Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros











Base de dados
Intervalo de ano de publicação
1.
J Thorac Dis ; 16(2): 935-947, 2024 Feb 29.
Artigo em Inglês | MEDLINE | ID: mdl-38505025

RESUMO

Background: Pulmonary epithelioid hemangioendothelioma (PEH) is a rare vascular tumour, and its early diagnosis remains challenging. This study aims to comprehensively analyse the imaging features of PEH and develop a model for predicting PEH. Methods: Retrospective and pooled analyses of imaging findings were performed in PEH patients at our center (n=25) and in published cases (n=71), respectively. Relevant computed tomography (CT) images were extracted and used to build a deep learning model for PEH identification and differentiation from other diseases. Results: In this study, bilateral multiple nodules/masses (n=19) appeared to be more common with most nodules less than 2 cm. In addition to the common types and features, the pattern of mixed type (n=4) and isolated nodules (n=4), punctate calcifications (5/25) and lymph node enlargement were also observed (10/25). The presence of pleural effusion is associated with a poor prognosis in PEH. The deep learning model, with an area under the receiver operating characteristic curve (AUC) of 0.71 [95% confidence interval (CI): 0.69-0.72], has a differentiation accuracy of 100% and 74% for the training and test sets respectively. Conclusions: This study confirmed the heterogeneity of the imaging findings in PEH and showed several previously undescribed types and features. The current deep learning model based on CT has potential for clinical application and needs to be further explored in the future.

2.
J Thorac Dis ; 15(5): 2559-2570, 2023 May 30.
Artigo em Inglês | MEDLINE | ID: mdl-37324067

RESUMO

Background: Asthma is a public health problem worldwide. However, only a few studies have reported the epidemiology of asthma in various age groups in East Asia. The present study aimed to analyze and predict trends in the incidence of asthma in East Asia through the Global Burden of Disease 2019 (GBD 2019) study and provide information for prevention and control strategies. Methods: The estimates of incidence, deaths, disability-adjusted life years (DALYs), and risk factors of asthma in China, South Korea, Japan, and the world from 1990-2019 were retrieved from the GBD 2019 study. The age-standardized rates (ASRs) and the average annual percentage changes (AAPCs) assessed the incidence, deaths, and DALYs of asthma, and the projection was assessed by applying the age-period-cohort model. Results: The burden of asthma in South Korea and Japan was slightly higher than in China and slightly lower than that worldwide. The age-standardized incidence rate (ASIR) of asthma in China decreased slightly from 394.58/100,000 in 1990 to 355.33/100,000 in 2019 (with an AAPC of -0.59), while the age-standardized death rate (ASDR) and the age-standardized DALY rate (ASDALR) decreased significantly (with a AAPCs of -5.22 and -2.89, respectively), which were lower than those in South Korea and Japan. Moreover, males in China, South Korea, and Japan were significantly more affected by tobacco and environmental/occupational factors than females, while the proportion of metabolic factors in females was higher than that in males. The prediction for the burden of asthma in the three East Asian countries continued to decline or stabilize until 2030, especially in China and Japan. Conclusions: Although the overall asthma burden has a downward trend according to GBD 2019, it is still heavy in East Asia, especially South Korea. In addition, increased concern and control measures are needed for the disease burden in elderly patients.

SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA