Purpose: We aimed to develop a predictive model able to stratify patients with non-functioning adrenal incidentalomas (AIs), according to their risk for developing autonomous cortisol secretion (ACS) during follow-up.
Methods: This was a retrospective study of patients with non-functioning AIs consecutively evaluated at a single institution between 2013 and 2019 in whom hormonal follow-up information was available for at least 1 year. Clinical, biochemical, and radiological features were used to build a multivariate Cox regression model using the estimation of all possible equations.
Results: We included 331 patients with non-functioning AIs. ACS (post-dexamethasone suppression test (DST) serum cortisol > 1.8 µg/dL) developed in 73 patients during a median follow-up time of 35.7 months [range 12.8-165.4]. The best predictive model for ACS development during follow-up combined age, post-DST serum cortisol, and bilaterality at presentation and showed good diagnostic accuracy (AUC-ROC 0.70 [95% CI 0.65-0.75]). The lowest risk for ACS development was found among patients < 50 years old with cortisol post-DST values < 0.45 µg/dL and with unilateral tumors (risk 2.42%). Baseline post-DST serum cortisol levels at diagnosis were the most important factor for the development of ACS during follow-up (hazard ratio 3.56 for each µg/dL, p < 0.001). The rate of ACS development was associated with post-DST cortisol levels, being 19.2, 32.3, and 68.1 cases/10,000 person-years for patients with baseline post-DST cortisol < 0.9 µg/dL, 0.9-1.3 µg/dL, and > 1.3 µg/dL, respectively.
Conclusion: After ruling out malignancy, follow-up visits for patients < 50 years old with unilateral non-functioning AIs and post-DST serum cortisol < 0.45 µg/dL are considered unnecessary given the low risk of developing ACS during follow-up.
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Sci Rep
December 2024
KAUST Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Traditional prediction methods, dependent on homology and sequence similarity, often fail to predict functions for novel proteins and proteins without known homologs.
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December 2024
College of Mining Engineering, Guizhou University of Engineering Science, Bijie, 551700, China.
The Laurani high-sulfidation epithermal deposit, located in the northeastern Altiplano of Bolivia, is a representative gold-polymetallic deposit linked to the late Miocene volcanic rocks that were formed approximately at about 7.5 Ma. At Laurani, four mineralization stages are defined.
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December 2024
Department of Medical Device Development, Seoul National University College of Medicine, Seoul, Republic of Korea.
Vertebral collapse (VC) following osteoporotic vertebral compression fracture (OVCF) often requires aggressive treatment, necessitating an accurate prediction for early intervention. This study aimed to develop a predictive model leveraging deep neural networks to predict VC progression after OVCF using magnetic resonance imaging (MRI) and clinical data. Among 245 enrolled patients with acute OVCF, data from 200 patients were used for the development dataset, and data from 45 patients were used for the test dataset.
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December 2024
Department of Pharmaceutics, College of Pharmacy, University of Ha'il, Ha'il, 81442, Saudi Arabia.
This research article presents a thorough and all-encompassing examination of predictive models utilized in the estimation of viscosity for ionic liquid solutions. The study focuses on crucial input parameters, namely the type of cation, the type of anion, the temperature (measured in Kelvin), and the concentration of the ionic liquid (expressed in mol%). This study assesses three influential machine learning algorithms that are based on the Decision Tree methodology.
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December 2024
Computer Science Department, Saarland University, Saarbrücken, Germany.
Estimating the numbers and whereabouts of internally displaced people (IDP) is paramount to providing targeted humanitarian assistance. In conflict settings like the ongoing Russia-Ukraine war, on-the-ground data collection is nevertheless often inadequate to provide accurate and timely information. Satellite imagery may sidestep some of these challenges and enhance our understanding of the IDP dynamics.
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