脂肪肝患者 8 种血清肝酶和 3 种无创检测的年度生物变异和个性化参考区间。

IF 4.1 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2025-03-01 Epub Date: 2025-01-25 DOI:10.1016/j.cca.2025.120156
Shuo Wang , Min Zhao , Zihan Su, Dan Yang, Runqing Mu
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引用次数: 0

摘要

背景:肝功能检查和无创检查(NITs)在脂肪肝(FLD)的随访和监测中发挥着重要作用。我们的目标是首次建立肝功能检测的年度生物变异(BV)和个性化参考区间(prRIs),以便准确评估FLD的状态和进展。方法:选取67例连续6年每年1次定期体检的脂肪肝患者。基于这些患者,我们计算了年度BV和衍生参数,包括参考变化值(RCV)、个性指数(II)和真实稳态设定点(TVset)周围的总变化,这些参数可进一步用于推导prRI。结果:我们计算了脂肪肝患者8项肝功能检查和3项nit的年度体内BV (CVI)、体内BV (CVP)、RCV、II、TVset。脂肪肝患者半数肝功能测试的CVI估计值明显低于健康人,这可能导致较低的RCV。各项指标的i值为 ,P值与CVI相似;然而,不同被试的CVP存在显著的异质性。7项指标的年度TVset估计值较低,脂肪肝患者的prRI也比健康人窄。结论:基于脂肪肝患者的年度BV及其衍生参数可为FLD这一全球性流行病的监测和随访提供客观依据。
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Annual biological variation and personalized reference intervals of 8 serum liver enzymes and 3 noninvasive tests in fatty liver patients

Background

The liver function tests and noninvasive tests (NITs) play important roles in the follow-up and monitoring of fatty liver disease (FLD). Our aim is to establish annual biological variation (BV) and personalized reference intervals (prRIs) of liver function tests for the first time in order to accurately assess the status and progress of FLD.

Methods

67 fatty liver patients who participated in regular physical examination once a year for six consecutive years, were enrolled. Based on these patients, we calculated annual BV and derived parameters, including reference change value (RCV), index of individuality (II), and total variation around the true homeostatic set point (TVset) which could further be used to derive prRI.

Results

We calculated the annual within-subject BV (CVI), within-person BV (CVP), RCV, II, TVset of 8 liver function tests and 3 NITs for fatty liver patients. CVI estimates of fatty liver patients for half of liver function tests were significantly lower than those of healthy people and these could lead to a lower RCV. IIs of all measurands were < 1.4 except for total bile acids (TBA). The mean of CVP is similar to the CVI; however, there is a significant heterogeneity in CVP among different subjects. Annual TVset estimates for 7 measurands were lower and prRI was also narrower in fatty liver patients than that of healthy people.

Conclusion

Annual BV and their derived parameters based on fatty liver patients can provide an objective basis for the monitoring and follow-up of FLD, a global epidemic disease.
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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