Association of Glycemic Control Parameters with Clinical Outcomes in Chronic Critical Illness
ABSTRACT Objective: Chronic Critical Illness (CCI) designates patients requiring prolonged mechanical ventilation and tracheostomy, with associated poor outcomes. Our study assessed the impact of glycemic parameters on outcomes in a CCI population.Methods: A retrospective case series was performed on 148 patients in The Mount Sinai Hospital Respiratory Care Unit (2009-2010). Utilizing a semi-parametric mixture model, trajectories for the daily mean blood glucose, range and hypoglycemia rate over time identified low- (n=87) and high-risk (n=61) hyperglycemia groups, and low- (n=90) and high-risk (n=58) hypoglycemia groups. The cohort was also classified as diabetes (n=48), stress hyperglycemia (n=85), or normal glucose (n=15).Results: Hospital- (28% vs. 13%, p=0.0199) and one-year mortality (66% vs. 46%, p=0.0185) were significantly greater in the high- vs. low-risk hyperglycemia groups, respectively. The hypoglycemia rate (< 70 mg/dL) was lower among ventilator-liberated patients compared to those who failed to liberate (0.092 vs. 0.130; p<0.0001). In the stress hyperglycemia group, both hospital mortality (high-risk hyperglycemia 48%, low-risk hyperglycemia 15%; p=0.0013) and 1-year mortality (high-risk 74%, low-risk 50%; p=0.0482) remained significantly different, while in the diabetes group no significant difference was seen. There were lower hypoglycemia rates with stress hyperglycemia compared to diabetes (<70 mg/dl: 0.086 vs. 0.182, p<0.0001; <40 mg/dl: 0.012 vs. 0.022, p=0.0118, respectively).Conclusion: Tighter glycemic control was associated with improved outcomes in CCI patients with stress hyperglycemia, but not in CCI patients with diabetes. Confirmation of these findings may lead to stratified glycemic control protocols in CCI patients based on the presence or absence of diabetes.
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ABSTRACT: Nanotechnology-based approaches hold substantial potential for improving the care of patients with diabetes. Nanoparticles are being developed as imaging contrast agents to assist in the early diagnosis of type 1 diabetes. Glucose nanosensors are being incorporated in implantable devices that enable more accurate and patient-friendly real-time tracking of blood glucose levels, and are also providing the basis for glucose-responsive nanoparticles that better mimic the body's physiological needs for insulin. Finally, nanotechnology is being used in non-invasive approaches to insulin delivery and to engineer more effective vaccine, cell and gene therapies for type 1 diabetes. Here, we analyse the current state of these approaches and discuss key issues for their translation to clinical practice.dressNature Reviews Drug Discovery 11/2014; 14(1). DOI:10.1038/nrd4477 · 37.23 Impact Factor