ArticleEndocrine2023
Could the presence of adrenal incidentaloma negatively affect COVID 19 outcomes?
Article in Endocrine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 5 citations in OpenAlex.
- Benign Adrenal Adenomas Are Associated With Reduced Prevalence of Hospitalised Patients With COVID-19.Clinical endocrinology · 2026Article
- Assessing the informatics utility of artificial intelligence chatbots for patient and clinician support: the case of adrenal incidentaloma.Endocrine · 2026Article
- Relationship of obesity, body fat, benign adrenal tumors and the mediating mechanism: a two-step mendelian randomization study.BMC cancer · 2025Article
- Article
- Diabetes Mellitus in Non-Functioning Adrenal Incidentalomas: Analysis of the Mild Autonomous Cortisol Secretion (MACS) Impact on Glucose Profile.Biomedicines · 2024Review
- Clinical, radiological, and surgical outcomes of 431 patients with adrenal incidentalomas: retrospective study of a 10-year single-center experience.Turkish journal of medical sciences · 2024Article
- Post-COVID-19 incidentally discovered adrenal findings (a CT-focused real-life study).Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologieArticle
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveAdrenal incidentalomas (AIs) are lesions larger than 1 cm that are incidentally detected in the adrenal glands. Chest computed tomography (CCT) is widely used in the first evaluation of patients with suspected coronavirus disease (COVID-19) that resulted in many incidental findings in the thorax and upper abdomen. In this study, we aimed to investigate the frequency of AI and their effects on the course and outcome of COVID-19 regardless of functional status. MATERIAL AND
methodsWe included 2493 patients aged between 18 and 99 years and whose adrenal glands were clearly visible in CCT images. They were divided into two groups: those with AI (AI group) and without AI (Control group).
resultsAI was detected in 148 (5.93%) patients and 80 (54.1%) of them were male. There was no difference in sex distribution between the groups, but the median age of patients with AI was significantly higher than those without AI [54.5 (20-94 years) vs. 42 (18-99 years); p < 0.001)]. In addition, in the AI group, both hospitalizations due to COVID-19-related conditions (30.4 vs. 21.2%, p = 0.008) and the mortality rate experienced during this time was significantly higher (14.7 vs. 7%, p < 0.001) diseases. The AI group had a significantly higher comorbidity rate than the control group (61.5 vs. 41.9%, p < 0.001). The most common comorbid diseases were hypertension, cardiovascular diseases, diabetes mellitus, respiratory system diseases, and hyperlipidaemia. Advanced age and male gender in terms of mortality, advanced age and covid 19 positivity in terms of hospitalization were determined as significant risk factors.
conclusionsThe presence of AI may increase the morbidity and mortality rates associated with COVID-19, regardless of their functional status. Therefore, patients subjected to CCT imaging for COVID-19-related lung diseases should also be evaluated for AI. Careful follow-up of patients with COVID-19 and AI is necessary to monitor the progression of COVID-19.
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