Search results for " positive predictive value"

showing 2 items of 2 documents

Prediction of type 2 diabetes mellitus based on nutrition data

2021

Abstract Numerous predictive models for the risk of type 2 diabetes mellitus (T2DM) exist, but a minority of them has implemented nutrition data so far, even though the significant effect of nutrition on the pathogenesis, prevention and management of T2DM has been established. Thus, in the present study, we aimed to build a predictive model for the risk of T2DM that incorporates nutrition data and calculates its predictive performance. We analysed cross-sectional data from 1591 individuals from the population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013–14) and used a bootstrap enhanced elastic net penalised multivariate regression method in order to bu…

Elastic net regularizationFood intakeMultivariate statistics24HFL 24-h food listEndocrinology Diabetes and MetabolismPopulation030209 endocrinology & metabolismType 2 diabetesLogistic regression03 medical and health sciences0302 clinical medicinePredictive Value of TestsRisk FactorsElastic net regressionPrediction modelGermanyStatisticsmedicineHumans030212 general & internal medicineeducationNutritionMathematicseducation.field_of_studyNutrition and DieteticsReceiver operating characteristicDietary Surveys and Nutritional EpidemiologyType 2 Diabetes MellitusType 2 diabetesT2DM type 2 diabetes mellitusmedicine.diseasePPV positive predictive valueDietROC receiver operating characteristicCross-Sectional StudiesNPV negative predictive valueDiabetes Mellitus Type 2ROC CurveKORA Cooperative Health Research in the Region of Augsburg24hfl 24-h Food List ; Elastic Net Regression ; Kora Cooperative Health Research In The Region Of Augsburg ; Npv Negative Predictive Value ; Nutrition ; Ppv Positive Predictive Value ; Prediction Model ; Roc Receiver Operating Characteristic ; T2dmResearch ArticleFood ScienceJournal of Nutritional Science
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Determining a healthy reference range and factors potentially influencing PRO-C3 – A biomarker of liver fibrosis

2021

Background & Aims Progressive fibrosis has been identified as the major predictor of mortality in patients with non-alcoholic fatty liver disease (NAFLD). Several biomarkers are currently being evaluated for their ability to substitute the liver biopsy as the reference standard. Recent clinical studies in NAFLD/NASH patients support the utility of PRO-C3, a marker of type III collagen formation, as a marker for the degree of fibrosis, disease activity, and effect of treatment. Here we establish the healthy reference range, optimal sample handling conditions for both short- and long-term serum storage, and robustness for the PRO-C3 assay. Methods PRO-C3 was measured in 269 healthy volunteers…

NASH-CRN NASH Clinical Research NetworkBiopsyDiseaseAST aspartate aminotransferaseRC799-869Ethnic groupsGastroenterologyNIMBLE Non-Invasive Biomarkers of Metabolic Liver Disease (consortium)FibrosisImmunology and AllergyBody mass indexmedicine.diagnostic_testFatty liverNAS NAFLD Activity ScoreGastroenterologyDiseases of the digestive system. GastroenterologyHospitalsNPV negative predictive valueLiver biopsyBiomarker (medicine)Research Articlemedicine.medical_specialtyNAFLD non-alcoholic fatty liver diseaseADAM A Disintegrin and MetalloproteasesNASH non-alcoholic steatohepatitisReference rangeReference valuesAUROC area under the receiver operating characteristics curveInternal medicineALT alanine aminotransferaseBiopsyInternal MedicinemedicineHumansFIB-4 fibrosis-4Healthy volunteersHepatologyALP alkaline phosphatasebusiness.industryCLSI Clinical and Laboratory Standards InstituteT2DM type 2 diabetes mellitusELF™ test Enhanced Liver Fibrosis testmedicine.diseaseLITMUS Liver Investigation: Testing Marker Utility in Steatohepatitis (consortium)Collagen type IIIFibrosisPPV positive predictive valueReference standardsbusinessBody mass indexBiomarkersNon-alcoholic fatty liver disease
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