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Article

A Predictive Risk Score to Diagnose Adrenal Insufficiency in Outpatients: A 7 Year Retrospective Cohort Study

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Division of Endocrinology, Department of Internal Medicine, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
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Clinical Epidemiology Center, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
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Clinical Statistic Center, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
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Department of Anesthesiology, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
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Division of Pediatric Surgery, Department of Surgery, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
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Department of Orthopaedics, Faculty of Medicine, Chiang Mai University, Chiang Mai 50200, Thailand
*
Author to whom correspondence should be addressed.
Academic Editor: M Rosa Bernal-Lopez
Received: 17 February 2021 / Revised: 5 March 2021 / Accepted: 8 March 2021 / Published: 10 March 2021
(This article belongs to the Section Endocrinology and Metabolic Disorders)
Background: The diagnosis of adrenal insufficiency (AI) requires dynamic tests which may not be available in some institutions. This study aimed to develop a predictive risk score to help diagnose AI in outpatients with indeterminate serum cortisol levels. Methods: Five hundred and seven patients with intermediate serum cortisol levels (3–17.9 µg/dL) who had undergone ACTH (adrenocorticotropin) stimulation tests were included in the study. A predictive risk score was created using significant predictive factors identified by multivariable analysis using Poisson regression clustered by ACTH dose. Results: The seven predictive factors used in the development of a predictive model with their assigned scores are as follows: chronic kidney disease (9.0), Cushingoid appearance in exogenous steroid use (12.0), nausea and/or vomiting (6.0), fatigue (2.0), basal cortisol <9 µg/dL (12.5), cholesterol <150 mg/dL (2.5) and sodium <135 mEq/L (1.0). Predictive risk scores range from 0–50.0. A high risk level (scores of 19.5–50.0) indicates a higher possibility of having AI (positive likelihood ratio (LR+) = 11.75), while a low risk level (scores of <19.0) indicates a lower chance of having AI (LR+ = 0.09). The predictive performance of the scoring system was 0.82 based on the area under the curve. Conclusions: This predictive risk score can help to determine the probability of AI and can be used as a guide to determine which patients need treatment for AI and which require dynamic tests to confirm AI. View Full-Text
Keywords: adrenal insufficiency; predictive model; serum cortisol; ACTH stimulation test adrenal insufficiency; predictive model; serum cortisol; ACTH stimulation test
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MDPI and ACS Style

Manosroi, W.; Pipanmekaporn, T.; Khorana, J.; Atthakomol, P.; Phimphilai, M. A Predictive Risk Score to Diagnose Adrenal Insufficiency in Outpatients: A 7 Year Retrospective Cohort Study. Medicines 2021, 8, 13. https://0-doi-org.brum.beds.ac.uk/10.3390/medicines8030013

AMA Style

Manosroi W, Pipanmekaporn T, Khorana J, Atthakomol P, Phimphilai M. A Predictive Risk Score to Diagnose Adrenal Insufficiency in Outpatients: A 7 Year Retrospective Cohort Study. Medicines. 2021; 8(3):13. https://0-doi-org.brum.beds.ac.uk/10.3390/medicines8030013

Chicago/Turabian Style

Manosroi, Worapaka, Tanyong Pipanmekaporn, Jiraporn Khorana, Pichitchai Atthakomol, and Mattabhorn Phimphilai. 2021. "A Predictive Risk Score to Diagnose Adrenal Insufficiency in Outpatients: A 7 Year Retrospective Cohort Study" Medicines 8, no. 3: 13. https://0-doi-org.brum.beds.ac.uk/10.3390/medicines8030013

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