Risk Factor Analysis for the Formation of Postoperative Lower Limb Deep Vein Thrombosis in Patients with Traumatic Spinal Fracture

Risk Factor Analysis for the Formation of Postoperative Lower Limb Deep Vein Thrombosis in Patients with Traumatic Spinal Fracture | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Risk Factor Analysis for the Formation of Postoperative Lower Limb Deep Vein Thrombosis in Patients with Traumatic Spinal Fracture Diao Yang, Shiwen Chen, Can Zhuo, Haidan Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4588401/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective To analyze the independent risk factors for Deep Venous Thrombosis (DVT) in the lower limbs of patients after traumatic spinal fractures. Methods The clinical data of 205 patients who underwent surgical treatment for traumatic spinal fracture due to high-energy injury in our hospital from September 2021 to February 2024 were retrospectively analyzed. Included patients were treated with low molecular weight heparin and mechanical prevention of DVT. Patients underwent ultrasound examination within 1 week after surgery and were divided into DVT group and non-DVT group. Results The overall incidence of postoperative DVT was 26.9% (55/205). Proximal thrombus occurred in 3 patients (1.5%) and distal thrombus in 52 patients (25.4%). No patients developed pulmonary embolism. Binary Logistic analysis showed that age (OR= 1.120, P<0.001), D-dimer (OR=1.347, P=0.002), bed time (OR=1.313, P<0.001), hypoproteinemia (OR=14.380, P<0.001), Blood transfusion (OR=5.707, P=0.003) was an independent risk factor for postoperative DVT in patients with traumatic spinal fractures. The value of different risk factors in the diagnosis of postoperative DVT was analyzed by ROC curve. The AUC values of age, bed time, blood transfusion and hypoproteinemia were 0.734, 0.822, 0.760 and 0.777, respectively. The diagnostic value of D-dimer (AUC value =0.884) was the highest among these risk factors. The diagnostic cut-off value of postoperative D-dimer was determined by Jorden index to be 3.185mg/L. Conclusions Despite chemical and mechanical prevention of DVT, the incidence of postoperative DVT remains high, with D-dimer>3.185mg/l on the first day after surgery, bed time, age, blood transfusion, and hypoproteinemia being independent risk factors for postoperative DVT in patients with traumatic spinal fractures. Spinal fracture Deep vein thrombosis Risk factors D-dimer Figures Figure 1 Introduction Traumatic spinal fractures refer to spinal fractures caused by high-energy impacts such as traffic accidents, falls from heights, and heavy objects striking the body. Patients with this type of fracture usually require surgical treatment. Due to the necessity of prolonged bed rest for those with spinal fractures, the risk of developing deep venous thrombosis DVT in the lower extremities post-operatively is also increased[1]. DVT and pulmonary embolism PE are collectively referred to as venous thromboembolism VTE, which is one of the complications of spinal fractures[2]. Lower extremity DVT can be asymptomatic, making it insidious. Some patients experience no symptoms until they present with leg pain, swelling, or even symptoms such as difficulty breathing and chest pain, which often indicates the presence of DVT. In severe cases, pulmonary embolism may occur, endangering the patient's life[3]. These complications not only impose an increased economic burden on the patient but also affect their quality of life[4]. Currently, there is significant clinical research focusing on the risk factors and prevention of lower extremity DVT during the perioperative period for hip fractures, pelvic fractures, total knee replacement, and total hip replacement[5,6]. Research on the risk factors and prevention of lower limb DVT during the perioperative period for traumatic spinal fractures is limited, and no consensus has been reached. The unique characteristics of these patients, typically resulting from high-energy injuries, include long-term absolute bed rest, trauma stress, spinal cord injuries, and multiple fractures, which contribute to a higher number of independent risk factors for DVT compared to lower limb fractures and joint replacement surgeries. Furthermore, there are no specific guidelines for preventing DVT in patients with traumatic spinal fractures.Therefore, identifying the risk factors for lower limb DVT following surgery for traumatic spinal fractures, taking corresponding preventive measures to reduce the incidence of DVT, and improving the prognosis of patients with spinal fractures are of significant importance. For this reason, our research focuses on the risk factors for deep venous thrombosis in the lower limbs after surgery for traumatic spinal fractures, identifying the risk factors affecting DVT, and exploring the diagnostic value of different risk factors to provide references for diagnosis and treatment. Materials and methods Patients A retrospective analysis was conducted on patients with traumatic spinal fractures caused by high-energy injuries treated at our hospital from September 2021 to February 2024. Inclusion criteria included: 1. No DVT detected in preoperative examinations; 2. Spinal fractures caused by high-energy injuries (falls from heights, traffic accidents, heavy object impacts); 3. Patients requiring surgical treatment; 4. Patients without hemophilia, coagulation disorders, or lower limb varicose veins; 5. Patients who underwent anticoagulant therapy after admission. Exclusion criteria included: 1. Patients with fractures in other locations; 2. Patients with old spinal fractures >4 weeks; 3. Patients with osteoporotic or pathological spinal fractures; 4. Patients on continuous anticoagulant therapy with abnormal coagulation function; 5. Patients diagnosed with DVT before surgery; 6. Patients with a history of venous thromboembolism; 7. Patients with incomplete medical records or imaging data. A total of 205 patients were included in the study, comprising of 159 males and 46 females, aged 18-80 years (mean age 50.7±12.9 years); fracture locations were: cervical spine (59 cases), thoracic spine (45 cases), lumbar spine (62 cases), combined cervical and thoracic spine (5 cases), combined cervical and lumbar spine (2 cases), combined cervical, thoracic, and lumbar spine (2 cases), and thoracolumbar spine (30 cases). This study was approved by the hospital's ethics committee, and all patients agreed to participate in the study and signed the relevant documents. Research methodology After admission, Caprini venous thrombosis risk assessment scale is routinely applied to assess the risk of DVT in lower limbs. For patients with high risk of DVT in lower limbs, after excluding contraindications such as subarachnoid hemorrhage, skin damage in lower limbs, bleeding tendency and abnormal coagulation function, all patients are treated with low molecular weight heparin for prevention (dalteparin sodium, 5000U,once a day, Subcutaneous injection, Nanjing Jianyou Company, China) and mechanical prophylaxis (intermittent pneumatic compression device, twice a day, once for 30 minutes) prevent DVT until post-operative mobility. The injection of low molecular weight heparin was stopped 12 h before surgery and 24 h after surgery. We classify DVT into two types: proximal DVT(located at or near the popliteal vein) and distal DVT(located at the distal popliteal vein). The presence of both proximal and distal popliteal vein thrombosis was defined as proximal DVT. All patients underwent venous color Doppler ultrasonography of both lower limbs after admission, and were re-examined within 1 week after surgery. Patients were divided into DVT group and non-DVT group according to the postoperative color Doppler ultrasonography results of both lower limbs. Non-DVT patients were given subcutaneous injection of low molecular weight heparin 5000U once a day and mechanical prophylaxis; Patients with DVT were given subcutaneous injection of low molecular weight heparin twice a day, 5000U/ times, and mechanical prophylaxis, anticoagulation contraindications or proximal thrombus were stopped, and inferior vena cava filter was used if necessary. Vascular surgery consultation was requested to assist in guiding treatment, and individual treatment plan was developed to prevent pulmonary embolism. Observation indicators General Information: Age, gender, comorbidities (hypertension, coronary heart disease, diabetes), smoking status, spinal cord injury, key lower limb muscle strength (<3/ ≥3), fracture location. Perioperative Data: Time from fracture to surgery, bed rest duration, surgical duration, blood loss, blood transfusion. Laboratory Data: D-dimer, C-reactive protein (CRP), hemoglobin (HGB), neutrophil (NEUT) count, platelet count (PLT), red cell volume distribution width (RDW), fibrinogen plasma (FIB), thrombin time (TT), activated partial thromboplastin time (APTT), prothrombin time (PT), hypoproteinemia, on the first day post-surgery. Statistical methods Statistical analysis was performed using SPSS software. Since all continuous variable data did not meet the criteria for normality and homogeneity of variance, they are represented by median (interquartile range, IQR). Univariate analysis was conducted using the Mann-Whitney U test. Categorical variables are presented proportionally and compared using the chi-square test. A binary logistic regression model was used to explore the risk factors for lower limb DVT in patients with traumatic spinal fractures. The diagnostic value of each risk factor was evaluated using the receiver operating characteristic (ROC) curve and the area under thecurve(AUC). A test level of P＜0.05 was considered statistically significant. Results Comparison of the general conditions of the two groups of patients Table 1 The incidence of postoperative DVT in 205 patients with traumatic spinal fractures was 26.9% (55/205). Of these, 3 cases (1.5%) were proximal thromboses and 52 cases (25.4%) were distal thromboses, with all proximal thromboses treated with inferior vena cava filters, and no patients experienced pulmonary embolism. Comparing the DVT group of 55 patients with the non-DVT group of 150 patients, the median age in the DVT group was 58 years (IQR=6) versus 50 years (IQR=7) in the non-DVT group, indicating the DVT group was older (P＜0.05). There were statistically significant differences between the two groups in terms of hypertension, coronary artery disease, spinal cord injury, and key muscle group strength in the lower limbs (P＜0.05). Patients with hypertension, coronary artery disease, spinal fractures with spinal cord injury, and lower limb muscle strength < grade 3 had a higher risk of developing DVT. There were no significant differences between the two groups regarding gender, diabetes, smoking, and fracture location (P＞0.05). Table 1 Comparison demographic data of two groups of patients Variables DVT Group (n=55) Non-DVT Group (n=150) a Test Statistics P Value Age(years) 58(6) 50(7) -5.127 ＜0.001 Gender Male Female 46 113 2.023 0.364 9 37 Comorbidities Hypertension 14/55 15/150 7.914 0.005 Coronary heart disease 17/55 6/150 29.225 ＜0.001 Diabetes 5/55 14/150 0.003 0.958 Smoke Yes No 20 42 1.334 0.248 35 108 spinal cord injury Yes No 37 36 32.865 ＜0.001 18 114 b Lower extremity ＜3 ≥3 30 30 23.199 ＜0.001 25 120 Fracture location Cervical fracture 12 47 11.44 0.076 thoracic fracture 9 36 Lumbar fracture 17 45 Cervical and thoracic fracture 2 3 Cervical and Lumbar fracture 2 0 Cervical and thoracolumbar fracture 1 1 thoracolumbar fracture 12 18 a Z Value or χ²Value； b Manual muscle test score(0-5) Perioperative Data Comparison Table 2 When comparing perioperative data between the two groups, the time from fracture to surgery was 5 days (IQR=4) for the DVT group and 5 days (IQR=2.5) for the non-DVT group, with no significant difference observed (P＞0.05). The bed rest duration was 15 days (IQR=2) for the DVT group compared to 8 days (IQR=1.5) for the non-DVT group, showing a significant difference (P＜0.05). The surgery duration for the DVT group was 275 minutes (IQR=85), whereas it was 200 minutes (IQR=53.125) for the non-DVT group, with this difference being significant (P＜0.05). The surgical blood loss for the DVT group was 500 ml (IQR=275) compared to 200 ml (IQR=170) for the non-DVT group, also showing a significant difference (P＜0.05). The risk of perioperative blood transfusion was higher in the DVT group than in the non-DVT group, with a significant difference between the two groups (P＜0.05). Table 2 Comparison of perioperative variables of two groups of patients Variables DVT Group (n=55) Non-DVT Group (n=150) a Test Statistics P Value Time from fracture to surgery(days) 5(4) 5(2.5) -0.356 0.721 Duration of bed(days) 15(2) 8(1.5) -7.16 ＜0.001 Operation time(min) 275(85) 200(53.125) -4.668 ＜0.001 Blood loss(ml) 500(275) 200(170) -4.991 ＜0.001 Blood transfusion Yes 44 42 44.686 ＜0.001 No 11 108 a Z Value or χ²Value Laboratory Results Comparison Table 3 The comparison of laboratory results between the two groups showed significant differences in D-dimer, CRP, HGB, NEUT, PLT, RDW, PT, and hypoproteinemia on the first day post-surgery (P＜0.05). There were no significant differences in FIB, TT, and APTT (P＞0.05). Table 3 Comparison of Laboratory results Variables DVT Group (n=55) Non-DVT Group (n=150) a Test Statistics P Value Postoperative D-dimer(mg/l) 5.95(3.41) 1.85(0.99) -8.421 ＜0.001 CRP(mg/l) 25.56(21.68) 16.05(11.15) -3.052 0.002 HGB(g/l) 117.0(14) 126(10.25) -2.56 0.01 NEUT(×10^9/l) 8.67(3.76) 6.17(2.43) -2.56 0.01 PLT(×10^9/l) 157(52) 185.5(48.25) -2.467 0.014 RDW(%) 12.9(0.4) 12.7(0.61) -2.316 0.021 FIB(g/l) 3.88(0.88) 3.34(0.77) -2.134 0.33 TT(s) 16.5(1.15) 17(0.66) -1.912 0.056 APTT(s) 36.0(2.15) 35.3(2.39) -0.74 0.459 PT(s) 13.7(0.7) 13.1(0.55) -3.917 ＜0.001 b Hypoproteinemia Yes 47 45 50.028 ＜0.001 No 8 105 a Z Value or χ²Value b Hypoproteinemia is defined as plasma albumin level of less than 35g/l or plasma total protein less than 60g/l Multivariate analysis of risk factors for postoperative DVT of spinal fracture Multivariate Logistic Analysis Factors from univariate analysis that were statistically significant: age, hypertension, coronary artery disease, spinal cord injury, key muscle group strength in the lower limbs, bed rest duration, surgery duration, blood loss, transfusion, D-dimer on the first day post-surgery, CRP, HGB, NEUT, PLT, RDW, PT, and hypoproteinemia were included in the multivariate analysis. The results, as shown in Table 4 :Age (OR, 1.120; 95%CI: 1.061-1.183; P<0.001), D-dimer on the first day post-surgery (OR, 1.347; 95%CI: 1.112-1.633; P=0.002), bed rest duration (OR, 1.313; 95%CI:1.137-1.516; P<0.001), hypoproteinemia (OR, 14.380; 95%CI:3.957-52.263; P<0.001), and transfusion (OR,5.707; 95%CI:1.828-17.820; P=0.003) are independent risk factors for DVT after traumatic spinal fracture surgery. Table 4 Multivariate analysis of risk factors for postoperative DVT of spinal fracture Risk factors β SE Wald Exp(β) 95%CI P Value Age(years) 0.114 0.28 16.739 1.120 1.061-1.183 ＜0.001 Postoperative D-dimer(mg/l) 0.298 0.098 9.239 1.347 1.112-1.633 0.002 Duration of bed(days) 0.272 0.073 13.741 1.313 1.137-1.516 ＜0.001 hypoproteinemia 2.666 0.658 16.394 14.380 3.957-52.263 ＜0.001 Blood transfusion 1.742 0.581 13.741 5.707 1.828-17.820 0.003 ROC Curve Analysis of Different Risk Factors ROC curve analysis was employed to determine the diagnostic value of different risk factors for postoperative DVT. The ROC curves for the risk factors are shown in Figure 1. Table 5 The AUC values, indicating the diagnostic value of the predictors, were 0.734 for age, 0.822 for bed rest duration, 0.760 for transfusion, and 0.777 for hypoproteinemia. The diagnostic value of D-dimer (AUC=0.884) was the highest among these risk factors. The diagnostic cutoff value for postoperative D-dimer, determined by the Youden index, was 3.185mg/L, with a sensitivity of 85.5% and a specificity of 80%. Table 5 The ROC results of different factors Risk factors aCut-off value Sensitivity Specificity AUC SE 95%CI P Value Postoperative D-dimer(mg/l) 3.185 85.5% 80% 0.884 0.023 0.839-0.929 ＜0.001 Age(years) 47.5 87.3% 46% 0.734 0.038 0.660-0.808 ＜0.001 Duration of bed(days) 12.5 80.0% 80.7% 0.822 0.035 0.753-0.890 ＜0.001 Blood transfusion - 80% 72% 0.760 0.038 0.686-0.834 ＜0.001 hypoproteinemia - 85.5% 70% 0.777 0.036 0.707-0.847 ＜0.001 a The cut-off points of scores were determined by the Youden index DISCUSSION This study analyzed the clinical data of 205 patients with traumatic spinal fractures undergoing surgery. Through univariate, multivariate, and ROC curve analyses, it was found that D-dimer on the first day after surgery, age, bed rest duration, transfusion, and hypoproteinemia are independent risk factors for lower limb DVT in patients after traumatic spinal fracture. The incidence of postoperative lower limb DVT was 26.9%. There were 3 cases (1.5%) of proximal thrombosis and 52 cases (25.4%) of distal thrombosis; all proximal thromboses were managed with an inferior vena cava filter, and no patients experienced pulmonary embolism. Some scholars have shown that the incidence of DVT after spinal fracture surgery ranges from 0.3–31%[ 7 , 8 ]. All subjects in our study received prophylactic low molecular weight heparin (LMWH) for DVT, and no patients developed epidural hematomas. Research by Wang and others also showed no occurrence of epidural hematomas under prophylaxis with LMWH after spinal fracture surgery, indicating that the use of LMWH is safe and effective in patients with traumatic spinal fractures after excluding contraindications[ 9 ]. The theory of thrombus formation proposed by Virchow, which includes hypercoagulability of blood, damage to the endothelium of blood vessels, and venous stasis, has been recognized by clinicians[ 10 , 11 ]. In our study, we did not find that combined hypertension, diabetes and smoke were independent risk factors for postoperative DVT in patients with spinal fracture, which was consistent with the conclusions of some scholars[ 12 ]. At the same time, no correlation was found between fracture location and DVT. Some scholars have found that thoracic fracture is more likely to cause DVT than lumbar fracture[ 9 ].Coagulation indicators,HGB,and inflammation indicators in laboratory tests are not independent risk factors for DVT formation. As patients age, the elasticity of their blood vessels worsens, and the vessel walls become thinner, leading to vascular damage from traumatic spinal fractures. In older individuals, prolonged bed rest and reduced blood flow velocity, along with diminished vascular elasticity and endothelial function, slow blood circulation. Additionally, the decline in organ function in older patients, often accompanied by a series of underlying diseases, weakens the endothelial anti-coagulation and anti-inflammatory capabilities, increasing the likelihood of DVT[ 13 ]. Wang et al[ 9 ] studied 534 cases and found that, even with prophylactic use of low molecular weight heparin, advanced age is a risk factor for lower limb DVT following thoracolumbar fracture surgery, with the incidence of DVT increasing by 5% for each additional year of age. Lv et al[ 14 ]studied 936 patients with spinal fracture caused by high-energy injury and found that age was an independent risk factor for postoperative DVT after spinal fracture, and age was used as one of the risk factors for postoperative DVT by Nomogram model. Older patients have poorer cardiac function, reduced cardiac output, slower blood flow, increased fibrinogen activity, decreased fibrinolysis, and increased platelet aggregation, making them more prone to DVT[ 15 ]. However, Bengoa et al[ 12 ]argued that age is not related to DVT. In our study, the median age in the DVT group was 58 years compared to 50 years in the non-DVT group, making age an independent risk factor. For each additional year of age, the risk of developing DVT after spinal fracture surgery increased by 12%. For elderly patients with traumatic spinal fractures, it is crucial to actively take preventive measures against DVT, expedite preoperative preparations, and conduct surgery as early as possible. Postoperatively, patients should be encouraged to move around as soon as it's safe to do so, to reduce the incidence of DVT. The longer the duration of bed, the less physical activity, leading to decreased function of the leg muscle pump, reduced venous return in the legs, blood stasis, and slower blood flow, all of which facilitate a hypercoagulable state and increase the risk of DVT[ 16 ]. Wang et al[ 17 ] studied the risk factors for postoperative DVT in patients with thoracolumbar fractures due to high-energy injury under LMWH prevention, suggesting that time in bed stay > 12 days was an independent risk factor for postoperative DVT. In our study, the median bed time in the DVT group was 15days and in the non-DVT group was 8days,our study found that bed duration greater than 12.5 days is a risk factor for DVT after spinal fracture.Patients with DVT are worried about thrombus shedding after underground activities and stay in bed for a relatively longer time.Lack of spinal stability after spinal fracture, patients from admission to long-term bed immobilization after surgery, and partial paralysis patients, lower extremity motor function is completely lost, blood is more prone to stasis, lower extremity DVT incidence is higher. Therefore, in the presence of lower extremity motor function, patients with spinal fracture should get out of bed as soon as possible to perform functional exercise to prevent the occurrence of DVT. Hypoproteinemia is defined as a total serum protein level below 60g/L or a serum albumin level below 35g/L and is considered a sign of malnutrition in trauma patients[ 18 ]. Serum albumin can resist free radicals, prevent capillary adhesion, reduce platelet aggregation, and play a role in preventing thrombosis formation,patients with hypoproteinemia have reduced plasma osmotic pressure, increased blood viscosity, hypercoagulability, and a higher risk of DVT[ 19 ].Ma et al[ 20 ] Studies by 2432 patients with spinal fractures showed that patients with low albumin levels after spinal fracture had a 2.08 times higher chance of developing DVT compared to those with normal albumin levels. Lung and others also found that hypoproteinemia is a risk factor for DVT[ 21 ]. Once hypoproteinemia is detected in patients, prompt albumin transfusion and nutritional enhancement should be administered to correct hypoproteinemia and reduce the incidence of DVT. Transfusion increases the number of red blood cells in the blood, and the low temperature of the stored blood increases blood viscosity, promoting the aggregation of platelets and red blood cells, leading to a hypercoagulable state and facilitating the occurrence of DVT[ 22 ]. Lin et al[ 23 ] conducted a retrospective analysis on the risk of venous thromboembolism associated with transfusion and found that transfusion increases the risk of thromboembolic diseases, with the risk of DVT in the transfusion group being 1.99 times that of the non-transfusion group. Many scholars have found that transfusion increases the incidence of lower limb DVT after thoracolumbar spine fracture surgery, after cervical spine fracture combined with spinal cord injury surgery, and after lower limb fracture surgery, making transfusion an independent risk factor for postoperative DVT, which is consistent with our research findings[ 14 , 17 ]. High-energy spinal fractures, which involve significant surgical trauma and blood loss, often require transfusion to correct anemia in patients. Therefore, if there is no severe blood loss, it is advisable to avoid transfusion; if excessive blood loss leads to insufficient blood volume or even complications such as shock, transfusion should be considered after weighing the pros and cons. D-dimer is primarily a specific degradation product generated by the plasmin-mediated hydrolysis of cross-linked fibrin monomers activated by factors[ 24 ]. This substance effectively indicates the body's hypercoagulable state and concurrent fibrinolysis. In terms of blood indicators, D-dimer is a crucial test for diagnosing DVT, exhibiting a high negative predictive value and sensitivity. However, its specificity is relatively low because D-dimer levels can also increase in postoperative, infectious, neoplastic, and traumatic conditions. Despite being influenced by various factors, D-dimer is still considered the most powerful indicator of venous thromboembolism events[ 25 ]. Surgical procedures can lead to a stress-induced elevation in D-dimer levels, with more noticeable changes in D-dimer levels observed when patients develop lower limb DVT[ 26 ]. Matsumoto et al[ 27 ] reported that on the third day after spinal surgery, the sensitivity and specificity of D-dimer were 72.7% and 76.5%, respectively, with a cutoff level of 5.82 µg/ml. Lv et al[ 14 ]found that in patients with cervical spine fractures complicated with spinal cord injury, the incidence of DVT upon admission was as high as 21.71%. Masuda et al[ 28 ]using a prospective study of 211 patients with SCI, showed that 22 patients (10.4%) developed DVT. D-dimer could be used to predict the likelihood of DVT in acute cervical fracture with SCI. The optimal screening time was 2 weeks after injury, and the optimal threshold level of D-dimer for DVT 16µg/dL.Factors such as decreased lower limb muscle strength, time from injury to admission, and D-dimer levels were identified as risk factors for DVT, with D-dimer demonstrating the highest diagnostic value among these risk factors. Our study found that on the first day after surgery, D-dimer had the highest diagnostic value among these five risk factors (AUC = 0.884), with a cutoff value of 3.185 mg/l, sensitivity of 85.5%, and specificity of 80%. In our study, we only discussed D-dimer levels on the first day after surgery. Factors such as surgical stimulation, trauma itself, release of inflammatory mediators, anesthesia, intraoperative bleeding, and postoperative fluid replacement may all lead to an increase in D-dimer levels, potentially masking the specificity of D-dimer in diagnosing DVT. The cutoff value of 3.185 mg/l in our study may not be particularly high, possibly due to the subcutaneous injection of low molecular weight heparin during the perioperative period. Therefore, D-dimer should be measured multiple times on postoperative days 1, 3, 5, and 7 to enhance its predictive value for DVT. Conclusions Elevated D-dimer levels exceeding 3.185 mg/l on the first day after surgery, prolonged bed rest, increasing age, blood transfusion, and hypoproteinemia are all independent risk factors for postoperative lower limb DVT in patients with traumatic spinal fractures. When patients present with these risk factors, clinicians should be vigilant and take appropriate preventive and therapeutic measures. Declarations Ethics approval The Ethics Committee of Yichang Central People's Hospital approved this study. Conflict of interest The authors declare no competing interests. Author Contribution D.Y.wrote the main manuscript text,and formal analysis, review and editing. 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Haemostasis and Inflammatory Parameters as Potential Diagnostic Biomarkers for VTE in Trauma-Immobilized Patients. Diagnostics (Basel). 2023;13(1):150. Published 2023 Jan 2. Freund Y, Chauvin A, Jimenez S, et al. Effect of a Diagnostic Strategy Using an Elevated and Age-Adjusted D-Dimer Threshold on Thromboembolic Events in Emergency Department Patients With Suspected Pulmonary Embolism: A Randomized Clinical Trial. JAMA. 2021;326(21):2141–9. Ke L, Cui S, Chen S, et al. Dynamics of D-dimer in non-small cell lung cancer patients receiving radical surgery and its association with postoperative venous thromboembolism. J Thorac cancer. 2020;11(9):2483–92. Matsumoto S, Suda K, Iimoto S, et al. Prospective study of deep vein thrombosis in patients with spinal cord injury not receiving anticoagulant therapy. Spinal Cord. 2015;53(4):306–9. Masuda M, Ueta T, Shiba K, et al. D-dimer screening for deep venous thrombosis in traumatic cervical spinal injuries. J Spine. 2015;15(11):2338–44. 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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-4588401","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":321551842,"identity":"c12f77ea-f24b-433e-a27d-a360c92c01d6","order_by":0,"name":"Diao Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBACNmaGhAMSFTZ2/PKPDxCnhY+94eEBizNpyZINaQnEaZHjOfj4QGXbYcYNDTkGRDpMIjnhwM02ZmYDhjMfb7xhsJPTbSCoJS3h4IxzbHzmjL2bLecwJBubHSCoJSfhsEQZD7NlM+82aR6GA4nbCGvJ/3D4D5sE44ZjPM+I1MJzABjIbQaMG87wsBGphb0BqOVMQrLkDDZjyzkGRPhFvpkh+YNExX87fgnmhzfeVNjJEdSCAiR4iIwaZC2k6hgFo2AUjIIRAQD3nUPzYFLnSgAAAABJRU5ErkJggg==","orcid":"","institution":"China Three Gorges University","correspondingAuthor":true,"prefix":"","firstName":"Diao","middleName":"","lastName":"Yang","suffix":""},{"id":321551846,"identity":"503d6e85-45cd-457f-a001-d50a2483da81","order_by":1,"name":"Shiwen Chen","email":"","orcid":"","institution":"China Three Gorges University","correspondingAuthor":false,"prefix":"","firstName":"Shiwen","middleName":"","lastName":"Chen","suffix":""},{"id":321551848,"identity":"ee97d296-faab-4eb8-bd14-3397d96f4964","order_by":2,"name":"Can Zhuo","email":"","orcid":"","institution":"China Three Gorges University","correspondingAuthor":false,"prefix":"","firstName":"Can","middleName":"","lastName":"Zhuo","suffix":""},{"id":321551851,"identity":"3b931b12-bc7d-4967-adae-015cf80bca21","order_by":3,"name":"Haidan Chen","email":"","orcid":"","institution":"China Three Gorges University","correspondingAuthor":false,"prefix":"","firstName":"Haidan","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-06-16 04:38:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4588401/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4588401/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":60344570,"identity":"929d606c-2de0-400d-937f-7b17e3fc69a0","added_by":"auto","created_at":"2024-07-15 19:23:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":43232,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curves of different risk factors\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4588401/v1/6635fde2bb32b693d8184b8b.jpg"},{"id":62404206,"identity":"2814b598-7288-4082-bed6-1b45071753fb","added_by":"auto","created_at":"2024-08-13 20:07:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":567290,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4588401/v1/9dbd1a3b-480f-4f78-adc4-f75609cf715d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk Factor Analysis for the Formation of Postoperative Lower Limb Deep Vein Thrombosis in Patients with Traumatic Spinal Fracture","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraumatic spinal fractures refer to spinal fractures caused by high-energy impacts such as traffic accidents, falls from heights, and heavy objects striking the body. Patients with this type of fracture usually require surgical treatment. Due to the necessity of prolonged bed rest for those with spinal fractures, the risk of developing deep venous thrombosis DVT in the lower extremities post-operatively is also increased[1]. DVT and pulmonary embolism PE are collectively referred to as venous thromboembolism VTE, which is one of the complications of spinal fractures[2]. Lower extremity DVT can be asymptomatic, making it insidious. Some patients experience no symptoms until they present with leg pain, swelling, or even symptoms such as difficulty breathing and chest pain, which often indicates the presence of DVT. In severe cases, pulmonary embolism may occur, endangering the patient\u0026apos;s life[3]. These complications not only impose an increased economic burden on the patient but also affect their quality of life[4]. Currently, there is significant clinical research focusing on the risk factors and prevention of lower extremity DVT during the perioperative period for hip fractures, pelvic fractures, total knee replacement, and total hip replacement[5,6]. Research on the risk factors and prevention of lower limb DVT during the perioperative period for traumatic spinal fractures is limited, and no consensus has been reached. The unique characteristics of these patients, typically resulting from high-energy injuries, include long-term absolute bed rest, trauma stress, spinal cord injuries, and multiple fractures, which contribute to a higher number of independent risk factors for DVT compared to lower limb fractures and joint replacement surgeries. Furthermore, there are no specific guidelines for preventing DVT in patients with traumatic spinal fractures.Therefore, identifying the risk factors for lower limb DVT following surgery for traumatic spinal fractures, taking corresponding preventive measures to reduce the incidence of DVT, and improving the prognosis of patients with spinal fractures are of significant importance. For this reason, our research focuses on the risk factors for deep venous thrombosis in the lower limbs after surgery for traumatic spinal fractures, identifying the risk factors affecting DVT, and exploring the diagnostic value of different risk factors to provide references for diagnosis and treatment.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003ePatients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA retrospective analysis was conducted on patients with traumatic spinal fractures caused by high-energy injuries treated at our hospital from September 2021 to February 2024. Inclusion criteria included: 1. No DVT detected in preoperative examinations; 2. Spinal fractures caused by high-energy injuries (falls from heights, traffic accidents, heavy object impacts); 3. Patients requiring surgical treatment; 4. Patients without hemophilia, coagulation disorders, or lower limb varicose veins; 5. Patients who underwent anticoagulant therapy after admission. Exclusion criteria included: 1. Patients with fractures in other locations; 2. Patients with old spinal fractures \u0026gt;4 weeks; 3. Patients with osteoporotic or pathological spinal fractures; 4. Patients on continuous anticoagulant therapy with abnormal coagulation function; 5. Patients diagnosed with DVT before surgery; 6. Patients with a history of venous thromboembolism; 7. Patients with incomplete medical records or imaging data. A total of 205 patients were included in the study, comprising of 159 males and 46 females, aged 18-80 years (mean age 50.7\u0026plusmn;12.9 years); fracture locations were: cervical spine (59 cases), thoracic spine (45 cases), lumbar spine (62 cases), combined cervical and thoracic spine (5 cases), combined cervical and lumbar spine (2 cases), combined cervical, thoracic, and lumbar spine (2 cases), and thoracolumbar spine (30 cases). This study was approved by the hospital\u0026apos;s ethics committee, and all patients agreed to participate in the study and signed the relevant documents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResearch methodology\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter admission, Caprini venous thrombosis risk assessment scale is routinely applied to assess the risk of DVT in lower limbs. For patients with high risk of DVT in lower limbs, after excluding contraindications such as subarachnoid hemorrhage, skin damage in lower limbs, bleeding tendency and abnormal coagulation function, all patients are treated with low molecular weight heparin for prevention (dalteparin sodium, 5000U,once a day, Subcutaneous injection, Nanjing Jianyou Company, China) and mechanical prophylaxis (intermittent pneumatic compression device, twice a day, once for 30 minutes) prevent DVT until post-operative mobility. The injection of low molecular weight heparin was stopped 12 h before surgery and 24 h after surgery. We classify DVT into two types: proximal DVT(located at or near the popliteal vein) and distal DVT(located at the distal popliteal vein). The presence of both proximal and distal popliteal vein thrombosis was defined as proximal DVT. All patients underwent venous color Doppler ultrasonography of both lower limbs after admission, and were re-examined within 1 week after surgery. Patients were divided into DVT group and non-DVT group according to the postoperative color Doppler ultrasonography results of both lower limbs. Non-DVT patients were given subcutaneous injection of low molecular weight heparin 5000U once a day and mechanical prophylaxis; Patients with DVT were given subcutaneous injection of low molecular weight heparin twice a day, 5000U/ times, and mechanical prophylaxis, anticoagulation contraindications or proximal thrombus were stopped, and inferior vena cava filter was used if necessary. Vascular surgery consultation was requested to assist in guiding treatment, and individual treatment plan was developed to prevent pulmonary embolism.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObservation indicators\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGeneral Information: Age, gender, comorbidities (hypertension, coronary heart disease, diabetes), smoking status, spinal cord injury, key lower limb muscle strength (\u0026lt;3/ \u0026ge;3), fracture location. Perioperative Data: Time from fracture to surgery, bed rest duration, surgical duration, blood loss, blood transfusion. Laboratory Data: D-dimer, C-reactive protein (CRP), hemoglobin (HGB), neutrophil (NEUT) count, platelet count (PLT), red cell volume distribution width (RDW), fibrinogen plasma (FIB), thrombin time (TT), activated partial thromboplastin time (APTT), prothrombin time (PT), hypoproteinemia, on the first day post-surgery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical methods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analysis was performed using SPSS software. Since all continuous variable data did not meet the criteria for normality and homogeneity of variance, they are represented by median (interquartile range, IQR). Univariate analysis was conducted using the Mann-Whitney U test. Categorical variables are presented proportionally and compared using the chi-square test. A binary logistic regression model was used to explore the risk factors for lower limb DVT in patients with traumatic spinal fractures. The diagnostic value of each risk factor was evaluated using the receiver operating characteristic (ROC) curve and the area under thecurve(AUC). A test level of P＜0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eComparison of the general conditions of the two groups of patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 1 The incidence of postoperative DVT in 205 patients with traumatic spinal fractures was 26.9% (55/205). Of these, 3 cases (1.5%) were proximal thromboses and 52 cases (25.4%) were distal thromboses, with all proximal thromboses treated with inferior vena cava filters, and no patients experienced pulmonary embolism. Comparing the DVT group of 55 patients with the non-DVT group of 150 patients, the median age in the DVT group was 58 years (IQR=6) versus 50 years (IQR=7) in the non-DVT group, indicating the DVT group was older (P＜0.05). There were statistically significant differences between the two groups in terms of hypertension, coronary artery disease, spinal cord injury, and key muscle group strength in the lower limbs (P＜0.05). Patients with hypertension, coronary artery disease, spinal fractures with spinal cord injury, and lower limb muscle strength \u0026lt; grade 3 had a higher risk of developing DVT. There were no significant differences between the two groups regarding gender, diabetes, smoking, and fracture location (P＞0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 1 Comparison demographic data of two groups of patients\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003eDVT Group\u003c/p\u003e\n \u003cp\u003e(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003eNon-DVT Group\u003c/p\u003e\n \u003cp\u003e(n=150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003eTest Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e58(6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e50(7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e-5.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.82394366197182%\" colspan=\"4\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\" rowspan=\"2\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\" rowspan=\"2\"\u003e\n \u003cp\u003e2.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.290748898678416%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"57.709251101321584%\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.82394366197182%\" colspan=\"4\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e14/55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e15/150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e7.914\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eCoronary heart disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e17/55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e6/150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e29.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e5/55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e14/150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e0.958\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eSmoke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.82394366197182%\" colspan=\"4\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\" rowspan=\"2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\" rowspan=\"2\"\u003e\n \u003cp\u003e1.334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\" rowspan=\"2\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.290748898678416%\"\u003e\n \u003cp\u003e35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"57.709251101321584%\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003espinal cord injury\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\" rowspan=\"2\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\" rowspan=\"2\"\u003e\n \u003cp\u003e32.865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\" rowspan=\"2\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.290748898678416%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"57.709251101321584%\"\u003e\n \u003cp\u003e114\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003e Lower extremity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.82394366197182%\" colspan=\"4\"\u003e\n \u003cp\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\" rowspan=\"2\"\u003e\n \u003cp\u003e＜3\u003c/p\u003e\n \u003cp\u003e\u0026ge;3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\" rowspan=\"2\"\u003e\n \u003cp\u003e23.199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\" rowspan=\"2\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.290748898678416%\"\u003e\n \u003cp\u003e25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"57.709251101321584%\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eFracture location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.82394366197182%\" colspan=\"4\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.176056338028168%\"\u003e\n \u003cp\u003eCervical \u0026nbsp;fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.901408450704224%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\" rowspan=\"7\"\u003e\n \u003cp\u003e11.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\" rowspan=\"7\"\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.648648648648646%\"\u003e\n \u003cp\u003ethoracic \u0026nbsp;fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.945945945945947%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.648648648648646%\"\u003e\n \u003cp\u003eLumbar \u0026nbsp;fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.945945945945947%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.648648648648646%\"\u003e\n \u003cp\u003eCervical and\u0026nbsp;thoracic fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.945945945945947%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.648648648648646%\"\u003e\n \u003cp\u003eCervical and\u0026nbsp;Lumbar fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.945945945945947%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.648648648648646%\"\u003e\n \u003cp\u003eCervical and\u0026nbsp;thoracolumbar fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.945945945945947%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.648648648648646%\"\u003e\n \u003cp\u003ethoracolumbar fracture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25.945945945945947%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eZ Value or \u0026chi;\u0026sup2;Value；\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eManual muscle test score(0-5)\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePerioperative Data Comparison\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 2 When comparing perioperative data between the two groups, the time from fracture to surgery was 5 days (IQR=4) for the DVT group and 5 days (IQR=2.5) for the non-DVT group, with no significant difference observed (P＞0.05). The bed rest duration was 15 days (IQR=2) for the DVT group compared to 8 days (IQR=1.5) for the non-DVT group, showing a significant difference (P＜0.05). The surgery duration for the DVT group was 275 minutes (IQR=85), whereas it was 200 minutes (IQR=53.125) for the non-DVT group, with this difference being significant (P＜0.05). The surgical blood loss for the DVT group was 500 ml (IQR=275) compared to 200 ml (IQR=170) for the non-DVT group, also showing a significant difference (P＜0.05). The risk of perioperative blood transfusion was higher in the DVT group than in the non-DVT group, with a significant difference between the two groups (P＜0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 2 Comparison of perioperative variables of\u0026nbsp;two groups of patients\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"569\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.359154929577464%\"\u003e\n \u003cp\u003eDVT Group\u003c/p\u003e\n \u003cp\u003e(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003eNon-DVT Group\u003c/p\u003e\n \u003cp\u003e(n=150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003ea Test Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003eTime from fracture to surgery(days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.359154929577464%\"\u003e\n \u003cp\u003e5(4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e5(2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e-0.356\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003eDuration of bed(days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.359154929577464%\"\u003e\n \u003cp\u003e15(2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e8(1.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e-7.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003eOperation time(min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.359154929577464%\"\u003e\n \u003cp\u003e275(85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e200(53.125)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e-4.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003eBlood loss(ml)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.359154929577464%\"\u003e\n \u003cp\u003e500(275)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e200(170)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003e-4.991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.68365553602812%\"\u003e\n \u003cp\u003eBlood transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.31634446397189%\" colspan=\"4\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.718309859154928%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.359154929577464%\"\u003e\n \u003cp\u003e44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.06338028169014%\"\u003e\n \u003cp\u003e42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.718309859154928%\" rowspan=\"2\"\u003e\n \u003cp\u003e44.686\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.140845070422536%\" rowspan=\"2\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.27027027027027%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.32432432432432%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.4054054054054%\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eZ Value or \u0026chi;\u0026sup2;Value\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLaboratory Results Comparison\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3\u0026nbsp;The comparison of laboratory results between the two groups showed significant differences in D-dimer, CRP, HGB, NEUT, PLT, RDW, PT, and hypoproteinemia on the first day post-surgery (P＜0.05). There were no significant differences in FIB, TT, and APTT (P＞0.05).\u003c/p\u003e\n\u003cp\u003eTable 3 Comparison of Laboratory results\u003c/p\u003e\n\u003cdiv align=\"\"\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"564\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003eDVT Group\u003c/p\u003e\n \u003cp\u003e(n=55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003eNon-DVT Group\u003c/p\u003e\n \u003cp\u003e(n=150)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003ea Test Statistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003ePostoperative D-dimer(mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e5.95(3.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e1.85(0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-8.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eCRP(mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e25.56(21.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e16.05(11.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-3.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eHGB(g/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e117.0(14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e126(10.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eNEUT(\u0026times;10^9/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e8.67(3.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e6.17(2.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003ePLT(\u0026times;10^9/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e157(52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e185.5(48.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-2.467\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eRDW(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e12.9(0.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e12.7(0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-2.316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eFIB(g/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e3.88(0.88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e3.34(0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-2.134\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eTT(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e16.5(1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e17(0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-1.912\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eAPTT(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e36.0(2.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e35.3(2.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e0.459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003ePT(s)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e13.7(0.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e13.1(0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e-3.917\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003e\u003csup\u003eb\u003c/sup\u003eHypoproteinemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.511545293072825%\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.58436944937833%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.090586145648313%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.715808170515096%\" rowspan=\"2\"\u003e\n \u003cp\u003e50.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.097690941385435%\" rowspan=\"2\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"37.60217983651226%\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"26.975476839237057%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"35.42234332425068%\"\u003e\n \u003cp\u003e105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eZ Value or \u0026chi;\u0026sup2;Value\u003c/p\u003e\n\u003cp\u003e\u003csup\u003eb\u003c/sup\u003eHypoproteinemia is defined as plasma albumin level of less than 35g/l or plasma total protein less than 60g/l\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMultivariate analysis of risk factors for\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003epostoperative\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDVT of spinal fracture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMultivariate Logistic Analysis Factors from univariate analysis that were statistically significant: age, hypertension, coronary artery disease, spinal cord injury, key muscle group strength in the lower limbs, bed rest duration, surgery duration, blood loss, transfusion, D-dimer on the first day post-surgery, CRP, HGB, NEUT, PLT, RDW, PT, and hypoproteinemia were included in the multivariate analysis. The results, as shown in Table 4 :Age (OR, 1.120; 95%CI: 1.061-1.183; P\u0026lt;0.001), D-dimer on the first day post-surgery (OR, 1.347; 95%CI: 1.112-1.633; P=0.002), bed rest duration (OR, 1.313; 95%CI:1.137-1.516; P\u0026lt;0.001), hypoproteinemia (OR, 14.380; 95%CI:3.957-52.263; P\u0026lt;0.001), and transfusion (OR,5.707; 95%CI:1.828-17.820; P=0.003) are independent risk factors for DVT after traumatic spinal fracture surgery.\u003c/p\u003e\n\u003cp\u003eTable 4 Multivariate analysis of risk factors for\u0026nbsp;postoperative\u0026nbsp;DVT of spinal fracture\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"548\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.26277372262774%\" valign=\"bottom\"\u003e\n \u003cp\u003eRisk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.036496350364963%\" valign=\"bottom\"\u003e\n \u003cp\u003e\u0026beta;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.401459854014599%\" valign=\"bottom\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.496350364963504%\" valign=\"bottom\"\u003e\n \u003cp\u003eWald\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.138686131386862%\" valign=\"bottom\"\u003e\n \u003cp\u003eExp(\u0026beta;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.255474452554743%\" valign=\"bottom\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.408759124087592%\" valign=\"bottom\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.26277372262774%\" valign=\"top\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.036496350364963%\" valign=\"top\"\u003e\n \u003cp\u003e0.114\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.401459854014599%\" valign=\"top\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.496350364963504%\" valign=\"top\"\u003e\n \u003cp\u003e16.739\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.138686131386862%\" valign=\"top\"\u003e\n \u003cp\u003e1.120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.255474452554743%\" valign=\"top\"\u003e\n \u003cp\u003e1.061-1.183\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.408759124087592%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.26277372262774%\" valign=\"top\"\u003e\n \u003cp\u003ePostoperative D-dimer(mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.036496350364963%\" valign=\"top\"\u003e\n \u003cp\u003e0.298\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.401459854014599%\" valign=\"top\"\u003e\n \u003cp\u003e0.098\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.496350364963504%\" valign=\"top\"\u003e\n \u003cp\u003e9.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.138686131386862%\" valign=\"top\"\u003e\n \u003cp\u003e1.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.255474452554743%\" valign=\"top\"\u003e\n \u003cp\u003e1.112-1.633\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.408759124087592%\" valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.26277372262774%\" valign=\"top\"\u003e\n \u003cp\u003eDuration of bed(days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.036496350364963%\" valign=\"top\"\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.401459854014599%\" valign=\"top\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.496350364963504%\" valign=\"top\"\u003e\n \u003cp\u003e13.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.138686131386862%\" valign=\"top\"\u003e\n \u003cp\u003e1.313\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.255474452554743%\" valign=\"top\"\u003e\n \u003cp\u003e1.137-1.516\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.408759124087592%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.26277372262774%\" valign=\"top\"\u003e\n \u003cp\u003ehypoproteinemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.036496350364963%\" valign=\"top\"\u003e\n \u003cp\u003e2.666\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.401459854014599%\" valign=\"top\"\u003e\n \u003cp\u003e0.658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.496350364963504%\" valign=\"top\"\u003e\n \u003cp\u003e16.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.138686131386862%\" valign=\"top\"\u003e\n \u003cp\u003e14.380\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.255474452554743%\" valign=\"top\"\u003e\n \u003cp\u003e3.957-52.263\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.408759124087592%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"22.26277372262774%\" valign=\"top\"\u003e\n \u003cp\u003eBlood transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.036496350364963%\" valign=\"top\"\u003e\n \u003cp\u003e1.742\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.401459854014599%\" valign=\"top\"\u003e\n \u003cp\u003e0.581\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.496350364963504%\" valign=\"top\"\u003e\n \u003cp\u003e13.741\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.138686131386862%\" valign=\"top\"\u003e\n \u003cp\u003e5.707\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.255474452554743%\" valign=\"top\"\u003e\n \u003cp\u003e1.828-17.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.408759124087592%\" valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eROC Curve Analysis of Different Risk Factors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eROC curve analysis was employed to determine the diagnostic value of different risk factors for postoperative DVT. The ROC curves for the risk factors are shown in Figure 1.\u0026nbsp;Table 5\u0026nbsp;The AUC values, indicating the diagnostic value of the predictors, were 0.734 for age, 0.822 for bed rest duration, 0.760 for transfusion, and 0.777 for hypoproteinemia. The diagnostic value of D-dimer (AUC=0.884) was the highest among these risk factors. The diagnostic cutoff value for postoperative D-dimer, determined by the Youden index, was 3.185mg/L, with a sensitivity of 85.5% and a specificity of 80%.\u003c/p\u003e\n\u003cp\u003eTable 5 The ROC results of different factors\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"545\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.626151012891345%\" valign=\"bottom\"\u003e\n \u003cp\u003eRisk factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\" valign=\"bottom\"\u003e\n \u003cp\u003eaCut-off value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"bottom\"\u003e\n \u003cp\u003eSensitivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"bottom\"\u003e\n \u003cp\u003eSpecificity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.366482504604051%\" valign=\"bottom\"\u003e\n \u003cp\u003eAUC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.734806629834254%\" valign=\"bottom\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.469613259668508%\" valign=\"bottom\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.94475138121547%\" valign=\"bottom\"\u003e\n \u003cp\u003eP Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.626151012891345%\" valign=\"top\"\u003e\n \u003cp\u003ePostoperative D-dimer(mg/l)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\" valign=\"top\"\u003e\n \u003cp\u003e3.185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e85.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.366482504604051%\" valign=\"top\"\u003e\n \u003cp\u003e0.884\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.734806629834254%\" valign=\"top\"\u003e\n \u003cp\u003e0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.469613259668508%\" valign=\"top\"\u003e\n \u003cp\u003e0.839-0.929\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.94475138121547%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.626151012891345%\" valign=\"top\"\u003e\n \u003cp\u003eAge(years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\" valign=\"top\"\u003e\n \u003cp\u003e47.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e87.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e46%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.366482504604051%\" valign=\"top\"\u003e\n \u003cp\u003e0.734\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.734806629834254%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.469613259668508%\" valign=\"top\"\u003e\n \u003cp\u003e0.660-0.808\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.94475138121547%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.626151012891345%\" valign=\"top\"\u003e\n \u003cp\u003eDuration of bed(days)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\" valign=\"top\"\u003e\n \u003cp\u003e12.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e80.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e80.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.366482504604051%\" valign=\"top\"\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.734806629834254%\" valign=\"top\"\u003e\n \u003cp\u003e0.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.469613259668508%\" valign=\"top\"\u003e\n \u003cp\u003e0.753-0.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.94475138121547%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.626151012891345%\" valign=\"top\"\u003e\n \u003cp\u003eBlood transfusion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e72%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.366482504604051%\" valign=\"top\"\u003e\n \u003cp\u003e0.760\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.734806629834254%\" valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.469613259668508%\" valign=\"top\"\u003e\n \u003cp\u003e0.686-0.834\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.94475138121547%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.626151012891345%\" valign=\"top\"\u003e\n \u003cp\u003ehypoproteinemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.497237569060774%\" valign=\"top\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e85.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.180478821362799%\" valign=\"top\"\u003e\n \u003cp\u003e70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.366482504604051%\" valign=\"top\"\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.734806629834254%\" valign=\"top\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.469613259668508%\" valign=\"top\"\u003e\n \u003cp\u003e0.707-0.847\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.94475138121547%\" valign=\"top\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eThe cut-off points of scores were determined by the Youden index\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study analyzed the clinical data of 205 patients with traumatic spinal fractures undergoing surgery. Through univariate, multivariate, and ROC curve analyses, it was found that D-dimer on the first day after surgery, age, bed rest duration, transfusion, and hypoproteinemia are independent risk factors for lower limb DVT in patients after traumatic spinal fracture. The incidence of postoperative lower limb DVT was 26.9%. There were 3 cases (1.5%) of proximal thrombosis and 52 cases (25.4%) of distal thrombosis; all proximal thromboses were managed with an inferior vena cava filter, and no patients experienced pulmonary embolism. Some scholars have shown that the incidence of DVT after spinal fracture surgery ranges from 0.3\u0026ndash;31%[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. All subjects in our study received prophylactic low molecular weight heparin (LMWH) for DVT, and no patients developed epidural hematomas. Research by Wang and others also showed no occurrence of epidural hematomas under prophylaxis with LMWH after spinal fracture surgery, indicating that the use of LMWH is safe and effective in patients with traumatic spinal fractures after excluding contraindications[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The theory of thrombus formation proposed by Virchow, which includes hypercoagulability of blood, damage to the endothelium of blood vessels, and venous stasis, has been recognized by clinicians[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn our study, we did not find that combined hypertension, diabetes and smoke were independent risk factors for postoperative DVT in patients with spinal fracture, which was consistent with the conclusions of some scholars[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. At the same time, no correlation was found between fracture location and DVT. Some scholars have found that thoracic fracture is more likely to cause DVT than lumbar fracture[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].Coagulation indicators,HGB,and inflammation indicators in laboratory tests are not independent risk factors for DVT formation.\u003c/p\u003e \u003cp\u003eAs patients age, the elasticity of their blood vessels worsens, and the vessel walls become thinner, leading to vascular damage from traumatic spinal fractures. In older individuals, prolonged bed rest and reduced blood flow velocity, along with diminished vascular elasticity and endothelial function, slow blood circulation. Additionally, the decline in organ function in older patients, often accompanied by a series of underlying diseases, weakens the endothelial anti-coagulation and anti-inflammatory capabilities, increasing the likelihood of DVT[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Wang et al[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] studied 534 cases and found that, even with prophylactic use of low molecular weight heparin, advanced age is a risk factor for lower limb DVT following thoracolumbar fracture surgery, with the incidence of DVT increasing by 5% for each additional year of age. Lv et al[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]studied 936 patients with spinal fracture caused by high-energy injury and found that age was an independent risk factor for postoperative DVT after spinal fracture, and age was used as one of the risk factors for postoperative DVT by Nomogram model. Older patients have poorer cardiac function, reduced cardiac output, slower blood flow, increased fibrinogen activity, decreased fibrinolysis, and increased platelet aggregation, making them more prone to DVT[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, Bengoa et al[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]argued that age is not related to DVT. In our study, the median age in the DVT group was 58 years compared to 50 years in the non-DVT group, making age an independent risk factor. For each additional year of age, the risk of developing DVT after spinal fracture surgery increased by 12%. For elderly patients with traumatic spinal fractures, it is crucial to actively take preventive measures against DVT, expedite preoperative preparations, and conduct surgery as early as possible. Postoperatively, patients should be encouraged to move around as soon as it's safe to do so, to reduce the incidence of DVT.\u003c/p\u003e \u003cp\u003eThe longer the duration of bed, the less physical activity, leading to decreased function of the leg muscle pump, reduced venous return in the legs, blood stasis, and slower blood flow, all of which facilitate a hypercoagulable state and increase the risk of DVT[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Wang et al[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] studied the risk factors for postoperative DVT in patients with thoracolumbar fractures due to high-energy injury under LMWH prevention, suggesting that time in bed stay\u0026thinsp;\u0026gt;\u0026thinsp;12 days was an independent risk factor for postoperative DVT. In our study, the median bed time in the DVT group was 15days and in the non-DVT group was 8days,our study found that bed duration greater than 12.5 days is a risk factor for DVT after spinal fracture.Patients with DVT are worried about thrombus shedding after underground activities and stay in bed for a relatively longer time.Lack of spinal stability after spinal fracture, patients from admission to long-term bed immobilization after surgery, and partial paralysis patients, lower extremity motor function is completely lost, blood is more prone to stasis, lower extremity DVT incidence is higher. Therefore, in the presence of lower extremity motor function, patients with spinal fracture should get out of bed as soon as possible to perform functional exercise to prevent the occurrence of DVT.\u003c/p\u003e \u003cp\u003eHypoproteinemia is defined as a total serum protein level below 60g/L or a serum albumin level below 35g/L and is considered a sign of malnutrition in trauma patients[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Serum albumin can resist free radicals, prevent capillary adhesion, reduce platelet aggregation, and play a role in preventing thrombosis formation,patients with hypoproteinemia have reduced plasma osmotic pressure, increased blood viscosity, hypercoagulability, and a higher risk of DVT[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].Ma et al[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] Studies by 2432 patients with spinal fractures showed that patients with low albumin levels after spinal fracture had a 2.08 times higher chance of developing DVT compared to those with normal albumin levels. Lung and others also found that hypoproteinemia is a risk factor for DVT[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Once hypoproteinemia is detected in patients, prompt albumin transfusion and nutritional enhancement should be administered to correct hypoproteinemia and reduce the incidence of DVT.\u003c/p\u003e \u003cp\u003eTransfusion increases the number of red blood cells in the blood, and the low temperature of the stored blood increases blood viscosity, promoting the aggregation of platelets and red blood cells, leading to a hypercoagulable state and facilitating the occurrence of DVT[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Lin et al[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] conducted a retrospective analysis on the risk of venous thromboembolism associated with transfusion and found that transfusion increases the risk of thromboembolic diseases, with the risk of DVT in the transfusion group being 1.99 times that of the non-transfusion group. Many scholars have found that transfusion increases the incidence of lower limb DVT after thoracolumbar spine fracture surgery, after cervical spine fracture combined with spinal cord injury surgery, and after lower limb fracture surgery, making transfusion an independent risk factor for postoperative DVT, which is consistent with our research findings[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. High-energy spinal fractures, which involve significant surgical trauma and blood loss, often require transfusion to correct anemia in patients. Therefore, if there is no severe blood loss, it is advisable to avoid transfusion; if excessive blood loss leads to insufficient blood volume or even complications such as shock, transfusion should be considered after weighing the pros and cons.\u003c/p\u003e \u003cp\u003eD-dimer is primarily a specific degradation product generated by the plasmin-mediated hydrolysis of cross-linked fibrin monomers activated by factors[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This substance effectively indicates the body's hypercoagulable state and concurrent fibrinolysis. In terms of blood indicators, D-dimer is a crucial test for diagnosing DVT, exhibiting a high negative predictive value and sensitivity. However, its specificity is relatively low because D-dimer levels can also increase in postoperative, infectious, neoplastic, and traumatic conditions. Despite being influenced by various factors, D-dimer is still considered the most powerful indicator of venous thromboembolism events[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Surgical procedures can lead to a stress-induced elevation in D-dimer levels, with more noticeable changes in D-dimer levels observed when patients develop lower limb DVT[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Matsumoto et al[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e] reported that on the third day after spinal surgery, the sensitivity and specificity of D-dimer were 72.7% and 76.5%, respectively, with a cutoff level of 5.82 \u0026micro;g/ml. Lv et al[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]found that in patients with cervical spine fractures complicated with spinal cord injury, the incidence of DVT upon admission was as high as 21.71%. Masuda et al[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]using a prospective study of 211 patients with SCI, showed that 22 patients (10.4%) developed DVT. D-dimer could be used to predict the likelihood of DVT in acute cervical fracture with SCI. The optimal screening time was 2 weeks after injury, and the optimal threshold level of D-dimer for DVT 16\u0026micro;g/dL.Factors such as decreased lower limb muscle strength, time from injury to admission, and D-dimer levels were identified as risk factors for DVT, with D-dimer demonstrating the highest diagnostic value among these risk factors. Our study found that on the first day after surgery, D-dimer had the highest diagnostic value among these five risk factors (AUC\u0026thinsp;=\u0026thinsp;0.884), with a cutoff value of 3.185 mg/l, sensitivity of 85.5%, and specificity of 80%. In our study, we only discussed D-dimer levels on the first day after surgery. Factors such as surgical stimulation, trauma itself, release of inflammatory mediators, anesthesia, intraoperative bleeding, and postoperative fluid replacement may all lead to an increase in D-dimer levels, potentially masking the specificity of D-dimer in diagnosing DVT. The cutoff value of 3.185 mg/l in our study may not be particularly high, possibly due to the subcutaneous injection of low molecular weight heparin during the perioperative period. Therefore, D-dimer should be measured multiple times on postoperative days 1, 3, 5, and 7 to enhance its predictive value for DVT.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eElevated D-dimer levels exceeding 3.185 mg/l on the first day after surgery, prolonged bed rest, increasing age, blood transfusion, and hypoproteinemia are all independent risk factors for postoperative lower limb DVT in patients with traumatic spinal fractures. When patients present with these risk factors, clinicians should be vigilant and take appropriate preventive and therapeutic measures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval\u003c/strong\u003e \u003cp\u003e The Ethics Committee of Yichang Central People's Hospital approved this study.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConflict of interest\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eD.Y.wrote the main manuscript text,and formal analysis, review and editing. SW.C. participate in data collection.C.Z.prepared stables 1-5.HD. C. prepared figures 1,and conceptualization, methodology.All authors reviewed the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eManga S, Younes ABH, Dioum M, et al. Deep venous thrombosis of lower limbs: Prevalence, risk factors and treatment in Semi -urban areas in Senegal J. Open J Intern Med. 2021;11(4):194\u0026ndash;200.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAkeda K, Matsunaga H, Imanishi T, et al. Prevalence and countermeasures for venous thromboembolic diseases associated with spinal surgery: a follow-up study of an institutional protocol in 209 patients J. Spine (Phila Pa 1976). 2014;39(10):791\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWei B, Zhou H, Liu G et al. Risk factors for venous thromboembolism in patients with spinal cord injury: A systematic review and meta - analysis. J Spinal Cord Med, 2021 (5):1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDouillet D, Chapelle C, Ollier E, Mismetti P, Roy PM, Laporte S. 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Risk Factors for Venous Thromboembolism following Thoracolumbar Surgery: Analysis of 43,777 Patients from the American College of Surgeons National Surgical Quality Improvement Program 2005 to 2012. Global Spine J. 2016;6(8):738\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang H, Pei H, Ding W, et al. Risk factors of postoperative deep vein thrombosis (DVT) under low molecular weight heparin (LMWH) prophylaxis in patients with thoracolumbar fractures caused by high-energy injuries. J Thromb Thrombolysis. 2021;51(2):397\u0026ndash;404.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNavarrete S, Solar C, Tapia R, et al. Pathophysiology of deep vein thrombosis. Clin Exp Med. 2023;23(3):645\u0026ndash;54.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForan SJ, Taran S, Singh JM, et al. Timing of tracheostomy in acute traumatic spinal cord injury: A systematic review and meta-analysis. J Trauma Acute Care Surg. 2022;92(1):223\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBengoa F, Vicencio G, Schweitzer D, et al. High prevalence of deep vein thrombosis in elderly hip fracture patients with delayed hospital admission. J Eur J trauma Emerg surgery: official publication Eur Trauma Soc. 2020;46(4):913\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMagetsari R, Dewo P, Nugroho AS, et al. Deep Vein Thrombosis in Elderly Patients following Surgery for Fracture of the Proximal Femur. J Malays Orthop J. 2014;8(3):7\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLv B, Wang H, Zhang Z, et al. Nomogram for predicting postoperative deep vein thrombosis in patients with spinal fractures caused by high-energy injuries. Arch Orthop Trauma Surg. 2024;144(1):171\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eForan SJ, Taran S, Singh JM, et al. Timing of tracheostomy in acute traumatic spinal cord injury: A systematic review and meta-analysis. J Trauma Acute Care Surg. 2022;92(1):223\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang BF, Wei X, Huang H, et al. Deep vein thrombosis in bilateral lower extremities after hip fracture: a retrospective study of 463 patients. Clin Interv Aging. 2018;13:681\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang HY. Zhang ZP,L B,Analysis of risk factor for lower lower limb deep venous thrombosis in the perioperative period of high-energy thoracolumbar factors.J Trad Chin Orthop Thrauma.2022,34(2):24\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCross MB, Yi PH, Thomas CF, et al. Evaluation of malnutrition in orthopaedic surgery. J Am Acad Orthop Surg. 2014;22(3):193\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKunutsor SK, Seidu S, Katechia DT, Laukkanen JA. 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Dynamics of D-dimer in non-small cell lung cancer patients receiving radical surgery and its association with postoperative venous thromboembolism. J Thorac cancer. 2020;11(9):2483\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatsumoto S, Suda K, Iimoto S, et al. Prospective study of deep vein thrombosis in patients with spinal cord injury not receiving anticoagulant therapy. Spinal Cord. 2015;53(4):306\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMasuda M, Ueta T, Shiba K, et al. D-dimer screening for deep venous thrombosis in traumatic cervical spinal injuries. J Spine. 2015;15(11):2338\u0026ndash;44.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Spinal fracture, Deep vein thrombosis, Risk factors, D-dimer","lastPublishedDoi":"10.21203/rs.3.rs-4588401/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4588401/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective \u003c/strong\u003eTo analyze the independent risk factors for Deep Venous Thrombosis (DVT) in the lower limbs of patients after traumatic spinal fractures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eThe clinical data of 205 patients who underwent surgical treatment for traumatic spinal fracture due to high-energy injury in our hospital from September 2021 to February 2024 were retrospectively analyzed. Included patients were treated with low molecular weight heparin and mechanical prevention of DVT. Patients underwent ultrasound examination within 1 week after surgery and were divided into DVT group and non-DVT group.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eThe overall incidence of postoperative DVT was 26.9% (55/205). Proximal thrombus occurred in 3 patients (1.5%) and distal thrombus in 52 patients (25.4%). No patients developed pulmonary embolism. Binary Logistic analysis showed that age (OR= 1.120, P\u0026lt;0.001), D-dimer (OR=1.347, P=0.002), bed time (OR=1.313, P\u0026lt;0.001), hypoproteinemia (OR=14.380, P\u0026lt;0.001), Blood transfusion (OR=5.707, P=0.003) was an independent risk factor for postoperative DVT in patients with traumatic spinal fractures. The value of different risk factors in the diagnosis of postoperative DVT was analyzed by ROC curve. The AUC values of age, bed time, blood transfusion and hypoproteinemia were 0.734, 0.822, 0.760 and 0.777, respectively. The diagnostic value of D-dimer (AUC value =0.884) was the highest among these risk factors. The diagnostic cut-off value of postoperative D-dimer was determined by Jorden index to be 3.185mg/L.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eDespite chemical and mechanical prevention of DVT, the incidence of postoperative DVT remains high, with D-dimer\u0026gt;3.185mg/l on the first day after surgery, bed time, age, blood transfusion, and hypoproteinemia being independent risk factors for postoperative DVT in patients with traumatic spinal fractures.\u003c/p\u003e","manuscriptTitle":"Risk Factor Analysis for the Formation of Postoperative Lower Limb Deep Vein Thrombosis in Patients with Traumatic Spinal Fracture","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-15 19:23:20","doi":"10.21203/rs.3.rs-4588401/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b52b4b7a-cf91-4636-bf28-8d71d234013d","owner":[],"postedDate":"July 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-08-13T19:59:42+00:00","versionOfRecord":[],"versionCreatedAt":"2024-07-15 19:23:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4588401","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4588401","identity":"rs-4588401","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}