ResearchPad - 0406 https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Diabetes Diagnosis and Control: Missed Opportunities to Improve Health ]]> https://www.researchpad.co/article/elastic_article_14397 Diabetes is a prevalent condition in the U.S. and worldwide, with expanding impact over time as it affects progressively younger ages as well as older ages as people live longer. Costs of diabetes to those affected and to society as a whole continue to increase. Costs are realized through daily treatment regimens throughout life to control glycemia and other risk factors for complications as diabetes progresses, diabetes complications and disability and their treatments, health care visits and hospitalization, and as indirect costs via lower quality of life and lost productivity. Diagnosing diabetes is key to affording the opportunity to treat diabetes, and diabetes control is key to reducing the risk of complications. Yet the magnitude of undiagnosed diabetes and poor control of diabetes is large. And just as certain subgroups of the population are affected disproportionately by diabetes and diabetes complications, so are they affected disproportionately by undiagnosed diabetes and poor control. This review addresses the epidemiology of undiagnosed diabetes and diabetes control, largely covering their magnitude, demographic variation, trends over time, and predictors. For diabetes control, it focuses on control of A1C, blood pressure, and lipid levels, although there are many other facets of diabetes control and preventive care that also could be examined. The review is based predominantly on data from the National Health and Nutrition Examination Survey (NHANES), a U.S. health survey that includes both an interview and examination component that has been conducted continuously since 1999 and episodically for decades earlier. The interview elicits self-reported health responses pertaining to diabetes and other medical conditions and an examination that measures glycemic indicators, blood pressure, and lipids, which provide much of the material presented herein. Data from other studies are also presented and described.

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<![CDATA[A Network Analysis of Biomarkers for Type 2 Diabetes]]> https://www.researchpad.co/article/N25216815-6f10-4bae-802e-485a9d2aadfb

Numerous studies have investigated individual biomarkers in relation to risk of type 2 diabetes. However, few have considered the interconnectivity of these biomarkers in the etiology of diabetes as well as the potential changes in the biomarker correlation network during diabetes development. We conducted a secondary analysis of 27 plasma biomarkers representing glucose metabolism, inflammation, adipokines, endothelial dysfunction, IGF axis, and iron store plus age and BMI at blood collection from an existing case-control study nested in the Nurses’ Health Study (NHS), including 1,303 incident diabetes case subjects and 1,627 healthy women. A correlation network was constructed based on pairwise Spearman correlations of the above factors that were statistically different between case and noncase subjects using permutation tests (P < 0.0005). We further evaluated the network structure separately among diabetes case subjects diagnosed <5, 5–10, and >10 years after blood collection versus noncase subjects. Although pairwise biomarker correlations tended to have similar directions comparing diabetes case subjects to noncase subjects, most correlations were stronger in noncase than in case subjects, with the largest differences observed for the insulin/HbA1c and leptin/adiponectin correlations. Leptin and soluble leptin receptor were two hubs of the network, with large numbers of different correlations with other biomarkers in case versus noncase subjects. When examining the correlation network by timing of diabetes onset, there were more perturbations in the network for case subjects diagnosed >10 years versus <5 years after blood collection, with consistent differential correlations of insulin and HbA1c. C-peptide was the most highly connected node in the early-stage network, whereas leptin was the hub for mid- or late-stage networks. Our results suggest that perturbations of the diabetes-related biomarker network may occur decades prior to clinical recognition. In addition to the persistent dysregulation between insulin and HbA1c, our results highlight the central role of the leptin system in diabetes development.

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<![CDATA[Associations of Four Community Factors With Longitudinal Change in Hemoglobin A1c Levels in Patients With Type 2 Diabetes]]> https://www.researchpad.co/article/5c8eecf7d5eed0c484efbf6d

OBJECTIVE

To evaluate associations of community factors with glycated hemoglobin (HbA1c).

RESEARCH DESIGN AND METHODS

We identified patients with type 2 diabetes who had an HbA1c ≥7.5% (58 mmol/mol) and subsequent HbA1c testing within 90–270 days. We used mixed-effect models to assess whether treatment intensification (TI) and community domains (community socioeconomic deprivation [CSD], food availability, fitness assets, and utilitarian physical activity favorability [quartiled]) were associated with HbA1c change over 6 and 24 months, controlling for demographics, HbA1c, BMI, and time with evidence of type 2 diabetes. We evaluated whether community domains modified associations of TI with HbA1c change using cross product terms.

RESULTS

There were 15,308 patients with 69,818 elevated HbA1c measures. The average reduction in HbA1c over 6 months was 0.07% less in townships with a high level of CSD (third quartile versus the first). Reductions were 0.10% greater for HbA1c in townships with the best food availability (versus worst). HbA1c reductions were 0.17–0.19% greater in census tracts in the second and third quartiles of utilitarian physical activity favorability versus the first. The association of TI with 6-month HbA1c change was weaker in townships and boroughs with the worst CSD (versus best) and in boroughs with the best fitness assets (versus worst). The association of TI with 24-month HbA1c change was weaker in census tracts with the worst CSD (versus third quartile) and strongest in census tracts most favorable for utilitarian physical activity (versus worst).

CONCLUSIONS

Community domains were associated with HbA1c change and blunted TI effectiveness.

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<![CDATA[Characteristics Associated With Decreased or Increased Mortality Risk From Glycemic Therapy Among Patients With Type 2 Diabetes and High Cardiovascular Risk: Machine Learning Analysis of the ACCORD Trial]]> https://www.researchpad.co/article/5c8eeb2bd5eed0c484ef916f

OBJECTIVE

Identifying patients who may experience decreased or increased mortality risk from intensive glycemic therapy for type 2 diabetes remains an important clinical challenge. We sought to identify characteristics of patients at high cardiovascular risk with decreased or increased mortality risk from glycemic therapy for type 2 diabetes using new methods to identify complex combinations of treatment effect modifiers.

RESEARCH DESIGN AND METHODS

The machine learning method of gradient forest analysis was applied to understand the variation in all-cause mortality within the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 10,251), whose participants were 40–79 years old with type 2 diabetes, hemoglobin A1c (HbA1c) ≥7.5% (58 mmol/mol), cardiovascular disease (CVD) or multiple CVD risk factors, and randomized to target HbA1c <6.0% (42 mmol/mol; intensive) or 7.0–7.9% (53–63 mmol/mol; standard). Covariates included demographics, BMI, hemoglobin glycosylation index (HGI; observed minus expected HbA1c derived from prerandomization fasting plasma glucose), other biomarkers, history, and medications.

RESULTS

The analysis identified four groups defined by age, BMI, and HGI with varied risk for mortality under intensive glycemic therapy. The lowest risk group (HGI <0.44, BMI <30 kg/m2, age <61 years) had an absolute mortality risk decrease of 2.3% attributable to intensive therapy (95% CI 0.2 to 4.5, P = 0.038; number needed to treat: 43), whereas the highest risk group (HGI ≥0.44) had an absolute mortality risk increase of 3.7% attributable to intensive therapy (95% CI 1.5 to 6.0; P < 0.001; number needed to harm: 27).

CONCLUSIONS

Age, BMI, and HGI may help individualize prediction of the benefit and harm from intensive glycemic therapy.

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<![CDATA[The Adiponectin Paradox for All-Cause and Cardiovascular Mortality]]> https://www.researchpad.co/article/5c354b3ad5eed0c484dc4472

Basic science studies have shown beneficial effects of adiponectin on glucose homeostasis, chronic low-grade inflammation, apoptosis, oxidative stress, and atherosclerotic processes, so this molecule usually has been considered a salutary adipokine. It was therefore quite unexpected that large prospective human studies suggested that adiponectin is simply a marker of glucose homeostasis, with no direct favorable effect on the risk of type 2 diabetes and cardiovascular disease. But even more unforeseen were data addressing the role of adiponectin on the risk of death. In fact, a positive, rather than the expected negative, relationship was reported between adiponectin and mortality rate across many clinical conditions, comprising diabetes. The biology underlying this paradox is unknown. Several explanations have been proposed, including adiponectin resistance and the confounding role of natriuretic peptides. In addition, preliminary genetic evidence speaks in favor of a direct role of adiponectin in increasing the risk of death. However, none of these hypotheses are based on robust data, so further efforts are needed to unravel the elusive role of adiponectin on cardiometabolic health and, most important, its paradoxical association with mortality rate.

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<![CDATA[FGF23 Concentration and APOL1 Genotype Are Novel Predictors of Mortality in African Americans With Type 2 Diabetes]]> https://www.researchpad.co/article/5c35441fd5eed0c484d8aa62

OBJECTIVE

Cardiovascular and renal complications contribute to higher mortality in patients with diabetes. We assessed novel and conventional predictors of mortality in African American–Diabetes Heart Study (AA-DHS) participants.

RESEARCH DESIGN AND METHODS

Associations between mortality and subclinical atherosclerosis, urine albumin–to–creatinine ratio (UACR), estimated glomerular filtration rate (eGFR), plasma fibroblast growth factor 23 (FGF23) concentration, African ancestry proportion, and apolipoprotein L1 genotypes (APOL1) were assessed in 513 African Americans with type 2 diabetes; analyses were performed using Cox proportional hazards models.

RESULTS

At baseline, participants were 55.6% female with median (25th, 75th percentile) age 55 years (49.0, 62.0), diabetes duration 8 years (5.0, 13.0), glycosylated hemoglobin 60.7 mmol/mol (48.6, 76.0), eGFR 91.3 mL/min/1.73 m2 (76.4, 111.3), UACR 12.5 mg/mmol (4.2, 51.2), and coronary artery calcium 28.5 mg Ca2+ (1.0, 348.6); 11.5% had two APOL1 renal-risk variants. After 6.6-year follow-up (5.8, 7.5), 54 deaths were recorded. Higher levels of coronary artery calcified plaque, carotid artery calcified plaque, albuminuria, and FGF23 were associated with higher mortality after adjustment for age, sex, and African ancestry proportion. A penalized Cox regression that included all covariates and predictors associated with mortality identified male sex (hazard ratio [HR] 4.17 [95% CI 1.96–9.09]), higher FGF23 (HR 2.10 [95% CI 1.59–2.78]), and absence of APOL1 renal-risk genotypes (HR 0.07 [95% CI 0.01–0.69]) as the strongest predictors of mortality.

CONCLUSIONS

Accounting for conventional risk factors, higher FGF23 concentrations and APOL1 non–renal-risk genotypes associated with higher mortality in African Americans with diabetes. These data add to growing evidence supporting FGF23 association with mortality; mechanisms whereby these novel predictors impact survival remain to be determined.

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<![CDATA[Disparities in Environmental Exposures to Endocrine-Disrupting Chemicals and Diabetes Risk in Vulnerable Populations]]> https://www.researchpad.co/article/5c35442bd5eed0c484d8af89

Burgeoning epidemiological, animal, and cellular data link environmental endocrine-disrupting chemicals (EDCs) to metabolic dysfunction. Disproportionate exposure to diabetes-associated EDCs may be an underappreciated contributor to disparities in metabolic disease risk. The burden of diabetes is not uniformly borne by American society; rather, this disease disproportionately affects certain populations, including African Americans, Latinos, and low-income individuals. The purpose of this study was to review the evidence linking unequal exposures to EDCs with racial, ethnic, and socioeconomic diabetes disparities in the U.S.; discuss social forces promoting these disparities; and explore potential interventions. Articles examining the links between chemical exposures and metabolic disease were extracted from the U.S. National Library of Medicine for the period of 1966 to 3 December 2016. EDCs associated with diabetes in the literature were then searched for evidence of racial, ethnic, and socioeconomic exposure disparities. Among Latinos, African Americans, and low-income individuals, numerous studies have reported significantly higher exposures to diabetogenic EDCs, including polychlorinated biphenyls, organochlorine pesticides, multiple chemical constituents of air pollution, bisphenol A, and phthalates. This review reveals that unequal exposure to EDCs may be a novel contributor to diabetes disparities. Efforts to reduce the individual and societal burden of diabetes should include educating clinicians on environmental exposures that may increase disease risk, strategies to reduce those exposures, and social policies to address environmental inequality as a novel source of diabetes disparities.

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<![CDATA[Acute Kidney Injury in Patients on SGLT2 Inhibitors: A Propensity-Matched Analysis]]> https://www.researchpad.co/article/5c11bec8d5eed0c48477e39f

OBJECTIVE

Sodium-glucose cotransporter-2 (SGLT2) inhibitors are new medications that improve cardiovascular and renal outcomes in patients with type 2 diabetes (T2D). However, the Food and Drug Administration has issued alerts regarding increased acute kidney injury (AKI) risk with canagliflozin and dapagliflozin. We aimed to assess the real-world risk of AKI in new SGLT2 inhibitor users in two large health care utilization cohorts of patients with T2D.

RESEARCH DESIGN AND METHODS

We used longitudinal data from the Mount Sinai chronic kidney disease registry and the Geisinger Health System cohort. We selected SGLT inhibitor users and nonusers (patients with T2D without SGLT2 inhibitor prescription). We determined AKI by the KDIGO (Kidney Disease: Improving Global Outcomes) definition (AKIKDIGO). We performed 1:1 nearest-neighbor propensity matching and calculated unadjusted hazard ratios (HRs) and adjusted HRs (aHRs; accounting for covariates poorly balanced) for AKI in primary and sensitivity analyses.

RESULTS

We identified 377 SGLT2 inhibitor users and 377 nonusers in the Mount Sinai cohort, of whom 3.8 and 9.7%, respectively, had an AKIKDIGO event over a median follow-up time of 14 months. The unadjusted hazards of AKIKDIGO were 60% lower in users (HR 0.4 [95% CI 0.2–0.7]; P = 0.01), which was unchanged (aHR 0.4 [95% CI 0.2–0.7]; P = 0.004) postadjustment. Similarly, we identified 1,207 SGLT2 inhibitor users and 1,207 nonusers in the Geisinger cohort, of whom 2.2 and 4.6% had an AKIKDIGO event. AKIKDIGO unadjusted hazards were lower in users (HR 0.5 [95% CI 0.3–0.8]; P < 0.01) with modest attenuation postadjustment for covariates (aHR 0.6 [95% CI 0.4–1.1]; P = 0.09). These estimates did not qualitatively change across several sensitivity analyses.

CONCLUSIONS

Our findings do not suggest an increased risk of AKI associated with SGLT2 inhibitor use in patients with T2D in two large health systems.

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<![CDATA[A National Effort to Prevent Type 2 Diabetes: Participant-Level Evaluation of CDC’s National Diabetes Prevention Program]]> https://www.researchpad.co/article/5c0e0ce1d5eed0c484dcfca6

OBJECTIVE

To assess participant-level results from the first 4 years of implementation of the National Diabetes Prevention Program (National DPP), a national effort to prevent type 2 diabetes in those at risk through structured lifestyle change programs.

RESEARCH DESIGN AND METHODS

Descriptive analysis was performed on data from 14,747 adults enrolled in year-long type 2 diabetes prevention programs during the period February 2012 through January 2016. Data on attendance, weight, and physical activity minutes were summarized and predictors of weight loss were examined using a mixed linear model. All analyses were performed using SAS 9.3.

RESULTS

Participants attended a median of 14 sessions over an average of 172 days in the program (median 134 days). Overall, 35.5% achieved the 5% weight loss goal (average weight loss 4.2%, median 3.1%). Participants reported a weekly average of 152 min of physical activity (median 128 min), with 41.8% meeting the physical activity goal of 150 min per week. For every additional session attended and every 30 min of activity reported, participants lost 0.3% of body weight (P < 0.0001).

CONCLUSIONS

During the first 4 years, the National DPP has achieved widespread implementation of the lifestyle change program to prevent type 2 diabetes, with promising early results. Greater duration and intensity of session attendance resulted in a higher percent of body weight loss overall and for subgroups. Focusing on retention may reduce disparities and improve overall program results. Further program expansion and investigation is needed to continue lowering the burden of type 2 diabetes nationally.

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