Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

Heterogeneous effects of obesity on mental health: Evidence from Mexico

Obesity can spread more easily if it is not perceived negatively. This issue may be more pronounced among the poor, a conjecture that we test in this paper. We start with general evidence on the concave relationship between income and obesity, both across countries and within Mexico, a country characterized by very unequal development levels and the highest obesity rate in the world. We suggest a general model that explains this stylized fact from a simple necessary condition, namely, the complementarity between nonfood consumption and health concerns. Then, we test the direct effect of overweight on mental health among Mexican women. We find a positive effect of obesity in the low consumption group and a depressing effect among the rich. This result is robust to the inclusion of a range of confounders (childhood conditions, lifestyle variables, food expenditure, and household shocks) and after instrumenting individual fatness by the variation in genetic predisposition. The complementarity between living standards and weight concerns may reflect different norms, different labor market penalties, or simply different returns to healthy time across the social spectrum.     

Managing healthcare worker well‐being in an Australian emergency department during the COVID‐19 pandemic

Emergency Medicine staff in Australia and New Zealand are at the forefront of the healthcare response to COVID‐19. This article describes a well‐being plan for ED staff that has been devised to mitigate against the negative psychological impact of the COVID‐19 pandemic.