BACKGROUND Non-invasive tests,such as Fibrosis-4 index and transient elastography(com-monly FibroScan),are utilized in clinical pathways to risk stratify and diagnose non-alcoholic fatty liver disease(NAFLD).In 2018,a...BACKGROUND Non-invasive tests,such as Fibrosis-4 index and transient elastography(com-monly FibroScan),are utilized in clinical pathways to risk stratify and diagnose non-alcoholic fatty liver disease(NAFLD).In 2018,a clinical decision support tool(CDST)was implemented to guide primary care providers(PCPs)on use of FibroScan for NAFLD.AIM To analyze how this CDST impacted health care utilization and patient outcomes.METHODS We performed a retrospective review of adults who had FibroScan for NAFLD indication from January 2015 to December 2017(pre-CDST)or January 2018 to December 2020(post-CDST).Outcomes included FibroScan result,laboratory tests,imaging studies,specialty referral,patient morbidity and mortality.RESULTS We identified 958 patients who had FibroScan,115 before and 843 after the CDST was implemented.The percentage of FibroScans ordered by PCPs increased from 33%to 67.1%.The percentage of patients diagnosed with early F1 fibrosis,on a scale from F0 to F4,increased from 7.8%to 14.2%.Those diagnosed with ad-vanced F4 fibrosis decreased from 28.7%to 16.5%.There were fewer laboratory tests,imaging studies and biopsy after the CDST was implemented.Though there were more specialty referrals placed after the CDST was implemented,multivariate analysis revealed that healthcare utilization aligned with fibrosis score,whereby patients with more advanced disease had more referrals.Very few patients were hospitalized or died.CONCLUSION This CDST empowered PCPs to diagnose and manage patients with NAFLD with appropriate allocation of care towards patients with more advanced disease.展开更多
With growing pressures on marine ecosystems and on marine space,an increasingly needed strategy to optimise the use of marine space is to co-locate synergic marine human uses in close spatial–temporal proximity while...With growing pressures on marine ecosystems and on marine space,an increasingly needed strategy to optimise the use of marine space is to co-locate synergic marine human uses in close spatial–temporal proximity while separating conflicting marine human uses.The ArcMap toolbox SEANERGY is a new,cross-sectoral spatial decision support tool(DST)that enables maritime spatial planners to consider synergies and conflicts between marine uses to support assessments of co-location options.Cross-sectoral approaches are important to reach more integrative maritime spatial planning(MSP)processes.As this article demonstrates through a Baltic Sea analysis,SEANERGY presents a crosssectoral use catalogue for MSP through enabling the tool users to answer important specific questions to spatially and/or numerically weight potential synergies/conflicts between marine uses.The article discusses to what degree such a cross-sectoral perspective can support integrative MSP processes.While MSP integrative challenges still exist,SEANERGY enables MSP processes to move towards developing shared goals and initiate discussions built on best available knowledge regarding potential use-use synergies and use-use conflicts for whole sea basins at once.展开更多
Research has demonstrated a significant overlap between sleep issues and other medical conditions.In this paper,we consider mild difficulty in falling asleep(MDFA).Recognition of MDFA has the potential to assist in th...Research has demonstrated a significant overlap between sleep issues and other medical conditions.In this paper,we consider mild difficulty in falling asleep(MDFA).Recognition of MDFA has the potential to assist in the provision of appropriate treatment plans for both sleep issues and related medical conditions.An issue in the diagnosis of MDFA lies in subjectivity.To address this issue,a decision support tool based on dual-modal physiological feature fusion which is able to automatically identify MDFA is proposed in this study.Special attention is given to the problem of how to extract candidate features and fuse dual-modal features.Following the identification of the optimal feature set,this study considers the correlations between each feature and class and evaluates correlations between the inter-modality features.Finally,the recognition accuracy was measured using 10-fold cross validation.The experimental results for our method demonstrate improved performance.The highest recognition rate of MDFA using the optimal feature set can reach 96.22%.Based on the results of current study,the authors will,in projected future research,develop a real-time MDFA recognition system.展开更多
Background:Previous studies have surveyed golf courses to determine nitrogen(N)fertilizer application rates on golf courses,but no previous studies have attempted to quantify how efficiently golf courses use nitrogen....Background:Previous studies have surveyed golf courses to determine nitrogen(N)fertilizer application rates on golf courses,but no previous studies have attempted to quantify how efficiently golf courses use nitrogen.Methods:This study tests the ability of the growth potential(GP)N Requirement model as a benchmarking tool to predict a target level of N use on 76 golf courses in 5 regions of the US(Midwest,Northeast,East Texas,Florida,Northwest)and 3 countries in Europe(Denmark,Norway,UK).Results:The ratio of the golf course-wide N application rate to the GP N requirement prediction(termed the nitrogen efficiency score or NES)was 0.27,indicating that golf courses used 73%less N than predicted by the model.As such,the GP N Requirement model needs to be recalibrated to predict N use on golf courses.This was achieved by adjusting the Nmax coefficient in the model.N rates on golf courses were widely variable both within and across regions.All regions had a coefficient of variation in N rates of 0.46 or greater.Conclusions:The high variation in N rates,which is largely unexplained by climate,economic factors,grass type,and soil type,may be indicative of inefficient N use in golf course management.展开更多
文摘BACKGROUND Non-invasive tests,such as Fibrosis-4 index and transient elastography(com-monly FibroScan),are utilized in clinical pathways to risk stratify and diagnose non-alcoholic fatty liver disease(NAFLD).In 2018,a clinical decision support tool(CDST)was implemented to guide primary care providers(PCPs)on use of FibroScan for NAFLD.AIM To analyze how this CDST impacted health care utilization and patient outcomes.METHODS We performed a retrospective review of adults who had FibroScan for NAFLD indication from January 2015 to December 2017(pre-CDST)or January 2018 to December 2020(post-CDST).Outcomes included FibroScan result,laboratory tests,imaging studies,specialty referral,patient morbidity and mortality.RESULTS We identified 958 patients who had FibroScan,115 before and 843 after the CDST was implemented.The percentage of FibroScans ordered by PCPs increased from 33%to 67.1%.The percentage of patients diagnosed with early F1 fibrosis,on a scale from F0 to F4,increased from 7.8%to 14.2%.Those diagnosed with ad-vanced F4 fibrosis decreased from 28.7%to 16.5%.There were fewer laboratory tests,imaging studies and biopsy after the CDST was implemented.Though there were more specialty referrals placed after the CDST was implemented,multivariate analysis revealed that healthcare utilization aligned with fibrosis score,whereby patients with more advanced disease had more referrals.Very few patients were hospitalized or died.CONCLUSION This CDST empowered PCPs to diagnose and manage patients with NAFLD with appropriate allocation of care towards patients with more advanced disease.
基金supported by BONUS EEIG:[grant number 2017-06-19].
文摘With growing pressures on marine ecosystems and on marine space,an increasingly needed strategy to optimise the use of marine space is to co-locate synergic marine human uses in close spatial–temporal proximity while separating conflicting marine human uses.The ArcMap toolbox SEANERGY is a new,cross-sectoral spatial decision support tool(DST)that enables maritime spatial planners to consider synergies and conflicts between marine uses to support assessments of co-location options.Cross-sectoral approaches are important to reach more integrative maritime spatial planning(MSP)processes.As this article demonstrates through a Baltic Sea analysis,SEANERGY presents a crosssectoral use catalogue for MSP through enabling the tool users to answer important specific questions to spatially and/or numerically weight potential synergies/conflicts between marine uses.The article discusses to what degree such a cross-sectoral perspective can support integrative MSP processes.While MSP integrative challenges still exist,SEANERGY enables MSP processes to move towards developing shared goals and initiate discussions built on best available knowledge regarding potential use-use synergies and use-use conflicts for whole sea basins at once.
基金supported by National Natural Science Foundation of China (Nos. 61761027 and 61461025)the Yong Scholar Fund of Lanzhou Jiaotong University (No. 2016004)the Teaching Reform Project of Lanzhou Jiaotong University (No. JGY201841)。
文摘Research has demonstrated a significant overlap between sleep issues and other medical conditions.In this paper,we consider mild difficulty in falling asleep(MDFA).Recognition of MDFA has the potential to assist in the provision of appropriate treatment plans for both sleep issues and related medical conditions.An issue in the diagnosis of MDFA lies in subjectivity.To address this issue,a decision support tool based on dual-modal physiological feature fusion which is able to automatically identify MDFA is proposed in this study.Special attention is given to the problem of how to extract candidate features and fuse dual-modal features.Following the identification of the optimal feature set,this study considers the correlations between each feature and class and evaluates correlations between the inter-modality features.Finally,the recognition accuracy was measured using 10-fold cross validation.The experimental results for our method demonstrate improved performance.The highest recognition rate of MDFA using the optimal feature set can reach 96.22%.Based on the results of current study,the authors will,in projected future research,develop a real-time MDFA recognition system.
文摘Background:Previous studies have surveyed golf courses to determine nitrogen(N)fertilizer application rates on golf courses,but no previous studies have attempted to quantify how efficiently golf courses use nitrogen.Methods:This study tests the ability of the growth potential(GP)N Requirement model as a benchmarking tool to predict a target level of N use on 76 golf courses in 5 regions of the US(Midwest,Northeast,East Texas,Florida,Northwest)and 3 countries in Europe(Denmark,Norway,UK).Results:The ratio of the golf course-wide N application rate to the GP N requirement prediction(termed the nitrogen efficiency score or NES)was 0.27,indicating that golf courses used 73%less N than predicted by the model.As such,the GP N Requirement model needs to be recalibrated to predict N use on golf courses.This was achieved by adjusting the Nmax coefficient in the model.N rates on golf courses were widely variable both within and across regions.All regions had a coefficient of variation in N rates of 0.46 or greater.Conclusions:The high variation in N rates,which is largely unexplained by climate,economic factors,grass type,and soil type,may be indicative of inefficient N use in golf course management.
