Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Understanding age- and sex-specific biological changes in metabolic disease biomarkers is essential for their appropriate utilization in management of children with inborn errors of metabolism (IEM). The CALIPER program aimed to establish pediatric reference values in healthy community children for common metabolic biomarkers and determine the effects of key covariates including age and sex across the pediatric age.
Methods: A cohort of 500 healthy children and adolescents from birth to 19years were initially recruited to establish pediatric reference intervals according to the CLSI C28-A3 guidelines. Serum samples were used to measure 37 amino acids by ultra-performance liquid chromatography, 32 acylcarnitines, as well as free and total carnitine by tandem mass spectrometry, and β-hydroxybutyrate and free fatty acids using the Vitros 5.1 chemistry analyzer. P ediatric reference intervals were calculated using non-parametric statistics and partitioned based on age- and sex-distributions.
Results: Approximately 80% of all analytes required 2 to 4 age-dependent partitions, with over 50% of amino acids and over 70% of acylcarnitines exhibiting significant physiological changes during the neonatal period. Also, 21% of all analytes required partitioning during puberty and adolescence, half of which produced sex-specific distributions.
Conclusions: A comprehensive reference interval database for metabolic disease biomarkers established in this study will improve detection of IEMs by providing appropriate age- and sex-related information in the pediatric population. It will also aid newborn screening programs and guide the management of patients with known metabolic diseases, especially pubertal and adolescent boys and girls that display sex-specific concentrations.
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Source |
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http://dx.doi.org/10.1016/j.clinbiochem.2015.05.005 | DOI Listing |
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