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BMJ Open ; 12(10): e063046, 2022 10 12.
Article in English | MEDLINE | ID: covidwho-2064161


PURPOSE: The Scottish Diabetes Research Network (SDRN)-diabetes research platform was established to combine disparate electronic health record data into research-ready linked datasets for diabetes research in Scotland. The resultant cohort, 'The SDRN-National Diabetes Dataset (SDRN-NDS)', has many uses, for example, understanding healthcare burden and socioeconomic trends in disease incidence and prevalence, observational pharmacoepidemiology studies and building prediction tools to support clinical decision making. PARTICIPANTS: We estimate that >99% of those diagnosed with diabetes nationwide are captured into the research platform. Between 2006 and mid-2020, the cohort comprised 472 648 people alive with diabetes at any point in whom there were 4 million person-years of follow-up. Of the cohort, 88.1% had type 2 diabetes, 8.8% type 1 diabetes and 3.1% had other types (eg, secondary diabetes). Data are captured from all key clinical encounters for diabetes-related care, including diabetes clinic, primary care and podiatry and comprise clinical history and measurements with linkage to blood results, microbiology, prescribed and dispensed drug and devices, retinopathy screening, outpatient, day case and inpatient episodes, birth outcomes, cancer registry, renal registry and causes of death. FINDINGS TO DATE: There have been >50 publications using the SDRN-NDS. Examples of recent key findings include analysis of the incidence and relative risks for COVID-19 infection, drug safety of insulin glargine and SGLT2 inhibitors, life expectancy estimates, evaluation of the impact of flash monitors on glycaemic control and diabetic ketoacidosis and time trend analysis showing that diabetic ketoacidosis (DKA) remains a major cause of death under age 50 years. The findings have been used to guide national diabetes strategy and influence national and international guidelines. FUTURE PLANS: The comprehensive SDRN-NDS will continue to be used in future studies of diabetes epidemiology in the Scottish population. It will continue to be updated at least annually, with new data sources linked as they become available.

COVID-19 , Diabetes Mellitus, Type 2 , Diabetic Ketoacidosis , Sodium-Glucose Transporter 2 Inhibitors , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/drug therapy , Diabetes Mellitus, Type 2/epidemiology , Humans , Insulin Glargine , Middle Aged , Naphthalenesulfonates , Scotland/epidemiology
Cardiology ; 146(4): 481-488, 2021.
Article in English | MEDLINE | ID: covidwho-1201601


INTRODUCTION: Cardiovascular comorbidities may predispose to adverse outcomes in hospitalized patients with coronavirus disease 2019 (COVID-19). However, across the USA, the burden of cardiovascular comorbidities varies significantly. Whether clinical outcomes of hospitalized patients with COVID-19 differ between regions has not yet been studied systematically. Here, we report differences in underlying cardiovascular comorbidities and clinical outcomes of patients hospitalized with COVID-19 in Texas and in New York state. METHODS: We established a multicenter retrospective registry including patients hospitalized with COVID-19 between March 15 and July 12, 2020. Demographic and clinical data were manually retrieved from electronic medical records. We focused on the following outcomes: mortality, need for pharmacologic circulatory support, need for mechanical ventilation, and need for hemodialysis. Univariate and multivariate logistic regression analyses were performed. RESULTS: Patients in the Texas cohort (n = 296) were younger (57 vs. 63 years, p value <0.001), they had a higher BMI (30.3 kg/m2 vs. 28.5 kg/m2, p = 0.015), and they had higher rates of diabetes mellitus (41 vs. 30%; p = 0.014). In contrast, patients in the New York state cohort (n = 218) had higher rates of coronary artery disease (19 vs. 10%, p = 0.005) and atrial fibrillation (11 vs. 5%, p = 0.012). Pharmacologic circulatory support, mechanical ventilation, and hemodialysis were more frequent in the Texas cohort (21 vs. 13%, p = 0.020; 30 vs. 12%, p < 0.001; and 11 vs. 5%, p = 0.009, respectively). In-hospital mortality was similar between the 2 cohorts (16 vs. 18%, p = 0.469). After adjusting for differences in underlying comorbidities, only the use of mechanical ventilation remained significantly higher in the participating Texas hospitals (odds ratios [95% CI]: 3.88 [1.23, 12.24]). Median time to pharmacologic circulatory support was 8 days (interquartile range: 2, 13.8) in the Texas cohort compared to 1 day (0, 3) in the New York state cohort, while median time to in-hospital mortality was 16 days (10, 25.5) and 7 days (4, 14), respectively (both p < 0.001). In-hospital mortality was higher in the late versus the early study phase in the New York state cohort (24 vs. 14%, p = 0.050), while it was similar between the 2 phases in the Texas cohort (16 vs. 15%, p = 0.741). CONCLUSIONS: Geographical differences, including practice pattern variations and the impact of disease burden on provision of health care, are important for the evaluation of COVID-19 outcomes. Unadjusted data may cause bias affecting future regulatory policies and proper allocation of resources.

COVID-19 , Cardiovascular Diseases , Comorbidity , Hospitalization , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , Cardiovascular Diseases/epidemiology , Female , Hospital Mortality , Humans , Middle Aged , New York/epidemiology , Retrospective Studies , Texas/epidemiology