Abstract
Objective
Clinically-applicable diabetes severity measures are lacking, with no previous studies compared their predictive value to HbA1c. We developed and validated a type 2 diabetes severity score (DISSCO) and evaluated its association with risks of
hospitalisation and mortality, assessing its additional risk information to sociodemographic factors and HbA1c.
Research Design and Methods
We used UK primary and secondary care data for 139,626 individuals with type 2
diabetes between 2007-2017, aged ≥35 years, registered in 400 general practices. The study cohort was randomly divided to a training (N=111,748, 80%) to develop the severity tool, and 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 outcomes (hospitalisation due to: any
cause, diabetes, hypoglycaemia, or cardiovascular disease/procedures). Likelihood ratio (LR) tests fitted to assess significance of adding DISSCO to the sociodemographics and HbA1c models.
Results
A total of 139,626 patients aged 63±12 years, 45% women, 83% White, 18% from
deprived areas were included. Mean baseline severity scores was 1.3±2.0. In the
training cohort, 27,362 (20%) people died, and 99,951 (72%) had ≥1 hospitalisation.
A 1-unit increase in baseline DISSCO was associated with higher hazard of mortality
(HR: 1.14, 95%CI: 1.13; 1.15, AUROC=0.76), and cardiovascular hospitalisation (HR:
1.45, 95%CI: 1.43; 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to
socio-demographic 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.
Conclusions
Higher 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.
Clinically-applicable diabetes severity measures are lacking, with no previous studies compared their predictive value to HbA1c. We developed and validated a type 2 diabetes severity score (DISSCO) and evaluated its association with risks of
hospitalisation and mortality, assessing its additional risk information to sociodemographic factors and HbA1c.
Research Design and Methods
We used UK primary and secondary care data for 139,626 individuals with type 2
diabetes between 2007-2017, aged ≥35 years, registered in 400 general practices. The study cohort was randomly divided to a training (N=111,748, 80%) to develop the severity tool, and 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 outcomes (hospitalisation due to: any
cause, diabetes, hypoglycaemia, or cardiovascular disease/procedures). Likelihood ratio (LR) tests fitted to assess significance of adding DISSCO to the sociodemographics and HbA1c models.
Results
A total of 139,626 patients aged 63±12 years, 45% women, 83% White, 18% from
deprived areas were included. Mean baseline severity scores was 1.3±2.0. In the
training cohort, 27,362 (20%) people died, and 99,951 (72%) had ≥1 hospitalisation.
A 1-unit increase in baseline DISSCO was associated with higher hazard of mortality
(HR: 1.14, 95%CI: 1.13; 1.15, AUROC=0.76), and cardiovascular hospitalisation (HR:
1.45, 95%CI: 1.43; 1.46, AUROC=0.73). The LR tests showed that adding DISSCO to
socio-demographic 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.
Conclusions
Higher 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.
| Original language | English |
|---|---|
| Article number | e000962 |
| Number of pages | 11 |
| Journal | BMJ Open |
| Volume | 8 |
| Early online date | 7 May 2020 |
| DOIs | |
| Publication status | Published - 7 May 2020 |
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