Susceptibility and characteristics of infections in patients with glucocorticoid excess or insufficiency: the ICARO tool.

Objective: Registry data show that Cushing's syndrome (CS) and adrenal insufficiency (AI) increase mortality rates associated with infectious diseases. Little information is available on susceptibility to milder forms of infections, especially those not requiring hospitalization. This study aimed to investigate infectious diseases in patients with glucocorticoid disorders through the development of a specific tool. Methods: We developed and administered the InfeCtions in pAtients with endocRinOpathies (ICARO) questionnaire, addressing infectious events over a 12-month observation period, to 1017 outpatients referred to 4 University Hospitals. The ICARO questionnaire showed good test-retest reliability. The odds of infection (OR (95% CI)) were estimated after adjustment for confounders and collated into the ICARO score, reflecting the frequency and duration of infections. Results: In total, 780 patients met the inclusion criteria: 43 with CS, 32 with adrenal incidentaloma and mild autonomous cortisol secretion (MACS), and 135 with AI, plus 570 controls. Compared to controls, CS was associated with higher odds of urinary tract infections (UTIs) (5.1 (2.3-9.9)), mycoses (4.4 (2.1-8.8)), and flu (2.9 (1.4-5.8)). Patients with adrenal incidentaloma and MACS also showed an increased risk of UTIs (3.7 (1.7-8.0)) and flu (3.2 (1.5-6.9)). Post-dexamethasone cortisol levels correlated with the ICARO score in patients with CS. AI was associated with higher odds of UTIs (2.5 (1.6-3.9)), mycoses (2.3 (1.4-3.8)), and gastrointestinal infections (2.2 (1.5-3.3)), independently of any glucocorticoid replacement dose. Conclusions: The ICARO tool revealed a high prevalence of self-reported infections in patients with glucocorticoid disorders. ICARO is the first of its kind questionnaire, which could be a valuable tool for monitoring infections in various clinical settings.

A New Clinical Model to Estimate the Pre-Test Probability of Cushing's Syndrome: The Cushing Score.

Background: Hypercortisolism accounts for relevant morbidity and mortality and is often a diagnostic challenge for clinicians. A prompt diagnosis is necessary to treat Cushing's syndrome as early as possible. Objective: The aim of this study was to develop and validate a clinical model for the estimation of pre-test probability of hypercortisolism in an at-risk population. Design: We conducted a retrospective multicenter case-control study, involving five Italian referral centers for Endocrinology (Turin, Messina, Naples, Padua and Rome). One hundred and fifty patients affected by Cushing's syndrome and 300 patients in which hypercortisolism was excluded were enrolled. All patients were evaluated, according to current guidelines, for the suspicion of hypercortisolism. Results: The Cushing score was built by multivariable logistic regression, considering all main features associated with a clinical suspicion of hypercortisolism as possible predictors. A stepwise backward selection algorithm was used (final model AUC=0.873), then an internal validation was performed through ten-fold cross-validation. Final estimation of the model performance showed an average AUC=0.841, thus reassuring about a small overfitting effect. The retrieved score was structured on a 17.5-point scale: low-risk class (score value: ≤5.5, probability of disease=0.8%); intermediate-low-risk class (score value: 6-8.5, probability of disease=2.7%); intermediate-high-risk class (score value: 9-11.5, probability of disease=18.5%) and finally, high-risk class (score value: ≥12, probability of disease=72.5%). Conclusions: We developed and internally validated a simple tool to determine pre-test probability of hypercortisolism, the Cushing score, that showed a remarkable predictive power for the discrimination between subjects with and without a final diagnosis of Cushing's syndrome.