ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Endocrine Abstracts (2019) 63 P442 | DOI: 10.1530/endoabs.63.P442

Simplified model for diagnosis of secondary adrenal insufficiency using non-fasting cortisol and clinical parameters

Tae Ho Kim, Jung Kyun Oh, Hyun Mok Kim & Sun Hee Beom

Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul Medical Center, Seoul, Republic of Korea.

Objective: Although rapid adrenocorticotrophic hormone (ACTH) stimulation test is a standard test for primary and secondary adrenal insufficiency (AI), it is considered a costly and time-consuming method due to sampling three times in an hour. We aimed to develop a simpler diagnostic model of secondary AI using non-fasting basal cortisol and clinical parameters related to AI such as history of exogenous steroid use or hyponatremia.

Methods: Total 430 patients who had 250 ug ACTH stimulation testing as part of their diagnostic work-up were retrospectively analyzed. A peak cortisol levels <18 μ/dl after ACTH stimulation indicate abnormal adrenal function.

Results: Among participants who undergo ACTH stimulation test, 144 patients (33.4%) showed inadequate increase of cortisol and were diagnosed as AI. The receiver operating characteristic curve analysis showed an overall area under the curve (AUC) for basal cortisol of 0.853 and for 30 minute cortisol of 0.953. When we combined basal cortisol with clinical parameters related to AI, the AUC increased from 0.853 to 0.922, which was comparable to that of 30 minute cortisol (P=0.0782). In our study, participants with basal cortisol levels ≥14.8 μ/dl had normal adrenal function, whereas <3.6 μ/dl had abnormal adrenal function. Among several simplified diagnostic models, basal cortisol level <3.6 μ/dl and history of exogenous steroid use had the highest accuracy (85.5%, P<0.001) for predicting secondary AI.

Conclusion: Basal cortisol level <3.6 μ/dl with history of exogenous steroid use had high diagnostic accuracy, diminishing the need for formal ACTH testing. We suggest that this result can be helpful for clinicians for diagnosing secondary AI in terms of time and cost effectiveness.

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