Potential Predictive of Thoracic CT Value and Bone Mineral Density T-Value in COPD Complicated with Osteoporosis
International journal of general medicine(2024)SCI 4区
Department of Respiratory and Critical Care Medicine
Abstract
Background: COPD, combined with Osteoporosis, has a high incidence and potential for great harm. Choosing an optimal diagnostic method to achieve bone mineral density (BMD) screening is crucial for COPD patients. Studies on COPD patients with BMD reduction are lacking. Purpose: To identify the risk factors of BMD reduction and osteoporosis in COPD patients. Patients and Methods: We included a total of 81 patients with AECOPD, who were admitted to the hospital from July 1, 2019, to January 31, 2020. Patients were grouped into BMD normal group, BMD reduced group and OP group. The areas under ROC curve were used to explore the value of CT values in the diagnosis of bone abnormality, and clinical indicators were collected. Results: The CT value of the vertebral cancellous bone is highly correlated with the T value of BMD (R > 5.5, P < 0.0001). Using multivariate Logistic regression analysis, we showed that COPD duration, BMI, 25-hydroxyvitamin D3, and long-term inhaled glucocorticoid were independent factors affecting different BMD levels in COPD patients. No significant difference in bone formation indexes between groups. beta-crossL was negatively correlated with serum IL-6 (r=-0.254, P=0.022), and ALP was positively correlated with serum TNF-alpha (r=0.284, P=0.023). Conclusion: Thoracolumbar vertebral cancellous bone CT has potential value in the diagnosis of bone abnormality. COPD duration, BMI, 25-hydroxyvitamin D3, and long-term inhaled glucocorticoid may contribute to the BMD reduction in COPD patients, and serum IL-6 and TNF-alpha regulate bone metabolism in COPD patients.
MoreTranslated text
Key words
chronic obstructive pulmonary disease,osteoporosis,bone mineral density,chest CT
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
2010
被引用202 | 浏览
2002
被引用110 | 浏览
2014
被引用54 | 浏览
2015
被引用181 | 浏览
2016
被引用32 | 浏览
2004
被引用56 | 浏览
2023
被引用20 | 浏览
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper