Kontrola glikemii i jej zmienność głównymi czynnikami ryzyka mikroalbuminurii u dzieci chorych na cukrzycę typu 1

Nazim, Joanna; Fendler, Wojciech; Starzyk, Jerzy

doi:10.5603/ep.2014.0012

Cited by 18 publications

(7 citation statements)

References 35 publications

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“…Long-term variability in HbA 1c has been proposed as an important risk factor related to mortality [3][4][5][6], cardiovascular disease (CVD) [7][8][9], nephropathy [10][11][12] and other complications [13][14][15][16][17] independent of HbA 1c levels. Recently, there has been considerable interest in the emerging association between glycaemic variability and decline in cognitive function [18][19][20][21][22].…”

Section: Introductionmentioning

confidence: 99%

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

Zhu

et al. 2019

Diabetologia

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Aims/hypothesis The aim of this study was to investigate the association between visit-to-visit variability in HbA 1c and cognitive function decline in the elderly population. Methods We performed a pooled analysis of two prospective population-based cohorts (the Health Retirement Study [HRS] and the English Longitudinal Study of Ageing [ELSA]). Cognitive function, including memory and executive function, were assessed at baseline and every 2 years, while HbA 1c levels were assessed at baseline and every 4 years. Visit-to-visit variability (VVV) in HbA 1c was calculated using the CV, SD and variation independent of the mean (VIM) during the follow-up period. Linear mixed models were used to evaluate the association between HbA 1c variability and cognitive function decline with adjustment for demographics, mean HbA 1c , education, smoking, alcohol consumption, BMI, baseline hypertension, baseline diabetes status and HDL-cholesterol. Results The study enrolled 6237 participants (58.23% women, mean age 63.38 ± 8.62 years) with at least three measurements of HbA 1c. The median follow-up duration was 10.56 ± 1.86 years. In the overall sample, compared with the lowest quartile of HbA 1c variability, participants in the highest quartile of HbA 1c variability had a significantly worse memory decline rate (−0.094 SD/year, 95% CI −0.185, −0.003) and executive function decline rate (−0.083 SD/year, 95% CI −0.125, −0.041), irrespective of mean HbA 1c values over time. Among individuals without diabetes, each 1-SD increment in HbA 1c CV was associated with a significantly higher rate of memory z score decline (−0.029, 95% CI −0.052, −0.005) and executive function z score decline (−0.049, 95% CI −0.079, −0.018) in the fully adjusted model. Conclusions/interpretation We observed a significant association between long-term HbA 1c variability and cognitive decline among the non-diabetic population in this study. The effect of maintaining steady glucose control on the rate of cognitive decline merits further investigation.

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Section: Introductionmentioning

confidence: 99%

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

Zhu

et al. 2019

Diabetologia

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“…Studies have also demonstrated that MAU is also a powerful predictor of CVD in both diabetic and non-diabetic subjects [ 6 , 7 ]. MAU is usually absent at diagnosis but may develop in children with type 1 diabetes and poorer metabolic control [ 8 ]. On the other hand, intensive control of blood glucose level can prevent the onset and progression of MAU [ 9 ], and the incidence of decreased estimated glomerular filtration rate (eGFR) was rare in diabetic patients without preceding MAU [ 10 ].…”

Section: Introductionmentioning

confidence: 99%

All Components of Metabolic Syndrome Are Associated with Microalbuminuria in a Chinese Population

et al. 2016

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Background and AimAlbuminuria is a well-known predictor of poor renal and cardiovascular outcomes and associated with increased risk of all-cause mortality. The study aimed to evaluate the associations between metabolic characteristics and the presence of albuminuria.MethodsThis cross-sectional study included 18,384 adult Chinese who participated in health examinations during 2013–2014. Differences in clinical characteristics were compared for microalbuminuria (MAU) and albuminuria, and between genders. Potential risk factors associated with the risk of developing MAU and albuminuria were analyzed using univariate logistic regression. Multiple logistic regression was applied to further identify the independent associations between different levels of risk factors and the presence of MAU and albuminuria. The area under the ROC curve (AUC) was used to determine the discriminatory ability of metabolic risk factors in detecting albuminuria.ResultsThere were significant gender differences in clinical characteristics according to albuminuria status. Risk for the presence of albuminuria was significantly associated with age, male gender, waist circumference (WC), waist-to-height ratio (WHtR), hypertension, fasting plasma glucose (FPG), and triglycerides to high-density lipoprotein cholesterol ratio (TG/HDL-C) in univariate logistic regression. Multiple logistic regression analysis indicated that the factors significantly associated with the presence of MAU were WC > 90cm, WHtR at 0.6–0.7, hypertension, FPG > 6.1 mmole/L, and TG/HDL-C ratio > 1.6. The optimal cutoffs for risk factors of metabolic syndrome (MetS) to predict albuminuria in males and females were: WC, 90.8 vs. 80.0 cm; WHtR, 0.53 vs. 0.52; MAP, 97.9 vs. 91.9 mmHg; FPG, 5.40 vs. 5.28 mmole/L; and TG/HDL-C, 1.13 vs. 1.08.ConclusionMetS and all its components were associated with the presence of MAU in a health check-up population in China. Gender specific and optimal cutoffs for MetS components associated with the presence of MAU were determined.

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“…If we compare our results to other studies on HbA 1c variability, there have been three that have studied only DR development [ 13 , 15 , 16 ], three that have studied only nephropathy [ 11 , 12 , 14 ], and one that has studied both forms of microangiopathy [ 10 ]. The most important study was by Herman et al [ 15 ], a retrospective study focusing on the CV-HbA 1c of over 35,891 T1DM patients.…”

Section: Discussionmentioning

confidence: 97%

“…The first study is by Marcoveccchio et al [ 12 ], who found that 438 patients from a sample of 1232 patients with DM1 had a positive relationship between SD-HbA 1c and MA with HR 1.04, and also a positive relationship between SD-HbA 1c and MA with HR 1.31. The second study was by Nazim et al [ 14 ], a cross-sectional study that also found a positive relationship between MA and SD-HbA 1c (HR 1.04), and a third study by Waden et al [ 11 ], a prospective 5.7-year follow-up of 2107 T1DM patients again found a positive relationship between SD-HbA 1c and a progression in renal status (HR 1.92).…”

Section: Discussionmentioning

confidence: 99%

“…Initial studies attempted to evaluate the intra-day and inter-day changes in glycaemia, but with no success [ 7 , 8 , 9 ]. Since then, studies of long-term changes in glycaemia, measured by changes in HbA 1c , have been successful [ 10 , 11 , 12 , 13 , 14 , 15 , 16 ]. Long term changes in glycaemia can currently be calculated by measuring the mean and standard deviation of HbA 1c (SD-HbA 1c ), the coefficient of variation of HbA 1c (CV-HbA 1c ), the average real variability (ARV-HbA 1c ) and the variability independent of the mean (VIM-HbA 1c ) [ 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

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The Effect of HbA1c Variability as a Risk Measure for Microangiopathy in Type 1 Diabetes Mellitus

et al. 2021

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Background: To measure the relationship between variability in HbA1c and microalbuminuria (MA) and diabetic retinopathy (DR) in the long term. Methods: A prospective case-series study, was conducted on 366 Type 1 Diabetes Mellitus patients with normoalbuminuria and without diabetic retinopathy at inclusion. The cohort was followed for a period of 12 years. The Cox survival analysis was used for the multivariate statistical study. The effect of variability in microangiopathy (retinopathy and nephropathy) was evaluated by calculating the standard deviation of HbA1c (SD-HbA1c), the coefficient of variation of HbA1c (CV-HbA1c), average real variability (ARV-HbA1c) and variability irrespective of the mean (VIM-HbA1c) adjusted for the other known variables. Results: A total of 106 patients developed diabetic retinopathy (29%) and 73 microalbuminuria (19.9%). Overt diabetic nephropathy, by our definition, affected only five patients (1.36%). Statistical results show that the current age, mean HbA1c, SD-HbA1c and ARV-HbA1c are significant in the development of diabetic retinopathy. Microalbuminuria was significant for current age, mean HbA1c, CV-HbA1c and ARV-HbA1c. Conclusions: By measuring the variability in HbA1c, we can use SD-HbA1c and ARV-HbA1c as possible targets for judging which patients are at risk of developing DR and MA, and CV-HbA1c as the target for severe DR.

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Kontrola glikemii i jej zmienność głównymi czynnikami ryzyka mikroalbuminurii u dzieci chorych na cukrzycę typu 1

Cited by 18 publications

References 35 publications

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts

All Components of Metabolic Syndrome Are Associated with Microalbuminuria in a Chinese Population

The Effect of HbA1c Variability as a Risk Measure for Microangiopathy in Type 1 Diabetes Mellitus

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