A Nationwide Nepalese Study to Establish Reference Intervals for Major Biochemical Analytes with Elucidation of Nepalese Features of Reference Values

INDIAN JOURNAL OF CLINICAL BIOCHEMISTRY(2023)

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摘要
Despite immense importance of reference intervals (RIs) for clinical diagnosis, there have been no reliable RIs available for Nepalese. Hence, this nationwide study was organized to establish RIs for 30 common biochemical parameters. This study was conducted following the harmonized protocol provided by IFCC Committee on Reference Interval and Decision Limits (C-RIDL) with recruitment of 617 apparently healthy volunteers (18 − 65 years) by near-equal gender balance from 5 major cities. Fasting blood were collected, serum was separated and measured collectively using Beckman-Coulter/Olympus AU480 chemistry analyzer. The sources of variations of reference values (RVs) were evaluated by multiple regression analysis and nested ANOVA. Latent abnormal values exclusion (LAVE) method was applied to reduce influence of latent diseases. RIs were standardized based on a value-assigned serum panel provided by C-RIDL. By ANOVA, no between-city differences were observed, while sex-related changes were typically noted for urate, creatinine, iron, γ-glutamyl transferase (GGT), immunoglobulin M, and transferrin, but not for high-density lipoprotein cholesterol. Age-related changes were observed for total cholesterol (TC), triglyceride, low-density lipoprotein cholesterol, and C-reactive protein (CRP). RIs were successfully derived all parametrically. The LAVE procedure was effective in lowering upper limits for aspartate aminotransferase, alanine aminotransferase (ALT), and CRP. Compared to other collaborating countries, Nepalese RIs were low for urea, cholesterols, ALT, and high for triglyceride, GGT, CRP, immunoglobulin G, and complements. The RIs for major chemistry analytes were derived and standardized for nationwide use in Nepal. This study distinctly elucidated sources of variation and international features of Nepalese RIs.
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关键词
Latent abnormal values exclusion method,Multiple regression analysis,Parametric method,Reference value,Biochemistry analytes,Biological sources of variation
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