Objective To study the effect of clinical nursing path(CNP)on the swallowing training of stroke patients with neural deglutition disorders.Methods Sixty stroke patients with neural deglutition disorders were recruited from January 2012 to October 2012 in the department of neurology of our hospital.The patients were divided into two groups according to the sequence of admission:the experiment group(n=30)and the control group(n=30).CNP was applied in the experimental group and the traditional nursing approach in the control.The two groups were compared in terms of the improvement of deglutition disorder.Result The effective rate of the experiment group was significantly higher than the rate of the control group(P<0.05).Conclusion CNP is effective in improving stroke patients’neural deglutition disorders and enhancing their life quality.

Objective:To investigate the characteristics of macular perfusion and structures in patients with early stages of diabetic retinopathy (DR) using optical coherence tomography angiography (OCTA).Methods:A cross-sectional study was performed.Forty eyes of 27 diabetic patients without diabetic retinopathy (NDR), forty eyes of 24 patients with mild non-proliferative diabetic retinopathy (NPDR) and forty eyes of 28 patients with moderate NPDR were recruited in Guangdong Provincial People's Hospital from June 2017 to August 2018.RTVue-XR OCTA was used to scan a 6 mm×6 mm area centered in the fovea and the superficial vascular complex (SVC) and deep vascular complex (DVC) vessel density, fovea avascular zone (FAZ) area, FAZ perimeter, acircularity index (AI), and vessel density of a 300 μm wide ring area around FAZ (FD300) were quantified.The associations among stages of DR and macular vessel density, structures were analyzed.This study was approved by the Ethics Committee of the Guangdong Provincial People's Hospital (No.2016232A).Results:The vessel density of SVC and DVC tended to decrease as the progression of DR.The vessel density of SVC was (51.25±3.27)%, (48.81±3.99)%, (47.00±3.49)%, (45.73±3.35)%, and the vessel density of DVC was (53.89±6.30)%, (49.94±6.05)%, (46.69±4.87)% and (44.78±4.30)% in the control group, NDR group, mild NPDR group, and moderate NPDR group, respectively.The vessel densities of SVC and DVC were statistically different among the four groups ( F=18.33, 21.53; both at P<0.01). The vessel density of SVC and DVC in the NDR group, mild NPDR group, moderate NPDR group was significantly lower than that in the control group (all at P<0.01). The vessel densities of FD300 in the mild NPDR group and moderate NPDR group were significantly lower than that in the control group (all at P<0.01). The FAZ area of the control group, NDR group, mild NPDR group, and moderate NPDR group was (0.31±0.11), (0.32±0.09), (0.34±0.13), and (0.37±0.10)mm 2, respectively.There was no significant difference in the FAZ area among the four groups ( F=2.18, P=0.09). The FAZ perimeter and AI were significantly higher in the moderate NPDR group than those in the control group (both at P<0.05). Conclusions:OCTA is able to detect the decrease of vessel density in diabetic patients before the occurrence of visible fundus lesions.The vessel density of SVC and DVC in patients with early stages of DR is decreased.DVC vessel density may be a sensitive marker to indicate DR.FD300 is not significantly decreased until mild NPDR, FAZ area and perimeter are significantly increased in moderate NPDR, indicating a more irregular FAZ.

【Objective】 To construct and validate a risk prediction model for cognitive impairment after stroke based on demographic, clinical, and neuroimaging characteristics. 【Methods】 Through the medical record system, we collected all data of the patients. We finished cognitive function testing three months after the indexed stroke. The Mini-Mental State Examination Scale score≤26 was defined as cognitive dysfunction. Optimal subset regression analysis was used to screen variables, Logistic regression analysis was used to construct a predictive model for cognitive impairment, and C-index, calibration chart and clinical decision curve analyses were used to evaluate the discrimination, consistency, and clinical availability of the model. And nomograms were used to express the performance of the model. 【Results】 Seven variables were selected: cognitive function before stroke, age, years of education, National Institutes of Health Stroke Scale score at admission, history of ischemic heart disease, the number of old lacunar infarct lesions, and medial temporal lobe atrophy scale. The prediction model had a C-index of 0.845 (95% CI: 0.805-0.885). The clinical decision curve showed that the model had a positive net benefit when the threshold probability was 9.0%-90.0%. 【Conclusion】 The predictive model of cognitive impairment in stroke patients has good predictive efficiency and provides an effective assessment tool for screening high-risk cases of cognitive impairment in patients with stroke of various subtypes.