Postural control quantification in minimally and moderately impaired persons with multiple sclerosis:The reliability of a posturographic test and its relationships with functional ability

Background:Postural control has been associated with the functional impairment in persons with multiple sclerosis(pwMS).However,there is a need for reliable methods to assess postural control in early stages of the disease,when subtle changes can be difficult to detect.The aims of this study were to assess the absolute and relative reliability of a standing and a sitting posturographic protocol in minimally(Expanded Disability Status Scale≤2)and moderately(2.5≤Expanded Disability Status Scale≤4)impaired pwMS,and to analyze relationships among postural control and functional mobility and gait performance.Methods:To assess postural control in an upright stance,14 minimally and 16 moderately impaired pwMS performed six 70 s trials in tandem stance,3 with their weaker leg behind(TSWL)and 3 with their stronger leg behind(TSSL).Additionally,participants completed five 70 s trials using an unstable sitting protocol(US)to assess trunk stability.The mean radial errors of TSWL,TSSL,and US trials were calculated as postural control indexes.Furthermore,participants performed the Timed Up and Go test(TUG)and the Timed 25-foot Walk test(T25FW)to measure their functional mobility and gait speed,respectively.Reliability was evaluated using the intraclass correlation coefficient(ICC3,1)and the standard error of measurement(SEM).Analyses of variances were carried out to assess between-group differences.Hedges’g index(dg)was used to estimate the effect size of differences.Pearson correlation analyses(r)were performed to examine the relationships among the postural control and the functional tests.Results:Posturographic tests showed a high reliability in both minimally(0.87≤ICC≤0.92;9.32%≤SEM≤11.76%)and moderately(0.80≤ICC≤0.92;10.33%≤SEM≤15.33%)impaired pwMS.Similarly,T25FW and TUG displayed a high consistency in minimally(0.89≤ICC≤0.94;3.43%≤SEM≤5.17%)and moderately(0.85≤ICC≤0.93;5.57%≤SEM≤6.56%)impaired individuals.Minimally impaired pwMS showed a better performance on the TUG,T25FW,and TSWL than moderately impaired individuals(p<0.05;dg≥0.8).The TSWL,TSSL,and US variables correlated with TUG scores(0.419≤r≤0.604;p<0.05),but TSWL also correlated with T25FW scores(r=0.53;p<0.01).Furthermore,US scores correlated with both tandem stance parameters(TSWL:r=0.54,p<0.01;TSSL:r=0.43,p<0.05).Conclusion:Tandem and sitting posturographic tests provide reliable measures of postural control in pwMS,even in individuals with a homogeneous disease profile.Gait speed,functional mobility,and weaker leg status seem decisive in assessing the degree of physical activity limitation in pwMS.Finally,although trunk stability does not seem to be so affected by the course of the disease,it remains relevant for postural control and functional capacity.

A CRPS-Based Spatial Technique for the Verification of Ensemble Precipitation Forecasts

Traditional precipitation skill scores are affected by the well-known"double penalty"problem caused by the slight spatial or temporal mismatches between forecasts and observations.The fuzzy(neighborhood)method has been proposed for deterministic simulations and shown some ability to solve this problem.The increasing resolution of ensemble forecasts of precipitation means that they now have similar problems as deterministic forecasts.We developed an ensemble precipitation verification skill score,i.e.,the Spatial Continuous Ranked Probability Score(SCRPS),and used it to extend spatial verification from deterministic into ensemble forecasts.The SCRPS is a spatial technique based on the Continuous Ranked Probability Score(CRPS)and the fuzzy method.A fast binomial random variation generator was used to obtain random indexes based on the climatological mean observed frequency,which were then used in the reference score to calculate the skill score of the SCRPS.The verification results obtained using daily forecast products from the ECMWF ensemble forecasts and quantitative precipitation estimation products from the OPERA datasets during June-August 2018 shows that the spatial score is not affected by the number of ensemble forecast members and that a consistent assessment can be obtained.The score can reflect the performance of ensemble forecasts in modeling precipitation and thus can be widely used.

Land cover change and multiple remotely sensed datasets consistency in China

Introduction:Although numerous land cover datasets can act as references for understanding land cover change in China,the inconsistencies between the datasets can also provide understanding.Previous studies on the consistency between land cover datasets have mostly focused on land cover type consistencies and have ignored data consistencies in land cover change.Outcomes:Therefore,we aim to analyse the consistencies in land cover changes through likelihood assessment methods.We compared the spatiotemporal changes in forest,grassland,cropland,and bare land in the Climate Change Initiative land cover dataset(CCI-LC),Moderateresolution Resolution Imaging Spectroradiometer land cover dataset(MCD12Q1),China’s National Land Use and Cover Change(CNLUCC),Globeland30 and Global Land Cover Fine Surface Covering 30(GLC-FCS30)datasets in 2010.The results showed that the percentages and changes in each land cover type in MCD12Q1 were different from those in the other datasets.Discussion:For example,the proportion of grassland in MCD12Q1 was the highest,reaching 48.04%.The places with high consistency were the places where the land cover types were concentrated,and the bare land had the highest consistency.However,the consistency of China’s land cover change was quite low,and the percentage of low consistency was more than 87%from 2000-2018.Comparison of the data with the global artificial impervious area(GAIA)and Hansen-Global Forest Change(Hansen-GFC)datasets showed that the percentage of high construction gain consistency(38.83%)was higher than the forest change consistency,and the percentage forest loss high consistency(8.85%)was lower than the forest gain high consistency(12.76%).Conclusion:The results not only provide a basis for the use of land cover datasets but also give a clearer understanding of the pattern of land cover changes.