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886 results on '"Eliasson, Björn"'

14. Testing and Visualization of Associations in Three-Way Contingency Tables: A Study on Gender Gap in Patients with Type I Diabetes and Cardiovascular Complications

Author

Lombardo, Rosaria, primary, Beh, Eric J., additional, Prattichizzo, Francesco, additional, Lucisano, Giuseppe, additional, Nicolucci, Antonio, additional, Eliasson, Björn, additional, Carlsen, Hanne Krage, additional, Grotta, Rosalba La, additional, Pellegrini, Valeria, additional, and Ceriello, Antonio, additional

Published
2024
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22. Testing and Visualization of Associations in Three-Way Contingency Tables: A Study of the Gender Gap in Patients with Type 1 Diabetes and Cardiovascular Complications.

Author

Lombardo, Rosaria, Beh, Eric J., Prattichizzo, Francesco, Lucisano, Giuseppe, Nicolucci, Antonio, Eliasson, Björn, Carlsen, Hanne Krage, Grotta, Rosalba La, Pellegrini, Valeria, and Ceriello, Antonio

Subjects
TYPE 1 diabetes, DIABETES complications, CARDIOLOGICAL manifestations of general diseases, GENDER inequality, AGE groups
Abstract

Using data from the Swedish National Diabetes Register, this study examines the gender disparity among patients with type 1 diabetes who have experienced a specific cardiovascular complication, while exploring the association between their weight variability, age group, and gender. Fourteen cardiovascular complications have been considered. This analysis is conducted using three-way correspondence analysis (CA), which allows for the partitioning and decomposition of Pearson's three-way chi-squared statistic. The dataset comprises information organized in a data cube, detailing how weight variability among these patients correlates with a cardiovascular complication, age group, and gender. The three-way CA method presented in this paper allows one to assess the statistical significance of the association between these variables and to visualize this association, highlighting the gender gap among these patients. From this analysis, we find that the association between weight variability, age group, and gender varies among different types of cardiovascular complications. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Lifetime and 10‐year cardiovascular risk prediction in individuals with type 1 diabetes: The LIFE‐T1D model.

Author

Helmink, Marga A. G., Hageman, Steven H. J., Eliasson, Björn, Sattar, Naveed, Visseren, Frank L. J., Dorresteijn, Jannick A. N., Harris, Katie, Peters, Sanne A. E., Woodward, Mark, Szentkúti, Péter, Højlund, Kurt, Henriksen, Jan Erik, Sørensen, Henrik Toft, Serné, Erik H., van Sloten, Thomas T., Thomsen, Reimar W., and Westerink, Jan

Subjects
TYPE 1 diabetes, PROPORTIONAL hazards models, CARDIOVASCULAR diseases risk factors, SYSTOLIC blood pressure, GLOMERULAR filtration rate, BODY mass index
Abstract

Aims: To develop and externally validate the LIFE‐T1D model for the estimation of lifetime and 10‐year risk of cardiovascular disease (CVD) in individuals with type 1 diabetes. Materials and Methods: A sex‐specific competing risk‐adjusted Cox proportional hazards model was derived in individuals with type 1 diabetes without prior CVD from the Swedish National Diabetes Register (NDR), using age as the time axis. Predictors included age at diabetes onset, smoking status, body mass index, systolic blood pressure, glycated haemoglobin level, estimated glomerular filtration rate, non‐high‐density lipoprotein cholesterol, albuminuria and retinopathy. The model was externally validated in the Danish Funen Diabetes Database (FDDB) and the UK Biobank. Results: During a median follow‐up of 11.8 years (interquartile interval 6.1–17.1 years), 4608 CVD events and 1316 non‐CVD deaths were observed in the NDR (n = 39 756). The internal validation c‐statistic was 0.85 (95% confidence interval [CI] 0.84–0.85) and the external validation c‐statistics were 0.77 (95% CI 0.74–0.81) for the FDDB (n = 2709) and 0.73 (95% CI 0.70–0.77) for the UK Biobank (n = 1022). Predicted risks were consistent with the observed incidence in the derivation and both validation cohorts. Conclusions: The LIFE‐T1D model can estimate lifetime risk of CVD and CVD‐free life expectancy in individuals with type 1 diabetes without previous CVD. This model can facilitate individualized CVD prevention among individuals with type 1 diabetes. Validation in additional cohorts will improve future clinical implementation. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Association of glucagon-like peptide-1 receptor agonists with serious liver events among patients with type 2 diabetes: A scandinavian cohort study

Author

Engström, Arvid, primary, Wintzell, Viktor, additional, Melbye, Mads, additional, Svanström, Henrik, additional, Eliasson, Björn, additional, Gudbjörnsdottir, Soffia, additional, Hveem, Kristian, additional, Jonasson, Christian, additional, Hviid, Anders, additional, Ueda, Peter, additional, and Pasternak, Björn, additional

Published
2023
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32. Risk of fracture in adults with type 2 diabetes in Sweden: A national cohort study

Author

Axelsson, Kristian F., Litsne, Henrik, Kousoula, Konstantina, Franzén, Stefan, Eliasson, Björn, and Lorentzon, Mattias

Subjects
Fractures -- Risk factors -- Demographic aspects, Type 2 diabetes -- Complications and side effects, Biological sciences
Abstract

Background Type 2 diabetes mellitus (T2DM) is considered a risk factor for fracture but the evidence regarding the impact of T2DM on fracture risk is conflicting. The objective of the study was to determine if patients with T2DM have increased fracture risk and if T2DM-related risk factors could be identified. Methods and findings In this national cohort study in Sweden, we investigated the risk of fracture in 580,127 T2DM patients, identified through the national diabetes register including from both primary care and hospitals, and an equal number of population-based controls without diabetes matched for age, sex, and county from 2007 to 2017. The mean age at entry was 66.7 years and 43.6% were women. During a median follow-up time of 6.6 (interquartile range (IQR) 3.1 to 9.8) years, patients with T2DM had a marginally but significantly increased risk of major osteoporotic fracture (MOF) (hazard ratio (HR) 1.01 (95% confidence interval [CI] 1.00 to 1.03)) and hip fracture (HR 1.06 (95% CI 1.04 to 1.08)) compared to controls, associations that were only minimally affected (HR 1.05 (95% CI 1.03 to 1.06) and HR 1.11 (95% CI 1.09 to 1.14), respectively) by multivariable adjustment (age, sex, marital status, and an additional 20 variables related to general morbidity, cardiovascular status, risk of falls, and fracture). In a multivariable-adjusted Cox model, the proportion of the risk for all fracture outcomes (Heller's R2) explained by T2DM was below 0.1%. Among the T2DM patients, important risk factors for fracture were a low BMI ( Conclusion In this study, we observed only a marginally increased fracture risk in T2DM, a condition that explained less than 0.1% of the fracture risk. Consideration of the herein identified T2DM-related risk factors could be used to stratify T2DM patients according to fracture risk., Author(s): Kristian F. Axelsson 1,2, Henrik Litsne 1, Konstantina Kousoula 1,3, Stefan Franzén 4, Björn Eliasson 3,5, Mattias Lorentzon 1,6,7,* Introduction It has been estimated that 151 million people have [...]

Published
2023
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33. Anti-interleukin-21 antibody and liraglutide for the preservation of β-cell function in adults with recent-onset type 1 diabetes: a randomised, double-blind, placebo-controlled, phase 2 trial

Author

Ludvik, Bernhard, Prager, Rudolf, Paulweber, Bernhard, Ebenbichler, Christoph F, Keymeulen, B, De Block, C, Grossman, Loren, Houlden, Robyn, Perron, Patrice, Ransom, Thomas, Senior, Peter, Weisnagel, S. John, Woo, Vincent, Dumas, Richard, Thompson, David, Vilsbøll, Tina, Gram, Jeppe, Juhl, Claus Bogh, Hukkanen, Janne, Lahtela, Jorma, Niskanen, Leo, O'Shea, Donal, O'Brien, Timothy, Sreenan, Seamus, Wainstein, Julio, Phillip, Moshe, Knobler, Hilla, Dotta, Francesco, Piatti, Pier Marco, Roberto, Trevisan, Gnasso, Agostino, Gulseth, Hanne, Cooper, John, Pankowska, Ewa, Lukaszewicz, Monika, Wolnik, Bogumił, Manita, Isabel, Marques, Olinda, Roque, Cristina, Príncipe, Rosa Maria, Neves, Celestino, Heitor, Susana, Ruyatkina, L, Dvoryashina, Irina, Vagapova, Gulnar, Belousova, Lidiya, Sergeeva-Kondrachenko, Marina, Peskov, Andrey, Frolova, Elena, Golovach, Albina, Kunitsyna, Marina, Krasnopeeva (Kabachkova), Natalia, Ipatko, Irina, De la Cuesta, Carmen, Tinahones, Francisco José, Rigla, Mercedes, Merino, Juan Francisco, Gómez, Luis Alberto, Fernández, Mercè, Simó, Rafael, Rydén, Mikael, Jendle, Johan, Filipsson, Karin, Eliasson, Björn, Mankovsky, Borys, Lymar, Iurii, Sokolova, Liubov, Myshanych, Galyna, Zlova, Tetiana, Vlasenko, Maryna, Kuskalo -, Petro, Courtney, Hamish, Dayan, Colin, English, Patrick, Heller, Simon, Johnson, Andrew B, Nair, Sunil, Leslie, R. D, Narendran, P, Oliver, Nick, Ramtoola, Shenaz, Shaw, Jim, Viljoen -, Adie, Al-Karadsheh, Amer, Dostou, Jean Marie, Gangi, Sumana, Gottlieb, Peter, Jerkins, Terri, Magnotti, Michael, Marks, Jennifer, Nakhle, Samer, Bonabi, Gholamreza, Myers, Lyle, Pratley, Richard, Hagopian, William, Pettus, Jeremy, von Scholten, Bernt Johan, Wesley, Johnna D, Kreiner, Frederik F, von Herrath, Matthias, Bain, Stephen C, Bode, Bruce, Clausen, Jesper Ole, Coppieters, Ken, Gaysina, Leylya, Gumprecht, Janusz, Hansen, Troels Krarup, Mathieu, Chantal, Morales, Cristobal, Mosenzon, Ofri, Segel, Stine, Tsoukas, George, and Pieber, Thomas R

Published
2021
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37. Glucagon-like peptide 1 receptor agonist use and risk of thyroid cancer: Scandinavian cohort study.

Author

Pasternak, Björn, Wintzell, Viktor, Hviid, Anders, Eliasson, Björn, Gudbjörnsdottir, Soffia, Jonasson, Christian, Hveem, Kristian, Svanström, Henrik, Melbye, Mads, and Ueda, Peter

Subjects
GLUCAGON-like peptide-1 agonists, RISK assessment, THYROID gland tumors, RESEARCH funding, ENZYME inhibitors, HYPOGLYCEMIC agents, REPORTING of diseases, LONGITUDINAL method, SODIUM-glucose cotransporter 2 inhibitors, COMPARATIVE studies, CONFIDENCE intervals, DIABETES, PROPORTIONAL hazards models, PATIENT aftercare, DISEASE risk factors
Published
2024
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