Purpose: This study aimed to cross-validate a recently proposed equation for the prediction of maximal oxygen uptake (V˙O2max) in cycling exercise by using the average power output normalized by the body mass from a 5-minute time trial (RPO5-min) as the independent variable. Further, the study aimed to update the predictive equation using Bayesian informative prior distributions and meta-analysis.
Methods: On different days, 49 male cyclists performed an incremental graded exercise test until exhaustion and a 5-minute time trial on a stationary cycle ergometer. We compared the actual V˙O2max with the predicted value obtained from the RPO5-min, using a modified Bayesian Bland-Altman agreement analysis. In addition, this study updated the data on the linear regression between V˙O2max and RPO5-min, by incorporating information from a previous study as a Bayesian informative prior distribution or via meta-analysis.
Results: On average, the predicted V˙O2max using RPO5-min underestimated the actual V˙O2max by -6.6 mL·kg-1·min-1 (95% credible interval, -8.6 to -4.7 mL·kg-1·min-1). The lower and upper 95% limits of agreement were -17.2 (-22.7 to -12.3) and 3.8 (-1.0 to 9.5) mL·kg-1·min-1, respectively. When the current study's data were analyzed using the previously published data as a Bayesian informative prior distribution, the accuracy of predicting sample means was found to be better when compared with the data combined via meta-analyses.
Conclusions: The proposed equation presented systematic bias in our sample, in which the prediction underestimated the actual V˙O2max. We provide an updated equation using the previous one as the prior distribution, which could be generalized to a greater audience of cyclists.
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http://dx.doi.org/10.1123/ijspp.2023-0330 | DOI Listing |
Curr Med Imaging
January 2025
School of Life Sciences, Tiangong University, Tianjin 300387, China.
Objective: The objective of this research is to enhance pneumonia detection in chest X-rays by leveraging a novel hybrid deep learning model that combines Convolutional Neural Networks (CNNs) with modified Swin Transformer blocks. This study aims to significantly improve diagnostic accuracy, reduce misclassifications, and provide a robust, deployable solution for underdeveloped regions where access to conventional diagnostics and treatment is limited.
Methods: The study developed a hybrid model architecture integrating CNNs with modified Swin Transformer blocks to work seamlessly within the same model.
Mol Autism
January 2025
Department of Special Education, University of Haifa, Haifa, Israel.
Background: Alterations in sensory perception, a core phenotype of autism, are attributed to imbalanced integration of sensory information and prior knowledge during perceptual statistical (Bayesian) inference. This hypothesis has gained momentum in recent years, partly because it can be implemented both at the computational level, as in Bayesian perception, and at the level of canonical neural microcircuitry, as in predictive coding. However, empirical investigations have yielded conflicting results with evidence remaining limited.
View Article and Find Full Text PDFPLoS Med
January 2025
Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
Background: Globally, over one-third of pulmonary tuberculosis (TB) disease diagnoses are made based on clinical criteria after a negative bacteriological test result. There is limited information on the factors that determine clinicians' decisions to initiate TB treatment when initial bacteriological test results are negative.
Methods And Findings: We performed a systematic review and individual patient data meta-analysis using studies conducted between January 2010 and December 2022 (PROSPERO: CRD42022287613).
Ann Intensive Care
January 2025
Jiangsu Provincial Key Laboratory of Critical Care Medicine, Department of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, No. 87, Dingjiaqiao Road, Gulou District, Nanjing, 210009, People's Republic of China.
Background: The association between bedside ventilatory parameters-specifically arterial carbon dioxide pressure (PaCO) and ventilatory ratio (VR)-and mortality in patients with acute respiratory distress syndrome (ARDS) remains a topic of debate. Additionally, the persistence of this association over time is unclear. This study aims to investigate the relationship between 28-day mortality in ARDS patients and their longitudinal exposure to ventilatory inefficiency, as reflected by serial measurements of PaCO and VR.
View Article and Find Full Text PDFBiol Trace Elem Res
January 2025
Department of Geriatrics, The Second Affiliated Hospital, Nanjing Medical University, Nanjing, 210011, China.
Several studies have reported associations between specific heavy metals and essential trace elements and acute myocardial infarction (AMI). However, there is limited understanding of the relationships between trace elements and AMI in real-life co-exposure scenarios, where multiple elements may interact simultaneously. This cross-sectional study measured serum levels of 56 trace elements using inductively coupled plasma mass spectrometry.
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