Rationale: A recent study showed that doctors are excessively pessimistic about the prognosis in patients with COPD and suggested that a simple tool to predict outcome is needed.
Methods: In a prospective observational study, 3343 patients with an FEV1<80% of the predicted value and FEV1/FVC<70% were selected from a clinical network of patients screened for COPD in Tayside, Scotland. Data were collected during annual visits on demography, spirometry, smoking history, medical research council (MRC) dyspnoea scale, body mass index (BMI) and other variables. The main outcome measures were hospitalisations and death secondary to COPD. A proportional hazard model was used to identify significant risk factors.
Results: Increasing age, low BMI, worsening MRC dyspnoea score, decreased FEV1, and prior respiratory or cardiovascular admission hospitalisation were predictors of poor outcome. Influenza vaccination was protective.
Conclusion: We have developed a model that estimates the risk of respiratory hospitalisation and death in patients with COPD.
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http://dx.doi.org/10.1016/j.rmed.2009.04.021 | DOI Listing |
JMIR Med Inform
January 2025
INSERM U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 30 Bd Jean Monnet, Nantes, 44093, France, 33 2 40 08 74 10.
Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of a medical "digital twin" has recently become popular to designate digital representations of patients as a support for a wide range of data science applications. However, the concept is ambiguous when it comes to practical implementations.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
Department of Endocrinology and Metabolism, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, China.
Background: Many tools have been developed to predict the risk of diabetes in a population without diabetes; however, these tools have shortcomings that include the omission of race, inclusion of variables that are not readily available to patients, and low sensitivity or specificity.
Objective: We aimed to develop and validate an easy, systematic index for predicting diabetes risk in the Asian population.
Methods: We collected the data from the NAGALA (NAfld [nonalcoholic fatty liver disease] in the Gifu Area, Longitudinal Analysis) database.
J Sports Sci
January 2025
Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Sogndal, Norway.
Multivariate pattern analysis was recently extended with covariate projections to solve the challenging task of modelling and interpreting associations in the presence of linear dependent multivariate covariates. Within a joint model, this approach allows quantification of the net association pattern between the outcome and the explanatory variables and between the individual covariates and these variables. The aim of this paper is to apply this methodology to establish the net multivariate association pattern between cardiorespiratory fitness (CRF) and a high-resolution linear dependent physical activity (PA) intensity descriptor derived from accelerometry in children and to validate the crucial sub-regions in the PA spectrum predicting CRF.
View Article and Find Full Text PDFBiol Direct
January 2025
National Key Laboratory for Innovation and Transformation of Luobing Theory; The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, Jinan, China.
Background: Carotid atherosclerotic plaque is the primary cause of cardiovascular and cerebrovascular diseases. It is closely related to oxidative stress and immune inflammation. This bioinformatic study was conducted to identify key oxidative stress-related genes and key immune cell infiltration involved in the formation, progression, and stabilization of plaques and investigate the relationship between them.
View Article and Find Full Text PDFJ Orthop Surg Res
January 2025
Department of Rheumatology and Immunology, Affiliated Hospital of Yangzhou University, Yangzhou University, No. 368 Hanjiang Middle Road, Yangzhou, Jiangsu, 225000, China.
Rheumatoid arthritis (RA), a chronic inflammatory joint disease causing permanent disability, involves exosomes, nanosized mammalian extracellular particles. Circular RNA (circRNA) serves as a biomarker in RA blood samples. This research screened differentially expressed circRNAs in RA patient plasma exosomes for novel diagnostic biomarkers.
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