New risk equations for complications of type 2 diabetes are welcome, but a broader perspective is needed

The association between sleep and diabetes outcomes - A systematic review

AIM

This study aimed to systematically review the prevalence of diagnosed sleep disorders in people with diabetes and to determine the association between sleep disorders and blood glucose levels and diabetes outcomes.

METHODS

We conducted a literature search in the following databases: MEDLINE (Pubmed), EMBASE, CINAHL, PsychInfo and Web of Science Citation Index. Meta-analysis (random-effects models) was conducted to estimate the prevalence of sleep disorders in people with diabetes.

RESULTS

Forty-one articles measured the prevalence of sleep disorders in adults with diabetes. The estimated pooled prevalence of sleep disorders in diabetes was estimated to be 52% (95% CI 42-63%). The highest pooled prevalence was observed for unspecified sleep apnea (69%; 95% CI: 59-78%), followed by obstructive sleep apnea (60%; 95% CI 39-80%), and restless leg syndrome (27%; 95% CI 20-34%). Eleven studies examined the association between sleep disorders and diabetes control and complications. The presence of comorbid sleep disorders was associated with increased diabetes outcomes.

CONCLUSIONS

Diagnosed sleep disorders are highly prevalent in people with diabetes. Sleep disorders are associated with diabetes outcomes, though there was considerable heterogeneity across studies.

Development and validation of a Health Policy Model of Type 2 diabetes in Chinese setting

Aim: Due to the difference in epidemiology and outcomes between eastern and western populations with Type 2 diabetes mellitus (T2DM), an important challenge is determining how useful the outcomes from diabetes models based on western populations are for eastern patients. Consequently, the principal aim of this study was to develop and validate a Health Policy Model (Chinese Outcomes Model for T2DM [COMT]) for supporting Chinese medical and health economic studies. Methods: The model is created to simulate a series of important complications of T2DM diabetes based on the latest Risk Equations for Complications of Type 2 Diabetes, which was adjusted by adding the adjustment regulator to the linear predictor within the risk equation. The validity of the model was conducted by using a total of 171 validation outcomes from seven studies in eastern populations and ten studies in western populations. The simulation cohorts in the COMT model were generated by copying each validation study's baseline characteristics. Concordance was tested by assessing the difference between the identity (45°) line and the best-fitting regression of the scatterplots for the predicted versus observed outcomes. Results: The slope coefficients of the best-fitting regression line between the predicted and corresponding observed actual outcomes was 0.9631 and the R² was 0.8701. There were major differences between western and eastern populations. The slope and R² of predictions were 0.9473 and 0.9272 in the eastern population and 1.0566 and 0.8863 in the western population, which showed more perfect agreement with the observed values in the eastern population than the western populations. The subset of macro-vascular and micro-vascular outcomes in the eastern population showed an identical tendency (the slope coefficient was close to 1), and mortality outcomes showed a slight tendency toward overestimation (the slope coefficient was close to 0.9208). Some degree of underprediction of macro-vascular and micro-vascular end points and overprediction of mortality end point was found in the western population. Conclusion: The COMT diabetes model simulated the long-term patient outcomes observed in eastern Asian T2DM patients with prediction accuracy. This study supports the COMT as a credible tool for Chinese healthcare decision makers. Further work is necessary to incorporate new local data to improve model validity and credibility.