Aims/hypothesis: The aims of this study were to provide a contemporary picture of mortality and causes of death in Europe following a diagnosis of type 1 diabetes made before the 15th birthday, and to examine excess mortality by country for possible links to incidence level or national prosperity.
Methods: Thirteen population-based EURODIAB registers in 12 countries followed-up 28,887 children diagnosed since 1989, either by record linkage to population registers or through contact with doctors providing care.
Results: There were 141 deaths in the cohort during 219,061 person-years of follow-up compared with 69.1 deaths expected from national mortality rates, a standardised mortality ratio (SMR) of 2.0 (95% CI 1.7-2.4). The SMR varied from 0 to 4.7 between countries, but showed little relationship with the country's incidence rate or gross domestic product (US$ per capita). The SMR did not change significantly with attained age, calendar period or time since diagnosis. The female SMR (2.7; 95% CI 2.0-3.5) was greater than the male SMR (1.8; 95% CI 1.4-2.2), although absolute numbers of excess deaths were similar in the two sexes. One-third of deaths were classified as directly attributable to diabetes (many with mention of ketoacidosis) and half were unrelated to diabetes. There was a non-significant excess of accidental/violent deaths (48 observed vs 40.7 expected; SMR 1.2; 95% CI 0.9-1.6) but little excess in suicides (11 observed, 10.2 expected; SMR 1.1; 95% CI 0.5-1.9).
Conclusions/interpretation: Before the onset of late complications, significant excess mortality existed following the diagnosis of type 1 diabetes in childhood, even in recent years. Variation between countries in this excess could not be explained.
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http://dx.doi.org/10.1007/s00125-007-0824-8 | DOI Listing |
Am J Gastroenterol
January 2025
Department of Internal Medicine and Medical Therapeutics, University of Pavia, Italy.
Introduction: Long-term prognosis of non-celiac enteropathies (NCEs) is poorly understood. We aimed to evaluate long-term outcomes and develop a prognostic score for NCEs.
Methods: NCEs patients from an international multicenter cohort (4 Italian centers,1 UK, 1 French,1 Norwegian,1 USA,1 Indian) followed-up over 30 years were enrolled.
Backgrounds: Biomedical research requires sophisticated understanding and reasoning across multiple specializations. While large language models (LLMs) show promise in scientific applications, their capability to safely and accurately support complex biomedical research remains uncertain.
Methods: We present , a novel question-and-answer benchmark for evaluating LLMs in biomedical research.
Microb Pathog
January 2025
Department of Clinical Laboratory, The First People's Hospital of Lianyungang, The Affiliated Lianyungang Hospital of Xuzhou Medical University, The First Affiliated Hospital of Kangda College of Nanjing Medical University, Lianyungang, Jiangsu Province, China. Electronic address:
Background: Previous investigations into the causal relationship between infections and systemic lupus erythematosus (SLE) have yielded controversial results. This study delves into the bidirectional causal relationships between various infectious agents and SLE, employing two-sample Mendelian randomization (MR) from an immunological perspective.
Methods: Utilizing genome-wide association study (GWAS) data for 46 antibody-mediated immune responses (AMIRs) to 13 pathogens and three distinct SLE datasets, we employed Bayesian Weighted MR (BWMR) and inverse variance weighted (IVW) methods to ascertain causal links, supplemented by meta-analysis to resolve inconsistencies.
Prog Neuropsychopharmacol Biol Psychiatry
January 2025
Institute of Neuropsychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing 210029, China. Electronic address:
Background: Type 2 diabetes (T2D) is a chronic metabolic disorder that has high comorbidity with mental disorders. The genetic relationships between T2D and depression are far from being well understood.
Methods: We performed genetic correlation, polygenic overlap, Mendelian randomization (MR) analyses, cross-trait meta-analysis, and Bayesian colocalization analysis to assess genetic relationships between T2D and depression, in the forms of major depressive disorder (MDD) and depressed affect (DAF).
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