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

Impact of COVID-19 and Non-COVID-19 Hospitalized Pneumonia on Longer-Term Cardiovascular Mortality in People With Type 2 Diabetes: A Nationwide Prospective Cohort Study From Scotland

OBJECTIVE

In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim to quantify the relative cardiovascular disease (CVD) mortality risks associated with COVID-19 versus non-COVID-19 pneumonia.

RESEARCH DESIGN AND METHODS

With use of the SCI-Diabetes register, two cohorts were identified: individuals with type 2 diabetes in 2016 and at the 2020 pandemic onset. Hospital and death records were linked for determination of pneumonia exposure and CVD deaths. Poisson regression estimated rate ratios (RRs) for CVD death associated with both pneumonia types, with adjustment for confounders. Median follow-up durations were 1,461 days (2016 cohort) and 700 days (2020 cohort).

RESULTS

The adjusted RR for CVD death following non-COVID-19 pneumonia was 5.51 (95% CI 5.31-5.71) prepandemic and 7.3 (6.86-7.76) during the pandemic. For COVID-19 pneumonia, the RR was 9.13 (8.55-9.75). Beyond 30 days post pneumonia, the RRs converged, to 4.24 (3.90-4.60) for non-COVID-19 and 3.35 (3.00-3.74) for COVID-19 pneumonia, consistent even with exclusion of prior CVD cases.

CONCLUSIONS

Hospitalized pneumonia, irrespective of causal agent, marks an increased risk for CVD death immediately and over the long-term. COVID-19 pneumonia poses a higher CVD death risk than other pneumonias in the short-term, but this distinction diminishes over time. These insights underscore the need for including pneumonia in CVD risk assessments, with particular attention to the acute impact of COVID-19 pneumonia.

Cardiovascular risk management among individuals with type 2 diabetes and severe mental illness: a cohort study

AIMS/HYPOTHESIS

The aim of this study was to compare cardiovascular risk management among people with type 2 diabetes according to severe mental illness (SMI) status.

METHODS

We used linked electronic data to perform a retrospective cohort study of adults diagnosed with type 2 diabetes in Scotland between 2004 and 2020, ascertaining their history of SMI from hospital admission records. We compared total cholesterol, systolic BP and HbA1c target level achievement 1 year after diabetes diagnosis, and receipt of a statin prescription at diagnosis and 1 year thereafter, by SMI status using logistic regression, adjusting for sociodemographic factors and clinical history.

RESULTS

We included 291,644 individuals with type 2 diabetes, of whom 1.0% had schizophrenia, 0.5% had bipolar disorder and 3.3% had major depression. People with SMI were less likely to achieve cholesterol targets, although this difference did not reach statistical significance for all disorders. However, people with SMI were more likely to achieve systolic BP targets compared to those without SMI, with effect estimates being largest for schizophrenia (men: adjusted OR 1.72; 95% CI 1.49, 1.98; women: OR 1.64; 95% CI 1.38, 1.96). HbA1c target achievement differed by SMI disorder and sex. Among people without previous CVD, statin prescribing was similar or better in those with vs those without SMI at diabetes diagnosis and 1 year later. In people with prior CVD, SMI was associated with lower odds of statin prescribing at diabetes diagnosis (schizophrenia: OR 0.54; 95% CI 0.43, 0.68, bipolar disorder: OR 0.75; 95% CI 0.56, 1.01, major depression: OR 0.92; 95% CI 0.83, 1.01), with this difference generally persisting 1 year later.

CONCLUSIONS/INTERPRETATION

We found disparities in cholesterol target achievement and statin prescribing by SMI status. This reinforces the importance of clinical review of statin prescribing for secondary prevention of CVD, particularly among people with SMI.

Prediction of retinopathy progression using deep learning on retinal images within the Scottish screening programme

BACKGROUND/AIMS

National guidelines of many countries set screening intervals for diabetic retinopathy (DR) based on grading of the last screening retinal images. We explore the potential of deep learning (DL) on images to predict progression to referable DR beyond DR grading, and the potential impact on assigned screening intervals, within the Scottish screening programme.

METHODS

We consider 21 346 and 247 233 people with type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM), respectively, each contributing on average 4.8 and 4.4 screening intervals of which 1339 and 4675 intervals concluded with a referable screening episode. Information extracted from fundus images using DL was used to predict referable status at the end of interval and its predictive value in comparison to screening-assigned DR grade was assessed.

RESULTS

The DL predictor increased the area under the receiver operating characteristic curve in comparison to a predictor using current DR grades from 0.809 to 0.87 for T1DM and from 0.825 to 0.87 for T2DM. Expected sojourn time-the time from becoming referable to being rescreened-was found to be 3.4 (T1DM) and 2.7 (T2DM) weeks less for a DL-derived policy compared with the current recall policy.

CONCLUSIONS

We showed that, compared with using the current retinopathy grade, DL of fundus images significantly improves the prediction of incident referable retinopathy before the next screening episode. This can impact screening recall interval policy positively, for example, by reducing the expected time with referable disease for a fixed workload-which we show as an exemplar. Additionally, it could be used to optimise workload for a fixed sojourn time.

Ongoing burden and recent trends in severe hospitalised hypoglycaemia events in people with type 1 and type 2 diabetes in Scotland: A nationwide cohort study 2016-2022

AIMS

We examined severe hospitalised hypoglycaemia (SHH) rates in people with type 1 and type 2 diabetes in Scotland during 2016-2022, stratifying by sociodemographics.

METHODS

Using the Scottish National diabetes register (SCI-Diabetes), we identified people with type 1 and type 2 diabetes alive anytime during 2016-2022. SHH events were determined through linkage to hospital admission and death registry data. We calculated annual SHH rates overall and by age, sex, and socioeconomic status. Summary estimates of time and stratum effects were obtained by fitting adjusted generalised additive models using R package mgcv.

RESULTS

Rates for those under 20 with type 1 diabetes reached their minimum at the 2020-2021 transition, 30% below the study period average. A gradual decline over time also occurred among 20-49-year-olds with type 1 diabetes. Overall, females had 15% higher rates than males with type 2 diabetes (rate ratio 1.15, 95% CI 1.08-1.22). People in the most versus least deprived quintile experienced 2.58 times higher rates (95% CI 2.27-2.93) in type 1 diabetes and 2.33 times higher (95% CI 2.08-2.62) in type 2 diabetes.

CONCLUSIONS

Despite advances in care, SHH remains a significant problem in diabetes. Future efforts must address the large socioeconomic disparities in SHH risks.

Associations between glucagon prescribing, hospital admissions for hypoglycaemia and continuous glucose monitoring metrics in adults with type 1 diabetes

AIMS

To assess features associated with glucagon prescribing and hospital admissions with hypoglycaemia in type one diabetes.

METHODS

Observational study of 4462 adults. Outcome measures were features associated with glucagon prescriptions and predictors of hospital admissions with hypoglycaemia and high levels of glucagon prescribing.

RESULTS

74 % did not collect any glucagon prescriptions and 2.7 % collected >6 over 3.5 years. Hospital admission with hypoglycaemia (P = 0.032), impaired awareness (P = 0.049) and female sex (P < 0.001) were associated with glucagon collection. More frequent prescribing of glucagon was associated with diabetes duration (P < 0.001) and socioeconomic deprivation (P < 0.001). Higher average glucose (P = 0.047), higher time above 13.9 mM (P = 0.008) and higher SD (P = 0.002) were associated with glucagon prescribing. Diabetes duration (P < 0.001) and HbA1c (P < 0.001) were higher in people with hospitalised hypoglycaemia. Higher time above 13.9 mM (P = 0.004) and SD glucose (P < 0.001) were most clearly associated with hospitalised hypoglycaemia.

CONCLUSIONS

A minority of people with type 1 diabetes have access to glucagon suggesting more could be done to better target this treatment. Individuals with risk factors and those with frequent glucagon prescriptions should be identified for interventions known to reduce hypoglycaemia.

Type 1 diabetes incidence in Scotland between 2006 and 2019

AIMS

To describe type 1 diabetes incidence in Scotland between 2006 and 2019.

METHODS

Repeated annual cross-sectional studies of type 1 diabetes incidence were conducted. Incident cases were identified from the Scottish Care Information-Diabetes Collaboration (SCI-DC), a population-based register of people with diagnosed diabetes derived from primary and secondary care data. Mid-year population estimates for Scotland were used as the denominator to calculate annual incidence with stratification by age and sex. Joinpoint regression was used to investigate whether incidence changed during the study period. Age and sex-specific type 1 diabetes incidence over the whole time period was estimated by quintile of the Scottish Index of Multiple Deprivation (SIMD), an area-based measure, in which Q1 and Q5 denote the most and least deprived fifths of the population, respectively, with quasi-Poisson regression used to compare incidence for Q5 compared to Q1.

RESULTS

The median (IQR) age of the study population of 14,564 individuals with incident type 1 diabetes was 24.1 (12.3-42.4) years, 56% were men, 23% were in Q1 and 16% were in Q5. Incidence of T1DM was higher in men than women overall (at around 22 and 17 per 100,000, respectively) and in under 15 year olds (approximately 40 per 100,000 in both sexes) than other age groups and was similar across the study period in all strata. There was an inverse association between socio-economic status and type 1 diabetes incidence for 15-29, 30-49 and 50+ year olds [incidence rate ratio (IRR) for Q5 compared to Q1; IRR (95% CI) 0.52 (0.47-0.58), 0.68 (0.61-0.76) and 0.53(0.46-0.61), respectively] but not for under 15 year olds [1.02 (0.92-1.12)].

CONCLUSION

Incidence of type 1 diabetes varies by age, sex and socio-economic status and has remained approximately stable from 2006 to 2019 in Scotland.