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Updated: Jun 19, 2025

Fecal Glucocorticoid Analysis: Non-invasive Adrenal Monitoring in Equids
Published on: April 25, 2016
Clinical and Biochemical Data for the Diagnosis of Endogenous Hypercortisolism: The "Cushingomic" Approach
Filippo Ceccato1,2, Alessandro Bavaresco1,2, Eugenio Ragazzi3
1Department of Medicine DIMED, University of Padova, 35128 Padua, Italy.
Context:
The clinical presentation of Cushing syndrome (CS) overlaps with common conditions. Recommended screening tests are serum cortisol after 1-mg overnight dexamethasone suppression test (DST), urinary free cortisol (UFC), and late-night salivary cortisol (LNSC).
Objective:
We analyzed the diagnostic accuracy of screening tests in 615 patients without CS (263 suspected CS, 319 adrenal and 33 pituitary incidentaloma) and 40 with CS.
Methods:
Principal component analysis, K-means clustering, and neural network were used to compute an integrated analysis among tests, comorbidities, and signs/symptoms of hypercortisolism.
Results:
The diagnostic accuracy of screening tests for CS was high; DST and UFC were slightly superior to LNSC. The threshold of DST should be adapted to the population considered, especially in adrenal incidentaloma (AI) with mild autonomous cortisol secretion: The cutoff to differentiate CS should be increased to 196 nmol/L. Diabetes, hypertension, and obesity were more common in patients without CS: The direction of their vectors was not aligned and their correlation with screening tests was poor. Clustering allowed us to differentiate those patients without CS into cluster 1 (aged osteoporotic patients with impaired screening tests), cluster 2 (hypertensive and metabolic phenotype), and cluster 3 (young individuals with a low likelihood of overt CS). A neural network model that combined screening tests and clinical presentation was able to predict the CS diagnosis in the validation cohort with 99% precision and 86% accuracy.
Conclusion:
Despite the high diagnostic accuracy of screening tests to detect CS, cortisol-related comorbidities or AI should be considered when interpreting a positive test.
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