Endocrine Abstracts

Background and Aims: Growing scientific evidence supports the hypothesis of an increased cardiometabolic risk in patients harboring adrenal incidentalomas (AI). This risk would be higher in aging populations and patients with functioning adenomas. The current study aims to determine the clinical and biochemical characteristics of metabloic syndrome(MetS) and assess its prevalence in older patients with AI.

Patients and Method: We conducted a retrospective descriptive study including 69 patients aged 65 years and above diagnosed with AI. All patients have undergone clinical examination, adrenal CT, and biochemical workup at the Endocrinology Department of Hedi Chaker University Hospital, Sfax, Tunisia, from 2011 to 2020. MetS was diagnosed based on the National Cholesterol Education Program’s Adult Treatment Panel III (ATP III) criteria.

Results: The mean age at diagnosis was 71.4±4.2 years, with a female predominance (57.5%). Seventy percent of elderly patients had non-secreting AI. The functioning incidentalomas displayed autonomous cortisol secretion (32.5%), primary hyperaldosteronism (25%), or secondary hyperaldosteronism (21.8%). One senior had a secreting pheochromocytoma. Hypertension was the most common metabolic disorder encountered in 77.5% of aged patients. The mean Body mass index was 28.5±5.4 kg/m². Our elderly population was frequently overweight (32.5%) or obese (40%). Abdominal obesity affected remarkably the female gender (87% in females versus 35.3% in males) with a mean waist circumference of 106 cm in females and 99 cm in males. We noticed a glucose metabolism disorder in 70%: mainly diabetes mellitus in 60%, impaired fasting glucose in 7.5%, and impaired glucose tolerance in 2.5%. Most senior patients had disturbed lipid profiles. HypoHDLemia prevailed in 45.7%, while hypertriglyceridemia and hypercholesterolemia were found in 17.5% and 28.2%, respectively. The prevalence of MetS in our sample of geriatric patients carrying AI was 24.6%.

Conclusion: Recent scientific data has concluded that AI defines a novel risk factor of MetS [1]. We could hypothesize that AI (despite its hormonal profile) may be associated with a subtle excessive cortisol secretion, hardly labeled clinically and biochemically, which could cause an acquired condition of insulin resistance [2]. Along with multiple age-related mechanisms, this condition would be clinically manifest and result in overt MetS in the geriatric population.

References: 1. Ribeiro Cavalari, al. “Nonfunctioning adrenal incidentaloma: a novel predictive factor for metabolic syndrome.” Clinical endocrinology 89.5 (2018): 586–595.

2. Peppa, Melpomeni, et al. “Insulin resistance and metabolic syndrome in patients with nonfunctioning adrenal incidentalomas: a cause-effect relationship?.” Metabolism 59.10 (2010): 1435–1441.