Diabetes severity measured by treatment control status and number of anti-diabetic drugs affects presenteeism among workers with type 2 diabetes

Background The number of people with diabetes is increasing and resulting in major economic losses. Presenteeism accounts for the majority of economic losses, so measures against presenteeism are important. This study investigated the relationship between severity of type 2 diabetes and presenteeism. Methods A cross-sectional study was conducted among workers over 40 years of age. Participants were classified as normal group or diabetic treatment group using their medical examination results and health insurance claims data. Diabetic treatment groups were described by degree of treatment control: Good (HbA1c < 7%), Intermediate (7% ≤ HbA1c < 8%), and Poor (8% ≤ HbA1c). Therapy type was also divided into monotherapy and combination therapy. Logistic regression analysis was performed to predict presenteeism loss using the Quantity and Quality method. Results Data on 13,271 workers were analyzed. Presenteeism loss was significantly higher in all treatment control groups compared with the normal group, particularly for the intermediate and poor control groups. The monotherapy group did not differ from the normal group, but presenteeism loss was significantly higher in the combination therapy group than the normal group. Conclusions Presenteeism loss in workers with diabetes may be affected by diabetes severity, and even if treatment control were good, presenteeism loss could occur when the number of anti-diabetic drugs was high. Therefore, it is important to provide early intervention and continuous support as a preventive measure against not only diabetes and diabetes-related complications but also presenteeism.

Identification and Predictors for Cardiovascular Disease Risk Equivalents among Adults With Diabetes Mellitus

Objective: We examined diabetes mellitus (DM) as a cardiovascular disease (CVD) risk equivalent based on diabetes severity and other CVD risk factors. <p>Research Design and Methods: We pooled 4 US cohorts (ARIC, JHS, MESA, FHS-Offspring) and classified subjects by baseline DM/CVD. CVD risks between DM+/CVD- vs. DM-/CVD+ were examined by diabetes severity and in subgroups of other CVD risk factors. We developed an algorithm to identify subjects with CVD risk equivalent diabetes by comparing the relative CVD risk of being DM+/CVD- vs. DM-/CVD+. </p> <p>Results: The pooled cohort included 27,730 subjects (mean age of 58.5 years, 44.6% male). CVD rates per 1000 person-years were 16.5, 33.4, 43.2 and 71.4 among those with DM-/CVD-, DM+/CVD-, DM-/CVD+ and DM+/CVD+, respectively. Compared to those with DM-/CVD+, CVD risks were similar or higher for those with HbA1c≥7%, diabetes duration ≥10 years, or diabetes medication use while those with less severe diabetes had lower risks. Hazard ratios for DM+/CVD- vs. DM-/CVD+ were 0.96(0.86-1.07), 0.97(0.88-1.07), 0.96(0.82-1.13), 1.18(0.98-1.41), 0.93(0.85-1.02) and 1.00(0.89-1.13) among women, white race, age <55 years, triglycerides ≥2.26mmol/L, CRP≥2mg/L and eGFR<60mL/min/1.73m², respectively. In DM+/CVD- group, 19.1% had CVD risk equivalent diabetes with a lower risk score but a higher observed CVD risk. </p> <p>Conclusion: Diabetes is a CVD risk equivalent in one-fifth of CVD-free adults living with diabetes. High HbA1c, long diabetes duration, and diabetes medication use were predictors of CVD risk equivalence. Diabetes is a CVD risk equivalent for women, white people, those of younger age, with higher triglycerides or CRP, or reduced kidney function. </p>

Identification and Predictors for Cardiovascular Disease Risk Equivalents among Adults With Diabetes Mellitus

Objective: We examined diabetes mellitus (DM) as a cardiovascular disease (CVD) risk equivalent based on diabetes severity and other CVD risk factors. <p>Research Design and Methods: We pooled 4 US cohorts (ARIC, JHS, MESA, FHS-Offspring) and classified subjects by baseline DM/CVD. CVD risks between DM+/CVD- vs. DM-/CVD+ were examined by diabetes severity and in subgroups of other CVD risk factors. We developed an algorithm to identify subjects with CVD risk equivalent diabetes by comparing the relative CVD risk of being DM+/CVD- vs. DM-/CVD+. </p> <p>Results: The pooled cohort included 27,730 subjects (mean age of 58.5 years, 44.6% male). CVD rates per 1000 person-years were 16.5, 33.4, 43.2 and 71.4 among those with DM-/CVD-, DM+/CVD-, DM-/CVD+ and DM+/CVD+, respectively. Compared to those with DM-/CVD+, CVD risks were similar or higher for those with HbA1c≥7%, diabetes duration ≥10 years, or diabetes medication use while those with less severe diabetes had lower risks. Hazard ratios for DM+/CVD- vs. DM-/CVD+ were 0.96(0.86-1.07), 0.97(0.88-1.07), 0.96(0.82-1.13), 1.18(0.98-1.41), 0.93(0.85-1.02) and 1.00(0.89-1.13) among women, white race, age <55 years, triglycerides ≥2.26mmol/L, CRP≥2mg/L and eGFR<60mL/min/1.73m², respectively. In DM+/CVD- group, 19.1% had CVD risk equivalent diabetes with a lower risk score but a higher observed CVD risk. </p> <p>Conclusion: Diabetes is a CVD risk equivalent in one-fifth of CVD-free adults living with diabetes. High HbA1c, long diabetes duration, and diabetes medication use were predictors of CVD risk equivalence. Diabetes is a CVD risk equivalent for women, white people, those of younger age, with higher triglycerides or CRP, or reduced kidney function. </p>

Treatment with a DPP-4 inhibitor at time of hospital admission for COVID-19 is not associated with improved clinical outcomes: data from the COVID-PREDICT cohort study in The Netherlands

Purpose Inhibition of dipeptidyl peptidase (DPP-)4 could reduce coronavirus disease 2019 (COVID-19) severity by reducing inflammation and enhancing tissue repair beyond glucose lowering. We aimed to assess this in a prospective cohort study. Methods We studied in 565 patients with type 2 diabetes in the CovidPredict Clinical Course Cohort whether use of a DPP-4 inhibitor prior to hospital admission due to COVID-19 was associated with improved clinical outcomes. Using crude analyses and propensity score matching (on age, sex and BMI), 28 patients using a DPP-4 inhibitor were identified and compared to non-users. Results No differences were found in the primary outcome mortality (matched-analysis = odds-ratio: 0,94 [95% confidence interval: 0,69 – 1,28], p-value: 0,689) or any of the secondary outcomes (ICU admission, invasive ventilation, thrombotic events or infectious complications). Additional analyses comparing users of DPP-4 inhibitors with subgroups of non-users (subgroup 1: users of metformin and sulphonylurea; subgroup 2: users of any insulin combination), allowing to correct for diabetes severity, did not yield different results. Conclusions We conclude that outpatient use of a DPP-4 inhibitor does not affect the clinical outcomes of patients with type 2 diabetes who are hospitalized because of COVID-19 infection.

Diabetes Severity Measured by Treatment Control Status and Number of Anti-diabetic Drugs Affects Presenteeism Among Workers With Type 2 Diabetes

Background: The number of people with diabetes is increasing and resulting in major economic losses. Presenteeism accounts for the majority of economic losses, so measures against presenteeism are important. This study investigated the relationship between severity of type 2 diabetes and presenteeism.Methods: A cross-sectional study was conducted among workers over 40 years of age. Participants were classified as normal group or diabetic treatment group using their medical examination results and health insurance claims data. Diabetic treatment groups were described by degree of treatment control: Good (HbA1c <7%), Intermediate (7%≤ HbA1c <8%), and Poor (8%≤ HbA1c). Therapy type was also divided into monotherapy and combination therapy. Logistic regression analysis was performed to predict presenteeism loss using the Quantity and Quality method.Results: Data on 13271 workers were analyzed. Presenteeism loss was significantly higher in all treatment control groups compared with the normal group, particularly for the intermediate and poor control groups. The monotherapy group did not differ from the normal group, but presenteeism loss was significantly higher in the combination therapy group than the normal group.Conclusions: Presenteeism loss in workers with diabetes may be affected by diabetes severity, and even if treatment control was good, presenteeism loss could occur when the number of anti-diabetic drugs was high. Therefore, it is important to provide early intervention and continuous support as a preventive measure against not only diabetes and diabetes-related complications but also presenteeism.

Development and validation of the DIabetes Severity SCOre (DISSCO) in 139 626 individuals with type 2 diabetes: a retrospective cohort study

ObjectiveClinically applicable diabetes severity measures are lacking, with no previous studies comparing their predictive value with glycated hemoglobin (HbA1c). We developed and validated a type 2 diabetes severity score (the DIabetes Severity SCOre, DISSCO) and evaluated its association with risks of hospitalization and mortality, assessing its additional risk information to sociodemographic factors and HbA1c.Research design and methodsWe used UK primary and secondary care data for 139 626 individuals with type 2 diabetes between 2007 and 2017, aged ≥35 years, and registered in general practices in England. The study cohort was randomly divided into a training cohort (n=111 748, 80%) to develop the severity tool and a validation cohort (n=27 878). We developed baseline and longitudinal severity scores using 34 diabetes-related domains. Cox regression models (adjusted for age, gender, ethnicity, deprivation, and HbA1c) were used for primary (all-cause mortality) and secondary (hospitalization due to any cause, diabetes, hypoglycemia, or cardiovascular disease or procedures) outcomes. Likelihood ratio (LR) tests were fitted to assess the significance of adding DISSCO to the sociodemographics and HbA1c models.ResultsA total of 139 626 patients registered in 400 general practices, aged 63±12 years were included, 45% of whom were women, 83% were White, and 18% were from deprived areas. The mean baseline severity score was 1.3±2.0. Overall, 27 362 (20%) people died and 99 951 (72%) had ≥1 hospitalization. In the training cohort, a one-unit increase in baseline DISSCO was associated with higher hazard of mortality (HR: 1.14, 95% CI 1.13 to 1.15, area under the receiver operating characteristics curve (AUROC)=0.76) and cardiovascular hospitalization (HR: 1.45, 95% CI 1.43 to 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to sociodemographic variables significantly improved the predictive value of survival models, outperforming the added value of HbA1c for all outcomes. Findings were consistent in the validation cohort.ConclusionsHigher levels of DISSCO are associated with higher risks for hospital admissions and mortality. The new severity score had higher predictive value than the proxy used in clinical practice, HbA1c. This reproducible algorithm can help practitioners stratify clinical care of patients with type 2 diabetes.

Blood Co-Circulating Extracellular microRNAs and Immune Cell Subsets Associate with Type 1 Diabetes Severity

Immune cell subsets and microRNAs have been independently proposed as type 1 diabetes (T1D) diagnostic and/or prognostic biomarkers. Here, we aimed to analyze the relationships between peripheral blood circulating immune cell subsets, plasmatic microRNAs, and T1D. Blood samples were obtained from both children with T1D at diagnosis and age-sex matched healthy controls. Then, immunophenotype assessed by flow cytometry was coupled with the quantification of 60 plasmatic microRNAs by quantitative RT-PCR. The associations between immune cell frequency, plasmatic microRNAs, and the parameters of pancreatic loss, glycemic control, and diabetic ketoacidosis were assessed by logistic regression models and correlation analyses. We found that the increase in specific plasmatic microRNAs was associated with T1D disease onset (let-7c-5p, let-7d-5p, let-7f-5p, let-7i-5p, miR-146a-5p, miR-423-3p, and miR-423-5p), serum C-peptide concentration (miR-142-5p and miR-29c-3p), glycated hemoglobin (miR-26a-5p and miR-223-3p) and the presence of ketoacidosis (miR-29c-3p) more strongly than the evaluated immune cell subset frequency. Some of these plasmatic microRNAs were shown to positively correlate with numbers of blood circulating B lymphocytes (miR-142-5p) and CD4+CD45RO+ (miR-146a-5p and miR-223-3p) and CD4+CD25+ cells (miR-423-3p and miR-223-3p) in children with T1D but not in healthy controls, suggesting a disease-specific microRNA association with immune dysregulation in T1D. In conclusion, our results suggest that, while blood co-circulating extracellular microRNAs and immune cell subsets may be biologically linked, microRNAs may better provide powerful information about T1D onset and severity.