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Division of Myocardial Enzyme Reference Intervals in Population Aged 1 to <18 Years Old Based on Fisher's Optimal Segmentation Method.

Authors :
Guo, Wenjia
Zhou, Qi
Jia, Yanan
Xu, Jiancheng
Source :
Computational & Mathematical Methods in Medicine. 3/31/2020, p1-8. 8p.
Publication Year :
2020

Abstract

Background. Reference interval (RI) research is to make it a concise, effective, and practical diagnostic tool. This study aimed to establish sex- and age-specific RI for myocardial enzyme activity in population aged 1–&lt;18 years old in Changchun, China. Methods. Healthy subjects (n = 6,322, 1–&lt;18 years old) were recruited from communities and schools. Aspartate aminotransferase (AST), lactate dehydrogenase (LDH), creatine kinase (CK), and creatine kinase isoenzyme (CKMB) were measured using an automatic biochemical analyzer. Fisher&#39;s optimal segmentation method was used to partition by including percentiles as impact factors, aiming at minimizing the sum of the squares of the total dispersion into groups as splitting sequence of ordered data. Results. AST decreased gradually and was partitioned as 1, 2∼&lt;10 and 10∼&lt;18 years old. LDH presented disparate descending rate among 1∼&lt;4, 4∼&lt;12, and 12∼&lt;18 years old. CK stood quite stable with the same RI in all ages. CKMB began to differ at 6 years of age sexually and then remained stable during 6∼&lt;14 years old for male while it continued to decline in female. Cardiac development was partitioned as 1∼&lt;6, 6∼&lt;13, and 13∼&lt;18 years old using multiple percentiles from massive data that reflect characteristics of totality as impact factors. Conclusions. Fisher&#39;s optimal segmentation method excelled for multidimensionality, continuity, and loop calculating as dealing with RIs for myocardial enzymes activity and cardiac development process despite limitations. In future, impact of partition on the overall interval should be delved into. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1748670X
Database :
Academic Search Index
Journal :
Computational & Mathematical Methods in Medicine
Publication Type :
Academic Journal
Accession number :
142492944
Full Text :
https://doi.org/10.1155/2020/2013148