176-LB: Long-Term Glycemic Variability in Diabetic Patients According to Their Glycemic Control in Follow-Up

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 176-LB
Author(s):  
HECTOR GARCIA-ALCALA
Keyword(s):  
Glycemic Control ◽  
Glycemic Variability ◽  
Diabetic Patients

scholarly journals Long-term glycemic variability and risk of stroke in patients with diabetes: a meta-analysis

2022 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiaoli Ren ◽  
Zhiyun Wang ◽  
Congfang Guo
Keyword(s):  
Standard Deviation ◽  
Coefficient Of Variation ◽  
Meta Analysis ◽  
Glycemic Variability ◽  
Diabetic Patients ◽  
Increased Risk ◽  
Follow Up Studies ◽  
Patients With Diabetes

Abstract Objectives Long-term glycemic variability has been related to increased risk of vascular complication in patients with diabetes. However, the association between parameters of long-term glycemic variability and risk of stroke remains not fully determined. We performed a meta-analysis to systematically evaluate the above association. Methods Medline, Embase, and Web of Science databases were searched for longitudinal follow-up studies comparing the incidence of stroke in diabetic patients with higher or lower long-term glycemic variability. A random-effect model incorporating the potential heterogeneity among the included studies were used to pool the results. Results Seven follow-up studies with 725,784 diabetic patients were included, and 98% of them were with type 2 diabetes mellitus (T2DM). The mean follow-up duration was 7.7 years. Pooled results showed that compared to those with lowest category of glycemic variability, diabetic patients with the highest patients had significantly increased risk of stroke, as evidenced by glycemic variability analyzed by fasting plasma glucose coefficient of variation (FPG-CV: risk ratio [RR] = 1.24, 95% confidence interval [CI] 1.11 to 1.39, P < 0.001; I2 = 53%), standard deviation of FPG (FPG-SD: RR = 1.16, 95% CI 1.02 to 1.31, P = 0.02; I2 = 74%), HbA1c coefficient of variation (HbA1c-CV: RR = 1.88, 95% CI 1.61 to 2.19 P < 0.001; I2 = 0%), and standard deviation of HbA1c (HbA1c-SD: RR = 1.73, 95% CI 1.49 to 2.00, P < 0.001; I2 = 0%). Conclusions Long-term glycemic variability is associated with higher risk of stroke in T2DM patients.

scholarly journals Patterns and Predictors of Long-Term Glycemic Control in Patients with Type 2 Diabetes

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Mohsen Janghorbani ◽  
Masoud Amini
Keyword(s):  
Type 2 Diabetes ◽  
Glycemic Control ◽  
Clinic Visit ◽  
Stepwise Multiple Regression ◽  
Diabetic Patients ◽  
Initial Visit ◽  
The Mean

Aims/Introduction. To describe patterns of long-term glycemic control among patients with type 2 diabetes in Isfahan, Iran and identify factors associated with glycemic control. Methods. During the mean (standard deviation (SD)) follow-up period of 8.4 (4.2) (range 1–18) years, 4,582 patients with type 2 diabetes have been examined to determine glycemic changes. Their glycated hemoglobin (GHb) at the last clinic visit was compared with the initial visit data. The mean (SD) age of participants was 49.3 (9.6) years with a mean (SD) duration of diabetes of 5.0 (5.1) years at initial registration. Results. Mean (SD) GHb was 8.7% (2.3) at baseline and 7.9% (1.9) at the study end and decreased by mean of 0.8% (95% confidence interval (CI) 0.74, 0.87; P < 0.001) and varied by the severity of baseline GHb. 74.6% at the initial visit versus 64.4% at the last clinic visit had GHb values above the target level of 7.0%. Using a stepwise multiple regression models, age, higher GHb, FPG, follow-up period, and number of follow-up visits increased and higher systolic BP and female gender significantly decreased the percent glycemic change. Conclusions. This study highlights that more than 64.4% of the patients have GHb values higher than 7.0% at last clinic visit andindicatesthe difficult challenges physicians face when treating their patients with type 2 diabetes. Clinical efforts should focus on more effective methods for glycemic control in diabetic patients.

scholarly journals Long-term Effect of Islet Transplantation on Glycemic Variability

2018 ◽  
Vol 27 (5) ◽  
pp. 840-846 ◽  
Author(s):  
Federico Bertuzzi ◽  
Luciano De Carlis ◽  
Mario Marazzi ◽  
Antonio Gaetano Rampoldi ◽  
Matteo Bonomo ◽  
...  
Keyword(s):  
Glycemic Control ◽  
Islet Transplantation ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Glucose Variability ◽  
Waiting List ◽  
Long Term Effect

Islet transplantation has been reported to restore normoglycemia and the overall metabolic control in type 1 diabetes mellitus (DM). In the most experienced centers, islet transplantation clinical outcome is similar to that of the whole pancreas transplantation. Long-term islet transplantation function remains a very interesting matter worth discussing. A progressive islet function decrease was reported, probably due to islet exhaustion. In 5 islet-transplanted patients with at least 3-yr follow-up and still insulin independent, their glycemic control was characterized by a blinded retrospective continuous glucose monitoring system (CGMS). Islet transplantation restored glycemic control and glucose variability. Data were compared with patients in the waiting list. All the parameters of glycemic variability tested had improved significantly in patients who had islet transplantation compared with those patients who were on the waiting list. In conclusion, islet transplantation is able to maintain a proper glucose control and normalize glycemic variability in selected patients. A blinded retrospective CGMS is a useful method to characterize glucose homeostasis deeply in vivo in islet-transplanted patients.

scholarly journals Are dipeptidyl peptidase-4 inhibitors effective and safe in long term when added to ongoing therapies of diabetics? a real-life study in tertiary referral center

2019 ◽  
Vol 6 (2) ◽  
pp. 264
Author(s):  
Deniz Avci ◽  
Ali Cetinkaya
Keyword(s):  
Hemoglobin A1c ◽  
Real Life ◽  
Dipeptidyl Peptidase ◽  
Diabetic Patients ◽  
Mean Values ◽  
Tertiary Referral Center ◽  
Dipeptidyl Peptidase 4 ◽  
Dipeptidyl Peptidase 4 Inhibitors

Background: The aim of this study was to determine how HbA1c, lipid, renal functions and such parameters were affected in the long term by adding dipeptidyl peptidase-4 inhibitors to the ongoing treatment regimens of patients with Type 2 diabetes mellitus.Methods: The study was conducted in diabetes mellitus outpatient clinic of Kayseri Training and Research Hospital between February 2012 and May 2017, with patients who did not achieve the sufficient success in diabetes their controls at the time of admission. From these patients, those who added (dipeptidyl peptidase-4 inhibitors) to their treatments were selected. Patients were followed up as long as they continued to these new treatments and the parameters at the baseline were compared with final values.Results: A total of 80 diabetic patients were followed in the study. The median age of the patients was 56.08±9.71 years. During this follow-up, an average decrease of 1.03% was noted when patients were compared with 9.53±1.87% of the initial hemoglobin A1c, and 8.50±1.48% of the Hemoglobin A1c values at the end of follow-up. This decrease was statistically significant (p <0.001). However, differences in the initial and final values of the lipid parameters of the patients were not statistically significant.Conclusions: Addition of dipeptidyl peptidase-4 inhibitors to patients' treatments causes significant decreases in Hemoglobin A1c mean values. This decline is long lasting. However, there are no positive or negative effects on biochemical parameters such as lipids, kidney and liver functions.

scholarly journals Association of Long-Term Change and Variability in Glycemia with Risk of Incident Heart Failure among Patients with Type 2 Diabetes Mellitus – A Secondary Analysis of the ACCORD Trial

2020 ◽  
Author(s):  
Matthew W. Segar ◽  
Kershaw V. Patel ◽  
Muthiah Vaduganathan ◽  
Melissa C. Caughey ◽  
Javed Butler ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Secondary Analysis ◽  
Glycemic Variability ◽  
Baseline Risk ◽  
Absolute Difference ◽  
Cox Models ◽  
Term Change ◽  
Alternative Measures

<b>Objective</b>: Evaluate the associations between long-term change and variability in glycemia with risk of HF among patients with T2DM. <p><b>Research Design and Methods: </b>Among participants with T2DM enrolled in the ACCORD trial, variability in HbA1c was assessed from stabilization of HbA1c following enrollment (8 months) to 3 years of follow-up as follows: average successive variability (ASV=average absolute difference between successive values), coefficient of variation (CV=standard deviation/mean), and standard deviation. Participants with HF at baseline or within 3 years of enrollment were excluded. Adjusted Cox models were used to evaluate the association of % change (from baseline to 3 years of follow-up) and variability in HbA1c over the first 3 years of enrollment and subsequent risk of HF.</p> <p><b>Results</b>: The study included 8,576 patients. Over a median follow-up of 6.4 years from the end of variability measurements at year 3, 388 patients had an incident HF hospitalization. Substantial changes in HbA1c were significantly associated with higher risk of HF [HR (95% CI) for ≥10% decrease = 1.32 (1.08-1.75), ≥10% increase = 1.55 (1.19-2.04), ref: <10% change in HbA1c]. Higher long-term variability in HbA1c was significantly associated with higher risk of HF [HR (95% CI) per 1 SD of ASV = 1.34 (1.17-1.54)] independent of baseline risk factors and interval changes in cardiometabolic parameters. Consistent patterns of association were observed using alternative measures of glycemic variability.</p> <p><b>Conclusions:</b> Substantial long-term changes and variability in HbA1c were independently associated with risk of HF among patients with T2DM.</p>

scholarly journals Teleassistance for Patients With Type 1 Diabetes During the COVID-19 Pandemic: Results of a Pilot Study (Preprint)

2020 ◽  
Author(s):  
Martina Parise ◽  
Linda Tartaglione ◽  
Antonio Cutruzzolà ◽  
Maria Ida Maiorino ◽  
Katherine Esposito ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Disease Management ◽  
Health Care Providers ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Care Providers ◽  
Virtual Visits

BACKGROUND Telemedicine use in chronic disease management has markedly increased during health emergencies due to COVID-19. Diabetes and technologies supporting diabetes care, including glucose monitoring devices, software analyzing glucose data, and insulin delivering systems, would facilitate remote and structured disease management. Indeed, most of the currently available technologies to store and transfer web-based data to be shared with health care providers. OBJECTIVE During the COVID-19 pandemic, we provided our patients the opportunity to manage their diabetes remotely by implementing technology. Therefore, this study aimed to evaluate the effectiveness of 2 virtual visits on glycemic control parameters among patients with type 1 diabetes (T1D) during the lockdown period. METHODS This prospective observational study included T1D patients who completed 2 virtual visits during the lockdown period. The glucose outcomes that reflected the benefits of the virtual consultation were time in range (TIR), time above range, time below range, mean daily glucose, glucose management indicator (GMI), and glycemic variability. This metric was generated using specific computer programs that automatically upload data from the devices used to monitor blood or interstitial glucose levels. If needed, we changed the ongoing treatment at the first virtual visit. RESULTS Among 209 eligible patients with T1D, 166 completed 2 virtual visits, 35 failed to download glucose data, and 8 declined the visit. Among the patients not included in the study, we observed a significantly lower proportion of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) users (n=7/43, 16% vs n=155/166, 93.4% and n=9/43, 21% vs n=128/166, 77.1%, respectively; <i>P</i>&lt;.001) compared to patients who completed the study. TIR significantly increased from the first (62%, SD 18%) to the second (65%, SD 16%) virtual visit (<i>P</i>=.02); this increase was more marked among patients using the traditional meter (n=11; baseline TIR=55%, SD 17% and follow-up TIR=66%, SD 13%; <i>P</i>=.01) than among those using CGM, and in those with a baseline GMI of ≥7.5% (n=46; baseline TIR=45%, SD 15% and follow-up TIR=53%, SD 18%; <i>P</i>&lt;.001) than in those with a GMI of &lt;7.5% (n=120; baseline TIR=68%, SD 15% and follow-up TIR=69%, SD 15%; <i>P</i>=.98). The only variable independently associated with TIR was the change of ongoing therapy. The unstandardized beta coefficient (B) and 95% CI were 5 (95% CI 0.7-8.0) (<i>P</i>=.02). The type of glucose monitoring device and insulin delivery systems did not influence glucometric parameters. CONCLUSIONS These findings indicate that the structured virtual visits help maintain and improve glycemic control in situations where in-person visits are not feasible.

1156Coronary artery bypass grafting vs. FFR-guided PCI in diabetic patients with multivessel disease

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
G Di Gioia ◽  
N Soto Flores ◽  
D Franco ◽  
I Colaiori ◽  
J Sonck ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Artery Bypass ◽  
Diabetic Patients ◽  
Bypass Grafting ◽  
Fractional Flow ◽  
Artery Bypass Grafting ◽  
The Individual ◽  
The Impact

Abstract Background In diabetic patients with multivessel coronary disease (MVD), coronary artery bypass grafting (CABG) has shown long-term benefits in mortality over percutaneous coronary revascularization (PCI). Nevertheless, the impact of fractional flow reserve (FFR)-guided PCI on clinical outcomes has never been investigated in these patients. Purpose To evaluate the long-term (5-year) clinical outcome of diabetic patients with MVD treated with FFR-guided PCI compared to CABG. Methods From February 2010 to February 2018, all diabetic patients undergoing coronary angiography in one centre (n=4622) were screened for inclusion. The inclusion criterion was presence of at least two-vessels CAD defined as with diameters stenosis ≥50%. In case of intermediate coronary stenosis (%DS 30–70%), FFR was performed at the discretion of the operator. Revascularization was performed when FFR ≤0.80. Exclusion criteria were ST-elevation myocardial infarction, prior CABG, and moderate or severe valvular heart dysfunction. To account for confounders, we compared outcomes by calculating an adjusted Kaplan-Meier estimator using inverse probability of treatment weighting (IPTW). Propensity score variables included age, sex, smoking habit, hypertension, hyperlipidemia, insulin therapy, family history of CAD, chronic obstructive pulmonary disease (COPD), glomerular filtration rate (GFR), prior myocardial infarction, peripheral vascular disease (PVD), admission for NSTEMI, ejection fraction, number of angiographic stenotic vessels. Odds ratios were calculated using generalized linear models (GLM). The primary endpoint was major adverse cardiovascular and cerebrovascular events (MACCE), defined as all-cause death, myocardial infarction and stroke. Secondary endpoints were the individual component of MACCE and any repeated revascularization. Results A total of 538 diabetic patients with MVD were included in the analysis. Among them, 317 (59%) patients underwent CABG and 221 (41%) FFR-guided PCI. Patients treated with FFR-guided PCI had more often COPD as compared to patients in the CABG-group, but patients treated with CABG had lower GFR, more PVD, higher number of angiographic stenotic vessels (2.8±0.4 vs. 2.5±0.5; p<0.01) and higher Syntax score (20±7 vs. 14±6; p<0.01) as compared to the FFR-guided PCI group. Clinical follow-up was obtained in 95% of the patients at a median follow-up of 5 years. The incidence of MACCE was similar in the CABG and in the FFR-guided PCI group [27% vs. 29%; OR (95% CI) 1.05 (0.68–1.63); p=0.74]. No differences were found in the individual components of MACCE. Repeat revascularization was more frequent in the FFR-guided PCI group than in the CABG group [27% vs. 7%; OR (95% CI) 4.3 (2.35–7.9); p<0.01]. Conclusions In diabetic patients with MVD undergoing FFR-guided PCI, no differences in major adverse events were observed at a median follow-up of 5 years compared with CABG.

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