ArticleDiabetes2008
Metabolic phenotypes, vascular complications, and premature deaths in a population of 4,197 patients with type 1 diabetes.
Article in Diabetes, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed, 92 citations in OpenAlex.
- Estimated glucose disposal rate as a candidate biomarker for thrombotic biomarkers in T1D: a pooled analysis.Journal of endocrinological investigation · 2021Trial
- Medication profiling in women with type 1 diabetes highlights the importance of adequate, guideline-based treatment in low-risk groups.Scientific reports · 2023Article
- Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic.International journal of obesity (2005) · 2023Observational
- The impact of diabetic nephropathy and severe diabetic retinopathy on chronic limb threatening ischemia risk in individuals with type 1 diabetes: a nationwide, population study.The Lancet regional health. Europe · 2023Article
- Whole-exome sequencing identifies novel protein-altering variants associated with serum apolipoprotein and lipid concentrations.Genome medicine · 2022Article
- Cross-sectional metabolic subgroups and 10-year follow-up of cardiometabolic multimorbidity in the UK Biobank.Scientific reports · 2022Article
- Is it time to change the goals of lipid management in type 1 diabetes mellitus? Changes in apolipoprotein levels during the first year of type 1 diabetes mellitus. Prospective InLipoDiab1 study.Archives of medical science : AMS · 2022Article
- Sphingomyelin and progression of renal and coronary heart disease in individuals with type 1 diabetes.Diabetologia · 2020Article
- EpiMetal: an open-source graphical web browser tool for easy statistical analyses in epidemiology and metabolomics.International journal of epidemiology · 2020Article
- Using Self Organizing Maps to Compare Sepsis Patients from the Neonatal and Adult Intensive Care Unit.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019Article
- Transcriptional networks of progressive diabetic peripheral neuropathy in the db/db mouse model of type 2 diabetes: An inflammatory story.Experimental neurology · 2018Article
- Article
- Data-driven metabolic subtypes predict future adverse events in individuals with type 1 diabetes.Diabetologia · 2017Article
- Novel genetic susceptibility loci for diabetic end-stage renal disease identified through robust naive Bayes classification.Diabetologia · 2014Article
- Early signs of atherosclerosis are associated with insulin resistance in non-obese adolescent and young adults with type 1 diabetes.Cardiovascular diabetology · 2012Article
- Sphingomyelin is associated with kidney disease in type 1 diabetes (The FinnDiane Study).Metabolomics : Official journal of the Metabolomic Society · 2012Article
- Cardiovascular risk in double diabetes mellitus--when two worlds collide.Nature reviews. Endocrinology · 2012Review
- Use of Self-Organizing Maps for Balanced Scorecard analysis to monitor the performance of dialysis clinic chains.Health care management science · 2012Article
- Discovery of early-stage biomarkers for diabetic kidney disease using ms-based metabolomics (FinnDiane study).Metabolomics : Official journal of the Metabolomic Society · 2012Article
- Soluble receptor for AGE (RAGE) is a novel independent predictor of all-cause and cardiovascular mortality in type 1 diabetes.Diabetologia · 2011Article
Corrections and comments
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Authors and funding
17 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePoor glycemic control, elevated triglycerides, and albuminuria are associated with vascular complications in diabetes. However, few studies have investigated combined associations between metabolic markers, diabetic kidney disease, retinopathy, hypertension, obesity, and mortality. Here, the goal was to reveal previously undetected association patterns between clinical diagnoses and biochemistry in the FinnDiane dataset. RESEARCH DESIGN AND
methodsAt baseline, clinical records, serum, and 24-h urine samples of 2,173 men and 2,024 women with type 1 diabetes were collected. The data were analyzed by the self-organizing map, which is an unsupervised pattern recognition algorithm that produces a two-dimensional layout of the patients based on their multivariate biochemical profiles. At follow-up, the results were compared against all-cause mortality during 6.5 years (295 deaths).
resultsThe highest mortality was associated with advanced kidney disease. Other risk factors included 1) a profile of insulin resistance, abdominal obesity, high cholesterol, triglycerides, and low HDL(2) cholesterol, and 2) high adiponectin and high LDL cholesterol for older patients. The highest population-adjusted risk of death was 10.1-fold (95% CI 7.3-13.1) for men and 10.7-fold (7.9-13.7) for women. Nonsignificant risk was observed for a profile with good glycemic control and high HDL(2) cholesterol and for a low cholesterol profile with a short diabetes duration.
conclusionsThe self-organizing map analysis enabled detailed risk estimates, described the associations between known risk factors and complications, and uncovered statistical patterns difficult to detect by classical methods. The results also suggest that diabetes per se, without an adverse metabolic phenotype, does not contribute to increased mortality.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.