Predictors of Suboptimal Glycemic Control for Hospitalized Patients with Diabetes: Targets for Clinical Action

Limitations

A limitation of this study is that it used observational data and was conducted within a single health care system, thus potentially reducing generalizability. Nevertheless, the sample size was large, there were many clinical and demographic characteristics to be leveraged in the analysis, the statistical approach utilized a complementary regression and classification approach to adjust and present the findings, and the sample included patients from three hospitals across San Diego County with diverse patient populations.

Conclusion

While much progress has been made understanding the need for appropriate glycemic management for patient with diabetes to reduce their risk for adverse outcomes, the knowledge base is still quite limited, especially regarding optimal glycemic limits for diverse patient populations. There is a need to identify predictors of SGC if risk stratification tools are to be built that can help target therapies with the potential to reducing the risk of poor glycemic control and adverse patient outcomes. This study identified 3 readily available factors—admission blood glucose, HbA1c and steroid use—that strongly predict SGC, controlling for other patient risk factors. In general, poor pre-admission diabetes control and inpatient steroid use strongly predict SGC, and the data suggests that earlier and frequently calibrated intervention may improve inpatient glycemic control for these patient populations. We identified a range of thresholds for these variables that may provide a basis for targeted treatment on admission. In conclusion, this study has important implications for meaningful use of readily available factors to identify patients at risk for SGC. Clinical therapies and guidelines incorporating empirically derived risk-stratification tools should enhance the ability to achieve the triple aim of better health, better care quality and more efficient care costs for hospitalized patient with diabetes.

Corresponding author: Miriam Bender, PhD, RN, University of California, Irvine, 252 Berk Hall, Irvine, CA 92697, miriamb@uci.edu.

Financial disclosures: None.

Author contributions: Author contributions: conception and design, MB, TCS, JT, KH; analysis and interpretation of data, MB, TCS, JT, KH; drafting of article, MB, TCS; critical revision of the article, MB, TCS, JT, KH; administrative or technical support, JT, KH; collection and assembly of data, MB, TCS, AK.