Angel O K Chan1, Norman F Taylor, S C Tiu, C C Shek. 1. Chemical Pathology Laboratory, Department of Pathology, Queen Elizabeth Hospital, Kowloon, Hong Kong, China. chanok@ha.org.hk
Abstract
BACKGROUND: Urinary steroid profiling by GC or GC-MS are established clinical tools to complement other biochemical tests in the diagnosis and investigation of a wide range of adrenocortical disorders, but normative data on adults using the more specific GC-MS are lacking. Our objective was to set up the reference intervals of commonly detected urinary steroid metabolites as well as marker metabolites seen in disease states. METHOD: Apparently healthy adult Chinese males and females were recruited by completing health questionnaires. A 24-h urine specimen was collected from all the participants for urinary steroid profiling by GC-MS in cyclic scan mode. The analyzer was calibrated by using authentic steroid standards. Statistical methods recommended by the National Committee for Clinical Laboratory Standards were followed for setting up the reference intervals of various steroid metabolites. After outliers were excluded, the data were tested for the necessity to partition into sex-, menopausal status- and age-specific reference intervals. RESULTS: 83 males and 89 females were recruited for the study. Necessity to partition into sex-specific reference intervals was demonstrated for almost all steroid metabolites. Menopausal status and age also had a significant impact on steroid metabolite excretion, making separate reference intervals necessary. CONCLUSIONS: We have set up the normative data on the levels of urinary steroid metabolite excretion in Chinese adults for future reference in patient management and research in steroid metabolism.
BACKGROUND: Urinary steroid profiling by GC or GC-MS are established clinical tools to complement other biochemical tests in the diagnosis and investigation of a wide range of adrenocortical disorders, but normative data on adults using the more specific GC-MS are lacking. Our objective was to set up the reference intervals of commonly detected urinary steroid metabolites as well as marker metabolites seen in disease states. METHOD: Apparently healthy adult Chinese males and females were recruited by completing health questionnaires. A 24-h urine specimen was collected from all the participants for urinary steroid profiling by GC-MS in cyclic scan mode. The analyzer was calibrated by using authentic steroid standards. Statistical methods recommended by the National Committee for Clinical Laboratory Standards were followed for setting up the reference intervals of various steroid metabolites. After outliers were excluded, the data were tested for the necessity to partition into sex-, menopausal status- and age-specific reference intervals. RESULTS: 83 males and 89 females were recruited for the study. Necessity to partition into sex-specific reference intervals was demonstrated for almost all steroid metabolites. Menopausal status and age also had a significant impact on steroid metabolite excretion, making separate reference intervals necessary. CONCLUSIONS: We have set up the normative data on the levels of urinary steroid metabolite excretion in Chinese adults for future reference in patient management and research in steroid metabolism.
Authors: Yeow-Kuan Chong; Chi-Chun Ho; Shui-Yee Leung; Susanna K P Lau; Patrick C Y Woo Journal: Comput Struct Biotechnol J Date: 2018-08-28 Impact factor: 7.271
Authors: Daniel Ackermann; Michael Groessl; Menno Pruijm; Belen Ponte; Geneviève Escher; Claudia H d'Uscio; Idris Guessous; Georg Ehret; Antoinette Pechère-Bertschi; Pierre-Yves Martin; Michel Burnier; Bernhard Dick; Bruno Vogt; Murielle Bochud; Valentin Rousson; Nasser A Dhayat Journal: PLoS One Date: 2019-03-29 Impact factor: 3.240
Authors: Valentin Rousson; Daniel Ackermann; Belen Ponte; Menno Pruijm; Idris Guessous; Claudia H d'Uscio; Georg Ehret; Geneviève Escher; Antoinette Pechère-Bertschi; Michael Groessl; Pierre-Yves Martin; Michel Burnier; Bernhard Dick; Murielle Bochud; Bruno Vogt; Nasser A Dhayat Journal: PLoS One Date: 2021-07-08 Impact factor: 3.240