Longitudinal HbA1c Research Articles

The Effect of City-Level Sugar-Sweetened Beverage Taxes on Longitudinal HbA1c and Incident Diabetes in Adults With Prediabetes.

Prediabetes, which is a condition characterized by higher-than-normal blood glucose levels that are under the threshold for diabetes, impacts over one-third of U.S. adults. Excise taxes on sugar-sweetened beverages (SSBs) are a proposed policy intervention to lower population consumption of SSBs and generate revenue to support health-related programs, thus potentially delaying or preventing the development of diabetes in individuals with prediabetes. We leveraged data from Kaiser Permanente in California to examine the impact of SSB taxes in California on individual-level mean HbA1c levels and rates of incident diabetes. We compared two outcomes, mean HbA1c levels and rates of incident diabetes, among a matched cohort of adults with prediabetes who lived and did not live in SSB excise tax cities, using outcomes collected in the 6 years prior and 4 years following SSB tax implementation. We used multivariable linear mixed effects models to analyze longitudinal mean HbA1c and discrete-time survival models for incident diabetes. We included 68,658 adults in the analysis. In adjusted models, longitudinal mean HbA1c was 0.007% (95% CI 0.002, 0.011) higher in the tax cities compared with control individuals; while the estimated difference was statistically significant, it was not clinically significant (HbA1c <0.5%). There was no significant difference in the risk of incident diabetes between individuals living in tax and control cities. We found no clinically significant association between SSB taxes and either longitudinal mean HbA1c or incident diabetes among adults with prediabetes in the 4 years following SSB tax implementation.

Longitudinal HbA1c patterns before the first treatment of diabetes in routine clinical practice: A latent class trajectory analysis

AimsTo examine the longitudinal heterogeneity of HbA1c preceding the initiation of diabetes treatment in clinical practice. MethodsIn this population-based study, we used HbA1c from routine laboratory and healthcare databases. Latent class trajectory analysis was used to classify individuals according to their longitudinal HbA1c patterns before first glucose-lowering drug prescription irrespective of type of diabetes. ResultsAmong 21,556 individuals initiating diabetes treatment during 2017–2018, 20,733 (96 %) had HbA1c measured (median 4 measurements [IQR 2–7]) in the 5 years preceding treatment initiation. Four classes with distinct HbA1c trajectories were identified, with varying steepness of increase in HbA1c. The largest class (74 % of the individuals) had mean HbA1c above the 48 mmol/mol threshold 9 months before treatment initiation. Mean HbA1c was 52 mmol/mol (95 % CI 52–52) at treatment initiation. In the remaining three classes, mean HbA1c exceeded 48 mmol/mol almost 1.5 years before treatment initiation and reached 79 mmol/mol (95 % CI 78–80), 105 mmol/mol (95 % CI 104–106), and 137 mmol/mol (95 % CI 135–140) before treatment initiation. ConclusionWe identified four distinct longitudinal HbA1c patterns before initiation of diabetes treatment in clinical practice. All had mean HbA1c levels exceeding the diagnostic threshold many months before treatment initiation, indicating therapeutic inertia.

Association between hemoglobin A1c trajectory during pregnancy and adverse birth outcomes among non-gestational diabetic women.

Previous studies have shown that higher hemoglobin A1c (HbA1c) levels within the normal range during pregnancy can increase the risk of adverse birth outcomes. However, the effects of the longitudinal HbA1c trajectory during pregnancy on adverse birth outcomes among non-gestational diabetic women are poorly characterized. We aimed to identify HbA1c trajectory during pregnancy among non-gestational diabetic women and to estimate their associations with adverse birth outcomes. Data was extracted from the Information System of Guangdong Women and Children Hospital, China, from January 2017 to July 2022. This study involved 13,979 women who did not have gestational diabetes mellitus and underwent repeated HbA1c measurements during pregnancy. Latent mixture modeling was used to identify HbA1c trajectory groups. Logistic regression was applied to explore the associations between HbA1c trajectory groups and adverse birth outcomes, including preterm delivery, low birth weight, macrosomia, small for gestational age, and large for gestational age (LGA). Three HbA1c trajectory groups were identified: low-stable (range 4.0% [20mmol/mol]-4.4% [25mmol/mol]), moderate-stable (range 4.6% [27mmol/mol]-5.1% [32mmol/mol]), and elevated-increasing (range 5.0% [31mmol/mol]-5.6% [38mmol/mol]). Compared with the low-stable HbA1c group, the elevated-increasing group had a higher risk of preterm delivery and LGA. The adjusted OR (95% CIs) were 1.67 (1.13, 2.49) and 1.47 (1.01, 2.12) for preterm delivery and LGA, respectively. Among non-gestational diabetic women, the elevated-increasing HbA1c trajectory group was associated with a higher risk of preterm delivery and LGA. This finding emphasizes the importance of maintaining optimal HbA1c levels throughout pregnancy.

Correlation Between the Glycemia Risk Index and Longitudinal Hemoglobin A1c in Children and Young Adults With Type 1 Diabetes.

The glycemia risk index (GRI) is a composite metric developed and used to estimate quality of glycemia in adults with diabetes who use continuous glucose monitor (CGM) devices. In a cohort of youth with type 1 diabetes (T1D), we examined the utility of the GRI for evaluating quality of glycemia between clinic visits by analyzing correlations between the GRI and longitudinal glycated hemoglobin A1c (HbA1c) measures. Using electronic health records and CGM data, we conducted a retrospective cohort study to analyze the relationship between the GRI and longitudinal HbA1c measures in youth (T1D duration ≥1 year; ≥50% CGM wear time) receiving care from a Midwest pediatric diabetes clinic network (March 2016 to May 2022). Furthermore, we analyzed correlations between HbA1c and the GRI high and low components, which reflect time spent with high/very high and low/very low glucose, respectively. In this cohort of 719 youth (aged = 2.5-18.0 years [median = 13.4; interquartile range [IQR] = 5.2]; 50.5% male; 83.7% non-Hispanic White; 68.0% commercial insurance), baseline GRI scores positively correlated with HbA1c measures at baseline and 3, 6, 9, and 12 months later (r = 0.68, 0.65, 0.60, 0.57, and 0.52, respectively). At all time points, strong positive correlations existed between HbA1c and time spent in hyperglycemia. Substantially weaker, negative correlations existed between HbA1c and time spent in hypoglycemia. In youth with T1D, the GRI may be useful for evaluating quality of glycemia between scheduled clinic visits. Additional CGM-derived metrics are needed to quantify risk for hypoglycemia in this population.

Terminal trajectory of HbA1c for 10 years supports the HbA1c paradox: a longitudinal study using Health and Retirement Study data.

We aimed to assess the potential time-varying associations between HbA1c and mortality, as well as the terminal trajectory of HbA1c in the elderly to reveal the underlying mechanisms. The design is a longitudinal study using data from the Health and Retirement Study. Data were from the Health and Retirement Study. A total of 10,408 participants aged ≥50 years with available HbA1c measurements at baseline (2006/2008) were included. Longitudinal HbA1c measured at 2010/2012 and 2014/2016 were collected. HbA1c values measured three times for their associations with all-cause mortality were assessed using Cox regression and restricted cubic splines. HbA1c terminal trajectories over 10 years before death were analyzed using linear mixed-effect models with a backward time scale. Women constitute 59.6% of the participants with a mean age of 69 years, with 3,070 decedents during the follow-up (8.9 years). The mortality rate during follow-up was 29.5%. Increased mortality risk became insignificant for the highest quartile of HbA1c compared to the third quartile (aHR 1.148, 1.302, and 1.069 for a follow-up of 8.9, 6.5, and 3.2 years, respectively) with a shorter follow-up, while it became higher for the lowest quartile of HbA1c (aHR 0.986, 1.068, and 1.439 for a follow-up of 8.9, 6.5, and 3.2 years, respectively). Accordingly, for both decedents with and without diabetes, an initial increase in HbA1c was followed by an accelerating terminal decline starting 5-6 years before death. The time-varying association between HbA1c and mortality mapped to the terminal trajectory in HbA1c. High and low HbA1c may have different clinical relationships with mortality. The HbA1c paradox may be partially explained by reverse causation, namely, early manifestation of death.

1387-P: Glutamic Acid Decarboxylase Autoantibodies (GADA) in Type 2 Diabetes Predict Glycemic Control over 16 Years

A minority of adults diagnosed with type 2 diabetes (T2D) have islet autoantibodies that may predict diabetes progression. We investigated the association between GADA, the most prevalent islet autoantibody, and longitudinal HbA1c in Look AHEAD (Action for Health in Diabetes), a trial that randomized adults with clinically-diagnosed T2D and overweight/obesity to intensive lifestyle intervention vs. control for 9.6 years, and then followed them observationally. GADA was measured by radioligand binding assay in 87% of the cohort at baseline and categorized as negative, low-level (35-199 U/mL) or high-level (≥200 U/mL). We analyzed the association between GADA category and HbA1c (yearly through year 4, then on alternating years) using linear mixed effects regression adjusted for age, sex, race/ethnicity, calendar time and study arm. Among 4,492 participants, the median age was 59 years and diabetes duration 5 years. GADA was low-level and high-level positive in 131 (2.9%) and 85 (1.9%), respectively. Over a median follow-up of 15.9 years, the modeled mean HbA1c was 7.24% in GADA-, 7.49% in low-level GADA, and 7.67% in high-level GADA (p&amp;lt;0.001). GADA+ participants had consistently higher HbA1c over follow-up in both study arms (Figure). In conclusion, a substantial minority of adults with clinically-diagnosed T2D had GADA positivity that predicted worse glycemic control for more than a decade. Disclosure S.J.Pilla: None. A.Ramelius: None. R.Bennet: None. Å.Lernmark: Advisory Panel; Diamyd Medical. N.N.Mathioudakis: None. J.Clark: None. N.M.Maruthur: Other Relationship; Johns Hopkins HealthCare Solutions. W.C.Knowler: None. A.Balasubramanyam: None. C.S.Hampe: Employee; Immusoft corp. S.Pietropaolo: None. A.M.Anderson: None. M.Li: None. N.Zhao: None. S.L.Zeger: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK126825, K23DK128572)

Trajectory of glycated haemoglobin over time, using real-world data, in type 2 diabetes patients with obesity on a U-100 basal-bolus insulin regimen.

To identify patient clusters with poor glucose control among type 2 diabetes mellitus (T2DM) patients with obesity who are receiving basal-bolus insulin and to identify the potential therapeutic inertia factors associated with poor control. Glycated haemoglobin (HbA1c) trajectories across a 3-year period were structured at 6-month intervals for a retrospective cohort of T2DM patients with obesity on basal-bolus insulin from the Veterans' Health Administration database. Based on each patient's longitudinal HbA1c features, an unsupervised clustering procedure was used to determine the numbers of clusters and associated trajectory patterns. Multinomial logistic regression was used to examine the association between HbA1c trajectory clusters and patient characteristics/treatment patterns. A total of 51 273 patients were included, of whom 11.2% were in a subgroup with persistent missingness of HbA1c values. For those with sufficient HbA1c observations, cluster analysis indicated six distinct HbA1c trajectories: stable low (35.8%); stable high (20.8%); descending low (10.5%); ascending low (10.2%); descending high (5.7%); and ascending high (5.7%). Being of Black ethnicity, not initiating noninsulin antihyperglycaemic agents (sodium-glucose cotransporter-2 inhibitors, glucagon-like peptide-1 receptor agonists or thiazolidinediones) or concentrated insulin, low adherence (measured by proportion of days covered), and reduced insulin prescription refills were factors associated with poorer HbA1c clusters; similar factors were associated with persistent HbA1c missingness. The present study found the potential for therapeutic inertia among a significant proportion of T2DM patients with obesity on basal-bolus insulin. Subgrouping T2DM patients based on HbA1c missingness and HbA1c trajectories can inform disease management strategies.

Longitudinal HbA1c trajectory modelling reveals the association of HbA1c and risk of hospitalization for heart failure for patients with type 2 diabetes mellitus.

Inconsistent conclusions in past studies on the association between poor glycaemic control and the risk of hospitalization for heart failure (HHF) have been reported largely due to the analysis of non-trajectory-based HbA1c values. Trajectory analysis can incorporate the effects of HbA1c variability across time, which may better elucidate its association with macrovascular complications. Furthermore, studies analysing the relationship between HbA1c trajectories from diabetes diagnosis and the occurrence of HHF are scarce. This is a prospective cohort study of the SingHealth Diabetes Registry (SDR). 17,389 patients diagnosed with type 2 diabetes mellitus (T2DM) from 2013 to 2016 with clinical records extending to the end of 2019 were included in the latent class growth analysis to extract longitudinal HbA1c trajectories. Association between HbA1c trajectories and risk of first known HHF is quantified with the Cox Proportional Hazards (PH) model. 5 distinct HbA1c trajectories were identified as 1. low stable (36.1%), 2. elevated stable (40.4%), 3. high decreasing (3.5%), 4. high with a sharp decline (10.8%), and 5. moderate decreasing (9.2%) over the study period of 7 years. Poorly controlled HbA1c trajectories (Classes 3, 4, and 5) are associated with a higher risk of HHF. Using the diabetes diagnosis time instead of a commonly used pre-defined study start time or time from recruitment has an impact on HbA1c clustering results. Findings suggest that tracking the evolution of HbA1c with time has its importance in assessing the HHF risk of T2DM patients, and T2DM diagnosis time as a baseline is strongly recommended in HbA1c trajectory modelling. To the authors' knowledge, this is the first study to identify an association between HbA1c trajectories and HHF occurrence from diabetes diagnosis time.

Association of poorly controlled HbA1c with increased risk of progression to end-stage kidney disease and all-cause mortality in patients with diabetes and chronic kidney disease.

Glycosylated hemoglobin (HbA1c) targets for patients with chronic kidney disease (CKD) and type 2 diabetes remain controversial. To evaluate whether baseline HbA1c and HbA1c trajectories are associated with the risk of end-stage kidney disease (ESKD) and all-cause mortality, we recruited adult patients with CKD and type 2 diabetes from a “Pre-ESKD Program” at a medical center in Taiwan from 2003 to 2017. Group-based trajectory modeling was performed to identify distinct patient groups that contained patients with similar longitudinal HbA1c patterns. Cox proportional hazard models were used to estimate hazard ratios (HRs) of ESKD and mortality associated with baseline HbA1c levels and HbA1c trajectories. In the analysis related to baseline HbA1c (n = 4543), the adjusted HRs [95% confidence interval (CI)] of all-cause mortality were 1.06 (0.95–1.18) and 1.25 (95% CI, 1.07–1.46) in patients with an HbA1c level of 7%–9% (53–75 mmol/mol) and >9% (>75 mmol/mol), respectively, as compared with those with an HbA1c level < 7% (<53 mmol/mol). In the trajectory analysis (n = 2692), three distinct longitudinal HbA1c trajectories were identified: nearly optimal (55.9%), moderate to stable (34.2%), and poor control (9.9%). Compared with the “nearly optimal” HbA1c trajectory group, the “moderate-to-stable” group did not have significantly higher mortality, but the “poorly controlled” group had 35% higher risk of mortality (adjusted HR = 1.35, 95% CI = 1.06–1.71). Neither baseline levels of HbA1c nor trajectories were associated with ESKD risk. In conclusion, in patients with CKD and type 2 diabetes, poor glycemic control was associated with an elevated risk of mortality but not associated with a risk of progression to ESKD.

HbA1c as a time predictive biomarker for an additional islet autoantibody and type 1 diabetes in seroconverted TEDDY children.

Increased level of glycated hemoglobin (HbA1c) is associated with type 1 diabetes onset that in turn is preceded by one to several autoantibodies against the pancreatic islet beta cell autoantigens; insulin (IA), glutamic acid decarboxylase (GAD), islet antigen-2 (IA-2) and zinc transporter 8 (ZnT8). The risk for type 1 diabetes diagnosis increases by autoantibody number. Biomarkers predicting the development of a second or a subsequent autoantibody and type 1 diabetes are needed to predict disease stages and improve secondary prevention trials. This study aimed to investigate whether HbA1c possibly predicts the progression from first to a subsequent autoantibody or type 1 diabetes in healthy children participating in the Environmental Determinants of Diabetes in the Young (TEDDY) study. A joint model was designed to assess the association of longitudinal HbA1c levels with the development of first (insulin or GAD autoantibodies) to a second, second to third, third to fourth autoantibody or type 1 diabetes in healthy children prospectively followed from birth until 15 years of age. It was found that increased levels of HbA1c were associated with a higher risk of type 1 diabetes (HR 1.82, 95% CI [1.57-2.10], p <0.001) regardless of first appearing autoantibody, autoantibody number or type. A decrease in HbA1c levels was associated with the development of IA-2A as a second autoantibody following GADA (HR 0.85, 95% CI [0.75, 0.97], p =0.017) and a fourth autoantibody following GADA, IAA and ZnT8A (HR 0.90, 95% CI [0.82, 0.99], p =0.036). HbA1c trajectory analyses showed a significant increase of HbA1c over time (p <0.001) and that the increase is more rapid as the number of autoantibodies increased from one to three (p <0.001). In conclusion, increased HbA1c is a reliable time predictive marker for type 1 diabetes onset. The increased rate of increase of HbA1c from first to third autoantibody and the decrease in HbA1c predicting the development of IA-2A are novel findings proving the link between HbA1c and the appearance of autoantibodies.

IDF21-0506 Clinical inertia and 2-year glycaemic trajectories in patients with long-term type 2 diabetes in Chinese primary care

Background: The serial measurements of HbA1c can form a trajectory of reflecting the long‐term glycaemic control of diabetes for each patient. Previous analysis has suggested that these HbA1c trajectories could be categorized into several distinct patterns. Cumulative glycaemic exposure over time has also been used to categorize HbA1c trajectories. Two main reasons for suboptimal glycaemic control were identified in clinical practice: (1) patient non-adherence to prescribed treatment and (2) clinical or therapeutic inertia, defined as the failure to start a therapy or its intensification/nonintensification when appropriate. The causes of clinical inertia included factors related to the healthcare professionals, patients and the national healthcare system. Aim: This study aimed to investigate: (1) patterns of HbA1c trajectories shown as cumulative glycaemic exposure, as measured by repeated HbA1c values in ≥12 months follow up after registration/management and (2) risk factors for poor glycaemic control and clinical inertia, originated from healthcare professionals (treatment titration) and patients (adherence to healthy diet, activity, self-monitor of blood glucose [SMBG] and medications). Method: This was an observational, multicenter, longitudinal, retrospective cohort study of 4690 subjects registered on diabetes share-care information system in 5 Ruijing Diabetes Chain Hospitals. Clinical data from 2016 to 2019 were extracted from electronic medical records, including serial HbA1c measurements, antidiabetic medication records and compliance to exercise, diet, medications and self-monitor of blood glucose (SMBG). Patterns of longitudinal HbA1c trajectories were identified using the percent of HbA1c measurements <7.5%. Clinical relevance of the clusters was assessed through multivariable analysis. Results: We identified four distinct HbA1c trajectories in this study population of median age 61.75 years and duration 9.58 years. Approximately half of the participants demonstrated good glycaemic control with 34.5% stable good and 13.7% relatively good, while 16.2% moderate control and 35.6% poor control. From good to poor control group, percentage of subjects treated with insulin at baseline (41.1-74.9%) and during follow up (39.6-75.3%) increased gradually, while the percentage of subjects being adherent to exercise, diet, medications and SMBG decreased gradually. Compared with baseline, the adherence to exercise, diet, medications and SMBG improved significantly. Approximately 50% and 26% of subjects had treatment change and HbA1c tests≥3 per year in the two poorest control groups. After multivariable adjustment, baseline HbA1c≥7.5%, HbA1c change ≥ −0.5% from visit 1 to baseline, insulin treatment, treatment change, poor adherence to diet, exercise, SMBG during follow up and HbA1c measurements <3 per year were significantly associated with poorer glycaemic control. Discussion: We identified 4 longitudinal HbA1c trajectories in patients with non-newly diagnosed type 2 diabetes. Aggressive treatment change, good adherence during follow up, annual HbA1c measurements≥3 and reducing HbA1c level to a certain extent at the first follow up visit was important for long term stable good glycaemic control.

Unmasking Fracture Risk in Type 2 Diabetes: The Association of Longitudinal Glycemic Hemoglobin Level and Medications.

Fracture risk is underestimated in people with type 2 diabetes (T2D). To investigate the longitudinal relationship of glycated hemoglobin (HbA1c) and common medications on fracture risk in people with T2D. This retrospective population-based cohort study was conducted using de-identified claims and electronic health record data obtained from the OptumLabs Data Warehouse for the period January 1, 2007, to September 30, 2015. For each individual, the study was conducted within a 2-year HbA1c observation period and a 2-year fracture follow-up period. A cohort of 157 439 individuals with T2D [age ≥ 55 years with mean HbA1c value ≥ 6%] were selected from 4 018 250 US Medicare Advantage/Commercial enrollees with a T2D diagnosis. All fractures and fragility fractures were measured. With covariates adjusted, poor glycemic control in T2D individuals was associated with an 29% increase of all fracture risk, compared with T2D individuals who had adequate glycemic control (HR: 1.29; 95% CI, 1.22-1.36). Treatment with metformin (HR: 0.88; 95% CI, 0.85-0.92) and DPP4 inhibitors (HR: 0.93; 95% CI, 0.88-0.98) was associated with a reduced all fracture risk, while insulin (HR: 1.26; 95% CI, 1.21-1.32), thiazolidinediones (HR: 1.23; 95% CI, 1.18-1.29), and meglitinides (HR: 1.12; 95% CI, 1.00-1.26) were associated with an increased all fracture risk (All P value < 0.05). Bisphosphonates were associated similarly with increased fracture risk in the T2D and nondiabetic groups. Longitudinal 2-year HbA1c is independently associated with elevated all fracture risk in T2D individuals during a 2-year follow-up period. Metformin and DPP4 inhibitors can be used for management of T2D fracture risk.

Impact of flash glucose monitoring on glycemic control varies with the age and residual β-cell function of patients with type 1 diabetes mellitus.

Aims/IntroductionWe aimed to explore the clinical factors associated with glycemic variability (GV) assessed with flash glucose monitoring (FGM), and investigate the impact of FGM on glycemic control among Chinese type 1 diabetes mellitus patients in a real‐life clinical setting.Materials and MethodsA total of 171 patients were included. GV was assessed from FGM data. A total of 110 patients wore FGM continuously for 6 months (longitudinal cohort). Hemoglobin A1c (HbA1c), fasting and 2‐h postprandial C‐peptide, and glucose profiles were collected. Changes in HbA1c and glycemic parameters were assessed during a 6‐month FGM period.ResultsIndividuals with high residual C‐peptide (HRCP; 2‐h postprandial C‐peptide >200 pmol/L) had less GV than patients with low residual C‐peptide ( 2‐h postprandial C‐peptide ≤200 pmol/L; P < 0.001). In the longitudinal cohort (n = 110), HbA1c and mean glucose decreased, time in range (TIR) increased during the follow‐up period (P < 0.05). The 110 patients were further divided into age and residual C‐peptide subgroups: (i) HbA1c and mean glucose were reduced significantly only in the subgroup aged ≤14 years during the follow‐up period, whereas time below range also increased in this subgroup at 3 months (P = 0.047); and (ii) HbA1c improved in the HRCP subgroup at 3 and 6 months (P < 0.05). The mean glucose decreased and TIR improved significantly in the low residual C‐peptide subgroup; however, TIR was still lower and time below range was higher than those of the HRCP subgroup at all time points (P < 0.05).ConclusionsHRCP was associated with less GV. FGM wearing significantly reduced HbA1c, especially in pediatric patients and those with HRCP. Additionally, the mean glucose and TIR were also found to improve.

The Impact of Racial and Ethnic Health Disparities in Diabetes Management on Clinical Outcomes: A Reinforcement Learning Analysis of Health Inequity Among Youth and Young Adults in the SEARCH for Diabetes in Youth Study.

To estimate difference in population-level glycemic control and the emergence of diabetes complications given a theoretical scenario in which non-White youth and young adults (YYA) with type 1 diabetes (T1D) receive and follow an equivalent distribution of diabetes treatment regimens as non-Hispanic White YYA. Longitudinal data from YYA diagnosed 2002-2005 in the SEARCH for Diabetes in Youth Study were analyzed. Based on self-reported race/ethnicity, YYA were classified as non-White race or Hispanic ethnicity (non-White subgroup) versus non-Hispanic White race (White subgroup). In the White versus non-White subgroups, the propensity score models estimated treatment regimens, including patterns of insulin modality, self-monitored glucose frequency, and continuous glucose monitoring use. An analysis based on policy evaluation techniques in reinforcement learning estimated the effect of each treatment regimen on mean hemoglobin A1c (HbA1c) and the prevalence of diabetes complications for non-White YYA. The study included 978 YYA. The sample was 47.5% female and 77.5% non-Hispanic White, with a mean age of 12.8 ± 2.4 years at diagnosis. The estimated population mean of longitudinal average HbA1c over visits was 9.2% and 8.2% for the non-White and White subgroup, respectively (difference of 0.9%). Within the non-White subgroup, mean HbA1c across visits was estimated to decrease by 0.33% (95% CI -0.45, -0.21) if these YYA received the distribution of diabetes treatment regimens of the White subgroup, explaining ∼35% of the estimated difference between the two subgroups. The non-White subgroup was also estimated to have a lower risk of developing diabetic retinopathy, diabetic kidney disease, and peripheral neuropathy with the White youth treatment regimen distribution (P < 0.05), although the low proportion of YYA who developed complications limited statistical power for risk estimations. Mathematically modeling an equalized distribution of T1D self-management tools and technology accounted for part of but not all disparities in glycemic control between non-White and White YYA, underscoring the complexity of race and ethnicity-based health inequity.

Clinical Inertia and 2-Year Glycaemic Trajectories in Patients with Non-Newly Diagnosed Type 2 Diabetes Mellitus in Primary Care: A Retrospective Cohort Study

ObjectiveTo analyse diabetes treatment, treatment change and self-management behaviours in association with 2-year glycaemic trajectories in patients with non-newly diagnosed type 2 diabetes mellitus in Chinese primary care.MethodsThis was an observational, multi-centre, longitudinal, retrospective cohort study. Clinical data of 4690 subjects were extracted from electronic medical records, including serial glycated haemoglobin A1c (HbA1c) measurements, antidiabetic medication records and compliance to exercise, diet, medications and self-monitoring of blood glucose (SMBG). Patterns of longitudinal HbA1c trajectories were identified using the percentage of HbA1c measurements <7.5% from the second available HbA1c measurement. Clinical relevance of the clusters was assessed through multivariable analysis.ResultsApproximately half of the participants demonstrated good glycaemic control; of these, 34.5% demonstrated stable, good control, and 13.7% demonstrated relatively good control. About 16.2% demonstrated moderate control, and 35.6% demonstrated poor control. From the good to poor control groups, the percentage of subjects treated with insulin at baseline and during the follow-up period increased gradually, while the percentage of subjects adhering to exercise, diet, medications and SMBG decreased gradually. Compared with baseline, the adherence to exercise, diet, medications and SMBG improved significantly. Approximately 50% and 26% of subjects in the two poorest control groups, respectively, experienced treatment changes. After multivariable adjustments, baseline HbA1c ≥7.5%, HbA1c change ≥−0.5% from baseline to visit 1, insulin treatment, treatment change, poor adherence to diet, exercise, SMBG during the follow-up period and HbA1c measurements <3 per year were significantly associated with poorer glycaemic control.ConclusionWe identified four longitudinal HbA1c trajectories in patients with non-newly diagnosed type 2 diabetes. Even if baseline HbA1c is suboptimal, aggressive treatment changes, good adherence during the follow-up period, ≥3 HbA1c measurements per year and reducing HbA1c levels to a certain extent by the first follow-up visit were important for good, stable, long-term glycaemic control.

Longitudinal Associations Between Illness Perceptions and Glycemic Control in Type 2 Diabetes.

BackgroundCross-sectional research demonstrates associations between illness perceptions and glycemic control in people with type 2 diabetes (T2D). Prospective studies are limited and show mixed findings. This study aimed to investigate (1) whether baseline illness perceptions predicted glycemic control (HbA1c levels) at 6–12-month follow-up and (2) possible differences in baseline illness perceptions between individuals who completed at least one HbA1c blood test during the 12-month follow-up and those who did not.MethodsA total of 115 individuals with T2D were recruited from an outpatient clinic. Demographic and clinical information and illness perceptions were assessed at baseline. HbA1c was assessed at baseline and 12 months later from clinical records. Hierarchical multiple linear regression examined associations between baseline illness perceptions and HbA1c levels at 6–12-month follow-up, controlling for age, sex, education, types of diabetes medication, and baseline HbA1c.ResultsUnivariate analysis showed perceived weight management effectiveness at baseline was associated with lower HbA1c at follow-up (rho = −.25, p = .04, n = 67). Adjusted multiple regression showed that HbA1c at baseline was the only significant predictor of HbA1c at 6–12-month follow-up (β = 0.51, p < .001). There were no significant differences in baseline illness perceptions between individuals who completed HbA1c blood tests during follow-up (n = 78) and those who did not (n = 34), p > .05.ConclusionIllness perceptions at baseline did not predict longitudinal HbA1c in adjusted analyses, nor completion of HbA1c tests. Results may be due to temporal variability in HbA1c and barriers to accessing blood tests.Supplementary InformationThe online version contains supplementary material available at 10.1007/s12529-021-10024-y.

Evaluation and management of COVID-19-related severity in people with type 2 diabetes

IntroductionPeople with type 2 diabetes (T2D) have an increased rate of hospitalization and mortality related to COVID-19. To identify ahead of time those who are at risk of developing severe...

Machine learning based study of longitudinal HbA1c trends and their association with all-cause mortality: Analyses from a National Diabetes Registry.

The association of long-term HbA1c variability with mortality has been previously suggested. However, the significance of HbA1c variability and trends in different age and HbA1c categories is unclear. Data on patients with diabetes listed in the Israeli National Diabetes Registry during years 2012-2016 (observation period) were collected. Patients with >4 HbA1c measurements, type 1 diabetes, eGFR<30mg/ml/min, persistent HbA1c<6% or malignancy were excluded. Utilizing machine learning methods, patients were classified into clusters according to their HbA1c trend (increasing, stable, decreasing). Mortality risk during 2017-2019 was calculated in subgroups defined by age (35-54, 55-69, 70-89 years) and last HbA1c (≤7% and >7%) at end of observation period. Models were adjusted for demographic, clinical and laboratory measurements including HbA1c, standard deviation (SD) of HbA1c and HbA1c trend. This historical cohort study included 293,314 patients. Increased HbA1c variability (high SD) during the observation period was an independent predictor of mortality in patients aged more than 55 years (p<0.01). The HbA1c trend was another independent predictor of mortality. Patients with a decreasing versus stable HbA1c trend had a greater mortality risk; this association persisted in all age groups in patients with HbA1c>7% at the end of the observation period (p=0.02 in age 35-54; p<0.01 in aged >55). Patients with an increasing versus stable HbA1c trend had a greater mortality risk only in the elderly group (>70), yet in both HbA1c categories (p<0.01). HbA1c variability and trend are important determinants of mortality risk and should be considered when adjusting glycaemic targets.

Glycemic Control, Diabetic Complications, and Risk of Dementia in Patients With Diabetes: Results From a Large U.K. Cohort Study

Type 2 diabetes is an established risk factor for dementia. However, the roles of glycemic control and diabetic complications in the development of dementia have been less well substantiated. This large-scale cohort study aims to examine associations of longitudinal HbA1c levels and diabetic complications with the risk of dementia incidence among patients with type 2 diabetes. Data of eligible patients with diabetes, aged ≥50 years in the U.K. Clinical Practice Research Datalink from 1987 to 2018, were analyzed. Time-varying Cox regressions were used to estimate adjusted hazard ratios (HRs) and 95% CIs for dementia risk. Among 457,902 patients with diabetes, 28,627 (6.3%) incident dementia cases were observed during a median of 6 years' follow-up. Patients with recorded hypoglycemic events or microvascular complications were at higher risk of dementia incidence compared with those without such complications (HR 1.30 [95% CI 1.22-1.39] and 1.10 [1.06-1.14], respectively). The HbA1c level, modeled as a time-varying exposure, was associated with increased dementia risk (HR 1.08 [95% CI 1.07-1.09] per 1% HbA1c increment) among 372,287 patients with diabetes with postdiagnosis HbA1c records. Similarly, a higher coefficient of variation of HbA1c during the initial 3 years of follow-up was associated with higher subsequent dementia risk (HR 1.03 [95% CI 1.01-1.04] per 1-SD increment). Higher or unstable HbA1c levels and the presence of diabetic complications in patients with type 2 diabetes are associated with increased dementia risk. Effective management of glycemia might have a significant role in maintaining cognitive health among older adults with diabetes.

Personal Glycation Factors and Calculated Hemoglobin A1c for Diabetes Management: Real-World Data from the Diabetes Prospective Follow-up (DPV) Registry.

Background: Glycated hemoglobin A1c (HbA1c) is a key biomarker in the glycemic management of individuals with diabetes, but the relationship with glucose levels can be variable. A recent kinetic model has described a calculated HbA1c (cHbA1c) that is individual specific. Our aim was to validate the routine clinical use of this glucose metric in younger individuals with diabetes under real-life settings. Materials and Methods: We retrieved HbA1c and glucose data from the German-Austrian-Swiss-Luxembourgian diabetes follow-up (DPV) registry, which covers pediatric individuals with type 1 diabetes (T1D). The new glycemic measure, cHbA1c, uses two individual parameters identified by data sections that contain continuous glucose data between two laboratory HbA1c measurements. The cHbA1c was prospectively validated using longitudinal HbA1c data. Results: Continuous glucose monitoring data from 352 T1D individuals in 13 clinics were analyzed together with HbA1c that ranged between 4.9% and 10.6%. In the prospective analysis, absolute deviations of estimated HbA1c (eHbA1c), glucose management indicator (GMI), and cHbA1c compared with laboratory HbA1c were (median [interquartile range]): 1.01 (0.50, 1.75), 0.46 (0.21, 084) and 0.26 (0.12, 0.46), giving an average bias of 0.6, 0.4 and 0.0, respectively, in National Glycohemoglobin Standardization Program (NGSP) % unit. For eHbA1c and GMI only 25% and 54% of subjects were within ±0.5% of laboratory HbA1c values, whereas 82% of cHbA1c were within ±0.5% of laboratory HbA1c results. Conclusions: Our data show the superior performance of cHbA1c compared with eHbA1c and GMI at reflecting laboratory HbA1c. These data indicate that cHbA1c can be potentially used instead in laboratory HbA1c, at least in younger individuals with T1D.