Cohort profile: the Scottish Diabetes Research Network national diabetes cohort – a population-based cohort of people with diabetes in Scotland

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

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.

Related collections

Most cited references 18

Record: found
Abstract: found
Article: not found

Risks of and risk factors for COVID-19 disease in people with diabetes: a cohort study of the total population of Scotland

Stuart J McGurnaghan, Amanda Weir, Jen Bishop … (2020)

Background We aimed to ascertain the cumulative risk of fatal or critical care unit-treated COVID-19 in people with diabetes and compare it with that of people without diabetes, and to investigate risk factors for and build a cross-validated predictive model of fatal or critical care unit-treated COVID-19 among people with diabetes. Methods In this cohort study, we captured the data encompassing the first wave of the pandemic in Scotland, from March 1, 2020, when the first case was identified, to July 31, 2020, when infection rates had dropped sufficiently that shielding measures were officially terminated. The participants were the total population of Scotland, including all people with diabetes who were alive 3 weeks before the start of the pandemic in Scotland (estimated Feb 7, 2020). We ascertained how many people developed fatal or critical care unit-treated COVID-19 in this period from the Electronic Communication of Surveillance in Scotland database (on virology), the RAPID database of daily hospitalisations, the Scottish Morbidity Records-01 of hospital discharges, the National Records of Scotland death registrations data, and the Scottish Intensive Care Society and Audit Group database (on critical care). Among people with fatal or critical care unit-treated COVID-19, diabetes status was ascertained by linkage to the national diabetes register, Scottish Care Information Diabetes. We compared the cumulative incidence of fatal or critical care unit-treated COVID-19 in people with and without diabetes using logistic regression. For people with diabetes, we obtained data on potential risk factors for fatal or critical care unit-treated COVID-19 from the national diabetes register and other linked health administrative databases. We tested the association of these factors with fatal or critical care unit-treated COVID-19 in people with diabetes, and constructed a prediction model using stepwise regression and 20-fold cross-validation. Findings Of the total Scottish population on March 1, 2020 (n=5 463 300), the population with diabetes was 319 349 (5·8%), 1082 (0·3%) of whom developed fatal or critical care unit-treated COVID-19 by July 31, 2020, of whom 972 (89·8%) were aged 60 years or older. In the population without diabetes, 4081 (0·1%) of 5 143 951 people developed fatal or critical care unit-treated COVID-19. As of July 31, the overall odds ratio (OR) for diabetes, adjusted for age and sex, was 1·395 (95% CI 1·304–1·494; p<0·0001, compared with the risk in those without diabetes. The OR was 2·396 (1·815–3·163; p<0·0001) in type 1 diabetes and 1·369 (1·276–1·468; p<0·0001) in type 2 diabetes. Among people with diabetes, adjusted for age, sex, and diabetes duration and type, those who developed fatal or critical care unit-treated COVID-19 were more likely to be male, live in residential care or a more deprived area, have a COVID-19 risk condition, retinopathy, reduced renal function, or worse glycaemic control, have had a diabetic ketoacidosis or hypoglycaemia hospitalisation in the past 5 years, be on more anti-diabetic and other medication (all p<0·0001), and have been a smoker (p=0·0011). The cross-validated predictive model of fatal or critical care unit-treated COVID-19 in people with diabetes had a C-statistic of 0·85 (0·83–0·86). Interpretation Overall risks of fatal or critical care unit-treated COVID-19 were substantially elevated in those with type 1 and type 2 diabetes compared with the background population. The risk of fatal or critical care unit-treated COVID-19, and therefore the need for special protective measures, varies widely among those with diabetes but can be predicted reasonably well using previous clinical history. Funding None.

0 comments Cited 161 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Estimated life expectancy in a Scottish cohort with type 1 diabetes, 2008-2010.

Shona Livingstone, Daniel Levin, Helen Looker … (2015)

Type 1 diabetes has historically been associated with a significant reduction in life expectancy. Major advances in treatment of type 1 diabetes have occurred in the past 3 decades. Contemporary estimates of the effect of type 1 diabetes on life expectancy are needed.

0 comments Cited 129 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Diabetes and pregnancy: national trends over a 15 year period

Sharon T. Mackin, Scott M Nelson, Joannes Kerssens … (2018)

Aims/hypothesis We aimed to examine time trends in national perinatal outcomes in pregnancies complicated by pre-existing type 1 or type 2 diabetes. Methods We analysed episode-level data on all obstetric inpatient delivery events (live or stillbirth) between 1 April 1998 and 31 March 2013 (n = 813,921) using the Scottish Morbidity Record (SMR02). Pregnancies to mothers with type 1 (n = 3229) and type 2 (n = 1452) diabetes were identified from the national diabetes database (Scottish Care Information-Diabetes), and perinatal outcomes were compared among women with type 1 diabetes, type 2 diabetes and those without diabetes. Results The number of pregnancies complicated by diabetes increased significantly, by 44% in type 1 diabetes and 90% in type 2 diabetes, across the 15 years examined, to rates of 1 in 210 and 1 in 504 deliveries, respectively. Compared with women without diabetes, delivery occurred 2.6 weeks earlier (type 1 diabetes 36.7 ± 2.3 weeks) and 2 weeks earlier (type 2 diabetes 37.3 ± 2.4 weeks), respectively, showing significant reductions for both type 1 (from 36.7 weeks to 36.4 weeks, p = 0.03) and type 2 (from 38.0 weeks to 37.2 weeks, p < 0.001) diabetes across the time period. The proportions of preterm delivery were markedly increased in women with diabetes (35.3% type 1 diabetes, 21.8% type 2 diabetes, 6.1% without diabetes; p < 0.0001), and these proportions increased with time for both groups (p < 0.005). Proportions of elective Caesarean sections (29.4% type 1 diabetes, 30.5% type 2 diabetes, 9.6% without diabetes) and emergency Caesarean sections (38.3% type 1 diabetes, 29.1% type 2 diabetes, 14.6% without diabetes) were greatly increased in women with diabetes and increased over time except for stable rates of emergency Caesarean section in type 1 diabetes. Gestational age-, sex- and parity-adjusted z score for birthweight (1.33 ± 1.34; p < 0.001) were higher in type 1 diabetes and increased over time from 1.22 to 1.47 (p < 0.001). Birthweight was also increased in type 2 diabetes (0.94 ± 1.34; p < 0.001) but did not alter with time. There were 65 perinatal deaths in offspring of mothers with type 1 diabetes and 39 to mothers with type 2 diabetes, representing perinatal mortality rates of 20.1 (95% CI 14.7, 24.3) and 26.9 (16.7, 32.9) per 1000 births, respectively, and rates 3.1 and 4.2 times, respectively, those observed in the non-diabetic population (p < 0.001). Stillbirth rates in type 1 and type 2 diabetes were 4.0-fold and 5.1-fold that in the non-diabetic population (p < 0.001). Perinatal mortality and stillbirth rates showed no significant fall over time despite small falls in the rates for the non-diabetic population. Conclusions/interpretation Women with diabetes are receiving increased intervention in pregnancy (earlier delivery, increased Caesarean section rates), but despite this, higher birthweights are being recorded. Improvements in rates of stillbirth seen in the general population are not being reflected in changes in stillbirth or perinatal mortality in our population with diabetes. Electronic supplementary material The online version of this article (10.1007/s00125-017-4529-3) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

0 comments Cited 56 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Journal

Journal ID (nlm-ta): BMJ Open

Journal ID (iso-abbrev): BMJ Open

Journal ID (hwp): bmjopen

Journal ID (publisher-id): bmjopen

Title: BMJ Open

Publisher: BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )

ISSN (Electronic): 2044-6055

Publication date Collection: 2022

Publication date (Electronic): 12 October 2022

Volume: 12

Issue: 10

Electronic Location Identifier: e063046

Affiliations

[1 ] departmentMRC Institute of Genetics and Cancer , The University of Edinburgh , Edinburgh, UK

[2 ] departmentNinewells Hospital , The Scottish Diabetes Research Network , Dundee, UK

[3 ] departmentSchool of Health and Life Sciences , Glasgow Caledonian University , Glasgow, UK

[4 ] departmentInstitute of Cardiovascular and Medical Sciences , University of Glasgow , Glasgow, UK

[5 ] departmentEdinburgh Centre for Endocrinology , Western General Hospital , Edinburgh, UK

[6 ] departmentInstitute of Applied Health Sciences , University of Aberdeen , Aberdeen, UK

[7 ] departmentBHF Glasgow Cardiovascular Research Centre , University of Glasgow , Glasgow, UK

[8 ] departmentInstitute of Health and Wellbeing , University of Glasgow , Glasgow, UK

[9 ] departmentDepartment of Medicine , Ninewells Hospital and Medical School , Dundee, UK

[10 ] departmentDivision of Molecular & Clinical Medicine, School of Medicine , University of Dundee , Dundee, UK

[11 ] departmentUsher Institute, College of Medicine and Veterinary Medicine , The University of Edinburgh , Edinburgh, UK

[12 ] departmentDepartment of Public Health , NHS Fife , Kirkcaldy, Fife, UK

Author notes

[Correspondence to ] Dr Stuart J. McGurnaghan; stuart.mcgurnaghan@ 123456ed.ac.uk

Author information

Stuart J. McGurnaghan http://orcid.org/0000-0002-3292-4633

Luke A. K. Blackbourn http://orcid.org/0000-0003-4234-8040

Thomas M. Caparrotta http://orcid.org/0000-0001-9009-9179

Joseph Mellor http://orcid.org/0000-0003-1452-887X

Anna Barnett http://orcid.org/0000-0002-6345-0194

Andy Collier http://orcid.org/0000-0001-5220-6244

Naveed Sattar http://orcid.org/0000-0002-1604-2593

John McKnight http://orcid.org/0000-0002-8214-7625

John Petrie http://orcid.org/0000-0002-4894-9819

Sam Philip http://orcid.org/0000-0001-6164-211X

Robert Lindsay http://orcid.org/0000-0002-9868-5217

Katherine Hughes http://orcid.org/0000-0001-5278-5282

David McAllister http://orcid.org/0000-0003-3550-1764

Graham P Leese http://orcid.org/0000-0003-0570-5678

Ewan R Pearson http://orcid.org/0000-0001-9237-8585

Sarah Wild http://orcid.org/0000-0001-7824-2569

Paul M McKeigue http://orcid.org/0000-0002-5217-1034

Helen M Colhoun http://orcid.org/0000-0002-8345-3288

Article

Publisher ID: bmjopen-2022-063046

DOI: 10.1136/bmjopen-2022-063046

PMC ID: 9562713

PubMed ID: 36223968

SO-VID: e1dde249-3871-4f0a-a779-f77ef512b358

License:

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

History

Date received : 24 March 2022

Date accepted : 16 September 2022

Funding

Funded by: Diabetes UK;

Award ID: 17/0005627

Funded by: Chief Scientist Office Scotland;

Award ID: ETM/47

Custom metadata

special-feature unlocked

ScienceOpen disciplines: Medicine

Keywords: epidemiology,diabetes & endocrinology,health informatics

Data availability:

ScienceOpen disciplines: Medicine

Keywords: epidemiology, diabetes & endocrinology, health informatics

Comments

Comment on this article

scite_

Cited by 3

See all cited by

Most referenced authors 240

See all reference authors

Cohort profile: the Scottish Diabetes Research Network national diabetes cohort – a population-based cohort of people with diabetes in Scotland

Read this article at

Abstract

Purpose

Participants

Findings to date

Future plans

Related collections

Novel Coronavirus Disease COVID-19

Most cited references 18

Risks of and risk factors for COVID-19 disease in people with diabetes: a cohort study of the total population of Scotland

Estimated life expectancy in a Scottish cohort with type 1 diabetes, 2008-2010.

Diabetes and pregnancy: national trends over a 15 year period

Author and article information

Journal

Affiliations

Author notes

Author information

Article

History

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 108

Cited by 3

Most referenced authors 240