door bhrw | apr 15, 2023 | diabetes, gezondheidszorg |
Aims/hypothesis: Optimal diabetes care and risk factor management are important to delay micro- and macrovascular complications in individuals with type 1 diabetes (T1D). Ongoing improvement of management strategies requires the evaluation of target achievement and identification of risk factors in individuals who do (or do not) achieve these targets.
Methods: Cross-sectional data were collected from adults with T1D visiting six diabetes centers in the Netherlands in 2018. Targets were defined as glycated hemoglobin (HbA1c) <53 mmol/mol, low-density lipoprotein-cholesterol (LDL-c) <2.6 mmoL/L (no cardiovascular disease [CVD] present) or <1.8 mmoL/L (CVD present), or blood pressure (BP) <140/90 mm Hg. Target achievement was compared for individuals with and without CVD.
Results: Data from 1737 individuals were included. Mean HbA1c was 63 mmol/mol (7.9%), LDL-c was 2.67 mmoL/L, and BP 131/76 mm Hg. In individuals with CVD, 24%, 33%, and 46% achieved HbA1c, LDL-c, and BP targets respectively. In individuals without CVD these percentages were 29%, 54%, and 77%, respectively. Individuals with CVD did not have any significant risk factors for HbA1c, LDL-c, and BP target achievement. In comparison, individuals without CVD were more likely to achieve glycemic targets if they were men and insulin pump users. Smoking, microvascular complications, and the prescription of lipid-lowering and antihypertensive medication were negatively associated with glycemic target achievement. No characteristics were associated with LDL-c target achievement. Microvascular complications and antihypertensive medication prescription were negatively associated with BP target attainment.
Conclusion: Opportunities for improvement of diabetes management exist for the achievement of glycemic, lipid, and BP targets but may differ between individuals with and without CVD.
You can read the full article at https://onlinelibrary.wiley.com/doi/10.1111/1753-0407.13368
door bhrw | apr 15, 2023 | gezondheidszorg, hypofyse |
Het volgende artikel schreef ik voor het magazine Hypofyse.
(meer…)
door bhrw | mrt 8, 2023 | diabetes, gezondheidszorg |
Fantasie wordt werkelijkheid… introductie van het mylife CamAPS FX systeem in Nederland.
Het totale systeem bestaat -zoals het plaatje aangeeft- uit de myLife YpsoPump insuline pomp, de Dexcom G6 glucose sensor, en het verbindende CamAPS FX software systeem, dat is ontworpen door professor Roman Hovorka, een genie op het gebied van diabetes en closed-loop software.
Kijk hier naar de opnames van dit webinar. De link is: https://www.youtube.com/watch?v=FNzAE-6A1-4
door bhrw | feb 26, 2023 | gezondheidszorg, pictures |
Voor het maken van een aantal presentaties heb ik me tot enkele AI websites gewend. Twee AI websites voor het genereren van foto’s worden met nadruk op TikTok en andere media geplugd. “Websites that will change the world.” “Secret websites that feel illegal to know.”
Ik had een paar wensen voor het converteren van tekst in een foto: foto’s van een arts, man of vrouw, in een witte jas met korte mouwen, al dan niet werkend aan een computer. Het ene programma doet het wat beter dan het andere. Beide hebben moeite met de anatomie van de handen en de constructie van zoiets simpels als een stethoscoop. Het 1e programma creëert wel een mooi gezicht, hoewel dit nog niet heel natuurlijk aandoet. Het 2e programma creëert verwrongen gezichten. Een paar resultaten:
Belangrijkste conclusie: AI is nog niet van zulke hoge kwaliteit……
door bhrw | jan 2, 2023 | gezondheidszorg, hypofyse |
Mijn recente column in het Hypofyse Nieuws.
door bhrw | dec 30, 2022 | AGEs, gezondheidszorg |
A non-invasive risk score including skin autofluorescence predicts diabetes risk in the general population.
Auteurs: Henderikus E Boersma, Melanie M van der Klauw, Andries J Smit, Bruce H R Wolffenbuttel
Affiliations: Departments of Endocrinology & Internal Medicine, University of Groningen, University Medical Center Groningen, HPC AA31, P.O. Box 30001, 9700 RB, Groningen, The Netherlands.
Abstract
Increased skin autofluorescence (SAF) predicts the development of diabetes-related complications and cardiovascular disease. We assessed the performance of a simple model which includes SAF to identify individuals at high risk for undiagnosed and incident type 2 diabetes, in 58,377 participants in the Lifelines Cohort Study without known diabetes. Newly-diagnosed diabetes was defined as fasting blood glucose ≥ 7.0 mmol/l and/or HbA1c ≥ 6.5% (≥ 48 mmol/mol) or self-reported diabetes at follow-up. We constructed predictive models based on age, body mass index (BMI), SAF, and parental history of diabetes, and compared to results with the concise FINDRISC model. At 2nd visit to Lifelines, 1113 (1.9%) participants were identified with undiagnosed diabetes and 1033 (1.8%) participants developed diabetes during follow-up. A model comprising age, BMI and SAF yielded an AUC of 0.783 and was non-inferior to the concise FINDRISC model, which had an AUC of 0.797 to predict new diabetes. At a score of 5.8, sensitivity was 78% and specificity of 66%. Model 2 which also incorporated parental diabetes history, had an AUC of 0.792, and a sensitivity of 74% and specificity of 70% at a score of 6.5. Net reclassification index (NRI) did not improve significantly (NRI 1.43% (- 0.50-3.37 p = 0.15). The combination of an easy to perform SAF measurement with age and BMI is a good alternative screening tool suitable for medical and non-medical settings. Parental history of diabetes did not significantly improve model performance in this homogeneous cohort.
Open access link: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9758123/
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