Impact of haemoglobin A1c trajectories on chronic kidney disease progression in type 2 diabetes

Risk factors associated with glycated hemoglobin A1c trajectories progressing to type 2 diabetes

BACKGROUND AND OBJECTIVE

The notion of prediabetes, defined by the ADA as glycated hemoglobin A1c (HbA1c) of 5.7-6.4%, implies increased vascular inflammatory and immunologic processes and higher risk for developing diabetes mellitus and major cardiovascular events. We aimed to determine the risk factors associated with rapid progression of normal and prediabetes patients to type 2 diabetes mellitus (T2DM).

METHODS

Retrospective cohort study in a single 8-hospital health system in southeast Michigan, between 2006 and 2020. All patients with HbA1c <6.5% at baseline and at least 2 other HbA1c measurements were clustered in five trajectories encompassing more than 95% of the study population. Multivariate linear regression analysis was performed to examine the association of demographic and comorbidities with HbA1c trajectories progressing to diabetes.

RESULTS

A total of 5,347 prediabetic patients were clustered based on their HbA1c progression (C1: 4,853, C2: 253, C66: 102, C12: 85, C68: 54). The largest cluster (C1) had a baseline median HbA1c value of 6.0% and exhibited stable HbA1c levels in prediabetic range across all subsequent years. The smallest cluster (C68) had the lowest median baseline HbA1c value and also remained stable across subsequent years. The proportion of normal HbA1c in each of the pre-diabetic trajectories ranged from 0 to 12.7%, whereas 81.5% of the reference cluster (C68) were normal HbA1c at baseline. The C2 (steady rising) trajectory was significantly associated with BMI (adj OR 1.10, 95%CI 1.03-1.17), and family history of DM (adj OR 2.75, 95%CI 1.32-5.74). With respect to the late rising trajectories, baseline BMI was significantly associated with both C66 and C12 trajectory (adj OR 1.10, 95%CI 1.03-1.18) and (adj OR 1.13, 95%CI 1.05-1.23) respectively, whereas, the C12 trajectory was also significantly associated with age (adj OR 1.62, 95%CI 1.04-2.53) and history of MACE (adj OR 3.20, 95%CI 1.14-8.93).

CONCLUSIONS

We suggest that perhaps a more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c, whether they have normal hemoglobin A1c or they have prediabetes.KEY MESSAGESProgression to diabetes from normal or prediabetic hemoglobin A1c within four years is associated with baseline BMI.A steady rise in HbA1c during a four-year period is associated with age and family history of T2DM, whereas age and personal history of MACE are associated with a rapid rise in HbA1c.A more aggressive preventative approach should be considered in patients with a family history of T2DM who have high BMI and year-to-year increase in HbA1c.

The Fruit and Veggies for Kidney Health Study: A Prospective Randomized Trial

Rationale & Objective

Providing fruits and vegetables (F&Vs) to health care system patients with elevated urine albumin-creatinine ratio (ACR) reduced ACR, slowed chronic kidney disease (CKD) progression and reduced cardiovascular disease (CVD) risk factors in previous studies. This study evaluated a community-based strategy in lower-income populations to identify African Americans with elevated ACR before health care system involvement and sustain them in a 6-month F&V protocol with (F&V + Cook) and without (F&V Only) cooking instructions, with the hypothesis that adjuvant cooking instructions with F&Vs would further reduce ACR.

Study Design

Prospective, randomized, parallel 2-arm design.

Setting & Participants

African American adults with ACR >10 mg/g creatinine randomized to 1 of 2 study arms.

Interventions

Two cups/day of F&Vs with or without cooking instructions in participants followed 6 months.

Outcomes

Participants sustaining the F&V protocol and between-group indicators of CVD risk, kidney injury, and dietary intake at 6 weeks and 6 months.

Results

A total of 142 African American adults (mean age, 57.0 years; ACR, 27.4 mg/g; body mass index, 34.4; 24.9% CKD 1; 24.8% CKD 2; 50.4% CKD 3; 55% female) randomized to F&V Only (n=72) or F&V + Cook (n=70), and 71% were retained at 6 months. Participants received 90% of available F&V pick-ups over 6 weeks and 69% over 6 months. In the adjusted model, 6-month ACR was 31% lower for F&V + Cook than F&V Only (P = 0.02). Net 6-week F&V intake significantly increased and biometric variables improved for participants combined into a single group.

Limitations

Small sample size, low-baseline ACR, and potential nonresponse bias for 24-hour dietary recall measure.

Conclusions

These data support the feasibility of identifying community-dwelling African Americans with ACR indicating elevated CVD and CKD risk and sustaining a F&V protocol shown to improve kidney outcomes and CVD risk factors and provides preliminary evidence that cooking instructions adjuvant to F&Vs are needed to lower ACR.

Funding

National Institute on Diabetes, Digestive, and Kidney Diseases grant "Reducing chronic kidney disease burden in an underserved population" (R21DK113440).

Trial Registration

NCT03832166.

Plain-Language Summary

African Americans, particularly those in low-income communities, have increased rates of chronic kidney disease (CKD) with worsening outcomes over time. Giving fruits and vegetables to individuals with CKD identified in health care systems was previously shown to reduce kidney damage, measured by urine protein albumin, and slow kidney function decline. We recruited African Americans in low-income communities with increased urine albumin levels. They received fruits and vegetables for 6 months, and we tested whether added cooking instructions further reduced urine albumin levels. Most participants continued to receive fruits and vegetables throughout the 6 months. Those given cooking instructions had lower urine albumin levels after 6 months, indicating decreased kidney damage. Providing cooking instructions with fruits and vegetables appears to lessen kidney damage more than just fruits and vegetables alone.

Longitudinal trajectories of glycemic control among U.S. Adults with newly diagnosed diabetes

AIMS

To identify longitudinal trajectories of glycemic control among adults with newly diagnosed diabetes, overall and by diabetes type.

METHODS

We analyzed claims data from OptumLabs® Data Warehouse for 119,952 adults newly diagnosed diabetes between 2005 and 2018. We applied a novel Mixed Effects Machine Learning model to identify longitudinal trajectories of hemoglobin A1c (HbA1c) over 3 years of follow-up and used multinomial regression to characterize factors associated with each trajectory.

RESULTS

The study population was comprised of 119,952 adults with newly diagnosed diabetes, including 696 (0.58%) with type 1 diabetes. Among patients with type 1 diabetes, 52.6% were diagnosed at very high HbA1c, partially improved, but never achieved control; 32.5% were diagnosed at low HbA1c and deteriorated over time; and 14.9% had stable low HbA1c. Among patients with type 2 diabetes, 67.7% had stable low HbA1c, 14.4% were diagnosed at very high HbA1c, partially improved, but never achieved control; 10.0% were diagnosed at moderately high HbA1c and deteriorated over time; and 4.9% were diagnosed at moderately high HbA1c and improved over time.

CONCLUSIONS

Claims data identified distinct longitudinal trajectories of HbA1c after diabetes diagnosis, which can be used to anticipate challenges and individualize care plans to improve glycemic control.

Time trajectories of key cardiometabolic parameters and of cardiovascular risk in subjects with diabetes in a real world setting

BACKGROUND AND AIMS

Diabetes is associated with increased cardiovascular risk. Glycated haemoglobin (HbA_1c), lipid parameters and blood pressure are known risk factors for adverse outcome. The aim of the study was to explore the time trajectories of these key parameters and of the associated cardiovascular risk.

METHODS

We linked the diabetes electronic health records to the laboratory information system so as to investigate the trajectories of key metabolic parameters from 3 years prior to the diagnosis of diabetes to 10 years after diagnosis. We calculated the cardiovascular risk at the different time points during this period using the United Kingdom Prospective Study (UKPDS) risk engine.

RESULTS

The study included 21,288 patients. The median age at diagnosis was 56 years and 55.3% were male. There was a sharp decrease in HbA_1c after diagnosis of diabetes, but there was a progressive rise thereafter. All lipid parameters after diagnosis also improved in the year of diagnosis, and these improvements persisted even up to 10 years post-diagnosis. There was no discernible trend in mean systolic or diastolic blood pressures following diagnosis of diabetes. There was a slight decrease in the UKPDS-estimated cardiovascular risk after diagnosis of diabetes followed by a progressive increase. Estimated glomerular filtration rate declined at an average rate of 1.33 ml/min/1.73 m²/year.

CONCLUSIONS

Our data suggest that lipid control should be tightened with increasing duration of diabetes since this is more readily achievable than HbA_1c lowering and since other factors such as age and duration of diabetes are unmodifiable.

Great diversity in the utilization and reporting of latent growth modeling approaches in type 2 diabetes: A literature review

Introduction

The progression of complications of type 2 diabetes (T2D) is unique to each patient and can be depicted through individual temporal trajectories. Latent growth modeling approaches (latent growth mixture models [LGMM] or latent class growth analysis [LCGA]) can be used to classify similar individual trajectories in a priori non-observed groups (latent groups), sharing common characteristics. Although increasingly used in the field of T2D, many questions remain regarding the utilization of these methods.

Objective

To review the literature of longitudinal studies using latent growth modeling approaches to study T2D.

Methods

MEDLINE (Ovid), EMBASE, CINAHL and Wb of Science were searched through August 25^th, 2021. Data was collected on the type of latent growth modeling approaches (LGMM or LCGA), characteristics of studies and quality of reporting using the GRoLTS-Checklist and presented as frequencies.

Results

From the 4,694 citations screened, a total of 38 studies were included. The studies were published beetween 2011 and 2021 and the length of follow-up ranged from 8 weeks to 14 years. Six studies used LGMM, while 32 studies used LCGA. The fields of research varied from clinical research, psychological science, healthcare utilization research and drug usage/pharmaco-epidemiology. Data sources included primary data (clinical trials, prospective/retrospective cohorts, surveys), or secondary data (health records/registries, medico-administrative). Fifty percent of studies evaluated trajectory groups as exposures for a subsequent clinical outcome, while 24% used predictive models of group membership and 5% used both. Regarding the quality of reporting, trajectory groups were adequately presented, however many studies failed to report important decisions made for the trajectory group identification.

Conclusion

Although LCGA were preferred, the contexts of utilization were diverse and unrelated to the type of methods. We recommend future authors to clearly report the decisions made regarding trajectory groups identification.

•

There is a growing body of literature on trajectory modeling in type 2 diabetes.

•

Latent class growth analysis can be used in many different contexts.

•

The current reporting of methods used should be improved.

Effect of Hemoglobin A1c Trajectories on Future Outcomes in a 10-Year Cohort With Type 2 Diabetes Mellitus

BACKGROUND

Hemoglobin A1c (HbA1c) variability may be a predictor of diabetic complications, but the predictive values of HbA1c trajectories remain unclear. We aimed to classify long-term HbA1c trajectories and to explore their effects on future clinical outcomes in a 10-year cohort with type 2 diabetes mellitus (T2DM).

METHODS

A total of 2,161 participants with T2DM from the Beijing Community Diabetes Study were included. The 10-year follow-up was divided into two stages for the present data analysis. Stage I (from 2008 to 2014) was used to identify the HbA1c trajectories and to calculate the adjusted SD of HbA1c (HbA1c-adjSD), or the coefficient of variation of HbA1c (HbA1c-CV). Stage II (from 2014 to 2018) was used to collect the records of the new occurrence of diabetes-related clinical outcomes. Latent growth mixture models were used to identify HbA1c trajectories. Cox proportional hazards models were used to explore the relationship between HbA1c trajectories, HbA1c-adjSD, or HbA1c-CV and the future outcomes.

RESULTS

Three HbA1c trajectories were identified, including low stable (88.34%), gradual decreasing (5.83%), and pre-stable and post-increase (5.83%). Either the risk of death or the chronic complications were significantly higher in the latter two groups compared to the low stable group after adjustment for average HbA1c and other traditional risk factors, the adjusted hazard ratios (HRs) for renal events, composite endpoint, and all-cause death for the pre-stable and post-increase group were 2.83 [95%CI: 1.25-6.41, p = 0.013], 1.85 (95%CI: 1.10-3.10, p = 0.020), and 3.01 (95%CI: 1.13-8.07, p = 0.028), respectively, and the adjusted HR for renal events for the gradual decreasing group was 2.37 (95%CI: 1.08-5.21, p = 0.032). In addition, both univariate and multivariate Cox HR models indicated that participants in the fourth and third quartiles of HbA1c-CV or HbA1c-adjSD were at higher risk of renal events compared to participants in the first quartile.

CONCLUSIONS

HbA1c trajectories, HbA1c-CV, and HbA1c-adjSD could all predict diabetes-related clinical outcomes. HbA1c trajectories could reflect long-term blood glucose fluctuation more intuitively, and non-stable HbA1c trajectories may predict increased risk of renal events, all-cause death, and composite endpoint events, independent of average HbA1c.

Examining the factors contributing to the association between non-albuminuric CKD and a low rate of kidney function decline in diabetes

BACKGROUND

Studies have shown that among people with diabetes, those with non-albuminuric chronic kidney disease (CKD) have a slower rate of reduction in renal function than do those with normal renal function. This suggests the presence of protective factors, the identification of which may open up targets for intervention. The aim of this study was to identify protective clinical factors and nonclinical biomarkers that contribute to the association between non-albuminuric CKD and the low rate of progression of CKD.

METHODS

We tested for significant associations of several clinical factors and 33 nonclinical biomarkers with (1) normoalbuminuria and (2) a low rate of CKD progression among participants with diabetes and CKD enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study in the United States. Factors significantly associated with both normoalbuminuria and a low rate of CKD progression were assessed in linear regression to estimate their potential contributions to the association between non-albuminuric CKD and rate of CKD progression.

RESULTS

Systolic blood pressure (SBP), glycated A1c (HbA1c), estimated glomerular filtration rate (eGFR) and six biomarkers [β-trace protein (BTP), kidney injury molecule (KIM-1), fibrinogen, fractalkine, brain natriuretic peptide (BNP) and high-sensitivity troponin-T (hsTnT)] were associated with both normoalbuminuria and a low rate of eGFR decline. The univariate β-coefficient for normoalbuminuria was 0.93 [95% confidence interval (CI): 0.82, 1.05]. When all associated factors and biomarkers were included, the regression coefficient decreased to 0.54 (95% CI: 0.40, 0.67). The factors that contributed to the association between non-albuminuric CKD and low rate of eGFR were lower levels of SBP, HbA1c, BTP, KIM-1, hsTnT, BNP, fibrinogen and fractalkine.

CONCLUSION

Lower levels of SBP and biomarkers that have pro-inflammatory and vascular modulating features may explain up to 40% of the association between non-albuminuric CKD and low rate of CKD progression. Further investigation of these biomarkers may lead to therapeutic interventions.

Trajectories of glycemic control with clinical pharmacy specialist management of veterans with type 2 diabetes

BACKGROUND

Improved control of glycemic control likely lowers the risk of diabetes complications and clinical pharmacy specialist (CPS) services can improve glycemic control. Though the pattern of control may also matter in terms of outcomes.

OBJECTIVES

The objective of this study was to examine the longitudinal trajectories of HbA1c among a large population of Veterans with type 2 diabetes who received CPS-led diabetes management.

METHODS

This is an observational, multicenter cohort study of Veterans with type-2 diabetes managed by CPSs between 7/1/2013 and 7/1/2017 with baseline glycosylated hemoglobin (HbA1c) level ≥8%. Two years of HbA1c measurements were used to group patients into distinct patterns of HbA1c trajectories over time using group-based trajectory modeling. Characteristics associated with successful HbA1c trajectories and association of assigned trajectories with all-cause and diabetes-related hospitalizations were analyzed using logistic regression.

RESULTS

A total of 4119 Veterans were included and able to be successfully segmented into six distinct HbA1c trajectory groups over time: High Gradually Decreasing (n = 325, 7.9%), Moderate Early Decline (n = 1692, 41.1%), Large Early Decline (n = 231, 5.6%), Uncontrolled Stable (n = 1468, 35.6%), Early Decline/Subsequent Increase (n = 266, 6.5%), and Very Uncontrolled Stable (n = 137, 3.3%). The distinguishing factor between successful and less successful trajectories appears to be the progress made within the first six months of pharmacist management.

CONCLUSIONS

Significant variability exists in the pattern of glycemic control over time of type 2 diabetes patients managed by clinical pharmacy specialists. Limited resources should be first prioritized to managing patients with very elevated HbA1c and into the first six months of CPS management.

Adherence to non-pharmacological treatment is associated with the goals of cardiovascular control and better eating habits in Mexican patients with type 2 diabetes mellitus

OBJECTIVE

To identify the association of diabetes education or medical nutrition therapy with the goals of control of cardiovascular risk indicators and dietary habits in patients with type 2 diabetes mellitus.

METHODS

Analytical cross-sectional study in 395 primary care patients. HbA1c, fasting glucose and lipid profile, blood pressure, weight, waist circumference, and body composition were measured. Dietary habits were measured using the «Instrument for measuring lifestyle in patients with type 2 diabetes mellitus» (IMEVID), in the nutrition dimension. Medical nutrition therapy (MNT) and diabetes education (DE) were considered as received by the patient when provided in their healthcare clinic.

RESULTS

Women comprised 68% of the patients, with a median of 6 years from diabetes diagnosis. Of the patients, 21% received DE and MNT, 28% DE or MNT, and 51% received neither. The HbA1c was lower in the patients with DE and MNT (7.7% ± 1.9% vs. 8.7% ± 2.3%, 8.4% ± 2.2%; p = .003) respectively. In the patients with DE and MNT, a higher proportion took physical exercise, consumed less tobacco, and had better dietary habits (p < .05). Patients who received DE and MNT achieved HbA1c and HDL-c control levels. A greater risk of HbA1c > 7% was identified when they only received DE or MNT or neither, a longer time since diagnosis of the disease and less frequent adherence to a diet to control the disease (p < .05).

CONCLUSION

Diabetes education and medical nutritional therapy favour the goal of cardiovascular risk control and better dietary habits in the patient with type 2 diabetes.

Metabolic Syndrome Including Glycated Hemoglobin A1c in Adults: Is It Time to Change?

(1) Background: To assess the suitability of replacing conventional markers used for insulin resistance and dysglycemia by HbA1c in both the quantitative and qualitative metabolic syndrome (MetS) definition criteria; (2) Methods: Confirmatory factorial analysis was used to compare three quantitative definitions of MetS that consisted of many single-factor models, one of which included HbA1c as the dysglycemia indicator. After that, the model with the better goodness-of-fit was selected. Furthermore, a new MetS qualitative definition was proposed by replacing fasting plasma glucose with HbA1c > 5.7% in the International Diabetes Federation (IDF) definition. The clinical performance of these two MetS criteria (IDF and IDF-modified including HbA1c as the dysglycemia indicator) to predict vascular damage (pulse wave velocity [PWv], intima media thickness [IMT] and albumin-to-creatinine ratio [ACR]) was estimated; (3) Results: The single-factor model including HbA1c showed the better goodness-of-fit (χ² = 2.45, df = 2, p = 0.293, CFI = 0.999, SRMR = 0.010). Additionally, the IDF-modified criteria gained in clinical performance to predict vascular damage (diagnostic Odds Ratio: 6.94, 1.34 and 1.90) for pulse wave velocity (PWv), intima media thickness (IMT) and albumin-to-creatinine ratio (ACR), respectively; and (4) Conclusions: These data suggest that HbA1c could be considered as a useful component to be included in the MetS definition.

Patient and disease characteristics of type-2 diabetes patients with or without chronic kidney disease: an analysis of the German DPV and DIVE databases

BACKGROUND

To evaluate the characteristics of type 2 diabetes (T2DM) patients with or without chronic kidney disease (CKD) in Germany.

METHODS

Using combined DPV/DIVE registry data, the analysis included patients with T2DM at least ≥ 18 years old who had an estimated glomerular filtration rate (eGFR) value available. CKD was defined as an eGFR < 60 mL/min/1.73 m2 or eGFR ≥ 60 mL/min/1.73 m2 and albuminuria (≥ 30 mg/g). Median values of the most recent treatment year per patient are reported.

RESULTS

Among 343,675 patients with T2DM 171,930 had CKD. Patients with CKD had a median eGFR of 48.9 mL/min/1.73 m2 and 51.2% had a urinary albumin level ≥ 30 mg/g. They were older, had a longer diabetes duration and a higher proportion was females compared to patients without CKD (all p < 0.001). More than half of CKD patients (53.5%) were receiving long-acting insulin-based therapy versus around 39.1% of those without (p < 0.001). CKD patients also had a higher rate of hypertension (79.4% vs 72.0%; p < 0.001). The most common antihypertensive drugs among CKD patients were renin-angiotensin-aldosteron system inhibitors (angiotensin converting enzyme inhibitors 33.8%, angiotensin receptor blockers 14.2%) and diuretics (40.2%). CKD patients had a higher rate of dyslipidemia (88.4% vs 86.3%) with higher triglyceride levels (157.9 vs 151.0 mg/dL) and lower HDL-C levels (men: 40.0 vs 42.0 mg/dL; women: 46.4 vs 50.0 mg/dL) (all p < 0.001) and a higher rate of hyperkalemia (> 5.5 mmol/L: 3.7% vs. 1.0%). Comorbidities were more common among CKD patients (p < 0.001).

CONCLUSION

The results illustrate the prevalence and morbidity burden associated with diabetic kidney disease in patients with T2DM in Germany. The data call for more attention to the presence of chronic kidney disease in patients with diabetes, should trigger intensified risk factor control up and beyond the control of blood glucose and HbA1c in these patients. They may also serve as a trigger for future investigations into this patient population asking for new treatment options to be developed.