Glucose control using a closed-loop device decreases inflammation after cardiovascular surgery without increasing hypoglycemia risk

Successful treatment of diabetic ketoacidosis secondary to fulminant type 1 diabetes mellitus using a closed-loop artificial pancreas in a pediatric patient

Diabetic ketoacidosis (DKA) is a life-threatening complication of pediatric diabetes mellitus (DM). A bedside closed-loop artificial pancreas (AP) (STG-55; NIKKISO, Tokyo, Japan) maintains the blood glucose (BG) levels within the target range via automatic infusion of insulin and glucose. We report the application of the closed-loop AP to safely control the BG levels of a pediatric patient with DKA. A 12-year-old child with an unremarkable medical history presented with fever and restlessness. The patient was diagnosed with DKA secondary to fulminant type 1 DM and was treated with insulin infusion. He presented with Glasgow Coma Scale of E2V3M4. Arterial blood gas analysis revealed metabolic acidosis and BG levels of 489 mg/dL. His urine test was positive for ketones. Along with infusion therapy, automatic BG control using a closed-loop AP was initiated after ICU admission. This was adjusted to maintain BG levels within 100 mg/dL/6 h or less. After 24 h in the ICU, the patient regained consciousness and recovered from the metabolic acidosis. His general condition improved, and he was prescribed a diet treatment. The treatment was shifted to continuous insulin infusion, and he was transferred to the general ward, and was discharged on the 33rd day of hospitalization. The closed-loop AP prevented repetitive blood extractions, achieved prompt glycemic control, and prevented cerebral edema in a pediatric patient with DKA. This is the first report of successful treatment of DKA using a bedside closed-loop AP.

Perioperative Glycemic Management in Cardiac Surgery: A Narrative Review

Diabetes and hyperglycemic events in cardiac surgical patients are associated with postoperative morbidity and mortality. The causes of dysglycemia, the abnormal fluctuations in blood glucose concentrations, in the perioperative period include surgical stress, surgical techniques, medications administered perioperatively, and patient factors. Both hyperglycemia and hypoglycemia lead to poor outcomes after cardiac surgery. While trying to control blood glucose concentration tightly for better postoperative outcomes, hypoglycemia is the main adverse event. Currently, there is no definite consensus on the optimum perioperative blood glucose concentration to be maintained in cardiac surgical patients. This review provides an overview of perioperative glucose homeostasis, the pathophysiology of dysglycemia, factors that affect glycemic control in cardiac surgery, and current practices for glycemic control in cardiac surgery.

Glycemic targets in critically ill adults: A mini-review

Illness-induced hyperglycemia impairs neutrophil function, increases pro-inflammatory cytokines, inhibits fibrinolysis, and promotes cellular damage. In turn, these mechanisms lead to pneumonia and surgical site infections, prolonged mechanical ventilation, prolonged hospitalization, and increased mortality. For optimal glucose control, blood glucose measurements need to be done accurately, frequently, and promptly. When choosing glycemic targets, one should keep the glycemic variability < 4 mmol/L and avoid targeting a lower limit of blood glucose < 4.4 mmol/L. The upper limit of blood glucose should be set according to casemix and the quality of glucose control. A lower glycemic target range (i.e., blood glucose 4.5-7.8 mmol/L) would be favored for patients without diabetes mellitus, with traumatic brain injury, or who are at risk of surgical site infection. To avoid harm from hypoglycemia, strict adherence to glycemic control protocols and timely glucose measurements are required. In contrast, a higher glycemic target range (i.e., blood glucose 7.8-10 mmol/L) would be favored as a default choice for medical-surgical patients and patients with diabetes mellitus. These targets may be modified if technical advances for blood glucose measurement and control can be achieved.

The development of a glucose prediction model in critically ill patients

PURPOSE

The aim of the current study is to develop a prediction model for glucose levels applicable for all patients admitted to the ICU with an expected ICU stay of at least 24 h. This model will be incorporated in a closed-loop glucose system to continuously and automatically control glucose values.

METHODS

Data from a previous single-center randomized controlled study was used. All patients received a FreeStyle Navigator II subcutaneous CGM system from Abbott during their ICU stay. The total dataset was randomly divided into a training set and a validation set. A glucose prediction model was developed based on historical glucose data. Accuracy of the prediction model was determined using the Mean Squared Difference (MSD), the Mean Absolute Difference (MAD) and a Clarke Error Grid (CEG).

RESULTS

The dataset included 94 ICU patients with a total of 134,673 glucose measurements points that were used for modelling. MSD was 0.410 ± 0.495 for the model, the MAD was 5.19 ± 2.63 and in the CEG 99.8% of the data points were in the clinically acceptable regions.

CONCLUSION

In this study a glucose prediction model for ICU patients is developed. This study shows that it is possible to accurately predict a patient's glucose 30 min ahead based on historical glucose data. This is the first step in the development of a closed-loop glucose system.

Closed-loop artificial endocrine pancreas from Japan

The development of a closed-loop artificial pancreas (AP) in the Western countries and Japan is different. In Western countries, wearable AP with a closed-loop glycemic control system has been developed as a treatment for patients with type 1 and type 2 diabetes. On the contrary, in Japan, bedside closed-loop AP explored by a Japanese company (Nikkiso, Tokyo, Japan) has developed as perioperative glycemic control device in surgical patients and acute care patients with emergency. In this article, we reviewed the scientific evidence in the past and present and future prospects of perioperative glycemic control using bedside AP with a closed-loop system in Japan. Conventional perioperative strict glycemic controls have three major problems: hyperglycemia, hypoglycemia, and variability in blood glucose concentrations. In Japan, perioperative strict glycemic control using the current bedside AP STG-55 (Nikkiso, Tokyo, Japan) has been developed since 2010. This novel glycemic control method achieved not only stable glycemic control without hyperglycemia, hypoglycemia, and less variability of blood glucose concentrations but also reduced postoperative infectious complications in patients undergoing major surgeries. Among the rapidly increasing number of surgical or emergency patients with diabetes, frailty, and sarcopenia of intrinsic glucose intolerance, more sophisticated and smaller AP available easily in operating rooms and intensive care units will be warranted to promote improved therapeutic outcomes in such critically ill patients.

Surgical Site Infections and Inflammatory Reaction After Cardiac Surgery; Bedside Artificial Pancreas Versus Conventional Insulin Therapy: A Propensity Score-Matched Analysis

OBJECTIVES

Perioperative hyperglycemia is associated with poor postoperative recovery, including compromised immune function and increased risk of infection. A closed-loop glycemic control system (artificial pancreas) has demonstrated strict safe perioperative glycemic control without hypoglycemia risk. The authors hypothesized that the artificial pancreas would reduce surgical site infections (SSIs) and postoperative inflammatory reactions. This study aimed to assess the effect of the artificial pancreas on SSIs and C-reactive protein (CRP) levels after cardiac surgery.

DESIGN

A single-center retrospective, propensity score-matched analysis.

SETTING

A university hospital.

PARTICIPANTS

In total, 295 patients who underwent cardiovascular surgery with cardiopulmonary bypass were included.

INTERVENTIONS

Patients were divided into two groups: artificial pancreas (target blood glucose: 120-150 mg/dL) and intravenous insulin infusion (conventional insulin therapy, target blood glucose: <200 mg/dL).

MEASUREMENTS AND MAIN RESULTS

The differences in the incidence of SSIs and CRP levels between the two groups were assessed. After 1:1 propensity score matching based on their covariates, 101 matched patients were selected from each group. The incidence of SSIs was reduced by 3%, 5% (conventional insulin therapy), and 2% (artificial pancreas), but the reduction was not statistically significant (p = 0.45). The postoperative maximum CRP level was significantly lower in the artificial pancreas group than in the conventional insulin therapy group, mean (standard deviation)14.53 (5.64) mg/dL v 16.57 (5.58) mg/dL; p = 0.01.

CONCLUSIONS

The artificial pancreas did not demonstrate a significant reduction in the incidence of SSIs. However, the artificial pancreas was safe and suppressed postoperative inflammation compared with conventional insulin therapy.

Managing hyperglycemia during the COVID-19 pandemic: Improving outcomes using new technologies in intensive care

Hyperglycemia is a significant risk for mortality in COVID-19 infections and is most dramatically noted in critically ill patients. Hyperglycemia and/or diabetes are noted in approximately 30%-40% of patients admitted with COVID-19 infections. Previous studies have shown a marked increase in mortality related to increased glucose concentrations and reduction with improved glucose control. In vivo and in vitro studies reveal the mechanisms by which hyperglycemia increases virulence and how glucose control and insulin reduce it. Optimal glucose control in intensive care is limited by manual sampling of glucose and intravenous insulin adjustment, as well as increased nursing workload and the need of protective equipment. Tools for safe and effective automation of glucose control in intensive care are discussed. A suitable closed loop device could save the lives of thousands of hospitalized hyperglycemic individuals infected with COVID-19 while protecting medical professionals from infection risk.

The Year in Cardiothoracic Critical Care: Selected Highlights from 2019

In 2019, cardiothoracic and vascular critical care remained an important focus and subspecialty. This article continues the annual series to review relevant contributions in postoperative critical care that may affect the cardiac anesthesiologist. Herein, the pertinent literature published in 2019 is explored and organized by organ system.

The Effect of Diabetes Mellitus on Prognosis of Patients with Non-Small-Cell Lung Cancer: A Systematic Review and Meta-Analysis

Purpose: To quantitatively evaluate the effect of preexisting diabetes mellitus (DM) on the outcomes of patients with non-small-cell lung cancer (NSCLC).

Materials and Methods: Observational studies comparing the prognosis of NSCLC patients with and without diabetes were identified from PubMed, EMBASE, and The Cochrane Central Register of Controlled Trials (CENTRAL). We searched for studies that published in English from inception to March 30, 2019, using search terms related to diabetes and NSCLC. Pooled hazard ratio (HR) and 95% confidence interval (CI) were calculated by a random-effect model and subgroup analyses were performed.

Results: In all, 17 of 1475 identified studies were finally included in the meta-analysis. The result revealed that preexisting diabetes had a significantly negative impact on the overall survival (OS) of patients with NSCLC (HR: 1.31, 95% CI: 1.12–1.54), especially in patients undergoing surgical treatment (HR: 1.46, 95% CI: 1.02–2.09) in comparison with those receiving only non-surgical treatment (HR: 1.33, 95% CI: 0.87–2.03). In addition, preexisting diabetes was more likely to be associated with a worse prognosis among Asian NSCLC patients than Western patients. Sensitivity analysis indicated that the main result was robust, and no evidence of publication bias was found.

Conclusion: Preexisting DM has a negative impact on diabetic NSCLC patients’ prognosis.