factors for postoperative lower extremity deep vein thrombosis in liver transplant patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-04 00:13:36","doi":"10.21203/rs.3.rs-6790586/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-29T13:07:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-10T02:22:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T20:27:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-08T06:17:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6750796755008922192002048673347511681","date":"2025-09-05T07:37:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-04T18:25:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-31T11:03:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"290045423320237590090773654523362642545","date":"2025-08-30T15:50:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"144654229224620451685543347174286430767","date":"2025-08-28T23:42:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298769631388621232021936257777739019302","date":"2025-08-28T05:13:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"154138085822260010894687245053564246260","date":"2025-08-27T12:16:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-27T11:58:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-06-12T12:52:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-06-10T09:57:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-10T09:56:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Surgery","date":"2025-05-31T11:02:45+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-surgery","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bsur","sideBox":"Learn more about [BMC Surgery](http://bmcsurg.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bsur/default.aspx","title":"BMC Surgery","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d8f96bfc-3ae6-4997-9661-f8da4de32fa8","owner":[],"postedDate":"September 4th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T16:06:19+00:00","versionOfRecord":{"articleIdentity":"rs-6790586","link":"https://doi.org/10.1186/s12893-025-03378-7","journal":{"identity":"bmc-surgery","isVorOnly":false,"title":"BMC Surgery"},"publishedOn":"2026-02-10 15:58:41","publishedOnDateReadable":"February 10th, 2026"},"versionCreatedAt":"2025-09-04 00:13:36","video":"","vorDoi":"10.1186/s12893-025-03378-7","vorDoiUrl":"https://doi.org/10.1186/s12893-025-03378-7","workflowStages":[]},"version":"v1","identity":"rs-6790586","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6790586","identity":"rs-6790586","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}