Consensus meeting on reporting glycated haemoglobin and estimated average glucose in the UK: time for 'Kilpatrick's Kludge'?

2009 ◽  
Vol 46 (1) ◽  
pp. 84-85 ◽  
Author(s):  
E. S Kilpatrick
Keyword(s):  
Glycated Haemoglobin ◽  
Consensus Meeting ◽  
The Uk ◽  
Average Glucose

scholarly journals Digitally enabled flash glucose monitoring for inpatients with COVID-19: Feasibility and pilot implementation in a teaching NHS Hospital in the UK

2022 ◽  
Vol 8 ◽  
pp. 205520762110593
Author(s):  
Tim Robbins ◽  
Adam Hopper ◽  
Jack Brophy ◽  
Elle Pearson ◽  
Risheka Suthantirakumar ◽  
...  
Keyword(s):  
Length Of Stay ◽  
Glucose Monitoring ◽  
Glycated Haemoglobin ◽  
University Hospitals ◽  
P Values ◽  
Flash Glucose Monitoring ◽  
Time In Range ◽  
The Uk ◽  
Monitoring Devices ◽  
Average Glucose

Background COVID-19 placed significant challenges on healthcare systems. People with diabetes are at high risk of severe COVID-19 with poor outcomes. We describe the first reported use of inpatient digital flash glucose monitoring devices in a UK NHS hospital to support management of people with diabetes hospitalized for COVID-19. Methods Inpatients at University Hospitals Coventry & Warwickshire (UHCW) NHS Trust with COVID-19 and diabetes were considered for digitally enabled flash glucose monitoring during their hospitalization. Glucose monitoring data were analysed, and potential associations were explored between relevant parameters, including time in hypoglycaemia, hyperglycaemia, and in range, glycated haemoglobin (HbA1c), average glucose, body mass index (BMI), and length of stay. Results During this pilot, digital flash glucose monitoring devices were offered to 25 inpatients, of whom 20 (type 2/type 1: 19/1; mean age: 70.6 years; mean HbA1c: 68.2 mmol/mol; mean BMI: 28.2 kg/m2) accepted and used these (80% uptake). In total, over 2788 h of flash glucose monitoring were recorded for these inpatients with COVID-19 and diabetes. Length of stay was not associated with any of the studied variables (all p-values >0.05). Percentage of time in hyperglycaemia exhibited significant associations with both percentage of time in hypoglycaemia and percentage of time in range, as well as with HbA1c (all p-values <0.05). The average glucose was significantly associated with percentage of time in hypoglycaemia, percentage of time in range, and HbA1c (all p-values <0.05). Discussion We report the first pilot inpatient use of digital flash glucose monitors in an NHS hospital to support care of inpatients with diabetes and COVID-19. Overall, there are strong arguments for the inpatient use of these devices in the COVID-19 setting, and the findings of this pilot demonstrate feasibility of this digitally enabled approach and support wider use for inpatients with diabetes and COVID-19.

scholarly journals Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 991
Author(s):  
Erik Widen ◽  
Timothy G. Raben ◽  
Louis Lello ◽  
Stephen D. H. Hsu
Keyword(s):  
Disease Risk ◽  
Smoking Status ◽  
Glycated Haemoglobin ◽  
European Ancestry ◽  
Risk Scores ◽  
Common Disease ◽  
Atherosclerotic Cardiovascular Disease ◽  
Uk Biobank ◽  
Lipoprotein A ◽  
The Uk

We use UK Biobank data to train predictors for 65 blood and urine markers such as HDL, LDL, lipoprotein A, glycated haemoglobin, etc. from SNP genotype. For example, our Polygenic Score (PGS) predictor correlates ∼0.76 with lipoprotein A level, which is highly heritable and an independent risk factor for heart disease. This may be the most accurate genomic prediction of a quantitative trait that has yet been produced (specifically, for European ancestry groups). We also train predictors of common disease risk using blood and urine biomarkers alone (no DNA information); we call these predictors biomarker risk scores, BMRS. Individuals who are at high risk (e.g., odds ratio of >5× population average) can be identified for conditions such as coronary artery disease (AUC∼0.75), diabetes (AUC∼0.95), hypertension, liver and kidney problems, and cancer using biomarkers alone. Our atherosclerotic cardiovascular disease (ASCVD) predictor uses ∼10 biomarkers and performs in UKB evaluation as well as or better than the American College of Cardiology ASCVD Risk Estimator, which uses quite different inputs (age, diagnostic history, BMI, smoking status, statin usage, etc.). We compare polygenic risk scores (risk conditional on genotype: PRS) for common diseases to the risk predictors which result from the concatenation of learned functions BMRS and PGS, i.e., applying the BMRS predictors to the PGS output.

scholarly journals Diabetes, glycated haemoglobin and the risk of myocardial infarction in women and men: a prospective cohort study of the UK Biobank

2020 ◽  
Author(s):  
Marit de Jong ◽  
Mark Woodward ◽  
Sanne A.E Peters
Keyword(s):  
Myocardial Infarction ◽  
Sex Differences ◽  
Glycated Haemoglobin ◽  
Incidence Rates ◽  
Undiagnosed Diabetes ◽  
Uk Biobank ◽  
Diabetes Status ◽  
Increased Risk ◽  
The Uk ◽  
Diagnosed Diabetes

<b>Objective:</b> Diabetes has shown to be a stronger risk factor for myocardial infarction (MI) in women than men. Whether sex differences exist across the glycaemic spectrum is unknown. We investigated sex differences in the associations of diabetes status and glycated haemoglobin (HbA1c) with the risk of MI. <br> <b>Research Design and Methods:</b> Data were used from 471,399 (56% women) individuals without cardiovascular disease (CVD) included in the UK Biobank. Sex-specific incidence rates were calculated by diabetes status and across levels of HbA1c, using Poisson regression. Cox proportional hazards analyses estimated sex-specific hazard ratios (HR) and women-to-men ratios by diabetes status and HbA1c for MI during a mean follow-up of 9 years. <br> <b>Results:</b> Women had lower incidence rates of MI than men, regardless of diabetes status or HbA1c level. Compared with individuals without diabetes, prediabetes, undiagnosed diabetes, and previously diagnosed diabetes were associated with increased risk of MI in both sexes. Previously diagnosed diabetes was more strongly associated with MI in women (HR 2∙33 [95%CI 1∙96;2∙78]) than men (1∙81 [1∙63;2∙02]), with a women-to-men ratio of HRs of 1∙29 (1∙05;1∙58). Each 1% higher HbA1c, independent of diabetes status, was associated with an 18% greater risk of MI in both women and men.<br> <b>Conclusions:</b> Although the incidence of MI was higher in men than women, the presence of diabetes is associated with a greater excess relative risk of MI in women. However, each 1% higher HbA1c was associated with an 18% greater risk of MI in both women and men.<br> <br>

scholarly journals Diabetes, glycated haemoglobin and the risk of myocardial infarction in women and men: a prospective cohort study of the UK Biobank

2020 ◽  
Author(s):  
Marit de Jong ◽  
Mark Woodward ◽  
Sanne A.E Peters
Keyword(s):  
Myocardial Infarction ◽  
Sex Differences ◽  
Glycated Haemoglobin ◽  
Incidence Rates ◽  
Undiagnosed Diabetes ◽  
Uk Biobank ◽  
Diabetes Status ◽  
Increased Risk ◽  
The Uk ◽  
Diagnosed Diabetes

<b>Objective:</b> Diabetes has shown to be a stronger risk factor for myocardial infarction (MI) in women than men. Whether sex differences exist across the glycaemic spectrum is unknown. We investigated sex differences in the associations of diabetes status and glycated haemoglobin (HbA1c) with the risk of MI. <br> <b>Research Design and Methods:</b> Data were used from 471,399 (56% women) individuals without cardiovascular disease (CVD) included in the UK Biobank. Sex-specific incidence rates were calculated by diabetes status and across levels of HbA1c, using Poisson regression. Cox proportional hazards analyses estimated sex-specific hazard ratios (HR) and women-to-men ratios by diabetes status and HbA1c for MI during a mean follow-up of 9 years. <br> <b>Results:</b> Women had lower incidence rates of MI than men, regardless of diabetes status or HbA1c level. Compared with individuals without diabetes, prediabetes, undiagnosed diabetes, and previously diagnosed diabetes were associated with increased risk of MI in both sexes. Previously diagnosed diabetes was more strongly associated with MI in women (HR 2∙33 [95%CI 1∙96;2∙78]) than men (1∙81 [1∙63;2∙02]), with a women-to-men ratio of HRs of 1∙29 (1∙05;1∙58). Each 1% higher HbA1c, independent of diabetes status, was associated with an 18% greater risk of MI in both women and men.<br> <b>Conclusions:</b> Although the incidence of MI was higher in men than women, the presence of diabetes is associated with a greater excess relative risk of MI in women. However, each 1% higher HbA1c was associated with an 18% greater risk of MI in both women and men.<br> <br>

scholarly journals Economic insecurity during the Great Recession and metabolic, inflammatory and liver function biomarkers: analysis of the UK Household Longitudinal Study

2017 ◽  
Vol 71 (10) ◽  
pp. 1005-1013 ◽  
Author(s):  
Claire L Niedzwiedz ◽  
Srinivasa Vittal Katikireddi ◽  
Aaron Reeves ◽  
Martin McKee ◽  
David Stuckler
Keyword(s):  
Liver Function ◽  
Density Lipoprotein ◽  
Hdl Cholesterol ◽  
Glycated Haemoglobin ◽  
Financial Strain ◽  
Gamma Glutamyl Transferase ◽  
Economic Insecurity ◽  
Linear Regression Models ◽  
The Uk ◽  
Glutamyl Transferase

BackgroundEconomic insecurity correlates with adverse health outcomes, but the biological pathways involved are not well understood. We examine how changes in economic insecurity relate to metabolic, inflammatory and liver function biomarkers.MethodsBlood analyte data were taken from 6520 individuals (aged 25–59 years) participating in Understanding Society. Economic insecurity was measured using an indicator of subjective financial strain and by asking participants whether they had missed any bill, council tax, rent or mortgage payments in the past year. We investigated longitudinal changes in economic insecurity (remained secure, increase in economic insecurity, decrease in economic insecurity, remained insecure) and the accumulation of economic insecurity. Linear regression models were calculated for nine (logged) biomarker outcomes related to metabolic, inflammatory, liver and kidney function (as falsification tests), adjusting for potential confounders.ResultsCompared with those who remained economically stable, people who experienced consistent economic insecurity (using both measures) had worsened levels of high-density lipoprotein (HDL)-cholesterol, triglycerides, C reactive protein (CRP), fibrinogen and glycated haemoglobin. Increased economic insecurity was associated with adverse levels of HDL-cholesterol (0.955, 95% CI 0.929 to 0.982), triglycerides (1.077, 95% CI 1.018 to 1.139) and CRP (1.114, 95% CI 1.012 to 1.227), using the measure of financial strain. Results for the other measure were generally consistent, apart from the higher levels of gamma-glutamyl transferase observed among those experiencing persistent insecurity (1.200, 95% CI 1.110 to 1.297).ConclusionEconomic insecurity is associated with adverse metabolic and inflammatory biomarkers (particularly HDL-cholesterol, triglycerides and CRP), heightening risk for a range of health conditions.

Burden of child and adolescent obesity on health services in England

2017 ◽  
Vol 103 (3) ◽  
pp. 247-254 ◽  
Author(s):  
Russell M Viner ◽  
Sanjay Kinra ◽  
Dasha Nicholls ◽  
Tim Cole ◽  
Anthony Kessel ◽  
...  
Keyword(s):  
Primary Care ◽  
Childhood Obesity ◽  
Young People ◽  
Secondary Care ◽  
Service Use ◽  
Lifestyle Modification ◽  
Glycated Haemoglobin ◽  
Obesity Management ◽  
Care Assessment ◽  
The Uk

ObjectiveTo assess the numbers of obese children and young people (CYP) eligible for assessment and management at each stage of the childhood obesity pathway in England.DesignPathway modelling study, operationalising the UK National Institute for Health and Care Excellence guidance on childhood obesity management against national survey data.SettingData on CYP aged 2–18 years from the Health Survey for England 2006 to 2013.Main outcome measuresClinical obesity (body mass index (BMI) >98th centile), extreme obesity (BMI ≥99.86th centile); family history of cardiovascular disease or type 2 diabetes; obesity comorbidities defined as primary care detectable (hypertension, orthopaedic or mobility problems, bullying or psychological distress) or secondary care detectable (dyslipidaemia, hyperinsulinaemia, high glycated haemoglobin, abnormal liver function).Results11.2% (1.22 million) of CYP in England were eligible for primary care assessment and for community lifestyle modification. 2.6% (n=283 500) CYP were estimated to be likely to attend primary care. 5.1% (n=556 000) were eligible for secondary care referral. Among those aged 13–18 years, 8.2% (n=309 000) were eligible for antiobesity drug therapy and 2.4% (90 500) of English CYP were eligible for bariatric surgery. CYP from the most deprived quintile were 1.5-fold to 3-fold more likely to be eligible for obesity management.ConclusionsThere is a mismatch between population burden and available data on service use for obesity in CYP in England, particularly among deprived young people. There is a need for consistent evidence-based commissioning of services across the childhood obesity pathway based on population burden.

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