This study aimed to explore the association between mean platelet volume (MPV) and preoperative deep vein thrombosis (DVT) in older patients with hip fracture. A total of 352 consecutive older patients with hip fracture were included from January 2014 to December 2020. MPV values were measured on admission, and color Doppler ultrasonography was performed for DVT screening before the planned surgery. The receiver operating characteristic (ROC) curve was used to establish the optimal cut-off value for the prediction of DVT. Univariate and multivariate logistic regression analysis were used to examine the association between factors and DVT. The overall prevalence of preoperative DVT was 15.1%, and patients with DVT had a lower value of MPV than non-DVT patients (11.6 ± 1.2 fL vs 12.3 ± 1.4 fL, P < .01). The cut-off point according to the ROC curve for MPV was 13.3 fL, and multivariate logistic regression analysis showed that MPV level < 13.3 fL was significantly associated with an increased risk of DVT (OR = 4.857, 95% CI: 1.091-21.617, P = .038), and with every 1.0 fL decrease in MPV, the risk increased by 27.7% (OR = 1.277, 95% CI: 1.001-1.629, P = .047). Our findings indicate that a low MPV level is associated with DVT in older patients with hip fracture. As MPV is a simple indicator that can be calculated from the blood routine test, it may be a potential biomarker of DVT with the combination of other tests, further studies are needed to confirm these results.
The disequilibrium theory in economics is used to depict the network traffic flow evolution process from disequilibrium to equilibrium. Three path choice behavior criteria are proposed, and the equilibrium traffic flow patterns formed by these three criteria are defined as price regulation user equilibrium, quantity regulation user equilibrium, and price-quantity regulation user equilibrium, respectively. Based on the principle of price-quantity regulation user equilibrium, the method of network tatonnement process is used to establish a network traffic flow evolution model. The unique solution of the evolution model is proved by using Picard's existence and uniqueness theorem, and the stability condition of the unique solution is derived based on stability theorem of nonlinear system. Through numerical experiments, the evolution processes of network traffic flow under different regulation modes are analyzed. The results show that all the single price regulation, single quantity regulation, and price-quantity regulation can simulate the evolution process of network traffic flow. Price-quantity regulation is the combination of price regulation user equilibrium and quantity regulation user equilibrium, which thus can simulate the evolution process of network traffic flow with multiple user class.
In many cases, the final path selection of travellers' is not the shortest path, due to the limited computing power and high cost of path search. To solve the problem, this paper proposes a day-today (DTD) stochastic traffic flow assignment model that regulates the traffic flow based on the travel time (travel cost) and residual congestion of optional paths. The regulation mechanism is called the mixed regulation. Then, the authored proved the existence, uniqueness and stability of the model solution. The proposed model was verified through simulation on a Nguyen-Dupuis road network. The results show that traffic flows and travel times of all paths reached the equilibrium state, thanks to the DTD mixed regulation for 20 ∼ 30 days. From the traffic flows and congestion degrees of different sections, it can be seen that our model with mixed regulation diverts the traffic flow to the sections with a low congestion degree, and encourages travellers to drive through the sections with a low traffic flow. In addition, the congestion degrees of the four most congested sections decreased by 5.8%, 4%, 7% and 1.2%, respectively, and the entire road network exhibited a slight downward trend in mean congestion degree. These results prove that our model can uniformize the traffic flow, improve the operation efficiency and alleviate the congestion of the road network. These findings shed new light on the control, guidance and planning of traffic flow in road networks.
Purpose To analyze the relationship between monocyte count and preoperative deep venous thrombosis (DVT) in older patients with hip fracture. Methods Consecutive older patients with hip fracture undergoing surgery were included from January 2014 to December 2021. Monocyte count was measured on admission, and Doppler ultrasonography was performed for DVT screening prior to surgery. Univariate and multivariate logistic regression analyses were used to assess the association between monocyte count and DVT. Results A total of 674 patients were finally included, and 128 patients (19.0%) were diagnosed with preoperative DVT. Patients with DVT exhibited a higher monocyte count than patients without DVT [0.55 (0.43-0.72) × 109/L versus 0.49 (0.38-0.63) × 109/L, P = 0.007]. Multivariate logistic regression analysis showed that a high monocyte count (> 0.6 × 109/L) was independently associated with a higher risk of DVT (OR = 1.705, 95% CI: 1.121-2.593, P = 0.013), and for every 0.1 × 109/L increase in monocyte count, the risk of DVT increased by 8.5% (OR = 1.085, 95% CI: 1.003-1.174, P = 0.041). Other risk factors associated with DVT included intertrochanteric fracture (OR = 1.596, 95% CI: 1.022-2.492, P = 0.040), and elevated fibrinogen level (OR = 1.236, 95% CI: 1.029-1.484, P = 0.023). Conclusion A high monocyte count is associated with an increased risk of DVT in older patients with hip fracture. Future studies should evaluate the potential role of monocyte in the prevention and treatment of thrombosis.
A new family of lanthanide complexes based on the tetrazole-1-acetic ligand and the 1,10-phenanthroline co-ligand were synthesized and characterized by IR spectra, thermogravimetric analyses, powder X-ray diffraction and single-crystal X-ray...
To analyze the influence of tradable credits and bus departure quantity on travelers' travel mode choice, this study investigated car travel and bus travel as research objects and established a two-mode day-to-day travel mode choice model based on tradable credits and bus departure quantity. To improve the guiding effect of tradable credits and bus departure quantity, an optimization scheme of tradable credits and bus departure quantity was developed with the goal of minimizing the system total travel time of car travel and the system total comprehensive cost of bus travel. Taking a test transportation network as an example, the influence of no tradable credits scheme, tradable credits scheme, and tradable credits and bus departure quantity scheme on the travelers’ travel mode choice behavior was analyzed. The results showed that the tradable credits and bus departure quantity scheme could reduce the saturation of road traffic and improve bus service quality.
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