{"title":"Reassessment of reference values of metabolic markers: A meta-analysis study","authors":"Saruby Sharma , Shriya Mehta , Nilakshi Mondal , Mokshi Jain , Divyanshi Verma , Kajal Kamboj , Kousheen Brar , Nandita Narayanasamy","doi":"10.1016/j.hnm.2023.200216","DOIUrl":null,"url":null,"abstract":"<div><p>Assessment of the metabolic status of mixed populations is based on narrowly defined, standardized reference values. We performed a systematic review to collate data from 40 observational and case-controlled studies, in order to determine whether the screened randomized control studies lie within the normal range provided by internationally accepted guidelines. Forest plots show a significant increase in overall effect size compared to the computed reference ranges for several metabolic parameters. We conclude that all metabolic parameters need to be categorized in subgroups like age, gender and ethnicity for the precise assessment of metabolic status in a random, diverse population.</p></div>","PeriodicalId":36125,"journal":{"name":"Human Nutrition and Metabolism","volume":"33 ","pages":"Article 200216"},"PeriodicalIF":1.9000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Nutrition and Metabolism","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666149723000336","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
引用次数: 0
Abstract
Assessment of the metabolic status of mixed populations is based on narrowly defined, standardized reference values. We performed a systematic review to collate data from 40 observational and case-controlled studies, in order to determine whether the screened randomized control studies lie within the normal range provided by internationally accepted guidelines. Forest plots show a significant increase in overall effect size compared to the computed reference ranges for several metabolic parameters. We conclude that all metabolic parameters need to be categorized in subgroups like age, gender and ethnicity for the precise assessment of metabolic status in a random, diverse population.
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