The incidence and risk factors of deep venous thrombosis in lower extremities following surgically treated femoral shaft fracture: a retrospective case-control study

Distribution characteristics of perioperative deep vein thrombosis (DVT) and risk factors of postoperative DVT exacerbation in patients with thoracolumbar fractures caused by high-energy injuries

OBJECTIVE

To investigate the distribution characteristics of perioperative deep venous thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries and analyze the risk factors of postoperative DVT exacerbation.

METHODS

From October 2016 to July 2021, a total of 550 patients with thoracolumbar fractures due to high-energy injuries in our hospital were retrospectively analyzed. Both lower limbs were examined by ultrasound before and after operation. Depending on whether the postoperative DVT was exacerbating, the group was divided into a DVT exacerbation group and a non-DVT exacerbation group. Clinical data were used to study the characteristics of perioperative DVT. Logistic regression analysis and receiver operating characteristic (ROC) curve were used to explore the risk factors of postoperative DVT exacerbation.

RESULTS

DVT was found in 97 patients before operation, including 78 cases of distal thrombus, 6 cases of proximal thrombus, and 13 cases of mixed thrombus. Postoperative DVT increased to 116, including 87 distal thrombus, 10 proximal thrombus, and 19 mixed thrombus. The intermuscular vein was the most easily involved vein. Compared with lumbar fractures, thoracic fractures were more likely to have postoperative proximal thrombus (P=0.014). There were 48 cases of thrombus exacerbation after operation. Logistic regression analysis revealed that age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation.

CONCLUSIONS

The intermuscular vein is the most easily involved vein. The anatomical distribution of DVT at different fracture sites is different, and patients with thoracic fractures are more likely to have proximal DVT after operation. Age, lower extremity muscle strength, time from injury to operation, and blood loss were risk factors for postoperative DVT exacerbation.

A nomogram to predict postoperative deep vein thrombosis in patients with femoral fracture: a retrospective study

OBJECTIVE

The implementation of more active anticoagulant prevention and treatment measures has indeed led to a significant reduction in the incidence of perioperative deep vein thrombosis (DVT) among patients with bone trauma. However, it is important to note that despite these efforts, the incidence of DVT still remains relatively high. According to the Caprini score, all patients undergoing major orthopedic surgery were defined as the high-risk group for DVT. Stratifying the risk further within high-risk groups for DVT continues to present challenges. As a result, the commonly used Caprini score during the perioperative period is not applicable to orthopedic patients. We attempt to establish a specialized model to predict postoperative DVT risk in patients with femoral fracture.

METHODS

We collected the clinical data of 513 patients undergoing femoral fracture surgery in our hospital from May 2018 to December 2019. According to the independent risk factors of DVT obtained by univariate and multivariate logistic regression analysis, the corresponding nomogram model was established and verified internally. The discriminative capacity of nomogram was evaluated by receiver operating characteristic (ROC) curve and area under the curve (AUC). The calibration curve used to verify model consistency was the fitted line between predicted and actual incidences. The clinical validity of the nomogram model was assessed using decision curve analysis (DCA) which could quantify the net benefit of different risk threshold probabilities. Bootstrap method was applied to the internal validation of the nomogram model. Furthermore, a comparison was made between the Caprini score and the developed nomogram model.

RESULTS

The Caprini scores of subjects ranged from 5 to 17 points. The incidence of DVT was not positively correlated with the Caprini score. The predictors of the nomogram model included 10 risk factors such as age, hypoalbuminemia, multiple trauma, perioperative red blood cell infusion, etc. Compared with the Caprini scale (AUC = 0.571, 95% CI 0.479-0.623), the calibration accuracy and identification ability of nomogram were higher (AUC = 0.865,95% CI 0.780-0.935). The decision curve analysis (DCA) indicated the clinical effectiveness of nomogram was higher than the Caprini score.

CONCLUSIONS

The nomogram was established to effectively predict postoperative DVT in patients with femoral fracture. To further reduce the incidence, more specialized risk assessment models for DVT should take into account the unique risk factors and characteristics associated with specific patient populations.

Risk factors for venous thromboembolism following surgical treatment of fractures: A systematic review and meta-analysis

This study aimed to determine the risk factors for postoperative venous thromboembolism (VTE) in patients treated surgically for fractures using a meta-analytic approach. Electronic searches were performed in PubMed, Embase, and the Cochrane library from inception until February 2022. The odds ratio (OR) and 95% confidence interval (CI) were applied to calculate the pooled effect estimate using the random-effects model. Sensitivity, subgroup, and publication bias tests were also performed. Forty-four studies involving 3 239 291 patients and reporting 11 768 VTE cases were selected for the meta-analysis. We found that elderly (OR: 1.72; 95% CI: 1.38-2.15; P < .001), American Society of Anesthesiologists (ASA) ≥ 3 (OR: 1.82; 95% CI: 1.46-2.29; P < .001), blood transfusion (OR: 1.82; 95% CI: 1.14-2.92; P = .013), cardiovascular disease (CVD) (OR: 1.40; 95% CI: 1.22-1.61; P < .001), elevated D-dimer (OR: 4.55; 95% CI: 2.08-9.98; P < .001), diabetes mellitus (DM) (OR: 1.36; 95% CI: 1.19-1.54; P < .001), hypertension (OR: 1.31; 95% CI: 1.09-1.56; P = .003), immobility (OR: 3.45; 95% CI: 2.23-5.32; P < .001), lung disease (LD) (OR: 2.40; 95% CI: 1.29-4.47; P = .006), obesity (OR: 1.52; 95% CI: 1.27-1.82; P < .001), peripheral artery disease (PAD) (OR: 2.13; 95% CI: 1.21-3.73; P = .008), prior thromboembolic event (PTE) (OR: 5.17; 95% CI: 3.14-8.50; P < .001), and steroid use (OR: 2.37; 95% CI: 1.73-3.24; P < .001) were associated with an increased risk of VTE. Additionally, regional anaesthesia (OR: 0.66; 95% CI: 0.45-0.96; P = .029) was associated with a reduced risk of VTE following surgical treatment of fractures. However, alcohol intake, cancer, current smoking, deep surgical site infection, fusion surgery, heart failure, hypercholesterolemia, liver and kidney disease, sex, open fracture, operative time, preoperative anticoagulant use, rheumatoid arthritis, and stroke were not associated with the risk of VTE. Post-surgical risk factors for VTE include elderly, ASA ≥ 3, blood transfusion, CVD, elevated D-dimer, DM, hypertension, immobility, LD, obesity, PAD, PTE, and steroid use.

Dynamic Changes and Relevant Factors of Perioperative Deep Vein Thrombosis in Patients with Thoracolumbar Fractures Caused by High-Energy Injuries

OBJECTIVE

To investigate the dynamic changes and relevant factors of deep vein thrombosis (DVT) in patients with thoracolumbar fractures caused by high-energy injuries.

METHODS

From January 2016 to June 2021, a total of 655 patients with thoracolumbar fractures who underwent surgical treatment in our hospital were retrospectively analyzed. The patients were examined by preoperative and postoperative ultrasonography, and divided into thrombus growth group, thrombus invariant group, and thrombus regression group according to the preoperative and postoperative ultrasonographic results. Medical record data, including demographic data, surgical data, and laboratory results, were collected and the differences in various factors among the groups were compared.

RESULTS

DVT was found in 99 patients (15.1%, 99/655) before surgery, including 79 cases of distal thrombus, 7 cases of proximal thrombus, and 13 cases of mixed thrombus. The incidence of postoperative DVT increased to 20.6% (134/655), including 96 cases of distal thrombus, 15 cases of proximal thrombus, and 23 cases of mixed thrombus. Among them, 39.7% had thrombus growth, 49.3% had thrombus basically unchanged and 11.0% had thrombolysis. There were significant differences in age, lower extremity muscle strength, time from trauma to surgery, operation time, blood loss, blood transfusion, and post 3-D-dimer among the three groups.

CONCLUSIONS

In patients with thoracolumbar fractures caused by high-energy injuries, the majority of patients with DVT do not change or grow after surgery, and only a few of them have thrombolysis. Younger age, lower extremity motor, and fewer blood transfusion contribute to thrombolysis. Delayed surgical intervention, longer operation time, and higher blood loss can lead to thrombosis growth. Post 3-D-dimer is closely related to the dynamic changes of thrombus.

Incidence and Related Factors for Low-Extremity Deep Vein Thrombosis in Breast Cancer Patients Who Underwent Surgical Resection: What Do We Know and What Should We Care

Malignancy, surgical resection, and neoadjuvant and/or adjuvant chemotherapy increase the low-extremity deep vein thrombosis (LDVT) risk in patients with breast cancer, bringing in great physical burdens, disabilities, and worse survivals. However, LDVT in surgical breast cancer patients is scarcely reported. Therefore, this study aimed to evaluate the incidence and related factors for LDVT in these patients. Patients with breast cancer who underwent surgical resection were included. LDVT was examined on the day of discharge and 1 month after the discharge. A total of 491 eligible patients were included, among which 11 (2.2%) patients occurred LDVT. Besides, higher age, history of diabetes mellitus, advanced T and tumor node metastasis (TNM) stages, higher platelet count, and shorter activated partial thromboplastin time (APTT) were correlated with increased LDVT incidence (all p < 0.05). Additionally, higher age [p = 0.004, odds ratio (OR) (95% CI): 1.082 (1.023–1.144)], history of diabetes mellitus [p = 0.003, OR (95% CI): 10.426 (2.219–48.986)], and a higher platelet count [p = 0.008, OR (95% CI): 1.017 (1.004–1.029)] were independent factors for increased LDVT incidence, while higher APTT [p = 0.004, OR (95% CI): 0.636 (0.467–0.866)] was an independent factor for decreased LDVT incidence. Lastly, the risk prediction model involving age, history of diabetes mellitus, platelet count, and APTT showed a good ability to predict LDVT occurrence (area under curve: 0.919, 95% CI: 0.869–0.968). In conclusion, the LDVT incidence is 2.2%, and its independent factors consist of age, history of diabetes mellitus, platelet count, and APTT in patients with breast cancer who underwent surgical resection, which provides evidence for the prevention and surveillance of LDVT in surgical breast cancer.