Hypoglycemia and outcome in critically ill patients

Metformin is associated with reduced risk of mortality and morbidity in burn patients compared to insulin

PURPOSE

The standard of care for burned patients experiencing hyperglycemia associated with the hypermetabolic response is insulin therapy. Insulin treatment predisposes burn patients to hypoglycemia, which increases morbidity and mortality. Metformin has been suggested as an alternative to insulin therapy for glycemic control in burn patients given its safety profile, but further research is warranted. This study investigated whether metformin use in burn patients is associated with improved glycemic control and morbidity/mortality outcomes compared to insulin use alone.

MATERIALS AND METHODS

Using the TriNetX database, we conducted a retrospective study of burned patients who were administered insulin, metformin, or both within one week of injury. Demographic, comorbidity, and burn severity information were collected. Patients were categorized by treatment type, propensity score-matched, and compared for the following outcomes within 3 months: hyperglycemia, hypoglycemia, sepsis, lactic acidosis, and death. Statistical significance was set a priori at p ≤ 0.05.

RESULTS

The insulin cohort was at increased risk for all outcomes (all p < 0.0001) compared to the metformin cohort, and an increased risk for sepsis, lactic acidosis, and death (all p ≤ 0.0002) compared to the insulin/metformin combination cohort. When compared to the metformin cohort, the combination cohort was at increased risk for all outcomes (all p ≤ 0.0107) except death.

CONCLUSIONS

Treatment with metformin after burn is associated with a reduced risk of morbidity and mortality compared to insulin. The combination of insulin and metformin is no more effective in reducing the risk of hyperglycemia and hypoglycemia than insulin alone but is less effective than metformin alone.

Predicting hypoglycemia in ICU patients: a machine learning approach

BACKGROUND

The current study sets out to develop and validate a robust machine-learning model utilizing electronic health records (EHR) to forecast the risk of hypoglycemia among ICU patients in Jordan.

RESEARCH DESIGN AND METHODS

The present study drew upon a substantial cohort of 13,567 patients admitted 26,248 times to the intensive care unit (ICU) over 10 years from July 2012 to July 2022. The primary outcome of interest was the occurrence of any hypoglycemic episode during the patient's ICU stay. Developing and testing predictor models was conducted using Python machine-learning libraries.

RESULTS

A total of 1,896 were eligible to participate in the study, 206 experienced at least one hypoglycemic episode. Eight machine-learning models were trained to predict hypoglycemia. All models showed predicting power with a range of 74.53-99.69 for AUROC. Except for Naive Bayes, the six remaining models performed distinctly better than the basic logistic regression usually used for prediction in epidemiological studies. CatBoost model was consistently the best performer with the highest AUROC (0.99), accuracy and precision, sensitivity and specificity, and recall.

CONCLUSIONS

We used machine learning to anticipate the likelihood of hypoglycemia, which can significantly decrease hypoglycemia incidents and enhance patient outcomes.

Risk factors at admission of in-hospital dysglycemia, mortality, and readmissions in patients with type 2 diabetes and pneumonia

AIMS

In-hospital dysglycemia is associated with adverse outcomes. Identifying patients at risk of in-hospital dysglycemia early on admission may improve patient outcomes.

METHODS

We analysed 117 inpatients admitted with pneumonia and type 2 diabetes monitored by continuous glucose monitoring. We assessed potential risk factors for in-hospital dysglycemia and adverse clinical outcomes.

RESULTS

Time in range (3.9-10.0 mmol/l) decreased by 2.9 %-points [95 % CI 0.7-5.0] per 5 mmol/mol [2.6 %] increase in admission haemoglobin A1c, 16.2 %-points if admission diabetes therapy included insulin therapy [95 % CI 2.9-29.5], and 2.4 %-points [95 % CI 0.3-4.6] per increase in the Charlson Comorbidity Index (CCI) (integer, as a measure of severity and amount of comorbidities). Thirty-day readmission rate increased with an IRR of 1.24 [95 % CI 1.06-1.45] per increase in CCI. In-hospital mortality risk increased with an OR of 1.41 [95 % CI 1.07-1.87] per increase in Early Warning Score (EWS) (integer, as a measure of acute illness) at admission.

CONCLUSIONS

Dysglycemia among hospitalised patients with pneumonia and type 2 diabetes was associated with high haemoglobin A1c, insulin treatment before admission, and the amount and severity of comorbidities (i.e., CCI). Thirty-day readmission rate increased with high CCI. The risk of in-hospital mortality increased with the degree of acute illness (i.e., high EWS) at admission. Clinical outcomes were independent of chronic glycemic status, i.e. HbA1c, and in-hospital glycemic status.

Evaluation of Nurse-Driven Management of Hypoglycemia In Critically Ill Patients

BACKGROUND

Intensive care unit (ICU) patients experience hypoglycemia at nearly 4 times the rate seen in non-ICU counterparts. Although inpatient hypoglycemia management relies on nurse-driven protocols, protocol adherence varies between institutions and units.

OBJECTIVE

To compare hypoglycemia management between ICU and non-ICU patients in an institution with high adherence to a hypoglycemia protocol.

METHODS

This secondary analysis used retrospective medical record data. Cases were ICU patients aged 18 years or older with at least 1 hypoglycemic event (blood glucose level < 70 mg/dL); non-ICU controls were matched by age within 10 years, sex, and comorbidities. Time from initial hypoglycemic blood glucose level to subsequent blood glucose recheck, number of interventions, time to normoglycemia, and number of spontaneous hypoglycemic events were compared between groups.

RESULTS

The sample included 140 ICU patients and 280 non-ICU controls. Median time to blood glucose recheck did not differ significantly between groups (19 minutes for both groups). Difference in mean number of interventions before normoglycemia was statistically but not clinically significant (ICU, 1.12; non-ICU, 1.35; P < .001). Eighty-four percent of ICU patients and 86% of non-ICU patients returned to normoglycemia within 1 hour. Median time to normoglycemia was lower in ICU patients than non-ICU patients (21.5 vs 26 minutes; P = .01). About 25% of patients in both groups experienced a spontaneous hypoglycemic event.

CONCLUSION

Adherence to nurse-driven hypoglycemia protocols can be equally effective in ICU and non-ICU patients. Further research is needed to determine protocol adherence barriers and patient characteristics that influence response to hypoglycemia interventions.

Acute severe hypoglycemia alters mouse brain microvascular proteome

Hypoglycemia increases the risk related to stroke and neurodegenerative diseases, however, the underlying mechanisms are unclear. For the first time, we studied the effect of a single episode (acute) of severe (ASH) and mild (AMH) hypoglycemia on mouse brain microvascular proteome. After four-hour fasting, insulin was administered (i.p) to lower mean blood glucose in mice and induce ∼30 minutes of ASH (∼30 mg/dL) or AMH (∼75 mg/dL), whereas a similar volume of saline was given to control mice (∼130 mg/dL). Blood glucose was allowed to recover over 60 minutes either spontaneously or by 20% dextrose administration (i.p). Twenty-four hours later, the brain microvessels (BMVs) were isolated, and tandem mass tag (TMT)-based quantitative proteomics was performed using liquid chromatography-mass spectrometry (LC/MS). When compared to control, ASH significantly downregulated 13 proteins (p ≤ 0.05) whereas 23 proteins showed a strong trend toward decrease (p ≤ 0.10). When compared to AMH, ASH significantly induced the expression of 35 proteins with 13 proteins showing an increasing trend. AMH downregulated only 3 proteins. ASH-induced downregulated proteins are involved in actin cytoskeleton maintenance needed for cell shape and migration which are critical for blood-brain barrier maintenance and angiogenesis. In contrast, ASH-induced upregulated proteins are RNA-binding proteins involved in RNA splicing, transport, and stability. Thus, ASH alters BMV proteomics to impair cytoskeletal integrity and RNA processing which are critical for cerebrovascular function.

Society of Critical Care Medicine Guidelines on Glycemic Control for Critically Ill Children and Adults 2024

RATIONALE

Maintaining glycemic control of critically ill patients may impact outcomes such as survival, infection, and neuromuscular recovery, but there is equipoise on the target blood levels, monitoring frequency, and methods.

OBJECTIVES

The purpose was to update the 2012 Society of Critical Care Medicine and American College of Critical Care Medicine (ACCM) guidelines with a new systematic review of the literature and provide actionable guidance for clinicians.

PANEL DESIGN

The total multiprofessional task force of 22, consisting of clinicians and patient/family advocates, and a methodologist applied the processes described in the ACCM guidelines standard operating procedure manual to develop evidence-based recommendations in alignment with the Grading of Recommendations Assessment, Development, and Evaluation Approach (GRADE) methodology. Conflict of interest policies were strictly followed in all phases of the guidelines, including panel selection and voting.

METHODS

We conducted a systematic review for each Population, Intervention, Comparator, and Outcomes question related to glycemic management in critically ill children (≥ 42 wk old adjusted gestational age to 18 yr old) and adults, including triggers for initiation of insulin therapy, route of administration, monitoring frequency, role of an explicit decision support tool for protocol maintenance, and methodology for glucose testing. We identified the best available evidence, statistically summarized the evidence, and then assessed the quality of evidence using the GRADE approach. We used the evidence-to-decision framework to formulate recommendations as strong or weak or as a good practice statement. In addition, "In our practice" statements were included when the available evidence was insufficient to support a recommendation, but the panel felt that describing their practice patterns may be appropriate. Additional topics were identified for future research.

RESULTS

This guideline is an update of the guidelines for the use of an insulin infusion for the management of hyperglycemia in critically ill patients. It is intended for adult and pediatric practitioners to reassess current practices and direct research into areas with inadequate literature. The panel issued seven statements related to glycemic control in unselected adults (two good practice statements, four conditional recommendations, one research statement) and seven statements for pediatric patients (two good practice statements, one strong recommendation, one conditional recommendation, two "In our practice" statements, and one research statement), with additional detail on specific subset populations where available.

CONCLUSIONS

The guidelines panel achieved consensus for adults and children regarding a preference for an insulin infusion for the acute management of hyperglycemia with titration guided by an explicit clinical decision support tool and frequent (≤ 1 hr) monitoring intervals during glycemic instability to minimize hypoglycemia and against targeting intensive glucose levels. These recommendations are intended for consideration within the framework of the patient's existing clinical status. Further research is required to evaluate the role of individualized glycemic targets, continuous glucose monitoring systems, explicit decision support tools, and standardized glycemic control metrics.

Glucose control and outcomes in diabetic and nondiabetic patients treated with targeted temperature management after cardiac arrest

Hyperglycemia is commonly observed in critically ill patients and postcardiac arrest patients, with higher glucose levels and variability associated with poorer outcomes. In this study, we aim to compare glucose control in diabetic and nondiabetic patients using glycated hemoglobin (HbA1c) levels, providing insights for better glucose management strategies. This retrospective observational study was conducted at Seoul St. Mary's Hospital from February 2009 to May 2022. Blood glucose levels were measured hourly for 48 h after return of spontaneous circulation (ROSC), and a glucose management protocol was followed to maintain arterial blood glucose levels between 140 and 180 mg/dL using short-acting insulin infusion. Patients were categorized into four groups based on diabetes status and glycemic control. The primary outcomes assessed were neurological outcome and mortality at 6 months after cardiac arrest. Among the 332 included patients, 83 (25.0%) had a previous diabetes diagnosis, and 114 (34.3%) had an HbA1c of 6.0% or higher. At least one hyperglycemic episode was observed in 314 patients (94.6%) and hypoglycemia was found in 63 patients (19.0%) during 48 h. After the categorization, unrecognized diabetes was noticed in 51 patients with median HbA1c of 6.3% (interquartile range [IQR] 6.1-6.6). Patients with inadequate diabetes control had the highest initial HbA1c level (7.0%, IQR 6.5-7.8) and admission glucose (314 mg/dL, IQR 257-424). Median time to target glucose in controlled diabetes was significantly shorter with the slowest glucose reducing rate. The total insulin dose required to reach the target glucose level and cumulative insulin requirement during 48 h were different among the categories (p <0.001). Poor neurological outcomes and mortality were more frequently observed in patients with diagnosed diabetes. Occurrence of a hypoglycemic episode during the 48 h after ROSC was independently associated with poor neurologic outcomes (odds ratio [OR] 3.505; 95% confidence interval [CI], 2.382-9.663). Surviving patients following cardiac arrest exhibited variations in glucose hemodynamics and outcomes according to the categories based on their preexisting diabetes status and glycemic condition. Specifically, even experiencing a single episode of hypoglycemia during the acute phase could have an influence on unfavorable neurological outcomes. While the classification did not directly affect neurological outcomes, the present results indicate the need for a customized approach to glucose control based on these categories.

Tigecycline and Hypoglycemia, When and How?

Objective: To describe the clinical characteristics of hypoglycemia that develop with tigecycline therapy and to review and summarize the current evidence of this uncommonly occurring metabolic adverse effect of tigecycline therapy. Underlying risk factors and potential mechanisms are also discussed. Data source: A 3-phase literature search was performed. In phase 1, the Cochrane Central Register of Controlled Trials (CENTRAL) Library, MEDLINE, and Embase electronic databases were searched for hypoglycemia and tigecycline, published from inception until August 2023. In phase 2, MEDLINE was searched for tigecycline randomized controlled trials and results were manually screened for hypoglycemia. In phase 3, the US Food and Drug Administration Adverse Event Reporting System public dashboard was searched for reports on tigecycline and hypoglycemia from June 2005 until July 2023. Study selection and data extraction: Relevant English-language citations and those conducted in humans were considered. Relevance to patient care and clinical practice: Hypoglycemia of various causes is an independent mortality risk. This review raises awareness among clinicians about the possibility of hypoglycemia with tigecycline therapy. Conclusion: Data on tigecycline-related hypoglycemia are scarce. Hypoglycemia may occur at any time during tigecycline therapy and can be severe and persist for days after tigecycline cessation. Renal dysfunction or renal replacement therapy may predispose to severe hypoglycemia during tigecycline therapy. Tigecycline-related hypoglycemia may develop in patients with or without diabetes mellitus and appears independent of insulin or antidiabetic agents. Intravenous dextrose showed efficacy in the restoration of euglycemia. Studies are needed to determine whether tigecycline-related hypoglycemia is iatrogenic or spontaneous.

Management of diabetic ketoacidosis

Diabetic ketoacidosis (DKA) is an acute life-threatening emergency in patients with diabetes, it can result in serious morbidity and mortality. Management of DKA requires reversing metabolic derangements, correcting volume depletion, electrolyte imbalances and acidosis while concurrently treating the precipitating illness. There are still controversies regarding certain aspects of DKA management. Different society guidelines have inconsistencies in their recommendations, while some aspects of treatment are not precise enough or have not been thoroughly studied. These controversies may include issues such as optimal fluid resuscitation, rate and type of Insulin therapy, potassium and bicarbonate replacement. Many institutions follow common society guidelines, however, other institutions either develop their own protocols for internal use or do not routinely use any protocols, resulting in inconsistencies in treatment and increased risk of complications and suboptimal outcomes. The objectives of this article are to review knowledge gaps and controversies in the treatment of DKA and provide our perspective on these issues. Moreover, we believe that special patient factors and comorbidities should receive more careful attention and consideration. Factors like pregnancy, renal disease, congestive heart failure, acute coronary syndrome, older age, use of sodium-glucose cotransporter-2 (SGLT2) inhibitors and site of care all impact the treatment approach and require tailored management strategies. However, guidelines often lack sufficient recommendations regarding specific conditions and comorbidities, we aim to address unique circumstances and provide an approach to managing complex patients with specific conditions and co-morbidities. We also sought to examine changes and trends in the treatment of DKA, illuminate on aspects of latest research with a perspective towards future developments and modifications.

Association of hypoglycaemia with the risks of arrhythmia and mortality in individuals with diabetes - a systematic review and meta-analysis

Background

Hypoglycaemia has been linked to an increased risk of cardiac arrhythmias by causing autonomic and metabolic alterations, which may be associated with detrimental outcomes in individuals with diabetes(IWD), such as cardiovascular diseases (CVDs) and mortality, especially in multimorbid or frail people. However, such relationships in this population have not been thoroughly investigated. For this reason, we conducted a systematic review and meta-analysis.

Methods

Relevant papers published on PubMed, Embase, Cochrane, Web of Knowledge, Scopus, and CINHAL complete from inception to December 22, 2022 were routinely searched without regard for language. All of the selected articles included odds ratio, hazard ratio, or relative risk statistics, as well as data for estimating the connection of hypoglycaemia with cardiac arrhythmia, CVD-induced death, or total death in IWD. Regardless of the heterogeneity assessed by the I2 statistic, pooled relative risks (RRs) and 95% confidence intervals (CI) were obtained using random-effects models.

Results

After deleting duplicates and closely evaluating all screened citations, we chose 60 studies with totally 5,960,224 participants for this analysis. Fourteen studies were included in the arrhythmia risk analysis, and 50 in the analysis of all-cause mortality. Hypoglycaemic patients had significantly higher risks of arrhythmia occurrence (RR 1.42, 95%CI 1.21-1.68), CVD-induced death (RR 1.59, 95% CI 1.24-2.04), and all-cause mortality (RR 1.68, 95% CI 1.49-1.90) compared to euglycaemic patients with significant heterogeneity.

Conclusion

Hypoglycaemic individuals are more susceptible to develop cardiac arrhythmias and die, but evidence of potential causal linkages beyond statistical associations must await proof by additional specifically well planned research that controls for all potential remaining confounding factors.

Pulmonary pathogenesis in a murine model of inhaled arsenical exposure

Arsenic trioxide (ATO), an inorganic arsenical, is a toxic environmental contaminant. It is also a widely used chemical with industrial and medicinal uses. Significant public health risk exists from its intentional or accidental exposure. The pulmonary pathology of acute high dose exposure is not well defined. We developed and characterized a murine model of a single inhaled exposure to ATO, which was evaluated 24 h post-exposure. ATO caused hypoxemia as demonstrated by arterial blood-gas measurements. ATO administration caused disruption of alveolar-capillary membrane as shown by increase in total protein and IgM in the bronchoalveolar lavage fluid (BALF) supernatant and an onset of pulmonary edema. BALF of ATO-exposed mice had increased HMGB1, a damage-associated molecular pattern (DAMP) molecule, and differential cell counts revealed increased neutrophils. BALF supernatant also showed an increase in protein levels of eotaxin/CCL-11 and MCP-3/CCL-7 and a reduction in IL-10, IL-19, IFN-γ, and IL-2. In the lung of ATO-exposed mice, increased protein levels of G-CSF, CXCL-5, and CCL-11 were noted. Increased mRNA levels of TNF-a, and CCL2 in ATO-challenged lungs further supported an inflammatory pathogenesis. Neutrophils were increased in the blood of ATO-exposed animals. Pulmonary function was also evaluated using flexiVent. Consistent with an acute lung injury phenotype, respiratory and lung elastance showed significant increase in ATO-exposed mice. PV loops showed a downward shift and a decrease in inspiratory capacity in the ATO mice. Flow-volume curves showed a decrease in FEV0.1 and FEF50. These results demonstrate that inhaled ATO leads to pulmonary damage and characteristic dysfunctions resembling ARDS in humans.

Preoperative carbohydrate load to reduce perioperative glycemic variability and improve surgical outcomes: A scoping review

The detrimental effects of both diabetes mellitus (DM) and hyperglycemia in the perioperative period are well established and have driven extensive efforts to control blood glucose concentration (BGC) in a variety of clinical settings. It is now appreciated that acute BGC spikes, hypoglycemia, and high glycemic variability (GV) lead to more endothelial dysfunction and oxidative stress than uncomplicated, chronically elevated BGC. In the perioperative setting, fasting is the primary approach to reducing the risk for pulmonary aspiration; however, prolonged fasting drives the body into a catabolic state and therefore may increase GV. Elevated GV in the perioperative period is associated with an increased risk for postoperative complications, including morbidity and mortality. These challenges pose a conundrum for the management of patients typically instructed to fast for at least 8 h before surgery. Preliminary evidence suggests that the administration of an oral preoperative carbohydrate load (PCL) to stimulate endogenous insulin production and reduce GV in the perioperative period may attenuate BGC spikes and ultimately decrease postoperative morbidity, without significantly increasing the risk of pulmonary aspiration. The aim of this scoping review is to summarize the available evidence on the impact of PCL on perioperative GV and surgical outcomes, with an emphasis on evidence pertaining to patients with DM. The clinical relevance of GV will be summarized, the relationship between GV and postoperative course will be explored, and the impact of PCL on GV and surgical outcomes will be presented. A total of 13 articles, presented in three sections, were chosen for inclusion. This scoping review concludes that the benefits of a PCL outweigh the risks in most patients, even in those with well controlled type 2 DM. The administration of a PCL might effectively minimize metabolic derangements such as GV and ultimately result in reduced postoperative morbidity and mortality, but this remains to be proven. Future efforts to standardize the content and timing of a PCL are needed. Ultimately, a rigorous data-driven consensus opinion regarding PCL administration that identifies optimal carbohydrate content, volume, and timing of ingestion should be established.

Continuous Glucose Monitoring in the Intensive Care Unit

Traditionally, the care of critically ill patients with diabetes or stress hyperglycemia in the intensive care unit (ICU) demands the use of continuous intravenous insulin (CII) therapy to achieve narrow glycemic targets. To reduce the risk of iatrogenic hypoglycemia and to achieve glycemic targets during CII, healthcare providers (HCP) rely on hourly point-of-care (POC) arterial or capillary glucose tests obtained with glucose monitors. The burden of this approach, however, was evident during the beginning of the pandemic when the immediate reduction in close contact interactions between HCP and patients with COVID-19 was necessary to avoid potentially life-threatening exposures. Taking advantage of the advancements in current diabetes technologies, including continuous glucose monitoring (CGM) devices integrated with digital health tools for remote monitoring, HCP implemented novel protocols in the ICU to care for patients with COVID-19 and hyperglycemia. We provide an overview of research conducted in the ICU setting with the use of initial CGM technology to current devices and summarize our recent experience in the ICU.

Model-based subcutaneous insulin for glycemic control of pre-term infants in the neonatal intensive care unit

Hyperglycaemia is a common problem in neonatal intensive care units (NICUs). Achieving good control can result in better outcomes for patients. However, good control is difficult, where poor control and resulting hypoglycaemia reduces outcomes and confounds results. Clinically validated models can provide good control, and subcutaneous insulin delivery can provide more options for insulin therapy for clinicians. However, this combination has only been significantly utilised in adult outpatient diabetes, but could hold benefit for treating NICU infants. This research combines a well-validated NICU metabolic model with subcutaneous insulin kinetics models to assess the feasibility of a model-based approach. Clinical data from 12 very/extremely pre-mature infants was collected for an average study duration of 10.1 days. Blood glucose, interstitial and plasma insulin, as well as subcutaneous and local insulin were modelled, and patient-specific insulin sensitivity profiles were identified for each patient. Modelling error was low, where the cohort median [IQR] mean percentage error was 0.8 [0.3 3.4] %. For external validation, insulin sensitivity was compared to previous NICU cohorts using the same metabolic model, where overall levels of insulin sensitivity were similar. Overall, the combined system model accurately captured observed glucose and insulin dynamics, showing the potential for a model-based approach to glycaemic control using subcutaneous insulin in this cohort. The results justify further model validation and clinical trial research to explore a model-based protocol.

Undernutrition Scored Using the CONUT Score with Hypoglycemic Status in ICU-Admitted Elderly Patients with Sepsis Shows Increased ICU Mortality

This study aimed to clarify whether the influence of undernutrition status and the degree of glycemic disorders affected the prognosis of patients with sepsis. A total of 307 adult patients with sepsis were retrospectively enrolled and analyzed. Characteristics, including nutrition status, calculated according to the Controlling Nutritional Status (CONUT) score of survivors and non-survivors, were examined. The independent prognostic factors of these patients with sepsis were extracted using multivariable logistic regression analysis. The CONUT scores in three glycemic categories were compared. Most patients with sepsis (94.8%) in the study had an undernutrition status according to their CONUT scores. High CONUT scores (odds ratio, 1.214; p = 0.002), indicating a poor nutritional status, were associated with high mortality. The CONUT scores in the hypoglycemic group were significantly higher than those in other groups with an undernutrition status (vs. hyperglycemic, p < 0.001; vs. intermediate glycemic, p = 0.006). The undernutrition statuses of patients with sepsis in the study scored using the CONUT were independent predictors of prognostic factors.

Post-Transplant and In-Hospital Risk Factors for ARDS After Hematopoietic Stem Cell Transplantation

BACKGROUND

ARDS is a serious complication of hematopoietic stem cell transplant (HSCT). Pre-transplant risk factors for developing ARDS after HSCT have been recently identified. The objective of this study was to better understand post-transplant risk factors for developing ARDS after HSCT.

METHODS

This was a nested case-control study. ARDS cases were matched to hospitalized non-ARDS controls by age, type of transplantation (allogeneic vs autologous), and time from transplantation. In a conditional logistic regression model, any potential risk factors were adjusted a priori for risk factors known to be associated with ARDS development.

RESULTS

One hundred and seventy ARDS cases were matched 1:1 to non-ARDS hospitalized controls. Pre-admission, cases were more likely to be on steroids (odds ratio [OR] 1.90 [1.13-3.19], P = .02). At time of admission, cases had lower platelet count (OR 0.95 [0.91-0.99], P = .02), lower bicarbonate (OR 0.94 [0.88-0.99], P = .035), and higher creatinine (OR 1.91 [1.23-2.94], P = .004). During the first 24 h after admission, cases were more likely to have received transfusion (OR 2.41 [1.48-3.94], P < .001), opioids (OR 2.94 [1.67-5.18], P < .001), and have greater fluid administration (OR 1.52 [1.30-1.78], P < .001). During the hospitalization, ARDS cases had higher temperature (OR 1.77 [1.34-2.33], P < .001) and higher breathing frequency (OR 1.52 [1.33-1.74], P < .001). ARDS cases were more likely to have had sepsis (OR 68.0 [15.2-301.7], P < .001), bloodstream infection (OR 4.59 [2.46-8.57], P < .001), and pneumonia (OR 9.76 [5.01-19.00], P < .001).

CONCLUSIONS

Several post-transplant predictors of ARDS development specific to the HSCT population were identified in the pre-hospital and early in-hospital domains. These findings can provide insights into causal mechanisms of ARDS development and be used to develop HSCT-specific risk prediction models.

Clinical challenges of glycemic control in the intensive care unit: A narrative review

Glucose control in patient admitted to the intensive care unit has been a topic of much debate over the past 20 years. The harmful effects of uncontrolled hyperglycemia and hypoglycemia in critically ill patients is well established. Although a large clinical trial in 2001 demonstrated significant mortality and morbidity benefits with tight glucose control in this patient population, the results could not be replicated by other investigators. The “Normoglycemia in Intensive Care Evaluation-Survival Using Glucose Algorithm Regulation” trial in 2009 established that tight glucose control was not only of no benefit, but in fact harmful due to the significant risk of hypoglycemia. The current guidelines suggest a moderate approach with the initiation of intravenous insulin therapy in critically ill patients when the blood glucose level is above 180 mg/dL. The most important factor that underpins glycemic management in intensive care unit patients is the consequent prevention of hypoglycemia. Robust glucose monitoring strategies and insulin protocols need to be implemented in order to achieve this goal.

Acute and Chronic Glucose Control in Critically Ill Patients With Diabetes: The Impact of Prior Insulin Treatment

BACKGROUND

Emerging data highlight the interactions of preadmission glycemia, reflected by admission HbA1c levels, glycemic control during critical illness, and mortality. The association of preadmission insulin treatment with outcomes is unknown.

METHODS

This observational cohort study includes 5245 patients admitted to the medical-surgical intensive care unit of a university-affiliated teaching hospital. Three groups were analyzed: patients with diabetes with prior insulin treatment (DM-INS, n = 538); patients with diabetes with no prior insulin treatment (DM-No-INS, n = 986); no history of diabetes (NO-DM, n = 3721). Groups were stratified by HbA1c level: <6.5%; 6.5%-7.9% and >8.0%.

RESULTS

Among the three strata of HbA1c, mean blood glucose (BG), coefficient of variation (CV), and hypoglycemia increased with increasing HbA1c, and were higher for DM-INS than for DM-No-INS. Among patients with HbA1c < 6.5%, mean BG ≥ 180 mg/dL and CV > 30% were associated with lower severity-adjusted mortality in DM-INS compared to patients with mean BG 80-140 mg/dL and CV < 15%, (P = .0058 and < .0001, respectively), but higher severity-adjusted mortality among DM-No-INS (P = .0001 and < .0001, respectively) and NON-DM (P < .0001 and < .0001, respectively). Among patients with HbA1c ≥ 8.0%, mean BG ≥ 180 mg/dL was associated with lower severity-adjusted mortality for both DM-INS and DM-No-INS than was mean BG 80-140 mg/dL (p < 0.0001 for both comparisons).

CONCLUSIONS

Significant differences in mortality were found among patients with diabetes based on insulin treatment and HbA1c at home and post-admission glycemic control. Prospective studies need to confirm an individualized approach to glycemic control in the critically ill.

Intensive versus conservative glycemic control in patients undergoing coronary artery bypass graft surgery: A protocol for systematic review of randomised controlled trials

Introduction

Hyperglycemia and hypoglycemia are common during coronary artery bypass graft (CABG) and are associated with a variety of postoperative outcomes. Therefore, the strategy of intraoperative glycemic control is an important issue for the patients undergoing CABG. This systematic review aims to evaluate the effect of different intraoperative glycemic control strategies on postoperative outcomes.

Methods and analyses

We will perform this systematic review of randomised controlled trials (RCTs) according to the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Relevant studies will be searched in Medline, Embase, Cochrane Library and Web of Science. Two independent reviewers will conduct study selection, data extraction, risk of bias and quality assessment. The primary outcome is postoperative mortality, and the secondary outcomes include the duration of mechanical ventilation in the intensive care unit (ICU), the incidence of postoperative myocardial infarction (MI), the incidence of postoperative atrial fibrillation (AF), the type and volume of blood product transfusion, the rate of rehospitalization, the rate of cerebrovascular accident, the rate of significant postoperative bleeding, the rate of infection, the incidence of acute kidney failure (AKF), hospital and ICU lengths of stay (LOS). ReviewManager 5.4 will be used for data management and statistical analysis. The Cochrane risk-of -bias tool 2.0 and GRADEpro will be applied for risk of bias and quality assessment of the evidence.

Discussion

There is no consensus that which strategy of glycemic control is better for improving postoperative complications of patients undergoing CABG. The results of our study might provide some evidence for the relationship between intraoperative glycemic control strategies and postoperative outcomes in patients undergoing CABG.

Hypoglycemia is associated with a higher risk of mortality and arrhythmias in ST-elevation myocardial infarction, irrespective of diabetes

Aims

We aimed to assess the impact of hypoglycemia in ST-elevation myocardial infarction (STEMI).

Background

Hypoglycemia increases the risk of mortality in patients with diabetes and high cardiovascular risk.

Methods

We used the National Inpatient Sample (2005–2017) database to identify adult patients with STEMI as the primary diagnosis. The secondary diagnosis was hypoglycemia. We compared cardiovascular and socio-economic outcomes between STEMI patients with and without hypoglycemia and assessed temporal trends.

Results

Hypoglycemia tends to complicate 0.17% of all cases hospitalized for STEMI. The mean age (±SD) of STEMI patients hospitalized with hypoglycemia decreased from 67 ± 15 in 2005 to 63 ± 12 in 2017 (p = 0.046). Mortality was stable with time, but the prevalence of ventricular tachycardia, ventricular fibrillation, acute renal failure, cardiogenic shock, total charges, and length of stay (LOS) increased with time (p < 0.05 for all). Compared to non-hypoglycemic patients, those who developed hypoglycemia were older and more likely to be black; only 6.7% had diabetes compared to 28.5% of STEMI patients (p = 0.001). Cardiovascular events were more likely to occur in hypoglycemia: mortality risk increased by almost 2.5-fold (adjusted OR = 2.625 [2.095–3.289]). There was a higher incidence of cardiogenic shock (adjusted OR = 1.718 [1.387–2.127]), atrial fibrillation (adjusted OR = 1.284 [1.025–1.607]), ventricular fibrillation (adjusted OR = 1.799 [1.406–2.301]), and acute renal failure (adjusted OR = 2.355 [1.902–2.917]). Patients who developed hypoglycemia were less likely to have PCI (OR = 0.596 [0.491–0.722]) but more likely to have CABG (OR = 1.792 [1.391–2.308]). They also had a longer in-hospital stay and higher charges/stay.

Conclusion

Hypoglycemia is a rare event in patients hospitalized with STEMI. However, it was found to have higher odds of mortality, arrhythmias, and other comorbidities, irrespective of diabetes.

American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a Diabetes Mellitus Comprehensive Care Plan-2022 Update

OBJECTIVE

The objective of this clinical practice guideline is to provide updated and new evidence-based recommendations for the comprehensive care of persons with diabetes mellitus to clinicians, diabetes-care teams, other health care professionals and stakeholders, and individuals with diabetes and their caregivers.

METHODS

The American Association of Clinical Endocrinology selected a task force of medical experts and staff who updated and assessed clinical questions and recommendations from the prior 2015 version of this guideline and conducted literature searches for relevant scientific papers published from January 1, 2015, through May 15, 2022. Selected studies from results of literature searches composed the evidence base to update 2015 recommendations as well as to develop new recommendations based on review of clinical evidence, current practice, expertise, and consensus, according to established American Association of Clinical Endocrinology protocol for guideline development.

RESULTS

This guideline includes 170 updated and new evidence-based clinical practice recommendations for the comprehensive care of persons with diabetes. Recommendations are divided into four sections: (1) screening, diagnosis, glycemic targets, and glycemic monitoring; (2) comorbidities and complications, including obesity and management with lifestyle, nutrition, and bariatric surgery, hypertension, dyslipidemia, retinopathy, neuropathy, diabetic kidney disease, and cardiovascular disease; (3) management of prediabetes, type 2 diabetes with antihyperglycemic pharmacotherapy and glycemic targets, type 1 diabetes with insulin therapy, hypoglycemia, hospitalized persons, and women with diabetes in pregnancy; (4) education and new topics regarding diabetes and infertility, nutritional supplements, secondary diabetes, social determinants of health, and virtual care, as well as updated recommendations on cancer risk, nonpharmacologic components of pediatric care plans, depression, education and team approach, occupational risk, role of sleep medicine, and vaccinations in persons with diabetes.

CONCLUSIONS

This updated clinical practice guideline provides evidence-based recommendations to assist with person-centered, team-based clinical decision-making to improve the care of persons with diabetes mellitus.

Impact of prolonged requirement for insulin on 90-day mortality in critically ill patients without previous diabetic treatments: a post hoc analysis of the CONTROLING randomized control trial

BACKGROUND

Stress hyperglycemia can persist during an intensive care unit (ICU) stay and result in prolonged requirement for insulin (PRI). The impact of PRI on ICU patient outcomes is not known. We evaluated the relationship between PRI and Day 90 mortality in ICU patients without previous diabetic treatments.

METHODS

This is a post hoc analysis of the CONTROLING trial, involving 12 French ICUs. Patients in the personalized glucose control arm with an ICU length of stay ≥ 5 days and who had never previously received diabetic treatments (oral drugs or insulin) were included. Personalized blood glucose targets were estimated on their preadmission usual glycemia as estimated by their glycated A1c hemoglobin (HbA1C). PRI was defined by insulin requirement. The relationship between PRI on Day 5 and 90-day mortality was assessed by Cox survival models with inverse probability of treatment weighting (IPTW). Glycemic control was defined as at least one blood glucose value below the blood glucose target value on Day 5.

RESULTS

A total of 476 patients were included, of whom 62.4% were male, with a median age of 66 (54-76) years. Median values for SAPS II and HbA1C were 50 (37.5-64) and 5.7 (5.4-6.1)%, respectively. PRI was observed in 364/476 (72.5%) patients on Day 5. 90-day mortality was 23.1% in the whole cohort, 25.3% in the PRI group and 16.1% in the non-PRI group (p < 0.01). IPTW analysis showed that PRI on Day 5 was not associated with Day 90 mortality (_IPTWHR = 1.22; CI 95% 0.84-1.75; p = 0.29), whereas PRI without glycemic control was associated with an increased risk of death at Day 90 (_IPTWHR = 3.34; CI 95% 1.26-8.83; p < 0.01).

CONCLUSION

In ICU patients without previous diabetic treatments, only PRI without glycemic control on Day 5 was associated with an increased risk of death. Additional studies are required to determine the factors contributing to these results.

Admission Blood Glucose Level and Its Association With Cardiovascular and Renal Complications in Patients Hospitalized With COVID-19

OBJECTIVE

To investigate the association between admission blood glucose levels and risk of in-hospital cardiovascular and renal complications.

RESEARCH DESIGN AND METHODS

In this multicenter prospective study of 36,269 adults hospitalized with COVID-19 between 6 February 2020 and 16 March 2021 (N = 143,266), logistic regression models were used to explore associations between admission glucose level (mmol/L and mg/dL) and odds of in-hospital complications, including heart failure, arrhythmia, cardiac ischemia, cardiac arrest, coagulation complications, stroke, and renal injury. Nonlinearity was investigated using restricted cubic splines. Interaction models explored whether associations between glucose levels and complications were modified by clinically relevant factors.

RESULTS

Cardiovascular and renal complications occurred in 10,421 (28.7%) patients; median admission glucose level was 6.7 mmol/L (interquartile range 5.8-8.7) (120.6 mg/dL [104.4-156.6]). While accounting for confounders, for all complications except cardiac ischemia and stroke, there was a nonlinear association between glucose and cardiovascular and renal complications. For example, odds of heart failure, arrhythmia, coagulation complications, and renal injury decreased to a nadir at 6.4 mmol/L (115 mg/dL), 4.9 mmol/L (88.2 mg/dL), 4.7 mmol/L (84.6 mg/dL), and 5.8 mmol/L (104.4 mg/dL), respectively, and increased thereafter until 26.0 mmol/L (468 mg/dL), 50.0 mmol/L (900 mg/dL), 8.5 mmol/L (153 mg/dL), and 32.4 mmol/L (583.2 mg/dL). Compared with 5 mmol/L (90 mg/dL), odds ratios at these glucose levels were 1.28 (95% CI 0.96, 1.69) for heart failure, 2.23 (1.03, 4.81) for arrhythmia, 1.59 (1.36, 1.86) for coagulation complications, and 2.42 (2.01, 2.92) for renal injury. For most complications, a modifying effect of age was observed, with higher odds of complications at higher glucose levels for patients age <69 years. Preexisting diabetes status had a similar modifying effect on odds of complications, but evidence was strongest for renal injury, cardiac ischemia, and any cardiovascular/renal complication.

CONCLUSIONS

Increased odds of cardiovascular or renal complications were observed for admission glucose levels indicative of both hypo- and hyperglycemia. Admission glucose could be used as a marker for risk stratification of high-risk patients. Further research should evaluate interventions to optimize admission glucose on improving COVID-19 outcomes.

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.

Effect of Treatment and Nutrition on Glycemic Variability in Critically Ill Patients

Nondiabetic hyperglycemia is a dangerous metabolic phenomenon in the intensive care unit. Inattentive treatment of glycemic disorders is a serious health hazard promoting negative outcomes. The aim of our study was to assess glycemic variability and its basic determinants, and to verify its relationship with mortality in patients hospitalized in a mixed ICU (intensive care unit). The medical records of 37 patients hospitalized 13 January−29 February 2020 were analyzed prospectively. The BG (blood glucose) variability during the stay was assessed using two definitions, i.e., the value of standard deviation (SD) from all the measurements performed and the coefficient of variation (CV). A correlation between the BG variability and insulin dose was observed (SD: R = 0.559; p < 0.01; CV: R = 0.621; p < 0.01). There was also a correlation between the BG variability and the total energy daily dose (SD: R = 0.373; p = 0.02; CV: R = 0.364; p = 0.03). Glycemic variability was higher among patients to whom treatment with adrenalin (p = 0.0218) or steroid (p = 0.0292) was applied. The BG variability, expressed using SD, was associated with ICU mortality (ROC = 0.806; 95% CI: 0.643−0.917; p = 0.0014). The BG variability in the ICU setting arises from the loss of balance between the supplied energy and the applied insulin dose and may be associated with a worse prognosis.

Agreement of Potassium, Sodium, Glucose, and Hemoglobin Measured by Blood Gas Analyzer With Dry Chemistry Analyzer and Complete Blood Count Analyzer: A Two-Center Retrospective Analysis

Background

Blood gas analyzers (BGAs) and dry biochemistry analyzers for potassium and sodium are based on direct electrode methods, and both involve glucose oxidase for glucose detection. However, data are lacking regarding whether the results of the two assay systems can be used interchangeably. In addition, there remains controversy over the consistency between BGA-measured hemoglobin and complete blood count analyzer data. Here, we compared the consistency of sodium, potassium, glucose, and hemoglobin levels measured by BGA and dry chemistry and complete blood count analyzers.

Methods

Data from two teaching hospitals, the Zhejiang Provincial People's Hospital (ZRY) and the Qianfoshan Hospital (QY), were retrospectively analyzed based on dry biochemistry and complete blood count analyzer results as the reference system (X) and BGA as the experimental system (Y). Plasma was used for biochemical analysis at the ZRY Hospital, and serum at the QY Hospital. Paired data from the respective hospitals were evaluated for consistency, and biases between methods were assessed by simple correlation, Passing–Bablok regression, and Bland–Altman analyses.

Results

The correlations of potassium, sodium, glucose, and hemoglobin measured by BGA and dry biochemistry and complete blood count analyzers were high, at 0.9573, 0.8898, 0.9849, and 0.9883 for the ZRY Hospital and 0.9198, 0.8591, 0.9764, and 0.8666, respectively, for the QY Hospital. The results of Passing to Bablok regression analysis showed that the predicted biases at each medical decision level were within clinically acceptable levels for potassium, sodium, glucose, and hemoglobin at the ZRY Hospital. Only the predicted bias of glucose was below the clinically acceptable medical decision levels at the QY Hospital, while potassium, sodium, and hemoglobin were not. Compared with the reference system, the mean bias for BGA measurements at the ZRY Hospital was −0.08 mmol/L (95% confidence interval [CI] −0.091 to −0.069) for potassium, 1.2 mmol/L (95% CI 1.06 to 1.42) for sodium, 0.20 mmol/L (95% CI 0.167 to 0.228) for glucose, and −2.8 g/L for hemoglobin (95% CI −3.14 to −2.49). The mean bias for potassium, sodium, glucose, and hemoglobin at the QY Hospital were −0.46 mmol/L (95% CI −0.475 to −0.452), 3.7 mmol/L (95% CI 3.57 to 3.85), −0.36 mmol/L (95% CI −0.433 to −0.291), and −8.7 g/L (95% CI −9.40 to −8.05), respectively.

Conclusion

BGA can be used interchangeably with plasma electrolyte results from dry biochemistry analyzers but does not show sufficient consistency with serum electrolyte results from dry biochemistry analyzers to allow data interchangeability. Good consistency was observed between BGA and plasma or serum glucose results from dry biochemistry analyzers. However, BGA-measured hemoglobin and hematocrit assay results should be treated with caution.

Aging and comorbidities influence the risk of hospitalization and mortality in diabetic patients experiencing severe hypoglycemia

BACKGROUND AND AIMS

To assess the risk of hospitalization and mortality within 1 year of severe hypoglycaemia and theirs clinical predictors.

METHODS AND RESULTS

We retrospectively examined 399 admissions for severe hypoglycemia in adults with DM at the Emergency Department (ED) of the University Hospital of Novara (Italy) between 2012-2017, and we compared the clinical differences between older (aged ≥65 years) and younger individuals (aged 18-64 years). A logistic regression model was used to explore predictors of hospitalization following ED access and 1-year later, according to cardiovascular (CV) or not (no-CV) reasons; 1-year all-cause mortality was also detected. The study cohort comprised 302 patients (median [IQR] age 75 [17] years, 50.3% females, 93.4% white, HbA_1c level 7.6% [1.0%]). Hospitalization following ED access occurred in 16.2% of patients and kidney failure (OR 0.50 [95% CI 1.29-5.03]) was the only predictor of no-CV specific hospitalization; 1-year hospitalization occurred in 24.5% of patients and obesity (OR 3.17 [95% CI 1.20-8.12]) and pre-existing heart disease (OR 3.20 [95% 1.20-9.39]) were associated with CV specific hospitalization; 1-year all-cause mortality occurred in 14.9% of patients and was associated with older age (OR 1.12 [95% CI 1.07-1.18]) and pre-existing heart disease (OR 2.63 [95% CI 1.19-6.14]) CONCLUSIONS: Severe hypoglycemia is associated with risk of hospitalization and mortality mainly in elderly patients and it may be predictive of future cardiovascular events in diabetic patients with pre-existing heart disease and obesity.

Stability of 1-unit/mL insulin aspart solution in cyclic olefin copolymer vials and polypropylene syringes

DISCLAIMER

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time.

PURPOSE

This study evaluated the stability of diluted insulin aspart solutions (containing insulin aspart and preservatives) at their most commonly used concentration in intensive care units (1 unit/mL), in 2 container types: cyclic olefin copolymer (COC) vials and polypropylene (PP) syringes.

METHODS

Insulin aspart solution (1 unit/mL, diluted in 0.9% sodium chloride injection) was stored for 365 days in COC vials with gray stoppers and PP syringes at refrigerated (5±3°C) and ambient temperatures (25°C ± 2°C at 60% ± 5% relative humidity and protected from light). Chemical testing was conducted monthly using a validated high-performance liquid chromatography method (quantification of insulin aspart, phenol, and metacresol). Physical stability was evaluated monthly via pH measurements, visible and subvisible particle counts, and osmolality measurements. Sterility testing was also performed to validate the sterile preparation process and the maintenance of sterility throughout the study.

RESULTS

The limit of stability was set at 90% of the initial concentrations of insulin aspart, phenol, and metacresol. The physicochemical stability of 1-unit/mL insulin solutions stored refrigerated and protected from light, was unchanged in COC vials for the 365-day period and for 1 month in PP syringes. At ambient temperature, subvisible particulate contamination as well as the chemical stability of insulin and metacresol were acceptable for only 1 month's storage in PP syringes, while insulin chemical stability was maintained for only 3 months' storage in COC vials.

CONCLUSION

According to our results, it is not recommended to administer 1-unit/mL pharmacy-diluted insulin solutions after 3 months' storage in COC vials at ambient temperature or after 1 month in PP syringes at ambient temperature. The findings support storage of 1-unit/mL insulin aspart solution in COC vials at refrigerated temperature as the best option over the long term. Sterility was maintained in every condition. Both sterility and physicochemical stability are essential to authorize the administration of a parenteral insulin solution.

Relationship between blood glucose variability and muscle composition in ICU patients receiving nutrition support: A pilot study

BACKGROUND AND AIMS

Many critically ill patients experience increased blood glucose variability (BGV). The objective of the current pilot study was to assess the relationship between muscle composition (defined as average Hounsfield units (HU)) among ICU patients with an abdominal CT scan within seven days of intubation, and BGV (defined as coefficient of variation (CV)) calculated from blood glucose levels measured each morning while intubated.

METHODS

The first serum blood glucose measurement obtained each day during intubation was recorded, blood glucose CV ((mean/SD)∗100) was calculated. Cross-sectional muscle area (CSA; cm²) at the third lumbar region was identified using the -29 to +150 HU range; muscle composition was calculated as the average HU. BGV predictors were determined using linear regression.

RESULTS

Eighty-two patients were included (53% female), with a median age of 64 (25th, 75 percentile (IQR): 51, 70) years. The median CV was 29% (IQR: 20, 37); 40% of subjects required insulin. The median CSA was 100.4 cm² (IQR: 84.0, 120.8) and muscle composition was 20.4 HU (IQR: 12.2, 29.4). Patients received only 36% of estimated calorie requirements. Insulin administration, history of diabetes, and muscle composition were significant BGV predictors.

CONCLUSION

Among these adult intubated ICU patients, higher muscle composition was associated with lower BGV. Future research is needed to corroborate these findings, determine other factors associated with poor muscle quality, and identify methods to describe muscle composition for all ICU patients.

The obesity paradox and hypoglycemia in critically ill patients

BACKGROUND

A high body mass index (BMI) has been associated with decreased mortality in critically ill patients. This association may, in part, relate to the impact of BMI on glycemia. We aimed to study the relationship between BMI, glycemia and hospital mortality.

METHODS

We included all patients with a recorded BMI from four large international clinical databases (n = 259,177). We investigated the unadjusted association of BMI with average glucose levels, mortality and hypoglycemia rate. We applied multivariate analysis to investigate the impact of BMI on hypoglycemia rate, after adjusting for glycemia-relevant treatments (insulin, dextrose, corticosteroids, enteral and parenteral nutrition) and key physiological parameters (previous blood glucose level, blood lactate, shock state, SOFA score).

RESULTS

We analyzed 5,544,366 glucose measurements. On unadjusted analysis, increasing BMI was associated with increasing glucose levels (average increase of 5 and 10 mg/dL for the 25-30, 30-35 kg/m2 BMI groups compared to normal BMI (18.5-25 kg/m2) patients). Despite greater hyperglycemia, increasing BMI was associated with lower hospital mortality (average decrease of 2% and 3.25% for the 25-30, 30-35 kg/m2 groups compared to normal BMI patients) and lower hypoglycemia rate (average decrease of 2.5% and 3.5% for the 25-30, 30-35 kg/m2 groups compared to normal BMI patients). Increasing BMI was significantly independently associated with reduced hypoglycemia rate, with odds ratio (OR) 0.72 and 0.65, respectively (95% CIs 0.67-0.77 and 0.60-0.71, both p < 0.001) when compared with normal BMI. Low BMI patients showed greater hypoglycemia rate, with OR 1.6 (CI 1.43-1.79, p < 0.001). The association of high BMI and decreased mortality did not apply to diabetic patients. Although diabetic patients had higher rates of hypoglycemia overall and higher glucose variability (p < 0.001), they also had a reduced risk of hypoglycemia with higher BMI levels (p < 0.001).

CONCLUSIONS

Increasing BMI is independently associated with decreased risk of hypoglycemia. It is also associated with increasing hyperglycemia and yet with lower mortality. Lower risk of hypoglycemia might contribute to decreased mortality and might partly explain the obesity paradox. These associations, however, were markedly modified by the presence of diabetes.

Pros and cons of continuous glucose monitoring in the intensive care unit

Diabetes mellitus affects people worldwide, and management of its acute complications or treatment-related adverse events is particularly important in critically ill patients. Previous reports have confirmed that hyperglycemia can increase the risk of mortality in patients cared in the intensive care unit (ICU). In addition, severe and multiple hypoglycemia increases the risk of mortality when using insulin or intensive antidiabetic therapy. The innovation of continuous glucose monitoring (CGM) may help to alert medical caregivers with regard to the development of hyperglycemia and hypoglycemia, which may decrease the potential complications in patients in the ICU. The major limitation of CGM is the measurement of interstitial glucose levels rather than real-time blood glucose levels; thus, there will be a delay in the treatment of hyperglycemia and hypoglycemia in patients. Recently, the European Union approved a state-of-art artificial intelligence directed loop system coordinated by CGM and a continuous insulin pump for diabetes control, which may provide a practical way to prevent acute adverse glycemic events related to antidiabetic therapy in critically ill patients. In this mini-review paper, we describe the application of CGM to patients in the ICU and summarize the pros and cons of CGM.

Hypoglycemia and mortality in sepsis patients: A systematic review and meta-analysis

BACKGROUND

Hypoglycemia frequently occurs in patients with sepsis. The status of prognosis of sepsis patients varies with the cause of hypoglycemia.

OBJECTIVE

A meta-analysis was performed to obtain a reliable basis for assessing the severity of disease in sepsis patients.

METHODS

A search of electronic databases was performed. The random-effects model was employed to calculate the overall odds ratio (OR) and 95% CI.

RESULTS

Five cohort studies were included. Decreased blood glucose level was associated with an increased risk of death [OR:1.68; 95% CI (1.12-2.53)]. Incidents of mortality were analyzed based on the causative factor of hypoglycemia. Patients with spontaneous hypoglycemia showed a significantly higher mortality rate than the control subjects[OR 1.65; 95% CI (1.20-2.28); p = 0.002].

CONCLUSION

In the early stages of sepsis, the occurrence of spontaneous hypoglycemia may be associated with the severity of the disease.

The paradox of the glycemic gap: Does relative hypoglycemia exist in critically ill patients?

BACKGROUND & AIMS

Elevated glycemic gap, as the differences between measured glucose and hemoglobin A1c (HbA1c)-derived average glucose (ADAG) levels, is a marker of stress-induced hyperglycemia and is a predictor of mortality in critically ill patients. Whether low glycemic gaps are associated with outcomes in critically ill patients remains unclear. We investigated the association of different glycemic gaps on mortality in critically ill patients.

METHODS

Totally 935 patients admitted to intensive care units (ICUs) were enrolled retrospectively after the exclusion of patients with absolute hypoglycemia, extreme hyperglycemia, and incomplete glycemic records. Patients were divided into 3 groups according to their glycemic gaps (<-29.7, -29.7-40, ≧40 mg/dL) at the time of ICU admission. The patients were followed for 1 year or until death.

RESULTS

Patients with low glycemic gap (glycemic gap < -29.7 mg/dL), which implied relative hypoglycemia, had lower serum glucose levels, higher HbA1c levels, and greater disease severity. Compared with medium group (glycemic gap -29.7-40 mg/dL), both the low and the high glycemic gap (glycemic gap ≧40 mg/dL) groups had significantly greater 30-day (log-rank p = 0.0464) and 1-year mortality (log-rank p = 0.0016). However, only the low glycemic gap group was independently associated with greater in-hospital mortality after adjusting for comorbidities (adjusted OR 1.78, 95% CI 1.00-3.16, p = 0.048).

CONCLUSION

This study revealed the presence of a U-shaped relationship between the glycemic gap and mortality in critically ill patients. Low glycemic gaps suggested relative hypoglycemia at the time of ICU admission, and were associated independently with greater in-hospital mortality.

The Interaction of Acute and Chronic Glycemia on the Relationship of Hyperglycemia, Hypoglycemia, and Glucose Variability to Mortality in the Critically Ill

OBJECTIVES

To determine the relationship between preadmission glycemia, reflected by hemoglobin A1c level, glucose metrics, and mortality in critically ill patients.

DESIGN

Retrospective cohort investigation.

SETTING

University affiliated adult medical-surgical ICU.

PATIENTS

The investigation included 5,567 critically ill patients with four or more blood glucose tests and hemoglobin A1c level admitted between October 11, 2011 and November 30, 2019. The target blood glucose level was 90-120 mg/dL for patients admitted before September 14, 2014 (n = 1,614) and 80-140 mg/dL or 110-160 mg/dL for patients with hemoglobin A1c less than 7% or greater than or equal to 7% (n = 3,953), respectively, subsequently.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients were stratified by hemoglobin A1c: less than 6.5.(n = 4,406), 6.5-7.9% (n = 711), and greater than or equal to 8.0% (n = 450). Increasing hemoglobin A1c levels were associated with significant increases in mean glycemia, glucose variability, as measured by coefficient of variation, and hypoglycemia (p for trend < 0.0001, < 0.0001, and 0.0010, respectively). Among patients with hemoglobin A1c less than 6.5%, mortality increased as mean glycemia increased; however, among patients with hemoglobin A1c greater than or equal to 8.0%, the opposite relationship was observed (p for trend < 0.0001 and 0.0027, respectively). Increasing glucose variability was independently associated with increasing mortality only among patients with hemoglobin A1c less than 6.5%. Hypoglycemia was independently associated with higher mortality among patients with hemoglobin A1c less than 6.5% and 6.5-7.9% but not among those with hemoglobin A1c greater than or equal to 8.0%. Mean blood glucose 140-180 and greater than or equal to 180 mg/dL were independently associated with higher mortality among patients with hemoglobin A1c less than 6.5% (p < 0.0001 for each). Among patients with hemoglobin A1c greater than or equal to 8.0% treated in the second era, mean blood glucose greater than or equal to 180 mg/dL was independently associated with decreased risk of mortality (p = 0.0358).

CONCLUSIONS

Preadmission glycemia, reflected by hemoglobin A1c obtained at the onset of ICU admission, has a significant effect on the relationship of ICU glycemia to mortality. The different responses to increasing mean glycemia support a personalized approach to glucose control practices in the ICU.

The goldilocks problem: Nutrition and its impact on glycaemic control

BACKGROUND

Glucose intolerance and insulin resistance manifest as hyperglycaemia in intensive care, which is associated with mortality and morbidities. Glycaemic control (GC) may improve outcomes, though safe and effective control has proven elusive. Nutritional glucose intake affects blood glucose (BG) outcomes, but few protocols actively control it. This study aims to examine BG outcomes in the context of nutritional management during GC.

METHODS

Retrospective cohort analysis of 5 glycaemic control cohorts spanning 4 years (n = 273) from Christchurch Hospital Intensive Care Unit (ICU). GC is delivered using a single model-based protocol (STAR), with default 4.4-8.0 mmol/L target range via. modulation of insulin and nutrition. Clinical adaptations/cohorts include variations on upper target (UL-9 with 9.0 mmol/L, reducing workload and nutrition responsiveness), and insulin only (IO) with clinically set nutrition at 3 glucose concentrations (71 g/L vs. 120 and 180 g/L in the TARGET study).

RESULTS

Percent of BG hours in the 4.4-8.0 mmol/L range highest under standard STAR conditions (78%), and was lower at 64% under UL-9, likely due to reduced time-responsiveness of nutrition-insulin changes. By comparison, IO only resulted in 64-69% BG in range across different nutrition types. A subset of patients receiving high glucose nutrition under IO were persistently hyperglycaemic, indicating patient-specific glucose tolerance.

CONCLUSION

STAR GC is most effective when nutrition and insulin are modulated together with timely responsiveness to persistent hyperglycaemia. Results imply modulation of nutrition alongside insulin improves GC, particularly in patients with persistent hyperglycaemia/low glucose tolerance.

A prospective randomized trial comparing computerized columnar insulin dosing chart (the Atlanta protocol) versus the joint British diabetes societies for inpatient care protocol in management of hyperglycemia in patients with acute coronary syndrome admitted to cardiac care unit in Alexandria, Egypt

BACKGROUND

Hyperglycemia in acute coronary syndrome (ACS) is linked to raised morbidity and mortality. Insulin administration using insulin infusion protocols (IIP) is the preferred strategy to control hyperglycemia in critically ill patients. To date, no specific IIP has been identified as the most efficient for achieving glycemic control.

AIM

to compare glycemic achievements (safety) (primary objective), and coronary and other clinical outcomes (efficacy) (secondary objective) by hyperglycemia management in Cardiac Care Unit (CCU) using computerized Atlanta Protocol (Group (I)) versus paper-based Joint British Diabetes Societies (JBDS) For Inpatient Care Protocol (Group (II)).

PATIENTS AND METHODS

The study was done on 100 ACS patients admitted to Alexandria Main University hospital CCU with RBG >180 mg/dL. They were randomized into the 2 groups in a 1:1 ratio. CBG was measured hourly for 72 hours and was managed by IV insulin infusion.

RESULTS

Group (I) showed statistically significant less mean time for target BG achievement (3.52 ± 1.53hours), lower incidence of Level 1 hypoglycemia (2%) than Group (II) (4.76 ± 2.33 hours, 22%, p = 0.013, 0.002 respectively) and statistically significant less mean number of episodes above the glycemic target after its achievement than Group (II) (p < 0.001). Regarding Level 2 hypoglycemia the difference was not significant statistically.

CONCLUSION

Both protocols successfully maintained target BG level with low incidence of clinically significant hypoglycemia, however, the computerized Atlanta protocol achieved better glycemic outcomes. We recommend the use of the computerized Atlanta protocol in CCU rather than JBDS for Inpatient Care Protocol whenever this is feasible.

Incorporating real-world evidence into the development of patient blood glucose prediction algorithms for the ICU

Objective

Glycemic control is an important component of critical care. We present a data-driven method for predicting intensive care unit (ICU) patient response to glycemic control protocols while accounting for patient heterogeneity and variations in care.

Materials and Methods

Using electronic medical records (EMRs) of 18 961 ICU admissions from the MIMIC-III dataset, including 318 574 blood glucose measurements, we train and validate a gradient boosted tree machine learning (ML) algorithm to forecast patient blood glucose and a 95% prediction interval at 2-hour intervals. The model uses as inputs irregular multivariate time series data relating to recent in-patient medical history and glycemic control, including previous blood glucose, nutrition, and insulin dosing.

Results

Our forecasting model using routinely collected EMRs achieves performance comparable to previous models developed in planned research studies using continuous blood glucose monitoring. Model error, expressed as mean absolute percentage error is 16.5%–16.8%, with Clarke error grid analysis demonstrating that 97% of predictions would be clinically acceptable. The 95% prediction intervals achieve near intended coverage at 93%–94%.

Discussion

ML algorithms built on observational data sources, such as EMRs, present a promising approach for personalization and automation of glycemic control in critical care. Future research may benefit from applying a combination of methodologies and data sources to develop robust methodologies that account for the variations seen in ICU patients and difficultly in detecting the extremes of observed blood glucose values.

Conclusion

We demonstrate that EMRs can be used to train ML algorithms that may be suitable for incorporation into ICU decision support systems.

Hypoglycemia: Comparison of Health Status Outcomes Between Patients After Allogeneic Hematopoietic Cell Transplantation

BACKGROUND

Patients who have undergone hematopoietic cell transplantation (HCT) often face lengthy hospital stays. Hospitalized patients' compromised health status puts them at risk for complications to recovery when glucose is not controlled.

OBJECTIVES

This study aimed to investigate differences in outcomes in patients who experienced hypoglycemia compared to patients who did not experience hypoglycemia post-allogeneic HCT.

METHODS

A retrospective chart review and secondary data analysis were conducted. The sample consisted of 198 adult patients hospitalized for their first allogeneic HCT at the University of Minnesota Medical Center between August 2015 and December 2017. Hypoglycemic patients were compared with nonhypoglycemic patients until discharge or 100 hospitalization days post-transplantation.

FINDINGS

A total of 20 patients (10%) experienced hypoglycemic events during the study time frame. There were significant differences between the two groups. Hypoglycemia may be a marker for higher acuity illness in this population. Nurses should increase vigilance in managing the blood glucose levels of patients undergoing HCT with known comorbidities and complications.

Hypoglycemic episodes predict length of stay in patients with acute burns

Hypoglycemic episodes are associated with worse hospital outcomes. All adult patients admitted to our burn center from 2015 to 2019 were retrospectively reviewed. Patient demographics and burn characteristics were recorded. The primary outcome was mortality, and secondary outcomes were total length-of-stay and intensive care unit length-of-stay. All patients experiencing at least one hypoglycemic episode were compared to patients who did not experience hypoglycemia. There were 914 patients with acute burns admitted during the study period, 33 of which (4%) experienced hypoglycemic episodes. Of these, 17 patients (52%) experienced a single hypoglycemic episode, while the remainder experienced multiple hypoglycemic episodes. Patients with one or more hypoglycemic events were matched to non-hypoglycemic controls using propensity matching. Patients that experienced hypoglycemia had significantly less TBSA involvement (5% vs. 13%,median, p < 0.0002), higher prevalence of diabetes (48% vs. 18%, p < 0.0001), higher mortality (18% vs. 7%, p = 0.01), longer total length-of-stay (22 vs. 8 days, median, p < 0.0001), and longer ICU length-of-stay (12 vs. 0 days, median, p < 0.0001). A single hypoglycemic episode was associated with prolonged total (IRR = 1.91, p < 0.0001) and ICU length-of-stay (IRR = 3.86, p < 0.0001). Hypoglycemia was not associated with higher mortality in the survival analysis (p = 0.46).

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.

Fifteen-minute Frequency of Glucose Measurements and the Use of Threshold Alarms: Impact on Mitigating Dysglycemia in Critically Ill Patients

BACKGROUND

The use of near-continuous blood glucose (BG) monitoring has the potential to improve glycemic control in critically ill patients. The MANAGE IDE trial evaluated the performance of the OptiScanner (OS) 5000 in a multicenter cohort of 200 critically ill patients.

METHODS

An Independent Group reviewed the BG run charts of all 200 patients and voted whether unblinded use of the OS, with alarms set at 90 and 130 to 150 mg/dL to alert the clinical team to impending hypoglycemia and hyperglycemia, respectively, would have eliminated episodes of dysglycemia: hypoglycemia, defined as a single BG <70 mg/dL; hyperglycemia, defined as >4 hours of BG >150 mg/dL; severe hyperglycemia, defined as >4 hours of BG >200 mg/dL and increased glucose variability (GV), defined as coefficient of variation (CV) >20%.

RESULTS

At least one episode of dysglycemia occurred in 103 (51.5%) of the patients, including 6 (3.0%) with hypoglycemia, 83 (41.5%) with hyperglycemia, 18 (9.0%) with severe hyperglycemia, and 40 (20.0%) with increased GV. Unblinded use of the OS with appropriate alarms would likely have averted 97.1% of the episodes of dysglycemia: hypoglycemia (100.0%), hyperglycemia (96.4%), severe hyperglycemia (100.0%), and increased GV (97.5%). Point accuracy of the OS was very similar to that of the point of care BG monitoring devices used in the trial.

CONCLUSION

Unblinded use of the OS would have eliminated nearly every episode of dysglycemia in this cohort of critically ill patients, thereby markedly improving the quality and safety of glucose control.

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.

Insulin sensitivity in critically ill patients: are women more insulin resistant?

Background

Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability, leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant difference would suggest GC and randomised trial design should consider sex differences to personalise care.

Methods

Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women. Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo simulations analyses where the number of men and women are equal.

Results

Demographic data between females and males were all similar, including GC outcomes (safety from hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different between males and females, but intra-patient variability was equivalent.

Conclusion

Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.

Insulin sensitivity in critically ill patients: are women more insulin resistant?

BACKGROUND

Glycaemic control (GC) in intensive care unit is challenging due to significant inter- and intra-patient variability, leading to increased risk of hypoglycaemia. Recent work showed higher insulin resistance in female preterm neonates. This study aims to determine if there are differences in inter- and intra-patient metabolic variability between sexes in adults, to gain in insight into any differences in metabolic response to injury. Any significant difference would suggest GC and randomised trial design should consider sex differences to personalise care.

METHODS

Insulin sensitivity (SI) levels and variability are identified from retrospective clinical data for men and women. Data are divided using 6-h blocks to capture metabolic evolution over time. In total, 91 male and 54 female patient GC episodes of minimum 24 h are analysed. Hypothesis testing is used to determine whether differences are significant (P < 0.05), and equivalence testing is used to assess whether these differences can be considered equivalent at a clinical level. Data are assessed for the raw cohort and in 100 Monte Carlo simulations analyses where the number of men and women are equal.

RESULTS

Demographic data between females and males were all similar, including GC outcomes (safety from hypoglycaemia and high (> 50%) time in target band). Females had consistently significantly lower SI levels than males, and this difference was not clinically equivalent. However, metabolic variability between sexes was never significantly different and always clinically equivalent. Thus, inter-patient variability was significantly different between males and females, but intra-patient variability was equivalent.

CONCLUSION

Given equivalent intra-patient variability and significantly greater insulin resistance, females can receive the same benefit from safe, effective GC as males, but may require higher insulin doses to achieve the same glycaemia. Clinical trials should consider sex differences in protocol design and outcome analyses.

Increased insulin resistance in intensive care: longitudinal retrospective analysis of glycaemic control patients in a New Zealand ICU

BACKGROUND

Critical care populations experience demographic shifts in response to trends in population and healthcare, with increasing severity and/or complexity of illness a common observation worldwide. Inflammation in critical illness impacts glucose-insulin metabolism, and hyperglycaemia is associated with mortality and morbidity. This study examines longitudinal trends in insulin sensitivity across almost a decade of glycaemic control in a single unit.

METHODS

A clinically validated model of glucose-insulin dynamics is used to assess hour-hour insulin sensitivity over the first 72 h of insulin therapy. Insulin sensitivity and its hour-hour percent variability are examined over 8 calendar years alongside severity scores and diagnostics.

RESULTS

Insulin sensitivity was found to decrease by 50-55% from 2011 to 2015, and remain low from 2015 to 2018, with no concomitant trends in age, severity scores or risk of death, or diagnostic category. Insulin sensitivity variability was found to remain largely unchanged year to year and was clinically equivalent (95% confidence interval) at the median and interquartile range. Insulin resistance was associated with greater incidence of high insulin doses in the effect saturation range (6-8 U/h), with the 75th percentile of hourly insulin doses rising from 4-4.5 U/h in 2011-2014 to 6 U/h in 2015-2018.

CONCLUSIONS

Increasing insulin resistance was observed alongside no change in insulin sensitivity variability, implying greater insulin needs but equivalent (variability) challenge to glycaemic control. Increasing insulin resistance may imply greater inflammation and severity of illness not captured by existing severity scores. Insulin resistance reduces glucose tolerance, and can cause greater incidence of insulin saturation and resultant hyperglycaemia. Overall, these results have significant clinical implications for glycaemic control and nutrition management.

Blood glucose levels should be considered as a new vital sign indicative of prognosis during hospitalization

BACKGROUND AND AIMS

The measurement of vital signs is an important part of clinical work up. Presently, measurement of blood glucose is a factor for concern mostly when treating individuals with diabetes. Significance of blood glucose measurement in prognosis of non-diabetic and hospitalized patients is not clear.

METHODS

A systematic search of literature published in the Electronic databases, PubMed and Google Scholar was performed using following keywords; blood glucose, hospital admissions, critical illness, hospitalizations, cardiovascular disease (CVD), morbidity, and mortality. This literature search was largely restricted to non-diabetic individuals.

RESULTS

Blood glucose level, even when in high normal range, or in slightly high range, is an important determinant of morbidity and mortality, especially in hospitalized patients. Further, even slight elevation of blood glucose may increase mortality in patients with COVID-19. Finally, blood glucose variability and hypoglycemia in critically ill individuals without diabetes causes excess in-hospital complications and mortality.

CONCLUSION

In view of these data, we emphasize the significance of blood glucose measurement in all patients admitted to the hospital regardless of presence of diabetes. We propose that blood glucose be included as the "fifth vital sign" for any hospitalized patient.

The Association of Mean Plasma Glucose and In hospital Death Proportion: A Retrospective, Cohort Study of 162,169 In-Patient Data

AIMS

To investigate the association between mean plasma glucose and inhospital death proportion.

METHODS

We retrospectively collected 162,169 inpatient data in Huashan Hospital from January 2012 to December 2015. Mean plasma glucose was calculated and considered as the average glycemia control during hospitalization. Patients were stratified into six groups according to mean plasma glucose. Nonlinear regression was performed to determine the associations between mean plasma glucose and inhospital death proportion, medical cost, and length of stay. Multivariate logistic regressions were performed to evaluate the relationship of mean plasma glucose and outcomes controlling for confounders including age, gender, and others. Subgroup analyses were performed on basis of whether they were surgical patients, ICU patients, patients with diabetes, or others.

RESULTS

Of the 162,169 hospitalized participants, 53.32% were male and 989 died during hospitalization. Nonlinear regression showed there were positive and significant associations between mean plasma glucose and death proportion, medical cost, and length of stay (P < 0.001 for all). Multivariate logistic regressions showed that, compared with group B, a statistically significant association between mean plasma glucose and predicted outcome was apparent, with the odds ratios (95% confidence interval) of 5.79 (3.51-9.55), 2.85 (2.40-3.38), 6.29 (5.24-7.54), 9.34 (7.51-11.62), and 23.52 (16.64-33.26), for group A, group C, group D, group E, and group F, respectively. There was a U-shaped association between mean plasma glucose and death proportion. Subgroup analyses showed similar associations between mean plasma glucose and death proportion, medical cost, and length of stay as in the whole sample.

CONCLUSIONS

There was a U-curve association between mean plasma glucose with inhospital death proportion. Mean plasma glucose was associated positively with medical cost and length of stay.