Study design A meta-analysis. Background Hip fracture (HF), as common geriatric fracture, is related to increased disability and mortality. Preoperative deep vein thrombosis (DVT) is one of the most common complications in patients with hip fractures, affecting 8–34.9% of hip fracture patients. The study aimed to assess the risk factors of preoperative DVT after hip fractures by meta-analysis. Methods An extensive search of the literature was performed in the English databases of PubMed, Embase, and the Cochrane Library; and the Chinese databases of CNKI and WAN FANG. We collected possible predictors of preoperative DVT from included studies, and data analysis was conducted with RevMan 5.3 and STATA 12.0. Results A total of 26 English articles were included, and the rate of DVT was 16.6% (1627 of 9823 patients) in our study. Our findings showed that advanced age [p = 0.0003, OR = 0.13 95% CI (0.06, 0.21)], female patients [p = 0.0009, OR = 0.82 95% CI (0.72, 0.92)], high-energy injury [p = 0.009, OR = 0.58 95% CI (0.38, 0.87)], prolonged time from injury to admission [p < 0.00001, OR = 0.54 95% CI (0.44, 0.65)], prolonged time from injury to surgery [p < 0.00001, OR = 2.06, 95% CI (1.40, 2.72)], hemoglobin [p < 0.00001, OR = − 0.32 95% CI (− 0.43, − 0.21)], coronary heart disease [p = 0.006, OR = 1.25 95% CI (1.07, 1.47)], dementia [p = 0.02, OR = 1.72 95% CI (1.1, 2.67)], liver and kidney diseases [p = 0.02, OR = 1.91 95% CI (1.12, 3.25)], pulmonary disease [p = 0.02, OR = 1.55 95% CI (1.07, 2.23)], smoking [p = 0.007, OR = 1.45 95% CI (1.11, 1.89)], fibrinogen [p = 0.0005, OR = 0.20 95% CI (0.09, 0.32)], anti-platelet drug [p = 0.01, OR = 0.51 95% CI (0.30, 0.85)], C-reactive protein [p = 0.02, OR = 5.95 95% CI (1.04, 10.85)], < 35 g/l albumin [p = 0.006, OR = 1.42 95% CI (1.1, 1.82)], and thrombosis history [p < 0.00001, OR = 5.28 95% CI (2.85, 9.78)] were risk factors for preoperative DVT. Conclusions Many factors, including advanced age, female patients, high-energy injury, prolonged time from injury to admission, prolonged time from injury to surgery, patients with a history of coronary heart disease, dementia, liver and kidney diseases, pulmonary disease, smoking, and thrombosis, fibrinogen, C-reactive protein, and < 35 g/l albumin, were found to be associated with preoperative DVT. Our findings suggested that the patient with above characteristics might have preoperative DVT. Level of evidence: Level III.

Background Surgical site infection (SSI) is one of the most common complications of orthopedic surgery, which can result in fever, pain, and even life-threatening sepsis. This study aimed to determine the predictors of SSI after fasciotomy in patients with acute leg compartment syndrome (ALCS). Methods We collected information on 125 ALCS patients who underwent fasciotomy in two hospitals between November 2013 and January 2021. Patients with SSI were considered as the SSI group and those without SSI as the non-SSI group. Univariate analysis, logistic regression analysis, and receiver operating characteristic (ROC) curve analyses were used to evaluate patient demographics, comorbidities, and admission laboratory examinations. Results In our research, the rate of SSI (26 of 125) was 20.8%. Several predictors of SSI were found using univariate analysis, including body mass index (BMI) (p = 0.001), patients with open fractures (p = 0.003), and patients with a history of smoking (p = 0.004). Besides, the levels of neutrophil (p = 0.022), glucose (p = 0.041), globulin (p = 0.010), and total carbon dioxide were higher in the SSI group than in the non-SSI group. According to the results of the logistic regression analysis, patients with open fractures (p = 0.023, OR 3.714), patients with a history of smoking (p = 0.010, OR 4.185), and patients with a higher BMI (p = 0.014, OR 1.209) were related predictors of SSI. Furthermore, ROC curve analysis indicated 24.69 kg/m2 as the cut-off value of BMI to predict SSI. Conclusions Our results revealed open fractures, BMI, and smoking history as independent risk factors for SSI following fasciotomy in patients with ALCS and determined the cut-off value of BMI, enabling us to individualize the evaluation of the risk for SSI to implement early targeted treatments.