Effect of mean HbA1c on the association of HbA1c variability and all-cause mortality in patients with type 2 diabetes

Correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus: a retrospective study

Objective

To investigate the correlation between long-term glycemic variability and cognitive function in middle-aged and elderly patients with type 2 diabetes mellitus (T2DM).

Methods

This retrospective analysis includes 222 patients hospitalized at Second Affiliated Hospital of Anhui Medical University from June 2021 to June 2023. Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). All patients were categorized into the MCI group and the non-MCI group based on their MoCA score. Long-term blood glucose fluctuations were measured using glycated hemoglobin A1c standard deviation (HbA1c-SD) and fasting plasma glucose standard deviation (FPG-SD). The study compared general clinical data, blood biochemical indicators, and glycemic variability indicators between the two groups. The differences between the groups were compared using t-test, Chi-Square Test, or Mann-Whitney U test. Kendall's correlation analysis, multivariate logistic regression analysis and ROC curve correlation analysis were further used to analyze the correlation and diagnostic power.

Results

The differences in age, MoCA scores, MMSE scores, HOMA-β, HbA1c-M, HbA1c-SD, FPG-M, FPG-SD, eGFR, Smoking, GLP-1RA and SGLT-2i usage were statistically significant between the two groups (P < 0.05). Kendall's correlation analysis showed that age, HbA1c-M, HbA1c-SD, FPG-M, and FPG-SD was negatively correlated with MoCA scores; meanwhile, the HOMA-β, and eGFR was positively correlated with MoCA scores. Multiple logistic regression analysis revealed that HbA1c-SD, FPG-SD and Smoking were risk factors for cognitive dysfunction, while eGFR, GLP-1RA and SGLT-2i usage was a protective effect. The area under the curve (AUC) values for predicting MCI prevalence were 0.830 (95% CI [0.774-0.877], P < 0.001) for HbA1c-SD, 0.791 (95% CI [0.655-0.808], P < 0.001) for FPG-SD, and 0.698 (95% CI [0.633-0.757], P < 0.001) for eGFR. The optimal diagnostic values were 0.91, 1.32, and 74.81 ml/min/1.73 m2 for HbA1c-SD, FPG-SD, and eGFR, respectively.

Conclusions

Cognitive function in middle-aged and elderly T2DM patients is influenced by long-term blood glucose variability, with poorer cognitive function observed in individuals with higher blood glucose variability. The impact of HbA1c-SD on MCI exhibited a greater magnitude compared to that of PFG-SD and smoking. Additionally, renal function, GLP-1RA and SGLT-2i usage exert positive effects on cognitive function.

Joint effect of blood pressure and glycemic variation on the risk of cardiovascular morbidity and mortality in persons with type 2 diabetes

OBJECTIVE

Few studies have explored the association of visit-to-visit variation in blood pressure (BP) and glycemic factors with cardiovascular disease (CVD) morbidity and mortality. This study aimed to examine the independent and joint effect of visit-to-visit BP and glycemic variation on CVD morbidity and mortality in persons with T2DM.

METHODS

The present study consisted of two retrospective cohort studies. The Taiwan Diabetes Study was based on a database of the National Diabetes Care Management Program (DCMP) and linked with cardiovascular morbidity incidence. The Taichung Diabetes Study was based on the DCMP database of a medical center, which can be linked with the National Death Registry dataset. The outcomes were analyzed by using Cox's proportional hazard models.

RESULTS

A total of 13,280 and 10,894 persons with T2DM in Taiwan and Taichung Diabetes Study, respectively, were included. SBP-CV, FPG-CV, and HbA1c-CV were significant predictors of stroke, CVD event or death, all-cause mortality, and expanded CVD mortality, whereas DBP-CV was a significant predictor of all-cause mortality and expanded and non-expanded CVD mortality. The joint effect of SBP, FPG, and HbA1c predicted the incidence of stroke and CVD event or death with increased risks of 16 %-35 %. In addition, the joint effect of SBP, DBP, FPG, and HbA1c was associated with all-cause and expanded CVD mortality with increased risks of 29 %-81 %.

CONCLUSIONS

The joint effect of BP and glucose variation improved the prediction of cardiovascular morbidity and mortality. Moreover, simultaneous measurement of visit-to-visit BP and glycemic variation may stratify persons with cardiovascular risks and may be regarded as important therapeutic goals in the care of T2DM.

Effect of Date Fruit Consumption on the Glycemic Control of Patients with Type 2 Diabetes: A Randomized Clinical Trial

Objective. Date fruit has been reported to have benefits in type 2 diabetes (T2D), though there is a concern, given the high sugar content, about its effects on glycemic control. Design and Setting. Prospective, interventional, randomized, parallel study. Participants. In total, 79 patients with T2D (39 male and 40 female). Intervention. Participants were randomly allocated to either 60 g date fruit or 60 g raisins daily of the equivalent glycemic index (amount split, given as midmorning and midafternoon snack) for 12 weeks. Main Outcome Measures. The primary outcome was to investigate the effect of date fruit on HbA1c and fasting blood glucose, and their variability, in patients with T2D in comparison to the same glycemic load of raisins. The secondary outcomes were to determine whether date fruit affected cardiovascular risk by measuring fasting lipids, C-reactive protein (CRP), blood pressure, and insulin resistance (IR) as measured by Homeostatic Model Assessment (HOMA-IR). Results. In total, 61 (27 female and 34 male) of 79 patients completed the study. There was no difference between or within groups for HbA1c or HbA1c variability, fasting glucose or glucose variability, insulin resistance (HOMA-IR), insulin sensitivity (HOMA-S), beta cell function (HOMA-B), the disposition index, lipids, systolic (SBP) or diastolic blood pressure (DBP), or C-reactive protein (CRP) (p > 0.05). Conclusion. No improvement in glycemic indices was seen following supplementation of 60 g daily date fruit or raisins, though neither had a deleterious effect on glycemic control over a 12-week period, indicating their safety when consumed in T2D. Additionally, no beneficial therapeutic effects of date fruit on other cardiovascular indices in T2D were seen.

Tacrolimus variability score outperforms coefficient of variation in predicting clinical outcomes of living kidney transplantation

AIMS

Intrapatient variability (IPV) was previously defined as coefficient of variation (CV) or standard deviation of tacrolimus (Tac) exposure while none of them was easily being interpreted and translated into clinical practice after kidney transplantation.

METHODS

We developed a novel Tac variability score (TVS) to evaluate IPV by calculating the frequency of clinically significant changes of Tac trough levels after kidney transplantation. Multivariate Cox proportional analyses were conducted to compare the impact of TVS and CV on transplant outcomes.

RESULTS

A total of 1343 patients were divided into high TVS (>0.30) and low TVS (<0.30) groups, and low CV (<0.30) and high CV (>0.30) groups. Univariate analyses showed that high TVS (hazard ratio [HR]: 2.323, 95% confidence interval [CI]: 1.455-3.709) and high CV (HR: 1.606, 95%CI: 1.044-2.471) were associated with inferior graft survival. However, only TVS was an independent predictor for graft failure in multivariate analyses (HR: 1.972, 95%CI: 1.2-3.24), and the correlation maintained in high CV (P = .020) and low CV (P = .037) subgroups, while CV failed to predict graft loss in neither low (P = .387) nor high TVS (P = .600) subgroups. In addition, TVS had a higher correlation with graft survival in patients with Tac exposure within the therapeutic range and the correlation was less influenced by mean Tac trough levels.

CONCLUSION

TVS is a novel measure of Tac IPV with higher correlation with graft survival and more convenience in clinical use than CV after kidney transplantation.

Association of Mean and Variability of HbA1c with Heart Failure in Patients with Type 2 Diabetes

Heart failure (HF) is a common presentation in patients with type 2 diabetes mellitus (T2DM). Previous studies revealed that the HbA1c level is significantly associated with HF. However, little is known about the association between HbA1c variability and HF. We aimed to evaluate the association of mean and variability of HbA1c with HF in patients with T2DM. Using Diabetes Share Care Program data, patients with T2DM who had mean HbA1c (HbA1c-Mean), and HbA1c variability (tertiles of HbA1c-SD and HbA1c-adjSD) within 12–24 months during 2001–2008 were included. The cutoffs of HbA1c-Mean were set at <7%, 7–7.9%, and ≥8%. Hazard ratios (HRs) for HF during 2008–2018 were estimated using Cox proportional hazard models. A total of 3824 patients were included, of whom 315 patients developed HF during the observation period of 11.72 years. The associated risk of HF increased with tertiles of HbA1c variability and cutoffs of HbA1c-Mean. In mutually adjusted models, HbA1c-Mean showed a consistent dose-response association with HF, while the association of HbA1c variability with HF disappeared. Among patients with HbA1c-Mean <7%, the associated risk of HF in patients with HbA1c variability in tertile 3 was comparable to patients with HbA1c-Mean ≥8%. In conclusion, mean HbA1c was an independent predictor of HF and not explained by HbA1c variability. In addition to absolute HbA1c level, targeting on stability of HbA1c in patients with good glycemic control was also important for the development of HF in patients with T2DM.

Lowering of hemoglobin A1C and risk of cardiovascular outcomes and all-cause mortality, a meta-regression analysis

BACKGROUND

The management of type 2 diabetes predominantly focuses on reducing hemoglobin A1C (HbA1c). We examined the association between the magnitude of reduction in HbA1c and cardiovascular outcomes for new diabetes medications: sodium-glucose cotransporter-2 [SGLT2] inhibitors, glucagon-like peptide-1 [GLP1] agonists, and dipeptidyl peptidase-4 [DPP4] inhibitors.

METHODS

We reviewed all published, placebo-controlled, randomized cardiovascular outcome trials. Meta-regression was performed to evaluate the association between HbA1c reduction (i.e., [post-intervention HbA1c for active drug - pre-intervention HbA1c for active drug] - [post-intervention HbA1c for placebo - pre-intervention HbA1c for placebo]) and the composite cardiovascular outcome (i.e., stroke, myocardial infarction, or cardiovascular death).

RESULTS

We identified 14 cardiovascular outcome clinical trials, the median sample size was 9401, the median age was 64 years, the median time since diagnosis of diabetes was 12 years, and the median duration of trial follow-up was 120 weeks. Within individual medication classes, each additional 0.5% reduction in HbA1c in the active drug arm, relative to placebo, was associated with a lower incidence of cardiovascular events for GLP1 agonists (0.82, 0.68-0.98) but not for SGLT2 (0.97, 0.69-1.36) or DPP4 (1.03, 0.39-2.74) inhibitors.

DISCUSSION

Our study provides further support that reducing the risk of cardiovascular events for adults with diabetes is partly explained by a reduction in HbA1c.

Comparative predictive ability of visit-to-visit HbA1c variability measures for microvascular disease risk in type 2 diabetes

BACKGROUND

To assess the associations of various HbA1c measures, including a single baseline HbA1c value, overall mean, yearly updated means, standard deviation (HbA1c-SD), coefficient of variation (HbA1c-CV), and HbA1c variability score (HVS), with microvascular disease (MVD) risk in patients with type 2 diabetes.

METHODS

Linked data between National Cheng Kung University Hospital and Taiwan's National Health Insurance Research Database were utilized to identify the study cohort. The primary outcome was the composite MVD events (retinopathy, nephropathy, or neuropathy) occurring during the study follow-up. Cox model analyses were performed to assess the associations between HbA1c measures and MVD risk, with adjustment for patients' baseline HbA1c, demographics, comorbidities/complications, and treatments.

RESULTS

In the models without adjustment for baseline HbA1c, all HbA1c variability and mean measures were significantly associated with MVD risk, except HVS. With adjustment for baseline HbA1c, HbA1c-CV had the strongest association with MVD risk. For every unit of increase in HbA1c-CV, the MVD risk significantly increased by 3.42- and 2.81-fold based on the models without and with adjustment for baseline HbA1c, respectively. The associations of HbA1c variability and mean measures with MVD risk in patients with baseline HbA1c < 7.5% (58 mmol/mol) were stronger compared with those in patients with baseline HbA1c ≥ 7.5% (58 mmol/mol).

CONCLUSIONS

HbA1c variability, especially HbA1c-CV, can supplement conventional baseline HbA1c measure for explaining MVD risk. HbA1c variability may play a greater role in MVD outcomes among patients with relatively optimal baseline glycemic control compared to those with relatively poor baseline glycemic control.