Impact of coronavirus disease 2019 in seasonal variation of hemoglobin A1c in adults with type 1 diabetes and the effect of the mode of treatment: a single-center retrospective study for 2019 and 2021 and analysis by the mode of treatment.

The study was aimed to investigate the seasonal variation of hemoglobin A1c (HbA1c) in adults with type 1 diabetes (T1D) and the impact of coronavirus disease 2019 (COVID-19) by comparing 2019 and 2021 data and differences in treatment modes. This was a single-center retrospective observational study including 52 adult patients with T1D who regularly visited hospital in 2019 and 2021. Twenty-five patients used multiple daily injections (MDI)/self-measurement of blood glucose (SMBG), 16 used MDI/intermittently scanned continuous glucose monitoring (isCGM), 9 used sensor-augmented pump (SAP), and 2 used continuous subcutaneous insulin infusion (CSII)/isCGM. The mean HbA1c level was calculated for each month. The correlation between monthly means of temperature and HbA1c was investigated. Similar analyses were performed for the MDI/SMBG, MDI/isCGM, and SAP + CSII/isCGM groups. HbA1c levels in 2019 decreased in summer and increased in winter and showed a significant negative correlation with temperature (r = -0.652, p = 0.022). However, HbA1c in 2021 showed no seasonal variation and no correlation with temperature (r = -0.134, p = 0.678) and tended to decline after the three emergency declarations. HbA1c in the MDI/SMBG group showed the same trend as the whole group in 2019 and 2021. However, the effect of seasonal variation in HbA1c was lower in the MDI/isCGM group and the lowest in the SAP + CSII/isCGM group in 2019. The impact of emergency declaration on HbA1c level was small for the MDI/isCGM group and smaller for the SAP + CSII/isCGM group in 2021. The COVID-19 pandemic has affected the seasonal variation of HbA1c levels in T1D; the variation differed according to the treatment mode.

Difference of seasonal variation between glycated albumin and glycated haemoglobin.

Background Glycated albumin reflects 2-3-week glycaemic controls, and in addition to glycated haemoglobin, it has been used as a glycaemic control indicator. We presumed that glycated albumin also has seasonal variations and is related to temperature, similar to glycated haemoglobin. Methods The subjects were diabetic outpatients from April 2007 to March 2013. This resulted in the enrolment of 2246 subjects and the collection of a total of 53,968 measurements. Mean glycated haemoglobin, glycated albumin, and plasma glucose were calculated for each month over six years. The associations of the measures with each other and the average temperature for each month in Tokyo were assessed using Spearman rank correlation coefficients. Results Plasma glucose was highest in January and lowest in May. Glycated haemoglobin was highest in March and lowest in September. Glycated albumin was highest in May and lowest in December. Glycated albumin tended to have a disjunction with plasma glucose in winter. Glycated haemoglobin had seasonal variation, but glycated albumin did not. Plasma glucose and glycated haemoglobin showed significant negative correlations with temperature (rs = -0.359, P < 0.001, rs = -0.449, P < 0.001, respectively), but glycated albumin did not. However, glycated albumin was inter-correlated with plasma glucose (rs = 0.396, P < 0.001) and glycated haemoglobin (rs = 0.685, P < 0.001), and glycated haemoglobin was inter-correlated with plasma glucose (rs = 0.465, P < 0.001). Conclusion Glycated albumin and glycated haemoglobin showed different seasonal variations from each other over the six-year study period. Thus, further studies to identify factors that contribute to glycated albumin are needed.

A Reduction of HbA1c after 3 Months Predicts 2-year Responsiveness to Sitagliptin Treatment.

OBJECTIVE: This retrospective study evaluated the long-term efficacy of sitagliptin and the factors contributing to its glucose-lowering effect. METHODS: Six hundred and sixteen dipeptidyl peptidase-4 inhibitor-naïve outpatients with type 2 diabetes who began sitagliptin treatment between December 1, 2009 and December 31, 2011 were included in this study. The inclusion criteria were that the patient had regularly visited our hospital for a period of ≥700 days from the initiation of sitagliptin treatment and the measurement of hemoglobin A1c (HbA1c) had been performed at 0, 3, 6, 12, 18, and 24 months after the initiation of treatment. From the population of 616 patients, 447 and 169 had received sitagliptin for ≥700 and <700 days, respectively. The primary endpoint was ΔHbA1c at 24 months. The factors associated with the hypoglycemic effect of sitagliptin were also investigated. RESULTS: Sitagliptin treatment significantly decreased the level of HbA1c, and the hypoglycemic effect was sustained for at least 2 years. The baseline HbA1c level, duration of diabetes, Δbody weight value, and ΔHbA1c value at 3 months were independently associated with the hypoglycemic effect of sitagliptin. CONCLUSION: Sitagliptin has a long-term hypoglycemic effect in type 2 diabetes patients. A patient's ΔHbA1c at 3 months may be a predictor of their ΔHbA1c at 24 months.

C-peptide immunoreactivity index is associated with improvement of HbA1c: 2-Year follow-up of sitagliptin use in patients with type 2 diabetes.

AIMS: This retrospective study aimed to determine the hypoglycaemic effect of 2 years of sitagliptin administration in terms of changes in HbA1c and C-peptide immunoreactivity (CPR) index (plasma CPR [ng/mL]/glucose [mg/dL]×100). METHODS: The inclusion criteria for DPP-4 inhibitor-naive outpatients with type 2 diabetes (n=285) were: continuation of sitagliptin for ≥700 days from initial administration and measurement of HbA1c, serum CPR, and plasma glucose levels at 0, 3, 6, 12, 18, and 24 months after sitagliptin initiation. Logistic regression analyses determined the factors contributing to the response to sitagliptin, based on responder (ΔHbA1c ≤-0.4% [≤-4 mmol/mol]) and non-responder (ΔHbA1c >-0.4% [>-4 mmol/mol]) groups. RESULTS: The HbA1c level decreased and CPR index increased from baseline to 3, 6, 12, 18, and 24 months after the start of sitagliptin administration (HbA1c: 7.4 ± 0.8% [57 ± 9 mmol/mol], 7.3 ± 0.9% [57 ± 9 mmol/mol], 7.4 ± 0.9% [58 ± 10 mmol/mol], 7.1 ± 0.8% [55 ± 9 mmol/mol], and 7.3 ± 0.9% [57 ± 10 mmol/mol], respectively, all P<0.001 vs. baseline [8.0 ± 1.0%, 64 ± 11 mmol/mol] and CPR index: 1.69 ± 0.96, 1.71 ± 1.10, 1.62 ± 0.96, 1.64 ± 0.92, and 1.66 ± 0.96, respectively, all P<0.05 vs. baseline [1.47 ± 0.81]). Higher baseline HbA1c level, shorter diabetes duration, and greater CPR index increase after sitagliptin administration were associated with the response to sitagliptin. CONCLUSIONS: Our results suggest that sitagliptin improves glycaemic control via an improved intrinsic insulin response.

Past Obesity as well as Present Body Weight Status Is a Risk Factor for Diabetic Nephropathy.

Aims. We analyzed the prevalence of nephropathy according to past body weight status in Japanese subjects with type 2 diabetes because the influence of past obesity on diabetic complications is not certain. Methods. We examined the prevalence of nephropathy in 2927 subjects with type 2 diabetes mellitus according to current BMI and maximum BMI in the past. We defined "current obesity" as BMI on hospitalization of 25 or more, "previous obesity" as BMI on hospitalization of less than 25 and self-reported maximum BMI in the past of 25 or more, and "continuously lean" as maximum BMI of less than 25. Results. The prevalence of nephropathy was significantly higher in subjects with current obesity (40.6%) or previous obesity (35.6%) than in those who were continuously lean (24.3%) (P < 0.017). In logistic regression analysis, previous obesity, as well as current obesity, was a significant risk factor for nephropathy, independent of sex, age, disease duration, hypertension, dyslipidemia, HbA1c, and diabetic retinopathy. Conclusions. Obesity in the past, as well as the present body weight status, was a risk factor for diabetic nephropathy.