A High Level of Cardiorespiratory Fitness is Associated with a Stiffer Spleen in a Population-Based Cohort Study
European Journal of Preventive Cardiology（2024）
Universitaetsmedizin Greifswald | Charité - Universitätsmedizin Berlin | Charité - University Medicine Berlin
Abstract
Higher cardiorespiratory fitness (CRF) and muscle strength are independently associated with reduced risk of cardiovascular disease and morbidity. Higher CRF and muscle strength are also associated with an improved immune response. Since the spleen plays an integral role in the innate and adaptive immune system, we hypothesized that CRF and muscle strength would be associated with biophysical characteristics of the spleen. We related CRF and muscle strength with spleen stiffness as measured by shear wave elastography in a large population-based cohort from the Study of Health in Pomerania (SHIP). We used cross-sectional data from 677 participants of the population-based, prospective Health Study in Pomerania (SHIP-START-4). A symptom-limited cardiopulmonary exercise test was performed according to a modified Jones protocol. Hand grip strength was determined using a JAMAR dynamometer. Time-harmonic elastography was used to measure splenic shear wave velocity as a surrogate for splenic stiffness. The shear waves in the spleen were generated by a loudspeaker integrated into an examination table, which emitted multifrequency vibrations in the range of 27 to 56 Hz. Tissue strain was encoded from radiofrequency data acquired by an ultrasound system. Shear wave velocity maps covering the entire visible spleen in B-mode were calculated using the k-MDEV method. Finally, mean values were calculated within a manually drawn region of interest. We used linear regression models adjusted for age, sex, and body weight to relate CRF and muscle strength to spleen shear wave velocity. The median age of the study population was 61 (25th quartile: 52 and 75th quartile: 70) years and 54% were women. A one liter/min higher VO2peak was associated with a 0.05 (95% confidence interval [CI] 0.01 - 0.07; p < 0.01) m/s higher splenic shear wave velocity. A 100 watt higher peak workload was also associated with a 0.05 (95% CI 0.01 - 0.08, p < 0.01) m/s higher splenic shear wave velocity. When CRF was normalized to body weight, a 1 ml/kg/min higher CRF was associated with a 0.007 (95% CI 0.005 - 0.009, p < 0.01) m/s higher splenic shear wave velocity. We found no associations between hand grip strength and splenic shear wave velocity. In our study, we found that higher VO2peak, VO2peak adjusted for body weight and maximal workload were associated with higher spleen stiffness. As a non-invasive and inexpensive test, time-harmonic shear wave elastography has potential for patient care. Interestingly, there seems to be no correlation between muscle strength and splenic shear wave velocity. It remains unclear why CRF, but not muscle strength, is related to splenic shear wave velocity.
MoreTranslated text
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
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