Objective To investigate the risk factors for postoperative loss of reduction in unstable distal radius fractures and to develop a predictive model, providing clinicians with a more precise risk assessment tool to support the formulation of individualized treatment plans. MethodsA retrospective analysis was conducted on the clinical data of 209 patients with unstable distal radius fractures who met the selection criteria between January 2018 and December 2023. There were 97 males and 112 females, aged 44-81 years with a mean age of 57.1 years. Univariate analysis was performed to identify factors associated with postoperative loss of reduction. Multivariate logistic regression analysis was then used to screen risk factors and construct a nomogram prediction model. The Hosmer-Lemeshow test was applied to assess model fit, while the area under the receiver operating characteristic (ROC) curve (AUC) was calculated to evaluate the predictive performance. Additionally, decision curve analysis was employed to assess the clinical utility of the model. ResultsAt 6 months after operation, radiographic evaluation showed loss of reduction in 68 cases. Univariate analysis identified the following as influencing factors for postoperative loss of reduction (P<0.05): age, fracture displacement, fracture classification, dorsal metaphyseal comminuted fracture, osteoporosis, operation time, and preoperative serum calcium level. Multivariate analysis confirmed the following as risk factors for postoperative loss of reduction (P<0.05): older age, more severe fracture type (higher AO/OTA classification), presence of fracture displacement, dorsal metaphyseal comminuted fracture, low preoperative serum calcium level, osteoporosis, and prolonged operation time. The nomogram prediction model constructed based on these factors demonstrated high accuracy in assessing the risk of loss of reduction, with an AUC of 0.946 (95%CI: 0.917, 0.975). The calibration curve showed good agreement between predicted and observed probabilities (χ2=4.735, P=0.785). Decision curve analysis indicated that when the predicted risk of postoperative loss of reduction exceeds 0.1, timely intervention can yield substantial net clinical benefit. ConclusionOlder age, AO/OTA type C fractures, fracture displacement, dorsal metaphyseal comminuted fracture, prolonged operation time, low preoperative serum calcium level, and comorbid osteoporosis are the main risk factors for postoperative loss of reduction in patients with unstable distal radius fractures. The established predictive nomogram model enables clinicians to more accurately assess the risk of postoperative loss of reduction and provides valuable support for personalized treatment decisions.
Alzheimer’ s disease is the most common kind of dementia without effective treatment. Via early diagnosis, early intervention after diagnosis is the most effective way to handle this disease. However, the early diagnosis method remains to be studied. Neuroimaging data can provide a convenient measurement for the brain function and structure. Brain structure network is a good reflection of the fiber structural connectivity patterns between different brain cortical regions, which is the basis of brain’s normal psychology function. In the paper, a brain structure network based on pattern recognition analysis was provided to realize an automatic diagnosis research of Alzheimer’s disease and gray matter based on structure information. With the feature selection in pattern recognition, this method can provide the abnormal regions of brain structural network. The research in this paper analyzed the patterns of abnormal structural network in Alzheimer’s disease from the aspects of connectivity and node, which was expected to provide updated information for the research about the pathological mechanism of Alzheimer’s disease.
Brain aging can affect the strength of functional connectivity between brain regions. In recent years, studies have shown that functional connectivity is fluctuant over time, and can reflect more physiological and pathological information. Therefore, in the study resting state functional magnetic resonance imaging (fMRI) data of 32 elderly subjects and 36 younger subjects were selected, and the sliding window technique was used to estimate dynamic functional connectivity network. Then, the dependency of fluctuating energy difference on frequency band was studied using wavelet packet analysis, conducting the linear regression with age at the same time. Results showed that the fluctuating energy in older group was significantly higher than that in the young group in low frequency, and it was significantly lower than that in the young people in high frequency. These results suggested that the dynamic functional connectivity between networks in the elderly exist slow wave phenomenon, which may be related to the decreased reaction rate of the elderly. This article provides new ideas and methods for the research about brain aging, and promotes a theoretical basis for further understanding of the physiological significance of brain dynamic functional connectivity.
Percutaneous ventricular assist device (PVAD) is a minimally invasive treatment which can replace the function of the failing heart. It provides circulatory support for patients with severe emergent cardiovascular diseases such as complex coronary artery disease, acute myocardial infarction complicated by cardiogenic shock, and acute decompensated chronic heart failure. PVAD has been developed since the rise of the Hemopump, to the prosperity of the Impella, and increasingly been used as a haemodynamic support to improve prognosis. This article will review the evolution and clinical application of PVAD.