Dingfeng Li1, Natalia Genere1, Emma Behnken2, Majlinda Xhikola3, Tiffany Abbondanza4, Anand Vaidya4, Irina Bancos1. 1. Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, Minnesota. 2. Knowledge and Evaluation Research (KER) Unit, Mayo Clinic, Rochester, Minnesota. 3. Division of Endocrinology, University of Florida and Malcom Randall VA Medical Center, Gainesville, Florida. 4. Center for Adrenal Disorders, Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women's Hospital, Boston, Massachusetts.
Abstract
CONTEXT: Current evidence on determinants of adverse health outcomes in patients with adrenal insufficiency (AI) is scarce, especially in regards to AI subtypes. OBJECTIVE: To determine predictors of adverse outcomes in different subtypes of AI. DESIGN AND SETTING: Cross-sectional survey study at 2 tertiary centers. PARTICIPANTS: A total of 696 patients with AI: primary AI (PAI, 42%), secondary AI (SAI, 32%), and glucocorticoid-induced AI (GIAI, 26%). INTERVENTION: Patient-centered questionnaire. MAIN OUTCOME MEASURES: Patients' knowledge, self-management of AI, self-perceived health, and adverse outcomes. RESULTS: The incidence rate of adrenal crisis was 24/100 patient-years with 44% experiencing at least 1 adrenal crisis since diagnosis (59% in PAI vs 31% in SAI vs 37% in GIAI, P < .0001). All patients described high degrees of discomfort with self-management and receiving prompt treatment. Patients with PAI were most likely to develop adrenal crises (adjusted OR 2.8, 95% CI 1.9-4.0) despite reporting better self-perceived health (adjusted OR 3.3, 95% CI 2.1-5.3), understanding of their diagnosis (89% vs 74-81% in other subtypes, P = .002), higher comfort with self-management (62% vs 52-61% in other sub types, P = .005), and higher likelihood to receive prompt treatment for adrenal crises in the emergency department (42% vs 19-30% in other subtypes, P < .0001). CONCLUSIONS: Patients with AI reported high degrees of discomfort with self-management and treatment delays when presenting with adrenal crises. Despite better self-perceived health and understanding of diagnosis, patients with PAI experienced the highest frequency of adrenal crises. A multidimensional educational effort is needed for patients and providers to improve the outcomes of all subtypes of AI.
CONTEXT: Current evidence on determinants of adverse health outcomes in patients with adrenal insufficiency (AI) is scarce, especially in regards to AI subtypes. OBJECTIVE: To determine predictors of adverse outcomes in different subtypes of AI. DESIGN AND SETTING: Cross-sectional survey study at 2 tertiary centers. PARTICIPANTS: A total of 696 patients with AI: primary AI (PAI, 42%), secondary AI (SAI, 32%), and glucocorticoid-induced AI (GIAI, 26%). INTERVENTION: Patient-centered questionnaire. MAIN OUTCOME MEASURES: Patients' knowledge, self-management of AI, self-perceived health, and adverse outcomes. RESULTS: The incidence rate of adrenal crisis was 24/100 patient-years with 44% experiencing at least 1 adrenal crisis since diagnosis (59% in PAI vs 31% in SAI vs 37% in GIAI, P < .0001). All patients described high degrees of discomfort with self-management and receiving prompt treatment. Patients with PAI were most likely to develop adrenal crises (adjusted OR 2.8, 95% CI 1.9-4.0) despite reporting better self-perceived health (adjusted OR 3.3, 95% CI 2.1-5.3), understanding of their diagnosis (89% vs 74-81% in other subtypes, P = .002), higher comfort with self-management (62% vs 52-61% in other sub types, P = .005), and higher likelihood to receive prompt treatment for adrenal crises in the emergency department (42% vs 19-30% in other subtypes, P < .0001). CONCLUSIONS: Patients with AI reported high degrees of discomfort with self-management and treatment delays when presenting with adrenal crises. Despite better self-perceived health and understanding of diagnosis, patients with PAI experienced the highest frequency of adrenal crises. A multidimensional educational effort is needed for patients and providers to improve the outcomes of all subtypes of AI.
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