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Title: Diagnostic performance of basal cortisol level at 0900-1300h in adrenal insufficiency
Authors: Worapaka Manosroi
Mattabhorn Phimphilai
Jiraporn Khorana
Pichitchai Atthakomol
Keywords: Agricultural and Biological Sciences
Biochemistry, Genetics and Molecular Biology
Issue Date: 1-Jan-2019
Abstract: © 2019 Manosroi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Objective An ACTH stimulation test is the standard diagnostic test for adrenal insufficiency (AI). We aimed to investigate the diagnostic performance between serum morning (0800 h) cortisol and serum basal (0900-1300 h) cortisol levels and determine the proper cut-off point to facilitate AI diagnosis to reduce the number of tests. Methods A six-year retrospective study was performed in a tertiary care medical center. We identified 416 patients who had undergone either low (LDT) or high dose (HDT) ACTH stimulation outpatient tests. AI was defined as a peak serum cortisol level of <500 nmol/L at 30 or 60 minutes after LDT or HDT. The associations between AI and serum basal and morning cortisol levels were demonstrated by logistic regression model. Diagnostic performance was evaluated by ROC analysis. Results Of the 416 patients, 93 (22.4%) were categorized as having AI. The adjusted area under the curve (AUC) for the basal cortisol level for the diagnosis of AI was significantly higher than that for the morning cortisol (0.82 vs 0.69, p <0.001) level. The proposed cut-off values for the basal cortisol were <85 nmol/L (specificity 99.7%) and >350 nmol/L(sensitivity 98.9%). By using these proposed cut-off points, approximately 30% of the ACTH stimulation tests could be eliminated. Conclusion The serum basal cortisol level with the proposed cut-off points were considered as an alternative option for diagnosis of AI. Utilizing the serum basal cortisol level can facilitate AI diagnosis as it is convenient, is not a time-specific test and has a high diagnostic performance.
ISSN: 19326203
Appears in Collections:CMUL: Journal Articles

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