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ObjectiveTo explore the clinical efficacy on training by using hydrogel to improve swallowing function in patients with dysphagia after stroke.MethodsIn accordance with the diagnostic criteria of stroke established by Neurology Society of Chinese Medical Association, a total of 80 patients with dysphagia after stroke and Functional Oral Intake Scale (FOIS) with FOIS grade 1-3 were enrolled from May 2020 to October 2020. According to the random number table, they were randomly divided into observation group and control group, with 40 cases in each group. In addition to the routine swallowing rehabilitation treatment by the routine nasogastric tube treatment, the observation group was given oral feeding training of hydrogel under nasal feeding state for 3 weeks. Before and after treatment, the swallowing function of the two groups was determined by FOIS, the leakage aspiration was assessed by Penetration-Aspiration scale (PAS), and the efficacy was evaluated by the rate of nasogastric tube removal. The mean FOIS, PAS and the extubation rate of nasogastic tube were compared between the two groups before and after treatment.ResultsThere was statistically significant difference in FOIS grade in the control group before and after treatment (χ2=38.892, P2=11.987, P>0.05). The extubation rate of nasogastic tube in the control group was 25%. The difference of FOIS and PAS grade in the observation group before and after treatment was statistically significant (χ2=94.517, P2=86.176, P2=57.411, P2=48, P

Aim: The chin‐down posture is a widely used compensatory manoeuvre for patients with dysphagia. The aim of this study was designed to systematically measure the effectiveness of chin‐down manoeuvre application. Methodology: We retrieved the PubMed, Web of Science, Embase, Cochrane Library, EBSCO, Medline, CNKI, WANFANG, VIP and SinoMed databases from inception to 30 August 2022. Raters independently screened literature according to inclusion and exclusion criteria. The quality of the included literature was evaluated, and data were extracted. The software Review Manager software 5.3 was used for statistical analysis. Results: Fourteen studies with a total of 571 patients were included in this meta‐analysis. The meta‐analysis indicated that chin‐down manoeuvre could significantly reduce the risk of aspiration (MD = −1.35, 95% CI [−2.25, −0.44], Z = 2.92, p <.01), decrease the chin angle (MD = −12.20, 95% CI [−14.61, −9.79], Z = 9.91, p <.001), shorten oral transit time (MD = −0.81, 95% CI [−1.20, −0.43], Z = 4.17, p <.001), reduce the maximum swallowing pressure at upper oesophageal sphincter (MD = −82.07, 95% CI [−112.77, −51.37], Z = 5.24, p <.001) and decrease pharyngeal residue. Conclusions: Existing evidence indicated that chin‐down manoeuvre could reduce the risk of aspiration and pharyngeal residue, decrease the maximum swallowing pressure at UES. More large‐sample, high‐quality clinical trials are still needed in the future to further ascertain the results of this research. [ABSTRACT FROM AUTHOR]

The climate–hydrological modelling chain is the most widely used approach for assessing likely future changes in streamflow but is also associated with large uncertainties. We present an alternative approach for modelling monthly streamflow directly from large‐scale atmospheric variables using statistical downscaling to streamflow for 42 catchments with flow generation regimes ranging from largely snowmelt‐driven to entirely rainfall‐driven. It aims to find the most appropriate combination of predictors and methods, which can best include information pertaining to snow storage and provide robust streamflow simulations under changing climate conditions. The effects of selection of probable predictors (five groups of potential variables from reanalysis data, three moving windows, calibration periods of two different lengths) and methods (eight combinations of pre‐processing methods and statistical models) were considered. Results indicate that the following selection of probable predictors gave a good and robust model performance: a combination of 13 independent climate variables and their lagged information, a 3‐month moving window and a calibration period of 31 years. Three combinations of methods performed best: (a) principal component analysis (PCA) and the relevance vector machine (RVM) statistical model using gridded data, (b) PCA and RVM using interpolated data and (c) the Pearson correlation analysis and RVM using interpolated data. Monthly streamflow was well reproduced for most catchments, with a median NSE (Nash and Sutcliffe efficiency) of 0.82 and PBIAS (percentage bias) of 0 in the calibration period and a median NSE over 0.60 and PBIAS less than −6 in the validation period. The best performance of the methods was associated with snow‐dominated catchments in inland regions. We also established that lagged information on atmospheric variables gave better results than snow variables from reanalysis data. The poorest results were associated with rainfall‐dominated catchments, and this was strongly correlated with the inter‐ versus the intra‐annual variability in monthly streamflow. [ABSTRACT FROM AUTHOR]