BACKGROUND Despite being the gold standard,the use of glycated hemoglobin(HbA1c)and fasting plasma glucose(FPG)for diagnosing dysglycemia is imperfect.In particular,a low level of agreement between HbA1c and FPG in de...BACKGROUND Despite being the gold standard,the use of glycated hemoglobin(HbA1c)and fasting plasma glucose(FPG)for diagnosing dysglycemia is imperfect.In particular,a low level of agreement between HbA1c and FPG in detecting prediabetes and diabetes has led to difficulties in clinical interpretation.Glycated albumin(GA)and 1,5-anhydroglucitol(1,5-AG)may potentially serve as biomarkers for the detection and prediction of diabetes,as well as glycemic monitoring.AIM To explore the diagnostic performance of GA and 1,5-AG for screening dysglycemia;assess whether they can be used for glycemic monitoring in Chinese morbidly-obese patients;and examine their predictive ability for incident diabetes in a Chinese community-based cohort.METHODS GA and 1,5-AG concentrations were measured in 462 morbidly-obese patients from the Obese Chinese Cohort(OCC).A sub-group of diabetes subjects(n=24)was prospectively followed-up after bariatric surgery.Differences between baseline and post-surgery biomarker values were converted to percentage change from baseline to assess the response to glycemic control.Predictive ability of the biomarkers was assessed in 132 incident diabetes cases and 132 matched non-diabetes controls in the community-based Cardiovascular Risk Factor Prevalence Study(CRISPS).A prediction model was developed and compared with clinical models based on conventional risk factors.RESULTS GA exhibited an excellent diagnostic value with an area under the receiver operating characteristic curve(AUC)of 0.919(95%CI:0.884-0.955)for identifying diabetes and a high agreement in the classification of diabetes with both FPG and HbA1c in the OCC.GA demonstrated the fastest response to glycemic control.In CRISPS,the‘B3A’prediction model,which consisted of body mass index(BMI)and 3 biomarkers(HbA1c,GA and 1,5-AG),achieved a comparable predictive value[AUC(95%CI):0.793(0.744-0.843)]to that of a clinical model comprising BMI,HbA1c,FPG and 2-hour glucose(2hG)[AUC(95%CI):0.783(0.733-0.834);DeLong P value=0.736].The‘B3A’was significantly superior to a clinical model including BMI,HbA1c,FPG and triglycerides[AUC(95%CI):0.729(0.673-0.784);DeLong P value=0.027].CONCLUSION GA and 1,5-AG have the potential to act as robust biomarkers for the screening and risk prediction of diabetes.FPG and 2hG may be replaced by GA and 1,5-AG in future diabetes predictions.展开更多
Multi-fidelity Data Fusion(MDF)frameworks have emerged as a prominent approach to producing economical but accurate surrogate models for aerodynamic data modeling by integrating data with different fidelity levels.How...Multi-fidelity Data Fusion(MDF)frameworks have emerged as a prominent approach to producing economical but accurate surrogate models for aerodynamic data modeling by integrating data with different fidelity levels.However,most existing MDF frameworks assume a uniform data structure between sampling data sources;thus,producing an accurate solution at the required level,for cases of non-uniform data structures is challenging.To address this challenge,an Adaptive Multi-fidelity Data Fusion(AMDF)framework is proposed to produce a composite surrogate model which can efficiently model multi-fidelity data featuring non-uniform structures.Firstly,the design space of the input data with non-uniform data structures is decomposed into subdomains containing simplified structures.Secondly,different MDF frameworks and a rule-based selection process are adopted to construct multiple local models for the subdomain data.On the other hand,the Enhanced Local Fidelity Modeling(ELFM)method is proposed to combine the generated local models into a unique and continuous global model.Finally,the resulting model inherits the features of local models and approximates a complete database for the whole design space.The validation of the proposed framework is performed to demonstrate its approximation capabilities in(A)four multi-dimensional analytical problems and(B)a practical engineering case study of constructing an F16C fighter aircraft’s aerodynamic database.Accuracy comparisons of the generated models using the proposed AMDF framework and conventional MDF approaches using a single global modeling algorithm are performed to reveal the adaptability of the proposed approach for fusing multi-fidelity data featuring non-uniform structures.Indeed,the results indicated that the proposed framework outperforms the state-of-the-art MDF approach in the cases of non-uniform data.展开更多
Colorectal cancer(CRC)is the third most common cancer and the second leading cause of cancer deaths worldwide[1].A considerable proportion of CRC is attributed to metabolic risk factors including type 2 diabetes(T2D),...Colorectal cancer(CRC)is the third most common cancer and the second leading cause of cancer deaths worldwide[1].A considerable proportion of CRC is attributed to metabolic risk factors including type 2 diabetes(T2D),with the relative risk reported to be 1.4[2].It is therefore imperative to develop effective preventive strategies to reduce CRC incidence in individuals with T2D.Among individuals with T2D,growing evidence supports the role of diabetes medications for CRC prevention.The current guidelines of the American Gastroenterological Association have recommended metformin as a potential chemopreventive medication against colonic neoplasia in patients with T2D[3].However,the use of metformin may be limited by various side effects including gastrointestinal disturbances,and is contraindicated in moderate-to-severe renal impairment.Furthermore,a clinical trial found diabetic patients on metformin,as compared to rosiglitazone and glyburide,had similar CRC risk[4].展开更多
基金Supported by the Hong Kong Research Grants Council Area of Excellence,No.AoE/M/707-18.
文摘BACKGROUND Despite being the gold standard,the use of glycated hemoglobin(HbA1c)and fasting plasma glucose(FPG)for diagnosing dysglycemia is imperfect.In particular,a low level of agreement between HbA1c and FPG in detecting prediabetes and diabetes has led to difficulties in clinical interpretation.Glycated albumin(GA)and 1,5-anhydroglucitol(1,5-AG)may potentially serve as biomarkers for the detection and prediction of diabetes,as well as glycemic monitoring.AIM To explore the diagnostic performance of GA and 1,5-AG for screening dysglycemia;assess whether they can be used for glycemic monitoring in Chinese morbidly-obese patients;and examine their predictive ability for incident diabetes in a Chinese community-based cohort.METHODS GA and 1,5-AG concentrations were measured in 462 morbidly-obese patients from the Obese Chinese Cohort(OCC).A sub-group of diabetes subjects(n=24)was prospectively followed-up after bariatric surgery.Differences between baseline and post-surgery biomarker values were converted to percentage change from baseline to assess the response to glycemic control.Predictive ability of the biomarkers was assessed in 132 incident diabetes cases and 132 matched non-diabetes controls in the community-based Cardiovascular Risk Factor Prevalence Study(CRISPS).A prediction model was developed and compared with clinical models based on conventional risk factors.RESULTS GA exhibited an excellent diagnostic value with an area under the receiver operating characteristic curve(AUC)of 0.919(95%CI:0.884-0.955)for identifying diabetes and a high agreement in the classification of diabetes with both FPG and HbA1c in the OCC.GA demonstrated the fastest response to glycemic control.In CRISPS,the‘B3A’prediction model,which consisted of body mass index(BMI)and 3 biomarkers(HbA1c,GA and 1,5-AG),achieved a comparable predictive value[AUC(95%CI):0.793(0.744-0.843)]to that of a clinical model comprising BMI,HbA1c,FPG and 2-hour glucose(2hG)[AUC(95%CI):0.783(0.733-0.834);DeLong P value=0.736].The‘B3A’was significantly superior to a clinical model including BMI,HbA1c,FPG and triglycerides[AUC(95%CI):0.729(0.673-0.784);DeLong P value=0.027].CONCLUSION GA and 1,5-AG have the potential to act as robust biomarkers for the screening and risk prediction of diabetes.FPG and 2hG may be replaced by GA and 1,5-AG in future diabetes predictions.
基金supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2020R1A6A1A03046811).This paper was also supported by Konkuk University Researcher Fund in 2021.
文摘Multi-fidelity Data Fusion(MDF)frameworks have emerged as a prominent approach to producing economical but accurate surrogate models for aerodynamic data modeling by integrating data with different fidelity levels.However,most existing MDF frameworks assume a uniform data structure between sampling data sources;thus,producing an accurate solution at the required level,for cases of non-uniform data structures is challenging.To address this challenge,an Adaptive Multi-fidelity Data Fusion(AMDF)framework is proposed to produce a composite surrogate model which can efficiently model multi-fidelity data featuring non-uniform structures.Firstly,the design space of the input data with non-uniform data structures is decomposed into subdomains containing simplified structures.Secondly,different MDF frameworks and a rule-based selection process are adopted to construct multiple local models for the subdomain data.On the other hand,the Enhanced Local Fidelity Modeling(ELFM)method is proposed to combine the generated local models into a unique and continuous global model.Finally,the resulting model inherits the features of local models and approximates a complete database for the whole design space.The validation of the proposed framework is performed to demonstrate its approximation capabilities in(A)four multi-dimensional analytical problems and(B)a practical engineering case study of constructing an F16C fighter aircraft’s aerodynamic database.Accuracy comparisons of the generated models using the proposed AMDF framework and conventional MDF approaches using a single global modeling algorithm are performed to reveal the adaptability of the proposed approach for fusing multi-fidelity data featuring non-uniform structures.Indeed,the results indicated that the proposed framework outperforms the state-of-the-art MDF approach in the cases of non-uniform data.
文摘Colorectal cancer(CRC)is the third most common cancer and the second leading cause of cancer deaths worldwide[1].A considerable proportion of CRC is attributed to metabolic risk factors including type 2 diabetes(T2D),with the relative risk reported to be 1.4[2].It is therefore imperative to develop effective preventive strategies to reduce CRC incidence in individuals with T2D.Among individuals with T2D,growing evidence supports the role of diabetes medications for CRC prevention.The current guidelines of the American Gastroenterological Association have recommended metformin as a potential chemopreventive medication against colonic neoplasia in patients with T2D[3].However,the use of metformin may be limited by various side effects including gastrointestinal disturbances,and is contraindicated in moderate-to-severe renal impairment.Furthermore,a clinical trial found diabetic patients on metformin,as compared to rosiglitazone and glyburide,had similar CRC risk[4].
