Management of diabetes and hyperglycemia in hospitals

Effects of glucocorticoids on interstitial glucose concentrations in individuals with hematologic cancer and without known diagnosis of diabetes: a pilot study

Objective

To analyze interstitial glucose behavior during glucocorticoid use in non-diabetic patients receiving chemotherapy for hematologic malignancies.

Methods

Prospective pilot study carried out to assess interstitial glucose levels in 15 non-diabetic individuals with hematologic malignancies who received glucocorticoids in combination with chemotherapy. The FreeStyle Libre flash monitoring system (Abbott Diabetes Care) was used for up to 14 days to measure interstitial glucose.

Results

Median age and body mass index were 53 (42-61) years and 25 (23-28) kg/m² respectively. Interstitial glucose levels >180mg/dL lasting at least one hour were detected in 60% of participants. Interstitial glucose profile parameters (median and peak interstitial glucose levels and percentage of time during which interstitial glucose levels were >180mg/dL) were significantly (p<0.01) higher during glucocorticoid use (115mg/dL, 218mg/dL and 10% respectively) than after glucocorticoid discontinuation (97mg/dL, 137mg/dL and 0% respectively). Mean interstitial glucose levels increased in the afternoon and at night during glucocorticoid use.

Conclusion

This pilot study was the first to evaluate interstitial glucose levels in non-diabetic individuals using glucocorticoids in treatment of hematologic cancer. Glucocorticoid use during chemotherapy significantly increases interstitial glucose levels in these patients.

Stress Hyperglycemia Is Associated With an Increased Risk of Subsequent Development of Diabetes Among Bacteremic and Nonbacteremic Patients

OBJECTIVE

Stress hyperglycemia is associated with an increased risk of diabetes among survivors of critical illness. We investigated whether patients without diabetes hospitalized for bacteremia or nonbacteremic diseases with transient stress hyperglycemia would have a higher risk of subsequent diabetes development compared with those who remained normoglycemic.

RESEARCH DESIGN AND METHODS

This retrospective observational study was conducted on 224,534 in-patients with blood culture records. Stress hyperglycemia was defined based on the highest random glucose level ≥7.8 mmol/L during the index admission period. Diagnosis of diabetes, as the primary end point of interest, was defined based on diagnostic codes, blood test results, or medication records. Differences in cumulative incidence and hazard ratios (HRs) of diabetes between groups were assessed using the Kaplan-Meier estimator and Cox regression.

RESULTS

After exclusion of patients with preexisting or undiagnosed diabetes or indeterminate diabetes status and propensity score matching, bacteremic patients with stress hyperglycemia had a significantly higher cumulative incidence of diabetes (HR 1.7, 95% CI 1.2-2.4) compared with those who remained normoglycemic. Stress hyperglycemia was further confirmed to be a diabetes predictor independent of age, sex, comorbidity, and other serological markers. For the nonbacteremic patients, stress hyperglycemia was similarly associated with a higher cumulative incidence of diabetes (HR 1.4, 95% CI 1.2-1.7).

CONCLUSIONS

Hospitalized patients with transient stress hyperglycemia had a higher risk of subsequent diabetes development compared with their normoglycemic counterparts. Recognition of an increased risk of diabetes in these patients can allow early detection and monitoring in their subsequent follow-ups.

Effect of the Concomitant Use of Subcutaneous Basal Insulin and Intravenous Insulin Infusion in the Treatment of Severe Hyperglycemic Patients

BACKGRUOUND

No consensus exists regarding the early use of subcutaneous (SC) basal insulin facilitating the transition from continuous intravenous insulin infusion (CIII) to multiple SC insulin injections in patients with severe hyperglycemia other than diabetic ketoacidosis. This study evaluated the effect of early co-administration of SC basal insulin with CIII on glucose control in patients with severe hyperglycemia.

METHODS

Patients who received CIII for the management of severe hyperglycemia were divided into two groups: the early basal insulin group (n=86) if they received the first SC basal insulin 0.25 U/kg body weight within 24 hours of CIII initiation and ≥4 hours before discontinuation, and the delayed basal insulin group (n=79) if they were not classified as the early basal insulin group. Rebound hyperglycemia was defined as blood glucose level of >250 mg/dL in 24 hours following CIII discontinuation. Propensity score matching (PSM) methods were additionally employed for adjusting the confounding factors (n=108).

RESULTS

The rebound hyperglycemia incidence was significantly lower in the early basal insulin group than in the delayed basal insulin group (54.7% vs. 86.1%), despite using PSM methods (51.9%, 85.2%). The length of hospital stay was shorter in the early basal insulin group than in the delayed basal insulin group (8.5 days vs. 9.6 days, P=0.027). The hypoglycemia incidence did not differ between the groups.

CONCLUSION

Early co-administration of basal insulin with CIII prevents rebound hyperglycemia and shorten hospital stay without increasing the hypoglycemic events in patients with severe hyperglycemia.

Comparison of Glycemic Variability and Hypoglycemic Events in Hospitalized Older Adults Treated with Basal Insulin plus Vildagliptin and Basal-Bolus Insulin Regimen: A Prospective Randomized Study

Background: The basal−bolus insulin regimen is recommended in hospitalized patients with diabetes mellitus (DM), but has an increased risk of hypoglycemia. We aimed to compare dipeptidyl peptidase 4 inhibitors (DPP4-i) and basal−bolus insulin glycemic outcomes in hospitalized type 2 DM patients. Methods and patients: Our prospective randomized study included 102 elderly T2DM patients (82 ± 9 years, HbA1c 6.6% ± 1.9). Glycemic control: A variability coefficient assessed by continuous glucose monitoring (Free Style® sensor), mean insulin dose and hypoglycemia rates obtained with the two treatments were analyzed. Results: No differences were found between groups in glycemic control (mean daily glycemia during the first 10 days: 152.6 ± 38.5 vs. 154.2 ± 26.3 mg/dL; p = 0.8). The total doses Kg/day were 0.40 vs. 0.20, respectively (p < 0.001). A lower number of hypoglycemic events (9% vs. 15%; p < 0.04) and lower glycemic coefficient of variation (22% vs. 28%; p < 0.0002) were observed in the basal−DPP4-i compared to the basal−bolus regimen group. Conclusions: Treatment of inpatient hyperglycemia with basal insulin plus DPP4-i is an effective and safe regimen in old subjects with T2DM, with a similar mean daily glucose concentration, but lower glycemic variability and fewer hypoglycemic episodes compared to the basal bolus insulin regimen.

Machine-learning Prediction of Hypo- and Hyperglycemia from Electronic Health Records: Algorithm Development and Validation

Background

Acute blood glucose (BG) decompensations (hypoglycemia and hyperglycemia) represent a frequent and significant risk for inpatients and adversely affect patient outcomes and safety. The increasing need for BG management in inpatients poses a high demand on clinical staff and health care systems in addition.

Objective

This study aimed to generate a broadly applicable multiclass classification model for predicting BG decompensation events from patients’ electronic health records to indicate where adjustments in patient monitoring and therapeutic interventions are required. This should allow for taking proactive measures before BG levels are derailed.

Methods

A retrospective cohort study was conducted on patients who were hospitalized at a tertiary hospital in Bern, Switzerland. Using patient details and routine data from electronic health records, a multiclass prediction model for BG decompensation events (<3.9 mmol/L [hypoglycemia] or >10, >13.9, or >16.7 mmol/L [representing different degrees of hyperglycemia]) was generated based on a second-level ensemble of gradient-boosted binary trees.

Results

A total of 63,579 hospital admissions of 38,250 patients were included in this study. The multiclass prediction model reached specificities of 93.7%, 98.9%, and 93.9% and sensitivities of 67.1%, 59%, and 63.6% for the main categories of interest, which were nondecompensated cases, hypoglycemia, or hyperglycemia, respectively. The median prediction horizon was 7 hours and 4 hours for hypoglycemia and hyperglycemia, respectively.

Conclusions

Electronic health records have the potential to reliably predict all types of BG decompensation. Readily available patient details and routine laboratory data can support the decisions for proactive interventions and thus help to reduce the detrimental health effects of hypoglycemia and hyperglycemia.

Practical approach to clinical controversies in glycemic control for hospitalized surgical patients

The importance of glycemic management in surgical patient populations stems from an association between hyperglycemia and increased rates of surgical site infections, sepsis, and mortality. Various guidelines provide recommendations regarding target glucose concentrations, but all stress the importance of avoiding hypoglycemia as well. Within the surgical patient population, glycemic targets may vary further depending on the surgical service, such as cardiac surgery, neurosurgery, or reconstructive burn surgery. Glycemic management in critically ill surgical patients is achieved primarily through the use of intravenous insulin infusion protocols. These protocols can include fixed protocols, multiplication factor protocols, and computerized algorithms. In contrast, noncritically ill surgical patients are generally managed through the utilization of subcutaneous insulin with a combination of basal, bolus, and sliding scale insulin. Insulin protocols should be effective at maintaining glucose concentrations within the specified target range with minimal hypoglycemic events. Monitoring glucose concentrations while on either an intravenous or subcutaneous insulin protocol is essential. Point-of-care testing is the primary method for monitoring glucose concentrations in both critically ill and noncritically ill surgical patients and allows for adjustment of the insulin regimen. As patients move between units and to the outpatient setting, ensuring adequate follow-up is essential to maintaining control of hyperglycemia.

Stress Hyperglycemia, Diabetes Mellitus and COVID-19 Infection: Risk Factors, Clinical Outcomes and Post-Discharge Implications

The novel severe acute respiratory distress syndrome-coronavirus 2 (SARS-CoV-2) has caused one of the most substantial pandemics that has affected humanity in the last century. At the time of the preparation of this review, it has caused the death of around 5 million people around the globe. There is ample evidence linking higher mortality risk rates from Coronavirus disease-19 (COVID-19) with male gender, advancing age and comorbidities, such as obesity, arterial hypertension, cardiovascular disease, chronic obstructive pulmonary disease, diabetes mellitus, and cancer. Hyperglycemia has been found to be accompanying COVID-19 not only in individuals with overt diabetes. Many authors claim that blood glucose levels should also be monitored in non-diabetic patients; moreover, it has been confirmed that hyperglycemia worsens the prognosis even without pre-existing diabetes. The pathophysiological mechanisms behind this phenomenon are complex, remain controversial, and are poorly understood. Hyperglycemia in the setting of COVID-19 could be a consequence of deterioration in pre-existing diabetes, new-onset diabetes, stress-induced or iatrogenic due to substantial usage of corticosteroids within the context of a severe COVID-19 infection. It is also plausible that it might be a result of adipose tissue dysfunction and insulin resistance. Last but not least, SARS-CoV-2 is also claimed to trigger sporadically direct β-cell destruction and β-cell autoimmunity. Pending further validations with longitudinal data are needed to legitimize COVID-19 as a potential risk factor for the development of diabetes. Hereby, we present an emphasized critical review of the available clinical data in an attempt to unravel the complex mechanisms behind hyperglycemia in COVID-19 infection. The secondary endpoint was to evaluate the bidirectional relationship between COVID-19 and diabetes mellitus. As the worldwide pandemic is still expanding, demand for answering these questions is arising. It will be of immense help for the management of COVID-19 patients, as well as for the implementation of post-discharge policies for patients with a high risk of developing diabetes.

Preoperative diabetes complicates postsurgical recovery but does not amplify readmission risk following pancreatic surgery

BACKGROUND

Diabetes is a significant and prevalent medical condition associated with increased comorbidities, longer hospital length of stay, and higher healthcare costs. We aimed to assess the association between diabetes mellitus and postoperative outcomes following pancreatic surgeries.

METHODS

Records for patients with major elective pancreatic surgeries were retrieved retrospectively from the Nationwide Readmission Database (2010-2014). Association of diabetic status with postoperative complications, in-hospital mortality, length of stay (LOS), readmission rate, and hospital costs were investigated. Logistic regression and decision tree analyses were employed to predict adverse outcomes.

RESULTS

A total of 8,401 patients who had pancreatic surgery were included. They were categorized according to their diabetic diagnosis. Results showed that diabetic patients had a higher risk of postoperative complications compared to non-diabetics (OR: 1.27, 95% CI: 1.08-1.49, P=0.003). Bleeding and renal complications were the most significant. Uncontrolled diabetes significantly required a longer hospital stay (9.17±4.28 vs. 8.03±4.96 days, P=0.001), and incurred higher hospital costs ($34,171.04±$20,846.61 vs. $28,182.21±$24,070.27, P=0.001). After multivariate regression, no association was found with in-hospital mortality or readmission rates; however, diabetic patients' length of stay during readmission was increased at 30- and 90-day readmissions (P=0.004 and 0.007, respectively).

CONCLUSIONS

Among patients who underwent pancreatic surgery, those with diabetes had a higher rate of postoperative complications compared to non-diabetics. Additionally, diabetic patients had higher hospital charges and costs during primary admission. Initial analysis of patients with diabetes showed they had higher rates of 30- and 90-day readmissions, though this did not maintain significance after regression analysis. Exploring the mechanisms underlying this finding would aid in preventing postoperative complications and reducing healthcare costs.

Glucose and Ethanol Detection with an Affinity-Switchable Lateral Flow Assay

The lateral flow assay (LFA) is one of the most successful analytical platforms for rapid on-site detection of target substances. This type of assay has been used in many rapid diagnoses, for example, pregnancy tests and infectious disease prevention. However, applications of LFAs for very small molecules remain a demanding challenge due to the problem of obtaining the corresponding binding partners to form sandwich complexes. In this paper, we report an affinity-switchable (AS) LFA (ASLFA) for the rapid and selective detection of hydrogen peroxide (H₂O₂), glucose, and ethanol in blood serum and urine samples. Unlike classical LFAs, which rely on the "always on" interaction between the antigen and the antibody, the working principle of ASLFA is based on the gold nanoparticle-conjugated AS biotin probe Au@H₂O₂-ASB, which can be activated by H₂O₂ for binding with the streptavidin (SA) protein. In the presence of glucose and ethanol, glucose oxidase and alcohol oxidase can react with the substrate to generate H₂O₂ and thereby activate Au@H₂O₂-ASB for binding with SA. Therefore, this ASLFA approach can be an alternative for classical glucose and ethanol detection methods in a wide variety of samples, where simple and rapid on-site detection is essential.

Risk of community acquired pneumonia in patients with diabetes mellitus: Review

The article for the first time provides a relatively comprehensive overview of the main aspects of the epidemiology and clinical features of infectious pathology, i.e., community-acquired pneumonia, as comorbid and aggravating conditions in patients with type 1 and type 2 diabetes mellitus. Risk factors and pathogenetic patterns of infectious processes development, as well as the special etiological role of pneumococcal infection in this group of patients, are considered. Particular attention is paid to the possibilities of and approaches to the primary prevention of vaccine-preventable infections as the causes of the development of community-acquired pneumonia and invasive diseases in patients with diabetes mellitus with a review of international studies, guidelines, and local experience data in pneumococcal infection immunization.

Hospital management of hyperglycemia in the context of COVID-19: evidence-based clinical considerations

The COVID-19 pandemic led to an unprecedented crisis, and early on, it has been shown that diabetes is an important risk factor for complications and mortality in infected patients, as demonstrated by several studies. Moreover, hyperglycemia, regardless of whether patients have diabetes, is associated with poorer outcomes, which suggests that adequate monitoring and treatment of elevated glycemia in the hospital setting can improve patient outcomes. In patients with COVID-19, glycemic control may be impaired as a consequence of the infection itself (aggravating pre-existing diabetes and potentially precipitating new-onset diabetes), inflammation, or corticosteroid use-a well-established therapy to reduce COVID-19 complications, especially in the intensive care unit. This article reviews the link between diabetes and hyperglycemia, and COVID-19, with a brief review of potential mechanisms, along with emerging evidence on the effect of glycemic control on COVID-19 outcomes, especially in hospital settings.

Continuous glucose monitoring in the hospital: an update in the era of COVID-19

PURPOSE OF REVIEW

Continuous glucose monitoring (CGM) systems are Food and Drug Administration approved devices for the ambulatory setting; however, they remain investigational systems for inpatient use. This review summarizes the most recent and relevant literature on the use of continuous glucose monitoring in the hospital setting.

RECENT FINDINGS

CGM provides real-time glucose data that enable healthcare professionals to make proactive and timelier clinical decisions with regards to diabetes management. CGM devices appear to be safe and accurate systems for glucose monitoring in the hospital setting. Real-time CGM systems and glucose telemetry can decrease hypoglycemia and reduce hyperglycemia in hospitalized patients with diabetes. Remote glucose monitoring decreases the need of frequent Point-of-care checks and personal protective equipment use while also mitigating staff exposure risk which is timely in the advent of the COVID-19 pandemic. Although most nursing staff have limited exposure and training on CGM technology, early studies show that CGM use in the hospital is well received by nurses.

SUMMARY

Given the evidence in the current literature regarding CGM use in the hospital, CGM devices may be incorporated in the inpatient setting.

Stress hyperglycemia is associated with in-hospital mortality in patients with diabetes and acute ischemic stroke

Background and Objective

Stress hyperglycemia may occur in diabetic patients with acute severe cerebrovascular disease, but the results regarding its association with stroke outcomes are conflicting. This study aimed to examine the association between stress‐induced hyperglycemia and the occurrence of in‐hospital death in patients with diabetes and acute ischemic stroke.

Research Design and Methods

All data were from the Chinese Stroke Center Alliance (CSCA) database and were collected between 2016 and 2018 from >300 centers across China. Patients’ demographics, clinical presentation, and laboratory data were extracted from the database. The primary endpoint was in‐hospital death. The ratio of fasting blood glucose (FBG) to HbA1c was calculated, that is, the stress‐induced hyperglycemia ratio (SHR), to determine stress hyperglycemia following acute ischemic stroke.

Results

A total of 168,381 patients were included. The mean age was 66.2 ± 10.7, and 77,688 (43.0%) patients were female. The patients were divided into two groups: survivors (n = 167,499) and non‐survivors (n = 882), as well as into four groups according to their SHR quartiles (n = 42,090–42,099/quartile). There were 109 (0.26%), 142 (0.34%), 196 (0.47%), and 435 (1.03%) patients who died in the Q1, Q2, Q3, and Q4 quartiles, respectively. Compared with Q1 patients, the death risk was higher in Q4 patients (odds ratio (OR) = 4.02) (adjusted OR = 1.80, 95% confidence interval [CI] = 1.10–2.92, p = 0.018 after adjustment for traditional cardiovascular risk factors). The ROC analyses showed that SHR (AUC = 0.667, 95% CI: 0.647–0.686) had a better predictive value for mortality than that of fasting blood glucose (AUC = 0.633, 95% CI: 0.613–0.652) and HbA1c (AUC = 0.523, 95% CI: 0.504–0.543).

Conclusions

The SHR may serve as an accessory parameter for the prognosis of patients with diabetes after acute ischemic stroke. Hyperglycemia in stroke patients with diabetes mellitus is associated with a higher risk of in‐hospital death.

Early Post-Renal Transplant Hyperglycemia

CONTEXT

Though posttransplant diabetes mellitus (PTDM, occurring > 45 days after transplantation) and its complications are well described, early post-renal transplant hyperglycemia (EPTH) (< 45 days) similarly puts kidney transplant recipients at risk of infections, rehospitalizations, and graft failure and is not emphasized much in the literature. Proactive screening and management of EPTH is required given these consequences.

OBJECTIVE

The aim of this article is to promote recognition of early post-renal transplant hyperglycemia, and to summarize available information on its pathophysiology, adverse effects, and management.

METHODS

A PubMed search was conducted for "early post-renal transplant hyperglycemia," "immediate posttransplant hyperglycemia," "post-renal transplant diabetes," "renal transplant," "diabetes," and combinations of these terms. EPTH is associated with significant complications including acute graft failure, rehospitalizations, cardiovascular events, PTDM, and infections.

CONCLUSION

Patients with diabetes experience better glycemic control in end-stage renal disease (ESRD), with resurgence of hyperglycemia after kidney transplant. Patients with and without known diabetes are at risk of EPTH. Risk factors include elevated pretransplant fasting glucose, diabetes, glucocorticoids, chronic infections, and posttransplant infections. We find that EPTH increases risk of re-hospitalizations from infections (cytomegalovirus, possibly COVID-19), acute graft rejections, cardiovascular events, and PTDM. It is essential, therefore, to provide diabetes education to patients before discharge. Insulin remains the standard of care while inpatient. Close follow-up after discharge is recommended for insulin adjustment. Some agents like dipeptidyl peptidase-4 inhibitors and glucagon-like peptide-1 receptor agonists have shown promise. The tenuous kidney function in the early posttransplant period and lack of data limit the use of sodium-glucose cotransporter 2 inhibitors. There is a need for studies assessing noninsulin agents for EPTH to decrease risk of hypoglycemia associated with insulin and long-term complications of EPTH.

Silicon Micropillar Array-Based Wearable Sweat Glucose Sensor

Wearable technologies have great potential in health monitoring and disease diagnostics. As a consequence, interest in the study of wearable sensors has dramatically increased over recent years. Successful translation of this technology from research prototypes to commercial products requires addressing some of the major challenges faced by wearable sensors such as loss of, and damage in, the biological recognition layer of the skin-interfaced sensors. In this work, we propose a solution to this challenge by integrating micropillar array (MPA) surfaces as part of the sensing layer with the aim to protect and prevent the loss of the enzyme layer from mechanical stress while the sensor is worn. The proposed wearable sensing patch is composed of reference, counter, and working electrodes, all made of MPAs and is designed for measuring glucose in sweat. MPA sensing patch has a wide linear range of 50 μM to 1.4 mM, a sensitivity of 4.7 ± 0.8 μA mM^-1, and a limit of detection of 26 ± 5 μM. The glucose sensing patch was tested using human sweat where glucose-level changes were successfully measured before and after meal consumption. The developed patch provides an alternative solution to the problem of the damage to the sensor microenvironment upon wear. But in addition, it also offers a user-friendly, cost-effective, and reliable sweat analysis platform with significant potential in health monitoring applications.

16. Diabetes Care in the Hospital: Standards of Medical Care in Diabetes-2022

The American Diabetes Association (ADA) "Standards of Medical Care in Diabetes" includes the ADA's current clinical practice recommendations and is intended to provide the components of diabetes care, general treatment goals and guidelines, and tools to evaluate quality of care. Members of the ADA Professional Practice Committee, a multidisciplinary expert committee (https://doi.org/10.2337/dc22-SPPC), are responsible for updating the Standards of Care annually, or more frequently as warranted. For a detailed description of ADA standards, statements, and reports, as well as the evidence-grading system for ADA's clinical practice recommendations, please refer to the Standards of Care Introduction (https://doi.org/10.2337/dc22-SINT). Readers who wish to comment on the Standards of Care are invited to do so at professional.diabetes.org/SOC.

A prediction model for acute respiratory distress syndrome among patients with severe acute pancreatitis: a retrospective analysis

Background:

Acute respiratory distress syndrome (ARDS) is a severe complication among patients with severe acute pancreatitis (SAP), which may be associated with increased mortality in hospitalized patients. Thus, an effective model to predict ARDS in patients with SAP is urgently required.

Methods:

We retrospectively analyzed the data from the patients with SAP who recruited in Xiangya Hospital between April 2017 and May 2021. Patients meeting the Berlin definition of ARDS were categorized into the ARDS group. Logistic regression models and a nomogram were utilized in the study. Descriptive statistics, logistic regression models, and a nomogram were used in the current study.

Results:

Comorbidity of ARDS occurred in 109 (46.58%) of 234 patients with SAP. The SAP patients with ARDS group had a higher 60-day mortality rate, an increased demand for invasive mechanical ventilation, and a longer intensive care unit (ICU) stay than those without ARDS (p < .001 for all). Partial pressure of oxygen (PaO2): fraction of inspired oxygen (FiO2) < 200, platelets <125 × 109/L, lactate dehydrogenase >250 U/L, creatinine >111 mg/dL, and procalcitonin >0.5 ng/mL were independent risk variables for development of ARDS in SAP patients. The area under the curve for the model was 0.814, and the model fit was acceptable [p = .355 (Hosmer–Lemeshow)]. Incorporating these 5 factors, a nomogram was established with sufficient discriminatory power (C-index 0.814). Calibration curve indicated the proper discrimination and good calibration in the predicting nomogram model.

Conclusion:

The prediction nomogram for ARDS in patients with SAP can be applied using clinical common variables after the diagnosis of SAP. Future studies would be warranted to verify the potential clinical benefits of this model.

Stress Hyperglycemia Is Independently Associated with Persistent Organ Failure in Acute Pancreatitis

BACKGROUND/AIMS

Stress hyperglycemia is common in critical illness but it has not been clearly studied in patients with acute pancreatitis (AP). This study aimed to investigate the specific blood glucose (BG) level that defines stress hyperglycemia and to determine the impact of stress hyperglycemia on clinical outcomes in AP patients.

METHODS

AP patients admitted ≤ 48 h after abdominal pain onset were retrospectively analyzed. Patients were stratified by pre-existing diabetes and stress hyperglycemia was defined using stratified BG levels for non-diabetes and diabetes with clinical outcomes compared.

RESULTS

There were 967 non-diabetic and 114 diabetic (10.5%) patients met the inclusion criteria and the clinical outcomes between these two groups were not significantly different. In non-diabetes, the cut-off BG level of ≥ 180 mg/dl was selected to define stress hyperglycemia with an 8.8-fold higher odds ratio for persistent organ failure (POF) (95% CI 5.4-14.3; P < 0.001). For diabetes, ≥ 300 mg/dl was selected with a 7.5-fold higher odds ratio for POF (95% CI 1.7-34.3; P = 0.009). In multivariable logistic regression, stress hyperglycemia was independently associated with POF, acute necrotic collection, major infection and mortality. The combination of BG and systemic inflammatory response syndrome (SIRS) score in predicting POF was better than SIRS or Glasgow score alone.

CONCLUSIONS

This study identifies a cut-off BG level of ≥ 180 mg/dl and ≥ 300 mg/dl was optimal to define stress hyperglycemia for non-diabetic and diabetic AP patients, respectively. There was a significant relationship between stress hyperglycemia and adverse clinical outcomes.

Inpatient use of metformin and acarbose is associated with reduced mortality of COVID-19 patients with type 2 diabetes mellitus

Aims

Type 2 diabetes mellitus (T2DM) is a strong risk factor for complications of coronavirus disease 2019 (COVID‐19). The effect of T2DM medications on COVID‐19 outcomes remains unclear. In a retrospective analysis of a cohort of 131 patients with T2DM hospitalized for COVID‐19 in Wuhan, we have previously found that metformin use prior to hospitalization is associated with reduced mortality. The current study aims to investigate the effects of inpatient use of T2DM medications, including metformin, acarbose, insulin and sulfonylureas, on the mortality of COVID‐19 patients with T2DM during hospitalization.

Methods

We continue to carry out a retrospective analysis of a cohort of 131 patients with T2DM hospitalized for COVID‐19 and treated with different combinations of diabetes medications.

Results

We found that patients using metformin (p = .02) and acarbose (p = .04), alone or both together (p = .03), after admission were significantly more likely to survive than those who did not use either metformin or acarbose. 37 patients continued to take metformin after admission and 35 (94.6%) survived. Among the 57 patients who used acarbose after admission, 52 survived (91.2%). A total of 20 patients used both metformin and acarbose, while 57 used neither. Of the 20 dual‐use patients, 19 (95.0%) survived.

Conclusion

Our analyses suggest that inpatient use of metformin and acarbose together or alone during hospitalization should be studied in randomized trials.

Pharmacokinetic and pharmacodynamic bioequivalence between regular human insulin (rDNA origin) in 0.9% sodium chloride ready-to-use infusion 1 U/mL and 100 U/mL concentrate diluted to 1 U/mL in healthy males

AIM

To show pharmacokinetic (PK) and pharmacodynamic (PD) bioequivalence between Myxredlin, a novel, ready-to-use regular human insulin 1 U/mL formulation (BAX-HI), and Novolin R 100 U/mL concentrate diluted to 1 U/mL (NOVO-HI).

MATERIALS AND METHODS

This phase 1, double-blind, randomized, two-way crossover study compared the PK and PD properties of BAX-HI and NOVO-HI. A total of 58 healthy males received 0.36 U/kg of each study drug, administered intravenously over a 6-hour period, concurrent with an 8-hour euglycaemic clamp at two treatment periods separated by a washout period of 7-10 days. The primary PK endpoint was the area under the insulin concentration-time curve at steady state (SS) measured from 300 to 360 minutes (AUC_{INS-SS 300-360 min} ). The primary PD endpoint was the area under the glucose infusion rate-time curve at SS measured from 300 to 360 minutes (AUC_{GIR-SS 300-360 min} ).

RESULTS

All subjects completed the first treatment period and 54 subjects completed both treatment periods. Bioequivalence between BAX-HI and NOVO-HI was shown for the primary endpoints as the 90% confidence interval (CI) of the geometric least-squares (LS) mean ratio for AUC_{INS-SS 300-360 min} , and the 90% CI and 95% CI of the geometric LS mean ratio for AUC_{GIR-SS 300-360 min} were entirely contained within the prespecified limits of 80%-125%. Safety profiles were comparable for both study drugs and there were no serious adverse events.

CONCLUSIONS

The study showed bioequivalence between BAX-HI and NOVO-HI in terms of PK and PD characteristics in healthy males.

In-Hospital Mortality and Glycemic Control in Patients with Hospital Hyperglycemia

BACKGROUND

Stress-induced hyperglycemia is a phenomenon that occurs typically in patients hospitalized for acute disease and resolves spontaneously after regression of the acute illness. However, it can also occur in diabetes patients, a fact that is sometimes overlooked. It is thus important to make a proper diabetes diagnosis if hospitalized patients with episodes of hyperglycemia with and without diabetes are studied.

AIMS

To estimate the extent of the association between stress-induced hyperglycemia and in-hospital mortality in patients with hospital hyperglycemia (HH), and to explore potential differences between patients diagnosed with diabetes (HH-DBT) and those with stress-induced hyperglycemia (SH), but not diagnosed with diabetes.

METHODS

A cohort of adults with hospital hyperglycemia admitted to a tertiary, university hospital in Buenos Aires, Argentina, was analyzed retrospectively.

RESULTS

In the study, 2,955 patients were included and classified for analysis as 1,579 SH and 1,376 HH-DBT. Significant differences were observed in glycemic goal (35.53% SH versus 25.80% HH-DBT, p < 0.01), insulin use rate (26.66% SH versus 46.58% HH-DBT, p < 0.01), and severe hypoglycemia rate (1.32% SH versus 1.74% HH-DBT, p < 0.01). There were no differences in hypoglycemia rate (8.23% SH versus 10.53% HH-DBT) and hospital mortality. There was no increase in risk of mortality in the SH group adjusted for age, non-scheduled hospitalization, major surgical intervention, critical care, hypoglycemia, oncological disease, cardiovascular comorbidity, and prolonged hospitalization.

CONCLUSIONS

In this study, we observed better glycemic control in patients with SH than in those with HH-DBT, and there was no difference in hospital mortality.

Automated Self-Adjusting Subcutaneous Insulin Algorithm for Patients NPO or on TPN or Enteral Feedings

BACKGROUND

Perioperative diabetes patients are often treated with sliding-scale insulin, despite a lack of evidence to support therapeutic effectiveness. We introduced an automated subcutaneous insulin algorithm (SQIA) to improve glycemic control in these patients while maintaining the simplicity of a q4 hour adjustable sliding-scale insulin order set.

METHODS

In this pilot study, we implemented a fully programmed, self-adjusting SQIA as part of a structured order set in the electronic medical record for adult patients who are nil per os, or on continuous enteral tube feedings or total parenteral nutrition. The nurse only enters the current glucose in the Medication Administration Record, and then the calculated dose is shown. The new dose is based on previous dose, and current and previous glucoses. The SQIA titrates the glucose to 120-180 mg/dL. For this pilot, this order set was utilized for complex perioperative oncologic patients.

RESULTS

The median duration on the SQIA was 58 hours. Glucoses at titration initiation were highest at 206 ± 63 mg/dL, and came down to 156 ± 29 mg/dL by 72 hours. The majority of measured glucoses (66.8%, n = 647) were maintained between 80 and 180 mg/dL. There were no glucoses lower than 60 mg/dL, and only 0.3% (n = 3) were below 70 mg/dL. There was a low rate of errors (1%).

CONCLUSIONS

A simple automated SQIA can be used to titrate insulin to meet the changing metabolic requirements of individuals perioperatively and maintain glucose within the target range for these hospitalized patients.

The impact of poor post-operative glucose control on neurosurgical surgical site infections (SSI)

Elevated HbA1c is associated with increased surgical site infections (SSI) in neurosurgical patients. How blood glucose control in the early post-operative period relates to SSI is incompletely understood. We hypothesized that poor early post-operative blood glucose control would be associated with SSI. Data from patients undergoing neurosurgical procedures at University of Missouri Hospital was retrospectively collected. Post-operative blood glucose for 72 h after surgery was assessed and categorized by levels of hyperglycemia; those with glucose ≥200 mg/dl were classified as poorly controlled. Patients with SSI were compared to patients without SSI using Chi-Square test with Fisher's exact test when appropriate. Of 500 patients having surgery, 300 had at least one post-operative blood glucose measurement. Of those 300 patients, 19 (6.33%) developed SSI. Patients with SSI had significantly higher mean post-operative blood glucose levels (p = 0.0081) and a greater mean number of point-of-care glucose level measurements >150 mg/dL (p = 0.0434). Pre-operative HbA1c and SSI were not associated (p = 0.0867). SSI was associated with pre-operative glucocorticoid use (p = 0.03), longer operative procedure (p = 0.0072), and required use of post-operative insulin drip (p = 0.047). Incidence of other wound complications (cellulitis, deep infection, dehiscence) increased with increase in post-operative blood glucose levels to >225 mg/dL. Post-operative hyperglycemia is associated with SSI after neurosurgical procedures, emphasizing the importance addressing blood glucose control after surgery.

Does a strict glycemic control during acute coronary syndrome play a cardioprotective effect? Pathophysiology and clinical evidence

A hyperglycemic state, also in non-diabetic subjects, may be associated with acute coronary syndrome (ACS). Aim of this review is to describe the pathophysiologic association between ACS and hyperglycemic state, the protective mechanisms of a tight glycaemic control in ACS on CV outcomes, and the supporting clinical evidence. Several mechanisms may be responsible of a poor CV outcome in subjects with hyperglycemia during ACS. Endothelial NAPDH oxidase-2 (NOX2) activation in response to high glucose alters the balance between Raf/MAPK-dependent vasoconstriction and PI3K/Akt-dependent vasodilation in favour of constriction. Hyperglycaemia induces an overproduction of superoxide by the mitochondrial electron transport chain through different molecular mechanisms. Moreover, hyperglycaemia increases the size of the infarct by causing myocardial cell death through apoptosis and reducing the collateral blood flow. High FFA concentrations lead to toxicity mechanisms in acutely ischemic myocardium. On the other hand, a tight glycaemic control in ACS exerts a cardioprotective action by anti-inflammatory and anti-apoptotic mechanisms, anti-oxidative stress, endothelium protection, FFA reduction, anti-glucotoxic effect, IR and cardiac fuel metabolisms improvement, heart stem cells protection and reduced activation of adrenergic system. Unfortunately, the clinical studies supporting the above pathophysiological background are few and sometimes controversial, more likely due the risk of hypoglycemia linked to the insulin therapy generally used during ACS. Intriguingly, GLP-1 RA and SGLT2i, demonstrated highly effective in the cardiovascular prevention in high-risk subjects without the risk of hypoglycemia, might keep this cardioprotective effect even in acute conditions such as ASC.

Inpatient Glycemic Control With Sliding Scale Insulin in Noncritical Patients With Type 2 Diabetes: Who Can Slide?

OBJECTIVE

Despite clinical guideline recommendations, sliding scale insulin (SSI) is widely used for the hospital management of patients with type 2 diabetes (T2D). We aimed to determine which patients with T2D can be appropriately managed with SSI in non-critical care settings.

METHODS

We used electronic health records to assess inpatient glycemic control in medicine and surgical patients treated with SSI according to admission blood glucose (BG) concentration between June 2010 and June 2018. Primary outcome was the percentage of patients with T2D achieving target glycemic control, defined as mean hospital BG 70 to 180 mg/dL without hypoglycemia <70 mg/dL during SSI therapy.

RESULTS

Among 25,813 adult patients with T2D, 8,095 patients (31.4%) were treated with SSI. Among patients with admission BG <140 mg/dL and BG 140 to 180 mg/dL, 86% and 83%, respectively, achieved target control without hypoglycemia, as compared with only 18% of those with admission BG ≥250 mg/dL (P < .001). After adjusting for age, gender, body mass index (BMI), race, Charlson Comorbidity Index score, and setting, the odds of poor glycemic control increased with higher admission BG (BG 140-180 mg/dL: odds ratio [OR], 1.8; 95% CI, 1.5-2.2; BG 181-250 mg/dL: OR, 3.7; 95% CI, 3.1-4.4; BG >250 mg/dL: OR, 7.2; 95% CI, 5.8-9.0), as compared with patients with BG <140 mg/dL. A total of 1,192 patients (15%) treated with SSI required additional basal insulin during hospitalization.

CONCLUSION

Most non-intensive care unit patients with admission BG <180 mg/dL treated with SSI alone achieve target glycemic control during hospitalization, suggesting that cautious use of SSI may be a viable option for certain patients with mild hyperglycemia.

Outcomes of "Real-World" Insulin Strategies in the Management of Hospital Hyperglycemia

Context

Guidelines recommend scheduled long-acting basal and short-acting bolus insulin several times daily to manage inpatient hyperglycemia. In the “real world,” insulin therapy is complicated, with limited data on the comparative effectiveness of different insulin strategies.

Objective

This work aimed to evaluate the association of different insulin strategies with glucose control and hospital outcomes after adjustment for patient and physician factors that influence choice of therapy.

Methods

This retrospective, observational study took place at an academic hospital. Participants included noncritically ill hospitalized medical/surgical patients (n = 4558) receiving subcutaneous insulin for 75% or longer during admission. Insulin therapy was grouped into 3 strategies within the first 48 hours: basal bolus (BB: scheduled long and short/rapid n = 2358), sliding scale (SS: short/rapid acting n = 1855), or basal only (BO: long only: n = 345). Main outcome measures included glucose control: hypoglycemic days, hyperglycemic days, euglycemic days, mean glucose; and hospitalization: in-hospital mortality, length of stay (LOS), and readmissions.

Results

Initial therapy with BB was associated with more hypoglycemic (2.40; CI, 2.04 to 2.82) (P < .001) and fewer euglycemic days (0.90; CI, 0.85 to 0.97) (P = .003) than SS, whereas BO was associated with fewer hyperglycemic days (0.70; CI, 0.62 to 0.79) (P < .001), lower mean glucose (–18.03; CI, –22.46 to –12.61) (P < .001), and more euglycemic days (1.22; CI, 1.09 to 1.37) (P < .001) compared to SS. No difference in mortality, LOS, and readmissions was found. However, decreased LOS was observed in the BB subgroup with a medical diagnostic related group (0.93; CI, 0.89 to 0.97) (P < .001).

Conclusion

BO had a more favorable hyperglycemia profile than SS. BB, on the other hand, showed worse glycemic control as compared to SS. In the real-world hospital, BO may be a simpler and more effective insulin strategy.

A Machine-Generated View of the Role of Blood Glucose Levels in the Severity of COVID-19

SARS-CoV-2 started spreading toward the end of 2019 causing COVID-19, a disease that reached pandemic proportions among the human population within months. The reasons for the spectrum of differences in the severity of the disease across the population, and in particular why the disease affects more severely the aging population and those with specific preconditions are unclear. We developed machine learning models to mine 240,000 scientific articles openly accessible in the CORD-19 database, and constructed knowledge graphs to synthesize the extracted information and navigate the collective knowledge in an attempt to search for a potential common underlying reason for disease severity. The machine-driven framework we developed repeatedly pointed to elevated blood glucose as a key facilitator in the progression of COVID-19. Indeed, when we systematically retraced the steps of the SARS-CoV-2 infection, we found evidence linking elevated glucose to each major step of the life-cycle of the virus, progression of the disease, and presentation of symptoms. Specifically, elevations of glucose provide ideal conditions for the virus to evade and weaken the first level of the immune defense system in the lungs, gain access to deep alveolar cells, bind to the ACE2 receptor and enter the pulmonary cells, accelerate replication of the virus within cells increasing cell death and inducing an pulmonary inflammatory response, which overwhelms an already weakened innate immune system to trigger an avalanche of systemic infections, inflammation and cell damage, a cytokine storm and thrombotic events. We tested the feasibility of the hypothesis by manually reviewing the literature referenced by the machine-generated synthesis, reconstructing atomistically the virus at the surface of the pulmonary airways, and performing quantitative computational modeling of the effects of glucose levels on the infection process. We conclude that elevation in glucose levels can facilitate the progression of the disease through multiple mechanisms and can explain much of the differences in disease severity seen across the population. The study provides diagnostic considerations, new areas of research and potential treatments, and cautions on treatment strategies and critical care conditions that induce elevations in blood glucose levels.

Management of diabetes in elderly patients during the COVID-19 pandemic: current and future perspectives

Introduction: The COVID-19 pandemic has affected the entire population with the most deleterious effects in elders. Elders, especially those with diabetes, are at the highest risk of COVID-19 related adverse outcomes and mortality. This is usually linked to the comorbidities that accumulate with age, diabetes-related chronic inflammation, and the pandemic's psychosocial effects.Areas covered: We present some approaches to manage these complicated elderly patients with diabetes during the COVID-19 pandemic. In the inpatient setting, we suggest similar (pre-pandemic) glycemic targets and emphasize the importance of using IV insulin and possible use of continuous glucose monitoring to reduce exposure and PPE utilization. Outside the hospital, we recommend optimal glycemic control within the limits imposed by considerations of safety. We also describe the advantages and challenges of using various technological platforms in clinical care.Expert opinion: The COVID-19 pandemic has lifted the veil off serious deficiencies in the infrastructures for care at both the individual level and the population level and also highlighted some of the strengths, all of which affect individuals with diabetes and COVID-19. We anticipate that things will not return to 'normal' after the COVID-19 pandemic has run its course, but rather they will be superseded by 'New Normal.'

A human factors approach to subcutaneous insulin chart design improves user-performance: An experimental study

Insulin is a high-risk medicine that has been implicated in serious adverse events for hospital inpatients, including medication-error related deaths. Most insulin errors occur during administration, and "wrong dose" is the most common type. A paper-based subcutaneous insulin chart (the "NSIC") was developed for the Australian Commission on Safety and Quality in Health Care, using a range of human factors methods, with the aim of reducing the opportunity for errors. The present lab-based study empirically assessed whether the NSIC's human factors design translates into improved user-performance in the determination of insulin doses, compared with a pre-existing chart. Forty-one experienced nurses and 48 novice chart-users completed 60 experimental trials (30 per chart), in which they determined doses to administer to patients. Both groups determined insulin doses faster, and made fewer dose errors, when using the NSIC. These results support the utility of the usability heuristics employed in developing the chart.

Access to inpatient diabetes resources: hospital characteristics from the inaugural Queensland Inpatient Diabetes Survey

AIMS

To establish the prevalence of diabetes in Queensland hospitals and assess the availability of specialised diabetes staff, educational resources and policies for inpatient diabetes management, including assessing equity of access to these resources.

METHODS

The hospital capacity, prevalence of diabetes, diabetes-related resources and the availability of diabetes-related guidelines were assessed in 25 hospitals medical, surgical, mental health, high-dependency and intensive care wards of level 2-6 public hospitals across Queensland. Diabetes-dedicated staffing measured in full-time equivalents, care delivery resources, access to educational resources, standard policies and procedures for care were assessed.

RESULTS

Twenty-five hospitals included 4265 occupied beds. The median prevalence of diabetes was 22.9% (IQR 17.3-28.5%) with an average 2.9 FTE per 100 patients with diabetes (IQR 0-6.3). There was difficulty in accessing a diabetes educator in 48% (n = 12), diabetes specialist in 44% (n = 11), orthopaedic surgeon in 48% (n = 12), podiatrist in 58% (n = 14) and vascular surgeon in 64% (n = 16) of hospitals. Small hospitals had more difficulty accessing all members of the diabetes team compared to large hospitals including credentialled diabetes educators 33% (n = 4) versus 62% (n = 8) (p = 0.0001), diabetes specialists 17% (n = 2) versus 69% (n = 9) (p < 0.00001) and vascular surgeons 33% (n = 4) versus 92% (n = 12) (p < 0.000001). Diabetes-related staff education and regular nurse training was available in 40% (n = 10) of hospitals. A multi-disciplinary foot care team was available in 28% (n = 7) of hospitals.

CONCLUSIONS

Queensland's has a high prevalence of diabetes in hospitalised patients and they have limited and inequitable access to inpatient diabetes-related care. This article is protected by copyright. All rights reserved.

An open source tool to compute measures of inpatient glycemic control: translating from healthcare analytics research to clinical quality improvement

Objectives

The objective of this study is to facilitate monitoring of the quality of inpatient glycemic control by providing an open-source tool to compute glucometrics. To allay regulatory and privacy concerns, the tool is usable locally; no data are uploaded to the internet.

Materials and Methods

We extended code, initially developed for healthcare analytics research, to serve the clinical need for quality monitoring of diabetes. We built an application, with a graphical interface, which can be run locally without any internet connection.

Results

We verified that our code produced results identical to prior work in glucometrics. We extended the prior work by including additional metrics and by providing user customizability. The software has been used at an academic healthcare institution.

Conclusion

We successfully translated code used for research methods into an open source, user-friendly tool which hospitals may use to expedite quality measure computation for the management of inpatients with diabetes.

Admission glucose level and short-term mortality in older patients with acute myocardial infarction: results from the KORA Myocardial Infarction Registry

STUDY OBJECTIVES

To investigate the association between admission blood glucose levels and 28-day mortality as well as in-hospital complications in older patients with incident acute myocardial infarction (AMI) undergoing modern treatment.

METHODS

From a German population-based regional MI registry, 5530 patients (2016 women), aged 65-84 years, hospitalised with an incident AMI between 1 January 2009 and 31 December 2016 were included in the study. Multivariable logistic regression models were used to assess the associations between admission blood glucose and 28-day mortality as well as in-hospital complications after AMI. Analyses stratified according to age, diabetes and type of infarction (ST-elevation MI (STEMI)/non-STEMI) were conducted.

RESULTS

The adjusted ORs for the association between admission blood glucose and 28-day mortality in young-old (65-74 years) and old (75-84 years) patients with AMI were 1.40 (95% CI: 1.21 to 1.62) and 1.21 (95% CI: 0.98 to 1.50) per 1 SD increase in admission blood glucose, respectively. Furthermore, higher admission blood glucose was related to case fatality irrespective of the diabetes status and type of infarction only in the under-75 group. For the patients aged 75-84 years, it was only true for those without diabetes and STEMI. Admission blood glucose was also associated with major cardiac complications in both age groups.

CONCLUSION

Admission blood glucose was significantly associated with 28-day case fatality in patients with AMI aged 65-74 years but not 75-84 years; furthermore, in both age groups there was an increased risk of major complications. It seems that admission glucose may play a rather minor role in terms of case fatality in higher aged patients with AMI.

Liraglutide hospital discharge trial: A randomized controlled trial comparing the safety and efficacy of liraglutide versus insulin glargine for the management of patients with type 2 diabetes after hospital discharge

AIM

To compare a glucagon-like peptide-1 receptor agonist with basal insulin at hospital discharge in patients with uncontrolled type 2 diabetes in a randomized clinical trial.

METHODS

A total of 273 patients with glycated haemoglobin (HbA1c) 7%-10% (53-86 mol/mol) were randomized to liraglutide (n = 136) or insulin glargine (n = 137) at hospital discharge. The primary endpoint was difference in HbA1c at 12 and 26 weeks. Secondary endpoints included hypoglycaemia, changes in body weight, and achievement of HbA1c <7% (53 mmol/mol) without hypoglycaemia or weight gain.

RESULTS

The between-group difference in HbA1c at 12 weeks and 26 weeks was -0.28% (95% CI -0.64, 0.09), and at 26 weeks it was -0.55%, (95% CI -1.01, -0.09) in favour of liraglutide. Liraglutide treatment resulted in a lower frequency of hypoglycaemia <3.9 mmol/L (13% vs 23%; P = 0.04), but there was no difference in the rate of clinically significant hypoglycaemia <3.0 mmol/L. Compared to insulin glargine, liraglutide treatment was associated with greater weight loss at 26 weeks (-4.7 ± 7.7 kg vs -0.6 ± 11.5 kg; P < 0.001), and the proportion of patients with HbA1c <7% (53 mmol/mol) without hypoglycaemia was 48% versus 33% (P = 0.05) at 12 weeks and 45% versus 33% (P = 0.14) at 26 weeks in liraglutide versus insulin glargine. The proportion of patients with HbA1c <7% (53 mmol/mol) without hypoglycaemia and no weight gain was higher with liraglutide at 12 (41% vs 24%, P = 0.005) and 26 weeks (39% vs 22%; P = 0.014). The incidence of gastrointestinal adverse events was higher with liraglutide than with insulin glargine (P < 0.001).

CONCLUSION

Compared to insulin glargine, treatment with liraglutide at hospital discharge resulted in better glycaemic control and greater weight loss, but increased gastrointestinal adverse events.

The Impact of a Nursing Strike on Glycemic Control in Hospitalized Patients with Diabetes

Introduction Hyperglycemia and hypoglycemia have been found to increase morbidity and mortality among hospitalized patients with diabetes. In July of 2018, our academic medical center experienced a 48-hour nursing strike, during which time 600 replacement nurses were employed. This cohort study evaluated the impact of the nursing strike on glycemic control among hospitalized patients with diabetes. Methods Point-of-care fingerstick blood glucose (POC BG) values among hospitalized patients with diabetes were compared between the 48-hour nursing strike period and two 48-hour periods when the nursing strike did not occur. We evaluated the percentage of POC BG values that were hyperglycemic (POC BG 181-250 mg/dL), severely hyperglycemic (POC BG >250 mg/dL), and hypoglycemic (POC BG <70 mg/dL). Additionally, we assessed the proportion of patients who experienced one or more days of hypoglycemia, hyperglycemia, or severe hyperglycemia. Results We found a significant association between the distributions of POC BG test results during the nursing strike; test results more frequently showed hyperglycemia, severe hyperglycemia, or hypoglycemia during the nursing strike than during the control period (p=0.006). There was a significant difference in the days of hypoglycemia, with 7.7% of patients experiencing one or more days of hypoglycemia during the strike period compared with 1.4% of patients during the control period (p=0.03). Conclusion Nursing strikes have been employed as a last resort in contract negotiations with hospitals, but they have the potential to significantly affect patient care and safety. Further studies are needed to evaluate these impacts to prepare for future workforce disruptions.

Outcomes and Healthcare Provider Perceptions of Real-Time Continuous Glucose Monitoring (rtCGM) in Patients With Diabetes and COVID-19 Admitted to the ICU

OBJECTIVE

We assessed the clinical utility and accuracy of real-time continuous glucose monitoring (rtCGM) (Dexcom G6) in managing diabetes patients with severe COVID-19 infection following admission to the intensive care unit (ICU).

METHODS

We present retrospective analysis of masked rtCGM in 30 patients with severe COVID-19. rtCGM was used during the first 24 hours for comparison with arterial-line point of care (POC) values, where clinicians utilized rtCGM data to adjust insulin therapy in patients if rtCGM values were within 20% of point-of-care (POC) values during the masked period. An investigator-developed survey was administered to assess nursing staff (n = 66) perceptions regarding the use of rtCGM in the ICU.

RESULTS

rtCGM data were used to adjust insulin therapy in 30 patients. Discordance between rtCGM and POC glucose values were observed in 11 patients but the differences were not considered clinically significant. Mean sensor glucose decreased from 235.7 ± 42.1 mg/dL (13.1 ± 2.1 mmol/L) to 202.7 ± 37.6 mg/dL (11.1 ± 2.1 mmol/L) with rtCGM management. Improvements in mean sensor glucose were observed in 77% of patients (n = 23) with concomitant reductions in daily POC measurements in 50% of patients (n = 15) with rtCGM management. The majority (63%) of nurses reported that rtCGM was helpful for improving care for patients with diabetes patients during the COVID-19 pandemic, and 49% indicated that rtCGM reduced their use of personal protective equipment (PPE).

CONCLUSIONS

Our findings provide a strong rationale to increase clinician awareness for the adoption and implementation of rtCGM systems in the ICU. Additional studies are needed to further understand the utility of rtCGM in critically ill patients and other clinical care settings.

Association between glycosylated haemoglobin and outcomes for patients discharged from hospital with diabetes: A health informatics approach

Aims/Objectives

Extensive research considers associations between inpatient glycaemic control and outcomes during hospital admission; this cautions against overly tight glycaemic targets. Little research considers glycaemic control following hospital discharge. This is despite a clear understanding that people with diabetes are at increased risk of negative outcomes, following discharge. We evaluate absolute and relative Hba1c values, and frequency of Hba1c monitoring, on readmission and mortality rates for people discharged from hospital with diabetes.

Methods

All discharges (n = 46,357) with diabetes from a major tertiary referral centre over 3 years were extracted, including biochemistry data. We conducted an evaluation of association between Hba1c, mortality and readmission, statistical significance and standardised Cohen's D effect size calculations.

Results

399 patients had a Hba1c performed during their admission. 3,138 patients had a Hba1c within 1 year of discharge. Mean average Hba1c for readmissions was 57.82 vs 60.39 for not readmitted (p = 0.009, Cohen's D 0.28). Mean average number of days to Hba1c testing in readmitted was 97 vs 113 for those not readmitted (p = 0.00006, Cohen's D 0.39). Further evaluation of mortality outcomes, cohorts of T1DM and T2DM and association of relative change in Hba1c was performed.

Conclusions

Lower Hba1c values following discharge from hospital are significantly associated with increased risk of readmission, as is a shorter duration until testing. Similar patterns observed for mortality. Findings particularly prominent for T1DM. Further research needed to consider underlying causation and design of appropriate risk stratification models.

Diabetes and Cancer: Metabolic Association, Therapeutic Challenges, and the Role of Natural Products

Cancer is considered the second leading cause of death worldwide and in 2018 it was responsible for approximately 9.6 million deaths. Globally, about one in six deaths are caused by cancer. A strong correlation was found between diabetes mellitus and carcinogenesis with the most evident correlation was with type 2 diabetes mellitus (T2DM). Research has proven that elevated blood glucose levels take part in cell proliferation and cancer cell progression. However, limited studies were conducted to evaluate the efficiency of conventional therapies in diabetic cancer patients. In this review, the correlation between cancer and diabetes will be discussed and the mechanisms by which the two diseases interact with each other, as well as the therapeutics challenges in treating patients with diabetes and cancer with possible solutions to overcome these challenges. Natural products targeting both diseases were discussed with detailed mechanisms of action. This review will provide a solid base for researchers and physicians to test natural products as adjuvant alternative therapies to treat cancer in diabetic patients.

The Stress Hyperglycemia Ratio is Associated with Hemorrhagic Transformation in Patients with Acute Ischemic Stroke

Background

Hemorrhagic transformation (HT) is a severe complication occurring in acute ischemic stroke (AIS) patients. Stress hyperglycemia is frequent in patients with acute illness such as stroke. We aimed to explore the association between stress hyperglycemia and HT in AIS patients.

Methods

A total of 287 consecutive participants with HT and 285 age- and sex-matched stroke patients without HT were enrolled in this study. Baseline glucose and glycated hemoglobin (HbA1c) levels were collected to measure stress hyperglycemia. The stress hyperglycemia ratio (SHR) was calculated by dividing the fasting plasma glucose at admission with HbA1c. HT was diagnosed by follow-up imaging assessment, and was radiologically classified as hemorrhagic infarction type (HI) 1 or 2 or parenchymal hematoma type (PH) 1 or 2.

Results

Univariate analysis showed that SHR is significantly higher among patients with HT than those without HT. Compared to the patients in the lower three quartiles of SHR, the incidence of HT was significantly higher among patients with the highest quartile of SHR in total population, diabetic and non-diabetic population. We also observed that patients with the highest SHR quartile were associated with an increased risk of hemorrhagic transformation after adjusted for potential covariates (68.4% versus 39.1%; adjusted odds ratio, 2.320; 95% confidence interval, 1.207-4.459; P=0.012).

Conclusion

The stress hyperglycemia ratio, representing the state of stress hyperglycemia, was significantly associated with an increased risk of hemorrhagic transformation in patients with acute ischemic stroke.

Symptomatic intracranial hemorrhage in patients with admission hyperglycemia and diabetes after mechanical thrombectomy: A systematic review and meta-analysis

OBJECTIVES

Symptomatic intracranial hemorrhage (sICH) is a severe complication of revascularization therapy. We aimed to investigate the association of admission hyperglycemia and sICH after mechanical thrombectomy in patients with acute ischemic stroke.

METHODS

We systematically searched PubMed, EMBASE and Cochrane Library to identify studies that reported incidence of sICH in patients with admission hyperglycemia and normoglycemia, or with and without a history of diabetes, or glucose level in patients with sICH and non-sICH from inception to December 10, 2019. The estimate effects were pooled by random-effects model.

RESULTS

Twelve eligible studies were included with 4892 patients enrolled. The risk of sICH was significantly higher in admission hyperglycemia patients than that in normoglycemia (OR 2.93, 95% CI 1.34-6.42, p = 0.007; adjusted OR1.95, 95% CI 1.22-3.13; p = 0.006). The admission glucose level was significantly higher in sICH patients than that in non-sICH with a mean difference of 37.49 (95% CI 3.03-71.94, p = 0.03). The risk of sICH increased with elevating glucose level (adjusted OR 1.06, 95% CI 1.01-1.11; p = 0.02). The risk of sICH was not significantly increased in patients with a history of diabetes than that of those without (OR 1.74, 95% CI 1.00-3.03, p = 0.05; adjusted OR 2.26, 95% CI 0.97-5.28; p = 0.06).

CONCLUSIONS

In patients of acute ischemic stroke treated with mechanical thrombectomy, the risk of sICH was associated with admission hyperglycemia but possibly not with a history of diabetes.

Monitoring the Impact of Aggressive Glycemic Intervention during Critical Care after Cardiac Surgery with a Glycemic Expert System for Nurse-Implemented Euglycemia: The MAGIC GENIE Project

A novel, multi-dimensional protocol named GENIE has been in use for intensive insulin therapy (IIT, target glucose <140 mg/dL) in the surgical intensive care unit (SICU) after open heart surgery (OHS) at VA Pittsburgh since 2005. Despite concerns over increased mortality from IIT after the publication of the NICE-SUGAR Trial, it remains in use, with ongoing monitoring under the MAGIC GENIE Project showing that GENIE performance over 12 years (2005-2016) aligns with the current consensus that IIT with target blood glucose (BG) <140 mg/dL is advisable only if it does not provoke severe hypoglycemia (SH). Two studies have been conducted to monitor glucometrics and outcomes during GENIE use in the SICU. One compares GENIE (n = 382) with a traditional IIT protocol (FORMULA, n = 289) during four years of contemporaneous use (2005-2008). The other compares GENIE's impact overall (n = 1404) with a cohort of patients who maintained euglycemia after OHS (euglycemic no-insulin [ENo-I], n = 111) extending across 12 years (2005-2016). GENIE performed significantly better than FORMULA during contemporaneous use, maintaining lower time-averaged glucose, provoking less frequent, severe, prolonged, or repetitive hypoglycemia, and achieving 50% lower one-year mortality, with no deaths from mediastinitis (0 of 8 cases vs 4 of 9 on FORMULA). Those benefits were sustained over the subsequent eight years of exclusive use in OHS patients, with an overall one-year mortality rate (4.2%) equivalent to the ENo-I cohort (4.5%). The results of the MAGIC GENIE Project show that GENIE can maintain tight glycemic control without provoking SH in patients undergoing OHS, and may be associated with a durable survival benefit. The results, however, await confirmation in a randomized control trial.

Insulin Infusion Computer Calculator Programmed Directly Into Electronic Health Record Medication Administration Record

BACKGROUND

Computerized insulin infusion protocols have demonstrated higher staff satisfaction, better compliance with protocols, and increased time with glucose in range compared to paper protocols. At University of California San Diego Health (UCSDH), we implemented an insulin infusion computer calculator (IICC) and transitioned it from a web-based platform directly into the electronic medication administration record (eMAR) of our primary electronic health record (EHR).

METHODS

This is a retrospective analysis of 6306 adult patients at UCSDH receiving intravenous (IV) insulin infusion from March 7, 2013 to May 30, 2019. We created three periods of the study-(1) the pre-eMAR integration period; (2) the eMAR integration period; and (3) the post-eMAR integration period-and looked at the percentage of readings within goal range (90-150 mg/dL for intensive care unit [ICU], 90-180 mg/dL for non-ICU) in patients with and without hyperglycemic emergencies. As our safety endpoints, we elected to look at incidence of blood glucose (BG) readings <70 mg/dL, <54 mg/dL, and <40 mg/dL.

RESULTS

Pre-eMAR 69.8% of readings were in the 90-150 mg/dL range compared to 70.2% post-eMAR (P = .03) and 82.7% of readings were in the 90-180 mg/dL range pre-eMAR versus 82.9% (P = .09) post-eMAR in patients without hyperglycemic emergencies. Rates of hypoglycemia with BG <70 mg/dL were 0.43%, <54 mg/dL were 0.07%, and <40 mg/dL were 0.01% of readings pre- and post-eMAR.

CONCLUSIONS

At UCSDH, our IICC has shown to be safe and effective in a wide variety of clinical situations and we were able to successfully transition it from a web-based platform directly into the eMAR of our primary EHR.

Management of diabetes and hyperglycaemia in the hospital

Hyperglycaemia in people with and without diabetes admitted to the hospital is associated with a substantial increase in morbidity, mortality, and health-care costs. Professional societies have recommended insulin therapy as the cornerstone of inpatient pharmacological management. Intravenous insulin therapy is the treatment of choice in the critical care setting. In non-intensive care settings, several insulin protocols have been proposed to manage patients with hyperglycaemia; however, meta-analyses comparing different treatment regimens have not clearly endorsed the benefits of any particular strategy. Clinical guidelines recommend stopping oral antidiabetes drugs during hospitalisation; however, in some countries continuation of oral antidiabetes drugs is commonplace in some patients with type 2 diabetes admitted to hospital, and findings from clinical trials have suggested that non-insulin drugs, alone or in combination with basal insulin, can be used to achieve appropriate glycaemic control in selected populations. Advances in diabetes technology are revolutionising day-to-day diabetes care and work is ongoing to implement these technologies (ie, continuous glucose monitoring, automated insulin delivery) for inpatient care. Additionally, transformations in care have occurred during the COVID-19 pandemic, including the use of remote inpatient diabetes management-research is needed to assess the effects of such adaptations.

Effects of an Intensive Discharge Intervention on Medication Adherence, Glycemic Control, and Readmission Rates in Patients With Type 2 Diabetes

OBJECTIVES

Patients with diabetes are at particularly high risk for adverse outcomes after hospitalization. The goals of this study were to design, implement, and evaluate a multipronged transitional care intervention among hospitalized patients with diabetes.

METHODS

We randomly assigned inpatients likely to be discharged home on insulin to an intensive transitional care intervention or usual care. The primary outcome was 90-day postdischarge insulin adherence, using prescription refill information to calculate a medication possession ratio. Unadjusted analyses were conducted using Wilcoxon rank sum; adjusted analyses used multivariable linear regression and weighted propensity scoring methods, with general estimating equations to account for clustering by admitting physician.

RESULTS

One hundred eighty patients participated. The mean (SD) medication possession ratio to all insulin types was 84.5% (22.6) among intervention and 76.4% (25.1) among usual care patients (difference = 8.1, 95% confidence interval = -1.0 to 17.2, P = 0.06), with a smaller difference for adherence to all medications (86.3% versus 82.0%). A1c levels decreased in both groups but was larger in the intervention arm (1.09 and 0.11, respectively) (difference = -0.98, 95% confidence interval = -2.03 to -0.07, P = 0.04). Differences between study arms were not significant for rates of hypoglycemic episodes, 30-day readmissions, or emergency department visits. In adjusted/clustered analyses, the difference in A1c reduction remained statistically significant, whereas differences in all other outcomes remained nonsignificant.

CONCLUSIONS

The intervention was associated with improvements in glycemic control, with nonsignificant trends toward greater medication adherence. Further research is needed to optimize and successfully implement interventions to improve patient safety and health outcomes during care transitions.

Adherence to a Hypoglycemia Protocol in Hospitalized Patients: A Retrospective Analysis

BACKGROUND

Hypoglycemia can be a common occurrence in hospitalized patients, both those with and without diabetes. Hypoglycemia poses significant risks to hospitalized patients, including increased mortality.

OBJECTIVES

This was a retrospective pre-post study of hypoglycemic patients in an academic medical center of an intervention to improve timely staff nurse adherence to a hypoglycemia protocol. The number of mild and severe hypoglycemia events pre- and postintervention, timeliness of adherence to the hypoglycemia protocol, the number of treatment interventions, and time to return patients to euglycemia were analyzed.

METHODS

Data from hospitalizations of patients who experienced hypoglycemia (<70 mg/dl) and met inclusion criteria 1 year prior to intervention and 3 years postintervention were extracted, including demographics, glycemic control medications, diagnostic-related group, length of stay, and Charlson comorbidity index. For clarity and to determine if any significant change was sustained, the analysis compared data from 1 year prior to intervention to the second-year postintervention.

RESULTS

A total of 7,895 unique hypoglycemic events in 3,819 patients experiencing 20,094 hypoglycemic measures were included in the analysis. Patients were primarily adult, female, and White. Only 58.7% of the sample had diabetes; the median Charlson comorbidity index was 6. Results demonstrated improvement postintervention to registered nurse hypoglycemia protocol adherence regardless of age category or hypoglycemia severity. There was a significant reduction in median time from the first hypoglycemia measure to the second measure. In addition, there was a significant difference in the number of treatment interventions and reduction in time from the first hypoglycemia measure to return of patient to a blood glucose of ≥70 mg/dl.

DISCUSSION

These study results support that the use of a standardized hypoglycemia protocol and appropriate nurse workflows enables nurses to manage hypoglycemia promptly and effectively in most acute and critically ill hospitalized patients. Results also supported a differentiation in nurse workflow for patients with mild versus severe hypoglycemia. Implementing these interventions may result in avoidance or mitigation of the potential consequences of severe and/or sustained hypoglycemia.

The influence of diabetes on postoperative complications following colorectal surgery

Background

Diabetes mellitus has been commonly associated with poor surgical outcomes. The aim of this meta-analysis was to assess the impact of diabetes on postoperative complications following colorectal surgery.

Methods

Medline, Embase and China National Knowledge Infrastructure electronic databases were reviewed from inception until May 9th 2020. Meta-analysis of proportions and comparative meta-analysis were conducted. Studies that involved patients with diabetes mellitus having colorectal surgery, with the inclusion of patients without a history of diabetes as a control, were selected. The outcomes measured were postoperative complications.

Results

Fifty-five studies with a total of 666,886 patients comprising 93,173 patients with diabetes and 573,713 patients without diabetes were included. Anastomotic leak (OR 2.407; 95% CI 1.837–3.155; p < 0.001), surgical site infections (OR 1.979; 95% CI 1.636–2.394; p < 0.001), urinary complications (OR 1.687; 95% CI 1.210–2.353; p = 0.002), and hospital readmissions (OR 1.406; 95% CI 1.349–1.466; p < 0.001) were found to be significantly higher amongst patients with diabetes following colorectal surgery. The incidence of septicemia, intra-abdominal infections, mechanical failure of wound healing comprising wound dehiscence and disruption, pulmonary complications, reoperation, and 30-day mortality were not significantly increased.

Conclusions

This meta-analysis and systematic review found a higher incidence of postoperative complications including anastomotic leaks and a higher re-admission rate. Risk profiling for diabetes prior to surgery and perioperative optimization for patients with diabetes is critical to improve surgical outcomes.

Electronic supplementary material

The online version of this article (10.1007/s10151-020-02373-9) contains supplementary material, which is available to authorized users.