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Primary pulmonary hyalinizing clear cell carcinoma (HCCC) is a very rare lung tumor that accounts for less than 0.09% of all primary lung tumors and has no specific epidemiology. The correct diagnosis requires imaging, laboratory, pathological, immunohistochemical, and molecular examination. The most typical feature of pulmonary HCCC is the clear cell component with clear stroma. In addition, the fusion gene EWSR1::ATF1 due to t(12;22)(q13;q12) is essential for the pathological diagnosis of pulmonary HCCC. The main treatment for pulmonary HCCC is surgery. This review focus on the pathological features, immunohistochemical examination, mutation analysis and treatment of pulmonary HCCC. [ABSTRACT FROM AUTHOR]

Background: Severe community-acquired pneumonia is one of the most lethal forms of CAP with high mortality. For rapid and accurate decisions, we developed a mortality prediction model specifically tailored for elderly SCAP patients. Methods: The retrospective study included 2365 elderly patients. To construct and validate the nomogram, we randomly divided the patients into training and testing cohorts in a 70% versus 30% ratio. The primary outcome was in-hospital mortality. Univariate and multivariate logistic regression analyses were used in the training cohort to identify independent risk factors. The robustness of this model was assessed using the C index, ROC and AUC. DCA was employed to evaluate the predictive accuracy of the model. Results: Six factors were used as independent risk factors for in-hospital mortality to construct the prediction model, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet, and BUN. The C index was 0.743 (95% CI 0.719–0.768) in the training cohort and 0.731 (95% CI 0.694–0.768) in the testing cohort. The ROC curves and AUC for the training cohort and testing cohort (AUC = 0.742 vs. 0.728) indicated a robust discrimination. And the calibration plots showed a consistency between the prediction model probabilities and observed probabilities. Then, the DCA demonstrated great clinical practicality. Conclusions: The nomogram incorporated six risk factors, including age, the use of vasopressor, chronic renal disease, neutrophil, platelet and BUN, which had great predictive accuracy and robustness, while also demonstrating clinical practicality at ICU admission. [ABSTRACT FROM AUTHOR]

Background: Modern medicine emphasizes that medical professionals engage in interprofessional collaboration to better meet the diverse needs of patients from physical, psychological, and social perspectives. As nursing students are the future reserve of the clinical nursing workforce, nursing educators worldwide should pay close attention to nursing students' interprofessional learning attitudes and take responsibility for training qualified interprofessional nursing personnel. However, little is known about the relationship between nursing students' readiness for interprofessional learning and academic self-efficacy. Thus, this study aims to investigate the level of readiness for interprofessional learning and academic self-efficacy among nursing students, and to explore the relationship between the two. Methods: A cross-sectional survey was conducted with a sample of 741 undergraduate nursing students pursuing four-year degrees from a school in Jinan, Shandong Province, China from November to December 2021. The social-demographic questionnaire, Readiness for Interprofessional Learning Scale, and Academic Self-efficacy Scale were used for data collection. Descriptive statistics used to analyze the data included: Cronbach's alpha, t-test, one-way ANOVA, Pearson's correlation, and multiple linear regression analysis. Results: Readiness for interprofessional learning mean score was (3.91 ± 0.44) and mean academic self-efficacy was (3.47 ± 0.42). Significant differences were found in the research variables according to participants' sex, grade, choice of nursing profession, and frequency of communication with health-related major students in studies (p < 0.05, p < 0.001). Pearson correlation analysis showed that academic self-efficacy was positively related to readiness for interprofessional learning (r = 0.316, p < 0.01). The hierarchical regression analysis showed that academic self-efficacy was positively related to readiness for interprofessional learning (β = 0.307, p < 0.001), The model explained 15.6% of the variance in readiness for interprofessional learning (F = 18.038, p < 0.001). Conclusions: Readiness for interprofessional learning and academic self-efficacy were in the middle level among nursing students. Moreover, there was a significant positive correlation between the two. Therefore, it is very important for nursing educators to improve nursing students' academic self-efficacy before improving their readiness for interprofessional learning. [ABSTRACT FROM AUTHOR]