Ophthalmic solution of organic-inorganic layered double hydroxides hybrid nanocomposites based on layered double hydroxides(LDH)intercalated with pirenoxine sodium(PRN)and chitosan-glutathione(CG)was prepared, characterized and evaluated using rabbit precorneal retention. Mg-Al-PRN-LDH, Zn-Al-PRN-LDH and CG-PRN-LDH were synthesized by co-precipitation. The nanocomposites were characterized by laser particle sizer, powder X-ray diffraction(X-RD), fourier transform infrared spectra(FTIR)and transmission electron micrographs(TEM). The release of PRN from Mg-Al-PRN-LDH, Zn-Al-PRN-LDH, and CG-PRN-LDH nanocomposites and API in artificial tear was compared. Based on in vivo precorneal retention studies, PRN-LDH and CG-PRN-LDH nanocomposite dispersions showed significantly higher AUC(3. 72-, 7. 59-folds)and MRT(2. 18-, 2. 60-folds)than that of the commercial eye drops group. Organic-inorganic layered double hydroxides hybrid nanocomposites CG-PRN-LDH dispersions could remarkably improve precorneal retention of PRN.

Objective To examine the incidence ,clinical characteristics ,and risk factors for falls within two years after stroke in elderly patients. Methods A total of 365 elderly stroke patients from the Department of Neurology at the 8th Nanning People's Hospital were recruited from June 1 , 2013 to December 31 ,2014. They were divided into a fall group and a non-fall group and were followed up for two years. The incidence and clinic characteristics of falls were analyzed. The risk factors for falls were analyzed by multiple Logistic regression analysis. Results Of the 365 stroke patients included in this study ,falls were observed in 146(40.2％ )patients. The interval between the stroke and the first fall :72(49.3％ )patients had the first fall within 3 months;22(15.1％ )occurred between 4 and 6 months;20 (13.7％ )between 7 and 12 months ;17 (11.6％ )between 13 and 18 months ;and 15 (10.3％ )between 19 and 24 months.A hundred and five(71.9％ )patients fell during daytime and 41 (28.1％ )patients during night.Eighteen(12.3％ )patients had one fall ;65(44.5％ )patients fell 2 to 4 times ;60(41.1％ )patients fell 5 to 10 times ;and 3(2.1％ )patients fell over 10 times.A total of 709 falls were observed.Places of falls :102(69.9％ )falls happened indoors and 44(30.1％ )falls occurred outdoors.Circumstances of falls :27 (18.5％ )patients fell when turning over ;23 (15.8％ )fell when rising from a seating position ;4(2.7％ )patients fell when showering ;15(10.3％ )patients fell while standing ;9(6.8％ )fell when turning around ;56(38.3％ )fell while walking ;and 12(8.2％ )fell while climbing the stairs or running.The severity of falls :52(35.6％ )patients had no injury ;78(53.2％ ) suffered soft tissue injury ;16 (11.0％ )had fractures ;and 78 (53.2％ )had fear of falling.Multiple Logistic regression analysis showed that age(OR=2.41 ;95％ CI :1.69-3.05) ,history of falls(OR =2.85 ;95％ CI :1.46-3.81) ,history of stroke(OR=1.87 ;95％ CI :1.12-2.79) ,right hemiplegia(OR=2.37 ;95％ CI :1.62-4.59) ,left hemiplegia(OR= 2.47 ;95％ CI :1.46-4.78) ,paraplegia(OR= 2.55 ;95％ CI :1.57-4.98) ,visual impairment(OR=2.35 ;95％ CI :1.35-6.62) ,apraxia(OR=2.53 ;95％ CI :1.42-5.63) ,unilateral spatial neglect (OR=3.34 ;95％ CI :2.82-6.34) ,use of psychotropic medications (OR= 1.76 ;95％ CI :1.11-1.98) ,impaired physical mobility (OR = 1.58 ;95％ CI :1.82-2.91) ,low MMSE scale(OR = 3.42 ;95％ CI :1.38-7.41) ,low Barthel Index score(OR = 2.83 ;95％ CI :0.97-4.68) ,BBS scale<45(OR=2.48 ;95％ CI :1.27-4.18) ,TUG>15seconds(OR=3.56 ;95％ CI :1.91-5.23) ,and lack of rehabilitation therapy (OR=3.42 ;95％ CI :1.38-7.41)were independent predictors for falls(all P<0.05). Conclusions Falls are common among elderly patients within two years after stroke.Most falls happen indoors ,during daytime and while moving.Age ,history of falls ,history of stroke ,hemiplegia ,visual impairment ,apraxia ,unilateral spatial neglect ,use of psychotropic medications ,walk with a walker ,low MMSE scale ,low Barthel Index score ,BBS scale<45 ,TUG>15 seconds ,and lack of rehabilitation therapy are independent risk factors for falls after stroke.

Objective:To investigate the incidence, clinical characteristics and risk factors for hip fractures in patients within two years after stroke onset.Methods:A total of 332 persons with first-onset stroke from the neurology department of our hospital between 1 June 2013 and 31 December 2014 were recruited and were divided into the hip fracture group and the non-hip fracture group.Clinical characteristics were recorded.Vision was tested as normal or impaired.Patients were accessed by the National Institutes of Health Stroke Scale(NIHSS), Behavioral Inattention Test, Baking Tray Task, Mini-Mental State Examination(MMSE), Birgitta Lindmark(BL)motor assessment scale, Berg Balance Scale(BBS), Timed Up & Go(TUG)Scale, and Stops Walking When Talking(SWWT)Scale.The clinic characteristics and risk factors for hip fractures were compared between the two groups after a 2-year follow-up.The accuracy of risk factors for fracture prediction was assessed by the sensitivity, specificity, and positive and negative predictive values.Results:Of 332 patients with stroke, 16 cases fractured their hips within two years after stroke onset, which corresponded to an incidence of 33‰/year(95% CI: 15‰/year-50‰/year). The 2-year mortality rate was 44%(95% CI: 25%-60%)and 48%(95% CI: 42%-54%)in patients with and without hip fractures respectively( χ2=0.036, P=0.724). The mean survival time for patients with and without hip fracture was 2.72 years(95% CI: 1.45-2.79)and 2.21 years(95% CI: 1.48-2.34)respectively.The proportions of patients with previous fractures history( χ2=16.780, P=0.041)and impaired vision( χ2=11.210, P=0.027), MMSE scale score( U=14.220, P=0.031), TUG ≥ 15 s( χ2=18.560, P=0.000)were higher, and SWWT( χ2=20.340, P=0.000)was lower in the hip fracture group than in the non-hip fracture group.The negative predictive values of previous fractures history, impaired vision, TUG and SWWT were higher than their positive predictive value.The specificities of previous fractures history, impaired vision, and SWWT were higher than their sensitivities.And the sensitivity of TUG was higher than its specificity. Conclusions:Hip fractures after stroke are common in elderly patients.Fractures often occur during daytime at home in daily activities.The previous fractures history, visual and cognitive dysfunction and impaired functional mobility are risk factors for hip fractures.We should take measures to prevent falls according to the relevant factors.Among the test scales, the timed up & go(TUG)scale could much more accurately identify patients at high risk for hip fractures.

Objective:To study the current status of longitudinal extrauterine growth restriction (EUGR) in extremely preterm infants (EPIs) and to develop a prediction model based on clinical data from multiple NICUs.Methods:From January 2017 to December 2018, EPIs admitted to 32 NICUs in North China were retrospectively studied. Their general conditions, nutritional support, complications during hospitalization and weight changes were reviewed. Weight loss between birth and discharge > 1SD was defined as longitudinal EUGR. The EPIs were assigned into longitudinal EUGR group and non-EUGR group and their nutritional support and weight changes were compared. The EPIs were randomly assigned into the training dataset and the validation dataset with a ratio of 7∶3. Univariate Cox regression analysis and multiple regression analysis were used in the training dataset to select the independent predictive factors. The best-fitting Nomogram model predicting longitudinal EUGR was established based on Akaike Information Criterion. The model was evaluated for discrimination efficacy, calibration and clinical decision curve analysis.Results:A total of 436 EPIs were included in this study, with a mean gestational age of (26.9±0.9) weeks and a birth weight of (989±171) g. The incidence of longitudinal EUGR was 82.3%(359/436). Seven variables (birth weight Z-score, weight loss, weight growth velocity, the proportion of breast milk ≥75% within 3 d before discharge, invasive mechanical ventilation ≥7 d, maternal antenatal corticosteroids use and bronchopulmonary dysplasia) were selected to establish the prediction model. The area under the receiver operating characteristic curve of the training dataset and the validation dataset were 0.870 (95% CI 0.820-0.920) and 0.879 (95% CI 0.815-0.942), suggesting good discrimination efficacy. The calibration curve indicated a good fit of the model ( P>0.05). The decision curve analysis showed positive net benefits at all thresholds. Conclusions:Currently, EPIs have a high incidence of longitudinal EUGR. The prediction model is helpful for early identification and intervention for EPIs with higher risks of longitudinal EUGR. It is necessary to expand the sample size and conduct prospective studies to optimize and validate the prediction model in the future.