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      Visit-to-visit variability of glycemia and vascular complications: the Hoorn Diabetes Care System cohort

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          Abstract

          Background

          Glycemic variation has been suggested to be a risk factor for diabetes-related complications. Previous studies did not address confounding of diabetes duration, number of visits and length of follow-up. Here, we characterize glycemic variability over time and whether its relation to diabetes-related complications and mortality is independent from diabetes- and follow-up duration.

          Materials and methods

          Individuals with type 2 diabetes (n = 6770) from the Hoorn Diabetes Care System cohort were included in this study. The coefficient of variation (CV) was calculated over 5-year sliding intervals. People divided in quintiles based on their CV. Cox proportional hazard models were used to investigate the role of glycemic CV as risk factor in diabetes-related complications and mortality.

          Results

          The coefficient of variation of glucose (FG-CV) increased with time, in contrast to HbA1c (HbA1c-CV). People with a high FG-CV were those with an early age of diabetes onset (Δ Q5–Q1 = − 2.39 years), a higher BMI (Δ Q5–Q1 = + 0.92 kg/m 2), an unfavorable lipid profile, i.e. lower levels of HDL-C (Δ Q5–Q1 = − 0.06 mmol/mol) and higher triglycerides (Δ Q5–Q1 =+ 1.20 mmol/mol). People with the highest FG-CV in the first 5-year interval showed an increased risk of insulin initiation, retinopathy, macrovascular complications and mortality independent of mean glycemia, classical risk factors and medication use. For HbA1c, the associations were weaker and less consistent.

          Conclusions

          Individuals with a higher FG-CV have an unfavorable metabolic profile and have an increased risk of developing micro- and macrovascular complications and mortality. The association of HbA1c-CV with metabolic outcomes and complications was less consistent in comparison to FG-CV.

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          Most cited references26

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          Chronic kidney disease.

          This issue provides a clinical overview of chronic kidney disease, focusing on prevention, diagnosis, treatment, and patient information. The content of In the Clinic is drawn from the clinical information and education resources of the American College of Physicians (ACP), including ACP Smart Medicine and MKSAP (Medical Knowledge and Self-Assessment Program). Annals of Internal Medicine editors develop In the Clinic from these primary sources in collaboration with the ACP's Medical Education and Publishing divisions and with the assistance of science writers and physician writers. Editorial consultants from ACP Smart Medicine and MKSAP provide expert review of the content. Readers who are interested in these primary resources for more detail can consult http://smartmedicine.acponline.org, http://mksap.acponline.org, and other resources referenced in each issue of In the Clinic.
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            Visit-to-visit variability of fasting plasma glucose as predictor of ischemic stroke: competing risk analysis in a national cohort of Taiwan Diabetes Study

            Background Glycemic variation as an independent predictor of ischemic stroke in type 2 diabetic patients remains unclear. This study examined visit-to-visit variations in fasting plasma glucose (FPG), as represented by the coefficient of variation (CV), for predicting ischemic stroke independently, regardless of glycated hemoglobin (HbA1c) and other conventional risk factors in such patients. Methods Type 2 diabetic patients enrolled in the National Diabetes Care Management Program, ≥30 years old and free of ischemic stroke (n = 28,354) in 2002 to 2004 were included, and related factors were analyzed with extended Cox proportional hazards regression models of competing risk data on stroke incidence. Results After an average 7.5 years of follow-up, there were 2,250 incident cases of ischemic stroke, giving a crude incidence rate of 10.56/1,000 person-years (11.64 for men, 9.63 for women). After multivariate adjustment, hazard ratios for the second, third and fourth versus first FPG-CV quartile were 1.11 (0.98, 1.25), 1.22 (1.08, 1.38) and 1.27 (1.12, 1.43), respectively, without considering HbA1c, and 1.09 (0.96, 1.23), 1.16 (1.03, 1.31) and 1.17 (1.03, 1.32), respectively, after considering HbA1c. Conclusions Besides HbA1c, FPG-CV was a potent predictor of ischemic stroke in type 2 diabetic patients, suggesting that different therapeutic strategies now in use be rated for their potential to (1) minimize glucose fluctuations and (2) reduce HbA1c level in type 2 diabetic patients to prevent ischemic stroke.
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              Hemoglobin A1c variability as an independent correlate of cardiovascular disease in patients with type 2 diabetes: a cross-sectional analysis of the Renal Insufficiency and Cardiovascular Events (RIACE) Italian Multicenter Study

              Background Previous reports have clearly indicated a significant relationship between hemoglobin (Hb) A1c change from one visit to the next and microvascular complications, especially nephropathy (albuminuria and albuminuric chronic kidney disease, CKD). In contrast, data on macrovascular disease are less clear. This study was aimed at examining the association of HbA1c variability with cardiovascular disease (CVD) in the large cohort of subjects with type 2 diabetes from the Renal Insufficiency and Cardiovascular Events (RIACE) Italian Multicenter Study. Methods Serial (3–5) HbA1c values obtained during the 2-year period preceding recruitment, including that obtained at the enrolment, were available from 8,290 subjects from 9 centers (out of 15,773 patients from 19 centers). Average HbA1c and HbA1c variability were calculated as the intra-individual mean (HbA1c-MEAN) and standard deviation (HbA1c-SD), respectively, of 4.52±0.76 values. Prevalent CVD, total and by vascular bed, was assessed from medical history by recording previous documented major acute events. Diabetic retinopathy (DR) was assessed by dilated fundoscopy. CKD was defined based on albuminuria, as measured by immunonephelometry or immunoturbidimetry, and estimated glomerular filtration rate, as calculated from serum creatinine. Results HbA1c-MEAN, but not HbA1c-SD, was significantly higher (P<0.0001) in subjects with history of any CVD (n. 2,133, 25.7%) than in those without CVD (n. 6,157, 74.3%). Median and interquartile range were 7.78 (7.04-8.56) and 7.49 (6.81-8.31), respectively, for HbA1c-MEAN, and 0.47 (0.29-0.75) and 0.46 (0.28-0.73), respectively, for HbA1c-SD. Logistic regression analyses showed that HbA1c-MEAN, but not HbA1c-SD (and independent of it), was a significant correlate of any CVD. Similar findings were observed in subjects with versus those without any coronary or cerebrovascular event or myocardial infarction. Conversely, none of these measures were associated with stroke, whereas both correlated with any lower limb vascular event and HbA1c-SD alone with ulceration/gangrene. All these associations were independent of known CVD risk factors and microvascular complications (DR and CKD). Conclusions In patients with type 2 diabetes, HbA1c variability has not a major impact on macrovascular complications, at variance with average HbA1c, an opposite finding as compared with microvascular disease, and particularly nephropathy. Trial registration ClinicalTrials.Gov NCT00715481
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                Author and article information

                Contributors
                r.slieker@amsterdamumc.nl
                Journal
                Cardiovasc Diabetol
                Cardiovasc Diabetol
                Cardiovascular Diabetology
                BioMed Central (London )
                1475-2840
                12 December 2019
                12 December 2019
                2019
                : 18
                : 170
                Affiliations
                [1 ]Department of Epidemiology and Biostatistics, Amsterdam Public Health Institute, Amsterdam UMC, Location VUMC, De Boelelaan 1089a, 1081 HV Amsterdam, The Netherlands
                [2 ]ISNI 0000000089452978, GRID grid.10419.3d, Department of Cell and Chemical Biology, , Leiden University Medical Center, ; Leiden, The Netherlands
                [3 ]Department of General Practice and Elderly Care Medicine, Amsterdam Public Health Institute, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
                [4 ]ISNI 0000000089452978, GRID grid.10419.3d, Molecular Epidemiology Section, Department of Biomedical Data Sciences, , Leiden University Medical Center, ; Leiden, The Netherlands
                [5 ]ISNI 0000000090126352, GRID grid.7692.a, Julius Center for Health Sciences and Primary Care, , University Medical Center Utrecht, ; Utrecht, The Netherlands
                Author information
                http://orcid.org/0000-0003-0961-9152
                Article
                975
                10.1186/s12933-019-0975-1
                6909524
                31830993
                40037f25-684c-4834-a37b-46d66351ff22
                © The Author(s) 2019

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 19 October 2019
                : 3 December 2019
                Funding
                Funded by: Innovative Medicines Initiative ()
                Award ID: 115881
                Award Recipient :
                Funded by: Dutch Diabetes Research Foundation
                Award ID: 2014.00.1753
                Award Recipient :
                Categories
                Original Investigation
                Custom metadata
                © The Author(s) 2019

                Endocrinology & Diabetes
                complications,glycemia,type 2 diabetes,variability
                Endocrinology & Diabetes
                complications, glycemia, type 2 diabetes, variability

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