PurposeThe Health in Central Denmark (HICD) cohort is a newly established cohort built on extensive questionnaire data linked with laboratory data and Danish national health and administrative registries. The aim is to establish an extensive resource for (1) gaining knowledge on patient-related topics and experiences that are not measured objectively at clinical health examinations and (2) long-term follow-up studies of inequality in diabetes and diabetes-related complications.ParticipantsA total of 1.3 million inhabitants reside in the Central Denmark Region. Using register data and a prespecified diabetes classification algorithm, we identified 45 507 persons aged 18–75 years with prevalent diabetes on 31 December 2018 and a group without diabetes of equal size matched by sex, age and municipality. A 90-item questionnaire was distributed to eligible members of this cohort on 18 November 2020 (estimated time required for completion: 15–20 min).Findings to dateWe invited 90 854 persons to take part in the survey, of whom 51 854 answered the questionnaire (57.1%). Among these respondents, 2,832 persons had type 1 diabetes (55.9%), 21,140 persons had type 2 diabetes (53.2%), while 27,892 persons were part of the matched group without diabetes (60.4%). In addition to questionnaire data, the cohort is linked to nationwide registries that provide extensive data on hospital diagnoses and procedures, medication use and socioeconomic status decades before enrolment while laboratory registries has provided repeated measures of biochemical markers, for example, lipids, albuminuria and glycated haemoglobin up to 10 years before enrolment.Future plansThe HICD will serve as an extensive resource for studies on patient-related information and inequality in type 1 diabetes and type 2 diabetes. Follow-up is planned to continue for at least 10 years and detailed follow-up questionnaires, including new topics, are planned to be distributed during this period, while registry data are planned to be updated every second year.
Background We aimed to examine the impact of gender and specific type of cardiovascular disease (CVD) diagnosis (ischemic heart disease [IHD], heart failure, peripheral artery disease [PAD] or stroke) on time-to-initiation of either a sodium glucose cotransporter 2 inhibitor or glucagon-like peptide 1 analogue (collectively termed cardioprotective GLD) after a dual diagnosis of type 2 diabetes (T2DM) and CVD. Methods In a nationwide cohort study, we identified patients with a new dual diagnosis of T2DM and CVD (January 1, 2012 and December 31, 2018). Cumulative user proportion (CUP) were assessed. Poisson models were used to estimate the initiation rate of cardioprotective GLDs. The final analyses were adjusted for potential confounders. Results In total, we included 70,538 patients with new-onset T2DM and CVD (38% female, mean age 70 ± 12 years at inclusion). During 183,256 person-years, 6,276 patients redeemed a prescription of a cardioprotective GLD. One-year CUPs of cardioprotective GLDs were lower in women than men. Initiation rates of GLDs were lower in women (female-to-male initiation-rate-ratio crude: 0.76, 95% CI 0.72–0.81); adjusted 0.92, 95% CI 0.87–0.97). In CVD-stratified analysis, the adjusted initiation rate ratio was lower in female patients with IHD and heart failure (IHD: 0.91 [95% CI 0.85–0.98], heart failure: 0.85 [95% CI 0.73–1.00], PAD: 0.92 [95% CI 0.78–1.09], and stroke: 1.06 [95% CI 0.93–1.20]). Conclusions Among patients with a new dual diagnosis of T2DM and CVD, female gender is associated with lower initiation rates of cardioprotective GLDs, especially if the patient has IHD or heart failure.
Purpose To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data. Patients and Methods After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18–74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the Open-Source Diabetes Classifier (OSDC), and 2) an existing Danish diabetes classifier, the Register for Selected Chronic Diseases (RSCD). These classifications were validated against self-reported data from the Health in Central Denmark survey – overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source R package osdc . Results A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730–0.813] (RSCD: 0.700 [0.653–0.744]) and positive predictive value (PPV) 0.943 [0.913–0.966] (RSCD: 0.944 [0.912–0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933–0.953] (RSCD: 0.905 [0.892–0.917]) and PPV 0.875 [0.861–0.888] (RSCD: 0.898 [0.884–0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40. Conclusion Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers.
AimTo examine disparities in glucose‐lowering drug (GLD) usage between migrants and native Danes with type 2 diabetes (T2D).Materials and MethodsIn a nationwide, register‐based cross‐sectional study of 253 364 individuals with prevalent T2D on December 31, 2018, we examined user prevalence during 2019 of (i) GLD combination therapies and (ii) individual GLD types. Migrants were grouped by origin (Middle East, Europe, Turkey, Former Yugoslavia, Pakistan, Sri Lanka, Somalia, Vietnam), and relative risk (RR) versus native Danes was computed using robust Poisson regression to adjust for clinical and socioeconomic characteristics.ResultsIn 2019, 34.7% of native Danes received combination therapy, and prevalence was lower in most migrant groups (RR from 0.78, 95% confidence interval CI 0.71‐0.85 [Somalia group] to 1.00, 95% CI 0.97‐1.04 [former Yugoslavia group]). Among native Danes, the most widely used oral GLD was metformin (used by 62.1%), followed by dipeptidyl peptidase‐4 inhibitors (13.3%), sodium‐glucose cotransporter‐2 inhibitors (11.9%) and sulphonylureas (5.2%), and user prevalence was higher in most migrant groups (RR for use of any oral GLD: 0.99, 95% CI 0.97‐1.01 [Europe group] to 1.09, 95% CI 1.06‐1.11 [Sri Lanka group]). Furthermore, 18.7% of native Danes used insulins and 13.3% used glucagon‐like peptide‐1 receptor agonists (GLP‐1RAs), but use was less prevalent in migrants (RR for insulins: 0.66, 95% CI 0.62‐0.71 [Sri Lanka group] to 0.94, 95% CI 0.89‐0.99 [Europe group]; RR for GLP‐1RAs: 0.29, 95% CI 0.22‐0.39 [Somalia group] to 0.95, 95% CI 0.89‐1.01 [Europe group]).ConclusionsDisparities in GLD types and combination therapy were evident between migrants and native Danes. Migrants were more likely to use oral GLDs and less likely to use injection‐based GLDs, particularly GLP‐1RAs, which may contribute to complication risk and mortality among this group.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.