Dysglycaemia in the critically ill and the interaction of chronic and acute glycaemia with mortality

Between blood glucose and mortality in critically ill patients: Retrospective analysis of the MIMIC-IV database

AIMS/INTRODUCTION

Mean blood glucose (MBG) level is associated with mortality among critically ill patients. We undertook a cohort study to investigate the relationship between MBG and mortality in critically ill patients.

MATERIALS AND METHODS

Critically ill patients were enrolled from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. MBG was calculated to represent the overall glycemic status during intensive care unit (ICU) hospitalization, and a multivariate logistic regression determined the relationship between MBG and ICU mortality in different subgroups of critically ill patients.

RESULTS

A total of 8,973 patients were included in the study, 1,244 of whom died within 28 days, including 5,402 men and 3,571 women. Multivariate adjusted restricted cubic spline analyses suggested that the relationship between MBG and ICU mortality was a "J" shape. Logistic regression showed 28 day mortality in group 3 (glucose ≥10 mmol/L): the adjusted odds ratio was 2.06 (95% confidence interval 1.65-2.57). The results of subgroup analysis showed that hyperglycemia had a more significant impact on ICU mortality in patients without diabetes, hypoglycemia and liver disease, and the ICU mortality risk of non-diabetes patients was always higher than that of diabetes patients with the same hyperglycemia level.

CONCLUSIONS

Current evidence suggested a J-shaped relationship between MBG and mortality in critically ill patients.

Association Between Individualized Versus Conventional Blood Glucose Thresholds and Acute Kidney Injury After Cardiac Surgery: A Retrospective Observational Study

OBJECTIVES

This study was designed to compare individualized and conventional hyperglycemic thresholds for the risk of acute kidney injury (AKI) after cardiac surgery.

DESIGN

This was an observational study.

SETTING

The study took place in a single-center tertiary teaching hospital.

PARTICIPANTS

Adult patients who underwent cardiac surgery between January 2012 and November 2021 were enrolled.

MEASUREMENTS AND MAIN RESULTS

Two blood glucose thresholds were used to define intraoperative hyperglycemia. While the conventional hyperglycemic threshold (CHT) was 180 mg/dL in all patients, the individualized hyperglycemic threshold (IHT) was calculated based on the preoperative hemoglobin A1c level. Various metrics of intraoperative hyperglycemia were calculated using both thresholds: any hyperglycemic episode, duration of hyperglycemia, and area above the thresholds. Postoperative AKI associations were compared using receiver operating characteristic curves and logistic regression analysis. Among the 2,427 patients analyzed, 823 (33.9%) developed AKI. The C-statistics of IHT-defined metrics (0.58-0.59) were significantly higher than those of the CHT-defined metrics (all C-statistics, 0.54; all p < 0.001). The duration of hyperglycemia (adjusted odds ratio, 1.09; 95% confidence interval, 1.02-1.16) and area above the IHT (1.003; 1.001-1.004) were significantly associated with the risk of AKI, except for the presence of any hyperglycemic episode. None of the CHT-defined metrics were significantly associated with the risk of AKI.

CONCLUSIONS

Individually defined intraoperative hyperglycemia better predicted postcardiac surgery AKI than universally defined hyperglycemia. Intraoperative hyperglycemia was significantly associated with the risk of AKI only for the IHT. Target blood glucose levels in cardiac surgical patients may need to be individualized based on preoperative glycemic status.

Association of Relative Dysglycemia With Hospital Mortality in Critically Ill Patients: A Retrospective Study

OBJECTIVES

Relative dysglycemia has been proposed as a clinical entity among critically ill patients in the ICU, but is not well studied. This study aimed to clarify associations of relative hyperglycemia and hypoglycemia during the first 24 hours after ICU admission with in-hospital mortality and the respective thresholds.

DESIGN

A single-center retrospective study.

SETTING

An urban tertiary hospital ICU.

PATIENTS

Adult critically ill patients admitted urgently between January 2016 and March 2022.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Maximum and minimum glycemic ratio (GR) was defined as maximum and minimum blood glucose values during the first 24 hours after ICU admission divided by hemoglobin A1c-derived average glucose, respectively. Of 1700 patients included, in-hospital mortality was 16.9%. Nonsurvivors had a higher maximum GR, with no significant difference in minimum GR. Maximum GR during the first 24 hours after ICU admission showed a J-shaped association with in-hospital mortality, and a mortality trough at a maximum GR of approximately 1.12; threshold for increased adjusted odds ratio for mortality was 1.25. Minimum GR during the first 24 hours after ICU admission showed a U-shaped relationship with in-hospital mortality and a mortality trough at a minimum GR of approximately 0.81 with a lower threshold for increased adjusted odds ratio for mortality at 0.69.

CONCLUSIONS

Mortality significantly increased when GR during the first 24 hours after ICU admission deviated from between 0.69 and 1.25. Further evaluation will necessarily validate the superiority of personalized glycemic management over conventional management.

The optimal glycemic target in critically ill patients: an updated network meta-analysis

Acute glycemic control significantly affects the clinical outcomes of critically ill patients. This updated network meta-analysis examines the benefits and harms of four target blood glucose levels (< 110, 110-144, 144-180, and > 180 mg/dL). Analyzing data of 27,541 patients from 37 trials, the surface under the cumulative ranking curve for mortality and hypoglycemia was highest at a target blood glucose level of 144-180 mg/dL, while for infection and acute kidney injury at 110-144 mg/dL. Further evidence is needed to determine whether 110-144 or 144-180 mg/dL is superior as an optimal glucose target, considering prioritized outcomes.

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.

Effects of Glycemic Variability in Critically Ill Patients with Coronavirus Disease 2019: A Retrospective Observational Study

Aim and background

Hyperglycemia is considered an adaptive metabolic manifestation of stress and is associated with poor outcomes. Herein, we analyzed the association between glycemic variability (GV) and hospital mortality in patients with coronavirus disease 2019 (COVID-19) admitted to the intensive care unit (ICU), and the association between GV and mechanical ventilation (MV), ICU stay, length of hospital stays, renal replacement therapy (RRT), hypoglycemia, nosocomial infections, insulin use, and corticosteroid class.

Materials and methods

In this retrospective observational study, we collected information on blood glucose levels during the first 10 days of hospitalization in a cohort of ICU patients with COVID-19 and its association with outcomes.

Results

In 239 patients, an association was observed between GV and hospital mortality between the first and last quartiles among patients without diabetes [odds ratio (OR), 3.78; confidence interval, 1.24-11.5]. A higher GV was associated with a greater need for RRT (p = 0.002), regular insulin (p < 0.001), and episodes of hypoglycemia (p < 0.001). Nosocomial infections were associated with intermediate GV quartiles (p = 0.02). The corticosteroid class had no association with GV (p = 0.21).

Conclusion

Glycemic variability was associated with high mortality in patients with COVID-19 and observed in the subgroup of patients without diabetes.

Clinical significance

Glycemic control in critically ill patients remains controversial and hyperglycemia is associated with worse outcomes. Diabetes mellitus (DM) is one of the most prevalent comorbidities in patients with COVID-19. In addition, they require corticosteroids due to pulmonary involvement, representing a challenge and an opportunity to better understand how glycemic changes can influence the outcome of these patients.

How to cite this article

Boschi E, Friedman G, Moraes RB. Effects of Glycemic Variability in Critically Ill Patients with Coronavirus Disease 2019: A Retrospective Observational Study. Indian J Crit Care Med 2024;28(4):381-386.

Diabetes Mellitus, Energy Metabolism, and COVID-19

Obesity, diabetes mellitus (mostly type 2), and COVID-19 show mutual interactions because they are not only risk factors for both acute and chronic COVID-19 manifestations, but also because COVID-19 alters energy metabolism. Such metabolic alterations can lead to dysglycemia and long-lasting effects. Thus, the COVID-19 pandemic has the potential for a further rise of the diabetes pandemic. This review outlines how preexisting metabolic alterations spanning from excess visceral adipose tissue to hyperglycemia and overt diabetes may exacerbate COVID-19 severity. We also summarize the different effects of SARS-CoV-2 infection on the key organs and tissues orchestrating energy metabolism, including adipose tissue, liver, skeletal muscle, and pancreas. Last, we provide an integrative view of the metabolic derangements that occur during COVID-19. Altogether, this review allows for better understanding of the metabolic derangements occurring when a fire starts from a small flame, and thereby help reducing the impact of the COVID-19 pandemic.

Relationship between time-weighted average glucose and mortality in critically ill patients: a retrospective analysis of the MIMIC-IV database

Blood glucose management in intensive care units (ICU) remains a controversial topic. We assessed the association between time-weighted average glucose (TWAG) levels and ICU mortality in critically ill patients in a real-world study. This retrospective study included critically ill patients from the Medical Information Mart for Intensive Care IV database. Glycemic distance is the difference between TWAG in the ICU and preadmission usual glycemia assessed with glycated hemoglobin at ICU admission. The TWAG and glycemic distance were divided into 4 groups and 3 groups, and their associations with ICU mortality risk were evaluated using multivariate logistic regression. Restricted cubic splines were used to explore the non-linear relationship. A total of 4737 adult patients were included. After adjusting for covariates, compared with TWAG ≤ 110 mg/dL, the odds ratios (ORs) of the TWAG > 110 mg/dL groups were 1.62 (95% CI 0.97-2.84, p = 0.075), 3.41 (95% CI 1.97-6.15, p < 0.05), and 6.62 (95% CI 3.6-12.6, p < 0.05). Compared with glycemic distance at - 15.1-20.1 mg/dL, the ORs of lower or higher groups were 0.78 (95% CI 0.50-1.21, p = 0.3) and 2.84 (95% CI 2.12-3.82, p < 0.05). The effect of hyperglycemia on ICU mortality was more pronounced in non-diabetic and non-septic patients. TWAG showed a U-shaped relationship with ICU mortality risk, and the mortality risk was minimal at 111 mg/dL. Maintaining glycemic distance ≤ 20.1 mg/dL may be beneficial. In different subgroups, the impact of hyperglycemia varied.

Hyperglycaemia and Its Prognostic Value in Patients with COVID-19 Admitted to the Hospital in Lithuania

BACKGROUND AND OBJECTIVES

Increased blood glucose levels atadmission are frequently observed in COVID-19 patients, even in those without pre-existing diabetes. Hyperglycaemia is associated with an increased incidence of severe COVID-19 infection. The aim of this study was to evaluate the association between hyperglycaemia at admission with the need for invasive mechanical ventilation (IMV) and in-hospital mortality in patients without diabetes who were hospitalized for COVID-19 infection.

MATERIALS AND METHODS

This retrospective observational study was conducted at Vilnius University Hospital Santaros Clinics, Lithuania with adult patients who tested positive for severe acute respiratory syndrome coronavirus 2 SARS-CoV-2 and were hospitalized between March 2020 and May 2021. Depersonalized data were retrieved from electronic medical records. Based on blood glucose levels on the day of admission, patients without diabetes were divided into 4 groups: patients with hypoglycaemia (blood glucose below 4.0 mmol/L), patients with normoglycaemia (blood glucose between ≥4.0 mmol/L and <6.1 mmol/L), patients with mild hyperglycaemia (blood glucose between ≥6.1 mmol/L and <7.8 mmol/L), and patients with intermittent hyperglycaemia (blood glucose levels ≥7.8 mmol/L and <11.1 mmol/L). A multivariable binary logistic regression model was created to determine the association between hyperglycaemia and the need for IMV. Survival analysis was performed to assess the effect of hyperglycaemia on outcome within 30 days of hospitalization.

RESULTS

Among 1945 patients without diabetes at admission, 1078 (55.4%) had normal glucose levels, 651 (33.5%) had mild hyperglycaemia, 196 (10.1%) had intermittent hyperglycaemia, and 20 (1.0%) had hypoglycaemia. The oddsratio (OR) for IMV in patients with intermittent hyperglycaemia was 4.82 (95% CI 2.70-8.61, p < 0.001), and the OR was 2.00 (95% CI 1.21-3.31, p = 0.007) in those with mild hyperglycaemia compared to patients presenting normal glucose levels. The hazardratio (HR) for 30-day in-hospital mortality in patients with mild hyperglycaemia was 1.62 (95% CI 1.10-2.39, p = 0.015), while the HR was 3.04 (95% CI 2.01-4.60, p < 0.001) in patients with intermittent hyperglycaemia compared to those with normoglycaemia at admission.

CONCLUSIONS

In COVID-19 patients without pre-existing diabetes, the presence of hyperglycaemia at admission is indicative of COVID-19-induced alterations in glucose metabolism and stress hyperglycaemia. Hyperglycaemia at admission in COVID-19 patients without diabetes is associated with an increased risk of invasive mechanical ventilation and in-hospital mortality. This finding highlights the importance for clinicians to carefully consider and select optimal support and treatment strategies for these patients. Further studies on the long-term consequences of hyperglycaemia in this specific population are warranted.

Effect of stress hyperglycaemia on acute kidney injury in non-diabetic critically ill patients?

BACKGROUND

Stress hyperglycaemia (SH) and acute kidney injury (AKI) occur frequently in critically ill patients, and particularly non-diabetics are associated with adverse outcome. Data is scarce on the effect of SH on AKI. We assessed whether SH (i) preceded AKI, (ii) was a risk factor of subsequent AKI, and (iii) how SH and tubular injury interacted in AKI development in critically ill, non-diabetics.

METHODS

Case-control study of 82 patients each with and without SH matched by propensity score for multiple demographic characteristics. AKI was defined by KDIGO criteria, SH either as blood glucose (BG) > 140 mg/dl (BG140), > 200 mg/dl (BG200), or stress hyperglycemia rate (SHR) ≥ 1.47 (SHR1.47) as measured 2 days before AKI. Urinary cystatin C and neutrophil gelatinase-associated lipocalin (NGAL) indicated tubular injury.

RESULTS

In AKI, SH rates were frequent using all 3 definitions applied, but highest when BG140 was applied. SH by all 3 definitions was consistently associated with AKI. This was independent of established risk factors of AKI such as sepsis and shock. Increments of BG, urinary NGAL or cystatin C, and its products, were independently associated with the likelihood of subsequent AKI, demonstrating their reciprocal potentiating effects on AKI development.

CONCLUSIONS

SH is frequent in critically ill, non-diabetics with AKI. SH was identified as an independent risk factor of AKI. Higher BG combined with tubular injury may potentiate their adverse effects on AKI.

Prognostic significance of the stress hyperglycemia ratio in critically ill patients

BACKGROUND

The stress hyperglycemia ratio (SHR) has demonstrated a noteworthy association with unfavorable cardiovascular clinical outcomes and heightened in-hospital mortality. Nonetheless, this relationship in critically ill patients remains uncertain. This study aims to elucidate the correlation between SHR and patient prognosis within the critical care setting.

METHODS

A total of 8978 patients admitted in intensive care unit (ICU) were included in this study. We categorized SHR into uniform groups and assessed its relationship with mortality using logistic or Cox regression analysis. Additionally, we employed the restricted cubic spline (RCS) analysis method to further evaluate the correlation between SHR as a continuous variable and mortality. The outcomes of interest in this study were in-hospital and 1-year all-cause mortality.

RESULTS

In this investigation, a total of 825 (9.2%) patients experienced in-hospital mortality, while 3,130 (34.9%) individuals died within the 1-year follow-up period. After adjusting for confounding variables, we identified a U-shaped correlation between SHR and both in-hospital and 1-year mortality. Specifically, within the SHR range of 0.75-0.99, the incidence of adverse events was minimized. For each 0.25 increase in the SHR level within this range, the risk of in-hospital mortality rose by 1.34-fold (odds ratio [OR]: 1.34, 95% CI: 1.25-1.44), while a 0.25 decrease in SHR within 0.75-0.99 range increased risk by 1.38-fold (OR: 1.38, 95% CI: 1.10-1.75).

CONCLUSION

There was a U-shaped association between SHR and short- and long-term mortality in critical ill patients, and the inflection point of SHR for poor prognosis was identified at an SHR value of 0.96.

Prognostic Value of Serum Glucose Level in Critically Ill Septic Patients on Admission to Pediatric Intensive Care Unit

Background

Sepsis is one of the major causes of admission to the pediatric intensive care unit (PICU), as well as a primary cause of poor outcomes. Glycemic variation may occur because of sepsis resulting in either hypoglycemia or hyperglycemia. Measuring the random blood glucose (RBG) level of patients presenting with sepsis in PICU is an easy way to assess their prognosis.

Objectives

A prospective study was done from February 2023 to June 2023 to evaluate the relation between the outcome of pediatric septic patients and blood glucose level upon PICU admission.

Patients and methods

One hundred three children diagnosed with sepsis underwent clinical assessment upon admission to the PICU and initial labs including blood glucose levels were done. Pediatric Sequential Organ Failure Assessment (pSOFA) was calculated for every patient. The outcome of sepsis including length of stay, review of body systems, and mortality was documented.

Results

Hypoglycemic patients had the highest percentage of non-survivors (20.4%). They had a higher pSOFA score with a median of 11 (interquartile range-IQR 7-15), shorter PICU stay with a median of 2 (IQR 1-6) days, lower RBG with a median of 95 (45-120), a higher percentage of ventilation (55.1%), and a higher percentage of inotropic support (87.8%) with statistical significance with p-value (< 0.001, < 0.001, 0.001, < 0.001, 0.002), respectively.

Conclusion

Critically ill patients with abnormal random blood sugar (RBS) had a higher possibility of non-survival particularly those with hypoglycemia. Accordingly, RBS measurement is a rapid and cheap method that could be used in any emergency and as an early indicator to detect outcome.

How to cite this article

Mohamed AO, Abd El-Megied MA, Hosni YA. Prognostic Value of Serum Glucose Level in Critically Ill Septic Patients on Admission to Pediatric Intensive Care Unit. Indian J Crit Care Med 2023;27(10):754-758.

Use of Peak Glucose Level and Peak Glycemic Gap in Mortality Risk Stratification in Critically Ill Patients with Sepsis and Prior Diabetes Mellitus of Different Body Mass Indexes

Sepsis remains a critical concern in healthcare, and its management is complicated when patients have pre-existing diabetes and varying body mass indexes (BMIs). This retrospective multicenter observational study, encompassing data from 15,884 sepsis patients admitted between 2012 and 2017, investigates the relationship between peak glucose levels and peak glycemic gap in the first 3 days of ICU admission, and their impact on mortality. The study reveals that maintaining peak glucose levels between 141-220 mg/dL is associated with improved survival rates in sepsis patients with diabetes. Conversely, peak glycemic gaps exceeding 146 mg/dL are linked to poorer survival outcomes. Patients with peak glycemic gaps below -73 mg/dL also experience inferior survival rates. In terms of predicting mortality, modified Sequential Organ Failure Assessment-Peak Glycemic Gap (mSOFA-pgg) scores outperform traditional SOFA scores by 6.8% for 90-day mortality in overweight patients. Similarly, the modified SOFA-Peak Glucose (mSOFA-pg) score demonstrates a 17.2% improvement over the SOFA score for predicting 28-day mortality in underweight patients. Importantly, both mSOFA-pg and mSOFA-pgg scores exhibit superior predictive power compared to traditional SOFA scores for patients at high nutritional risk. These findings underscore the importance of glycemic control in sepsis management and highlight the potential utility of the mSOFA-pg and mSOFA-pgg scores in predicting mortality risk, especially in patients with diabetes and varying nutritional statuses.

Fluid Therapy in Exotic Animal Emergency and Critical Care

Many new concepts are emerging in the understanding of fluid therapy in human and mammalian medicine, including the role of the glycocalyx, increased understanding of fluid, sodium, and chloride overload, and the advantages of colloid administration in the form of albumin. None of these concepts, however, appear to be directly applicable to non-mammalian exotic patients, and careful consideration of their alternate physiology is required when formulating fluid plans for these patients.

Inter-relationships between gastric emptying and glycaemia: Implications for clinical practice

Gastric emptying (GE) exhibits a wide inter-individual variation and is a major determinant of postprandial glycaemia in health and diabetes; the rise in blood glucose following oral carbohydrate is greater when GE is relatively more rapid and more sustained when glucose tolerance is impaired. Conversely, GE is influenced by the acute glycaemic environment acute hyperglycaemia slows, while acute hypoglycaemia accelerates it. Delayed GE (gastroparesis) occurs frequently in diabetes and critical illness. In diabetes, this poses challenges for management, particularly in hospitalised individuals and/or those using insulin. In critical illness it compromises the delivery of nutrition and increases the risk of regurgitation and aspiration with consequent lung dysfunction and ventilator dependence. Substantial advances in knowledge relating to GE, which is now recognised as a major determinant of the magnitude of the rise in blood glucose after a meal in both health and diabetes and, the impact of acute glycaemic environment on the rate of GE have been made and the use of gut-based therapies such as glucagon-like peptide-1 receptor agonists, which may profoundly impact GE, in the management of type 2 diabetes, has become commonplace. This necessitates an increased understanding of the complex inter-relationships of GE with glycaemia, its implications in hospitalised patients and the relevance of dysglycaemia and its management, particularly in critical illness. Current approaches to management of gastroparesis to achieve more personalised diabetes care, relevant to clinical practice, is detailed. Further studies focusing on the interactions of medications affecting GE and the glycaemic environment in hospitalised patients, are required.

Hyperglycemia in COVID-19 infection without diabetes mellitus: Association with inflammatory markers

BACKGROUND

New onset hyperglycemia is common in patients with severe coronavirus disease 2019 (COVID-19) infection. Cytokine storm due to COVID-19 infection is an essential etiology for new-onset hyperglycemia, but factors like direct severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced pancreatic β-cell failure have also been postulated to play a role.

AIM

We plan to investigate further the mechanisms underlying SARS-CoV-2 infection-induced hyperglycemia, particularly the rationale of the cytokine-induced hyperglycemia hypothesis, by evaluating the association between inflammatory markers and new onset hyperglycemia in non-diabetic patients with COVID-19 infection.

METHODS

We conducted a retrospective case-control study on adults without diabetes mellitus hospitalized for COVID-19 infection. The serum levels of glucose and inflammatory markers at presentation before initiation of corticosteroid were collected. Hyperglycemia was defined as glucose levels ≥ 140 mg/dL. C-Reactive protein (CRP) ≥ 100 mg/L, ferritin ≥ 530 ng/mL, lactate dehydrogenase (LDH) ≥ 590 U/L, and D-dimer ≥ 0.5 mg/L were considered elevated. We used the χ² test for categorical variables and the Mann-Whitney U test for continuous variables and calculated the logistic regression for hyperglycemia.

RESULTS

Of the 520 patients screened, 248 met the inclusion criteria. Baseline demographics were equally distributed between patients with hyperglycemia and those who were normoglycemic. Serum inflammatory markers in patients with or without new-onset hyperglycemia were elevated as follows: CRP (58.1% vs 65.6%, P = 0.29), ferritin (48.4% vs 34.9%, P = 0.14), D-dimer (37.1% vs 37.1%, P = 0.76) and LDH (19.4% vs 11.8%, P = 0.02). Logistic regression analysis showed LDH odds ratio (OR) = 1.623 (P = 0.256). We observed significantly higher mortality (24.2% vs 9.1%, P = 0.001; OR = 2.528, P = 0.024) and length of stay (8.89 vs 6.69, P = 0.026) in patients with hyperglycemia.

CONCLUSION

Our study showed no association between CRP, ferritin, LDH, D-dimer levels, and new-onset hyperglycemia in non-diabetic patients with COVID-19 infection. It also shows an increased mortality risk and length of stay in patients with hyperglycemia. With new-onset hyperglycemia being closely associated with poor prognostic indices, it becomes pivotal to understand the underlying pathophysiological mechanisms behind the SARS-CoV-2 infection-induced hyperglycemia. We conclude that the stress hyperglycemia hypothesis is not the only mechanism of SARS-CoV-2 infection-induced hyperglycemia but rather a multicausal pathogenesis leading to hyperglycemia that requires further research and understanding. This would help us improve not only the clinical outcomes of COVID-19 disease and inpatient hyperglycemia management but also understand the long-term effects of SARS-CoV-2 infection and further management.

Association of body mass index and hypoglycemia with mortality rates among sepsis patients: A retrospective sub-analysis of the FORECAST study

Aim

Hypoglycemia at admission is associated with high mortality in sepsis patients. However, the influence of body mass index (BMI) on this association remains unknown. Therefore, this study assesses the association of hypoglycemia at admission with mortality in patients with sepsis according to BMI.

Methods

This was a secondary analysis of a multicenter, prospective cohort study of 59 intensive care units in Japan. We included 1184 patients (age ≥16 years) with severe sepsis and excluded those with missing data on glucose level, BMI, or survival at discharge. The initial blood glucose level of <70 mg/dL was defined as hypoglycemia. Patients were assigned to the hypoglycemia or non-hypoglycemia group as per BMI category (<18.5 [low], 18.5-24.9 [normal], and ≥25 [high] kg/m²). The main outcome was in-hospital mortality. Multivariate logistic regression models were used to evaluate BMI category-by-hypoglycemia interactions.

Results

Overall, 1103 patients, including 65 with hypoglycemia, were analyzed. In the normal BMI group, patients with hypoglycemia had a higher in-hospital mortality rate (18/38, 47.4%) than those without (119/584, 20.4%). There was a significant interaction between normal BMI and hypoglycemia affecting in-hospital mortality; however, this effect was not observed for other BMI categories (odds ratio, 2.32; 95% confidence interval, 1.05-5.07; p-value for interaction = 0.0476).

Conclusion

The relationship between patients with sepsis and hypoglycemia on admission may differ according to BMI. Hypoglycemia on admission may be associated with high mortality in patients with normal BMI, but not in those with low or high BMI.

Relationship between stress hyperglycemia ratio and allcause mortality in critically ill patients: Results from the MIMIC-IV database

BACKGROUND

Stress hyperglycemia ratio (SHR) was developed to reduce the impact of long-term chronic glycemic factors on stress hyperglycemia levels, which have been linked to clinical adverse events. However, the relationship between SHR and the short- and long-term prognoses of intensive care unit (ICU) patients remains unclear.

METHODS

We retrospectively analyzed 3,887 ICU patients (cohort 1) whose initial fasting blood glucose and hemoglobin A1c data within 24 hours of admission were available and 3,636 ICU patients (cohort 2) who were followed-up for 1-year using the Medical Information Mart for Intensive Care IV v2.0 database. Patients were divided into two groups based on the optimal cutoff value of SHR, which was determined using the receiver operating characteristic (ROC) curve.

RESULTS

There were 176 ICU deaths in cohort 1 and 378 patients experienced all-cause mortality during 1 year of follow-up in cohort 2. The results of logistic regression revealed that SHR was associated with ICU death (odds ratio 2.92 [95% confidence interval 2.14-3.97] P < 0.001), and non-diabetic patients rather than diabetic patients showed an increased risk of ICU death. As per the Cox proportional hazards model, the high SHR group experienced a higher incidence of 1-year all-cause mortality (hazard ratio 1.55 [95% confidence interval 1.26-1.90] P < 0.001). Moreover, SHR had an incremental effect on various illness scores in predicting ICU all-cause mortality.

CONCLUSION

SHR is linked to ICU death and 1-year all-cause mortality in critically ill patients, and it has an incremental predictive value in different illness scores. Moreover, we found that non-diabetic patients, rather than diabetic patients, showed an increased risk of all-cause mortality.

Case-control Investigation of Previously Undiagnosed Diabetes in the Critically Ill

Context

The outcome of patients requiring intensive care can be influenced by the presence of previously undiagnosed diabetes (undiagDM).

Objective

This work aimed to define the clinical characteristics, glucose control metrics, and outcomes of patients admitted to the intensive care unit (ICU) with undiagDM, and compare these to patients with known DM (DM).

Methods

This case-control investigation compared undiagDM (glycated hemoglobin A1c [HbA1c] ≥ 6.5%, no history of diabetes) to patients with DM. Glycemic ratio (GR) was calculated as the quotient of mean ICU blood glucose (BG) and estimated preadmission glycemia, based on HbA1c ([28.7 × HbA1c] - 46.7 mg/dL). GR was analyzed by bands: less than 0.7, 0.7 to less than or equal to 0.9, 0.9 to less than 1.1, and greater than or equal to 1.1. Risk-adjusted mortality was represented by the Observed:Expected mortality ratio (OEMR), calculated as the quotient of observed mortality and mortality predicted by the severity of illness (APACHE IV prediction of mortality).

Results

Of 5567 patients 294 (5.3%) were undiagDM. UndiagDM had lower ICU mean BG (P < .0001) and coefficient of variation (P < .0001) but similar rates of hypoglycemia (P = .08). Mortality and risk-adjusted mortality were similar in patients with GR less than 1.1 comparing undiagDM and DM. However, for patients with GR greater than or equal to 1.1, mortality (38.5% vs 10.3% [P = .0072]) and risk-adjusted mortality (OEMR 1.18 vs 0.52 [P < .0001]) were higher in undiagDM than in DM.

Conclusion

These data suggest that DM patients may develop tolerance to hyperglycemia that occurs during critical illness, a protective mechanism not observed in undiagDM, for whom hyperglycemia remains strongly associated with higher risk of mortality. These results may shed light on the natural history of diabetes.

Conventional Glycaemic Control May Not Be Beneficial in Diabetic Patients Following Cardiac Surgery

INTRODUCTION

Stress hyperglycaemia is common following cardiac surgery. Its optimal management is uncertain and emerging literature suggests that flexible glycaemic control in diabetic patients may be preferable. This study aims to assess the relationship between maximal postoperative in-hospital blood glucose levels (BSL) and the morbidity and mortality outcomes of diabetic and non-diabetic cardiac surgery patients.

METHODS

A retrospective cohort analysis of all patients undergoing cardiac surgery at a tertiary single centre institution from 2015 to 2019 was undertaken. Early management and outcomes of hyperglycaemia following cardiac surgery were assessed via multivariable regression modelling. Follow-up was assessed to 1 year postoperatively.

RESULTS

Consecutive non-diabetic patients (n=1,050) and diabetic patients (n=689) post cardiac surgery were included. Diabetics with peak BSL ≤13.9 mmol/L did not have an increased risk of morbidity or mortality compared to non-diabetics with peak BSL ≤10.0 mmol/L. In non-diabetics, stress hyperglycaemia with peak BSL >10.0 mmol/L was associated with overall wound complications (5.7% vs 8.8%, OR 1.64 [1.00-2.69], p=0.049) and postoperative pneumonia (2.7% vs 7.3%, OR 2.35 [1.26-4.38], p=0.007). Diabetic patients with postoperative peak BSL >13.9 mmol/L were at an increased risk of overall wound complication (7.4% vs 14.8%, OR 2.47 [1.46-4.16], p<0.001), graft harvest site infection (3.7% vs 11.8%, OR 3.75 [1.92-7.30], p<0.001), and wound-related readmission (3.1% vs 8.8%, OR 3.11 [1.49-6.47], p=0.002) when compared to diabetics with peak BSL ≤13.9 mmol/L.

CONCLUSION

In non-diabetics, stress hyperglycaemia with peak BSL >10.0 mmol/L is associated with morbidity. In diabetic patients, hyperglycaemia with peak BSL ≤13.9 mmol/L was not associated with an increased risk of morbidity or mortality compared to non-diabetics with peak BSL ≤10.0 mmol/L. Further investigation of flexible glycaemic targets (target BSL ≤13.9 mmol/L) in diabetic patients is warranted.

Application of the PDCA Cycle for Managing Hyperglycemia in Critically Ill Patients

Introduction

Stress hyperglycemia is a common symptom in critically ill patients, and is not only a marker indicating the severity of illness but is also related to worsening outcomes. Managing stress hyperglycemia without increasing the likelihood of hypoglycemia is one of the most pressing challenges to be urgently addressed in clinics. The Plan-Do-Check-Act (PDCA) cycle management has been put forward in various surgical management scenarios, and has proven to be effective in the diagnosis and treatment of different diseases. It possesses dynamic characteristics and can be updated according to the results of glycemic control and feedback. This study focused on the use of PDCA to manage glucose levels in critically ill patients.

Methods

Based on the glucose level of 1003 critically ill patients admitted to the emergency intensive care unit (EICU) from 1 October 2019 to 31 December 2020, we collected and matched the prevalence of hyperglycemia, hypoglycemia, and glucose variability on a quarterly basis. According to the PDCA management method, we analyzed the possible causes, supervised the implementation of measures, summarized the feedback on improvements, and then proposed new improvement measures for implementation in the next quarter.

Results

Three measures were proposed and applied to enhance the management of hyperglycemia: (I) Updating and formulating three editions of the insulin infusion protocol and increasing the initial and maintenance doses of insulin on a case-by-case basis; (II) reducing the use of parenteral nutrition and ensuring that enteral nutrition is consumed at a uniform and slow rate; and (III) forming a training method during the COVID-19 pandemic and improving implementation of the insulin infusion protocol. Following PDCA management, the prevalence of hyperglycemia fell from 43.18% to 32.61%, the incidence of hypoglycemia was below 1.00%, and there was no significant fluctuation in blood glucose variability.

Conclusion

The PDCA method is helpful in developing a superior insulin infusion protocol for critically ill patients and lowering the prevalence of hyperglycemia in critically ill patients.

Nomogram for prediction of severe community-acquired pneumonia development in diabetic patients: a multicenter study

Background

Diabetic patients with community-acquired pneumonia (CAP) have an increased risk of progressing to severe CAP. It is essential to develop predictive tools at the onset of the disease for early identification and intervention. This study aimed to develop and validate a clinical feature-based nomogram to identify diabetic patients with CAP at risk of developing severe CAP.

Method

A retrospective cohort study was conducted between January 2019 to December 2020. 1026 patients with CAP admitted in 48 hospitals in Shanghai were enrolled. All included patients were randomly divided into the training and validation samples with a ratio of 7:3. The nomogram for the prediction of severe CAP development was established based on the results of the multivariate logistic regression analysis and other predictors with clinical relevance. The nomogram was then assessed using receiver operating characteristic curves (ROC), calibration curve, and decision curve analysis (DCA).

Results

Multivariate analysis showed that chronic kidney dysfunction, malignant tumor, abnormal neutrophil count, abnormal lymphocyte count, decreased serum albumin level, and increased HbA1c level at admission was independently associated with progression to severe CAP in diabetic patients. A nomogram was established based on these above risk factors and other predictors with clinical relevance. The area under the curve (AUC) of the nomogram was 0.87 (95% CI 0.83–0.90) in the training set and 0.84 (95% CI 0.78–0.90). The calibration curve showed excellent agreement between the predicted possibility by the nomogram and the actual observation. The decision curve analysis indicated that the nomogram was applicable with a wide range of threshold probabilities due to the net benefit.

Conclusion

Our nomogram can be applied to estimate early the probabilities of severe CAP development in diabetic patients with CAP, which has good prediction accuracy and discrimination abilities. Since included biomarkers are common, our findings may be performed well in clinical practice and improve the early management of diabetic patients with CAP.

One-hour plasma glucose level after a 75 g oral glucose load and its relationship to gastric emptying in survivors of critical illness and stress hyperglycaemia

Objective: A 1-hour plasma glucose level ≥ 8.6 mmol/L in a 75 g oral glucose tolerance test has been strongly associated with increased morbidity and mortality in outpatients without diabetes. Our primary aim was to evaluate the 1-hour plasma glucose level in a 75 g glucose tolerance test in survivors of critical illness with stress hyperglycaemia at 3 months after intensive care unit (ICU) discharge, with the secondary aims to evaluate the 2-hour plasma glucose level, glycated haemoglobin (HbA1c), and gastric emptying. Design:Post hoc analysis of a single-centre, prospective cohort study. Setting: Single-centre, tertiary referral, mixed medical-surgical ICU. Participants: Consecutively admitted patients aged ≥ 18 years who developed stress hyperglycaemia and survived to hospital discharge were eligible. Interventions: Participants returned at 3 months after ICU discharge and underwent a 75 g oral glucose tolerance test. Main outcome measures: One- and 2-hour post load plasma glucose level, HbA1c, and assessment of gastric emptying via an isotope breath test. Results: Thirty-five patients (12 females; mean age, 58.5 years [SD, 10.5]; mean HbA1c, 37.4 mmol/mol [SD, 7.0]) attended the followup. In 32/35 patients (91%) the 1-hour post load plasma glucose level was ≥ 8.6 mmol/L. There was a positive correlation between the plasma glucose level at 1 hour (r2 = 0.21; P = 0.006), but no correlation between the 2-hour glucose level (r2 = 0.006; P = 0.63) and gastric emptying. Conclusion: Glucose intolerance, when defined as 1-hour glucose level ≥ 8.6 mmol/L following a 75 g oral glucose load, persists at 3 months in most survivors of stress hyperglycaemia and is dependent on the rate of gastric emptying. Longitudinal studies to characterise mechanisms underlying dysglycaemia and progression to diabetes in individuals with stress hyperglycaemia are indicated.

Hyperglycemia in Severe and Critical COVID-19 Patients: Risk Factors and Outcomes

Background: Hyperglycemia is commonly seen in critically ill patients. This disorder was also seen in coronavirus disease 2019 (COVID-19) patients and was associated with a worse prognosis. The current study determined the prevalence, risk factors, and prognostic implications of hyperglycemia in COVID-19 patients.

Method: This was a retrospective observational study performed in an intensive care unit for COVID-19 patients. Electronic data of COVID-19 patients admitted to the intensive care unit from August 2nd to October 15th, 2021, were collected. Patients were divided into non-hyperglycemia, hyperglycemia in diabetic patients, and hyperglycemia in non-diabetic patients. Primary outcomes were 28-day and in-hospital mortalities. Multinomial logistic regression and multivariable Cox regression models were used to determine the risk factors for hyperglycemia and mortality, respectively.

Results: Hyperglycemia was documented in 65.6% of patients: diabetic patients (44.8%) and new-onset hyperglycemia (20.8%). In-hospital and 28-day mortality rates were 30.2% and 26.1%, respectively. Respiratory failure, corticosteroid therapy, and a higher level of procalcitonin were risk factors for hyperglycemia in diabetic patients, whereas cardiovascular diseases, respiratory failure, and higher aspartate aminotransferase/glutamate aminotransferase ratio were risk factors for hyperglycemia in non-diabetic patients. The risk of the 28-day mortality rate was highest in the new-onset hyperglycemia (hazard ratio [HR] 3.535, 95% confidence interval [CI] 1.338-9.338, p=0.011), which was higher than hyperglycemia in type 2 diabetes mellitus patients (HR 1.408, 95% CI 0.513-3.862, p=0.506).

Conclusion: Hyperglycemia was common in COVID-19 patients in the intensive care unit. Hyperglycemia reflected the disease severity but was also secondary to therapeutic intervention. New-onset hyperglycemia was associated with poorer outcomes than that in diabetic patients.

Intermittent feeding and circadian rhythm in critical illness

PURPOSE OF REVIEW

Circadian rhythms, i.e., periodic oscillations in internal biological processes, modulate metabolic processes such as hormonal signalling, nutrient absorption, and xenobiotic detoxification. Meal timing is a strong entraining cue for peripheral clocks in various organs, and eating out of circadian phases can impair glucose, gastrointestinal, and muscle metabolism. Sleep/wake cycles and circadian rhythms are extremely disrupted during critical illness. Timing of nutritional support may help preserve circadian rhythms and improve post-Intensive Care Unit (ICU) recovery. This review summarises circadian disruptors during ICU admission and evaluates the potential benefits of intermittent feeding on metabolism and circadian rhythms.

RECENT FINDINGS

Rhythmic expression of core clock genes becomes rapidly disturbed during critical illness and remains disturbed for weeks. Intermittent, bolus, and cyclic enteral feeding have been directly compared to routine continuous feeding, yet no benefits on glycaemic control, gastrointestinal tolerance, and muscle mass have been observed and impacts of circadian clocks remain untested.

SUMMARY

Aligning timing of nutritional intake, physical activity, and/or medication with circadian rhythms are potential strategies to reset peripheral circadian rhythms and may enhance ICU recovery but is not proven beneficial yet. Therefore, selecting intermittent feeding over continuous feeding must be balanced against the pros and cons of clinical practice.

Stress-Induced Hyperglycemia: Consequences and Management

Hyperglycemia during stress is a common occurrence seen in patients admitted to the hospital. It is defined as a blood glucose level above 180mg/dl in patients without pre-existing diabetes. Stress-induced hyperglycemia (SIH) occurs due to an illness that leads to insulin resistance and decreased insulin secretion. Such a mechanism causes elevated blood glucose and produces a complex state to manage with external insulin. This article compiles various studies to explain the development and consequences of SIH in the critically ill that ultimately lead to an increase in mortality while also discussing the dire impact of SIH on certain acute illnesses like myocardial infarction and ischemic stroke. It also evaluates multiple studies to understand the management of SIH with insulin and proper nutritional therapy in the hospitalized patients admitted to the Intensive care unit (ICU) alongside the non-critical care unit. While emphasizing the diverse effects of improper control of SIH in the hospital, this article elucidates and discusses the importance of formulating a discharge plan due to an increased risk of type 2 diabetes in the recovered. 

Association Between Glycemic Gap and Mortality in Critically Ill Patients with Diabetes

OBJECTIVES

Dysglycemia is associated with poor outcomes in critically ill patients,which is uncertain in patients with diabetes regarding to the situation of glucose control before hospitalization. This study was aimed to investigate the effect of the difference between the level of blood glucose during ICU stay and before admission to ICU upon the outcomes of critically ill patients with diabetes.

METHOD

Patients with diabetes expected to stay for more than 24hs were enrolled, HbA1c was converted to A1C-derived average glucose (ADAG) by the equation: ADAG  =  [ (HbA1c * 28.7) - 46.7 ] * 18^-1, blood glucose were measured four times a day during the first 7 days after admission, the mean glucose level(MGL) and SOFA (within 3, 5, and 7days) were calculated for each person, GAP_adm and GAP_mean was calculated as admission blood glucose and MGL minus ADAG, the incidence of moderate hypoglycemia(MH), severe hypoglycemia (SH), total dosage of glucocorticoids and average daily dosage of insulin, duration of renal replacement therapy(RRT), ventilator-free hours, and non-ICU days were also collected. Patients were divided into survival group and nonsurvival group according to survival or not at 28-day, the relationship between GAP and mortality were analyzed.

RESULTS

431 patients were divided into survival group and nonsurvival group. The two groups had a comparable level of HbA1c, the nonsurvivors had greater APACHE II, SOFA, GAP_adm, GAP_mean-3, GAP_mean-5, GAP_mean-7 and higher MH and SH incidences. Less duration of ventilator-free, non-ICU stay and longer duration of RRT were recorded in the nonsurvival group. GAP_mean-5 had the greatest predictive power with an AUC of 0.807(95%CI: 0.762-0.851), the cut-off value was 3.6 mmol/L (sensitivity 77.7% and specificity 76.6%). The AUC was increased to 0.852(95%CI: 0.814-0.889) incorporated with SOFA₅ (NRI  =  11.34%).

CONCLUSION

Glycemic GAP between the MGL within 5 days and ADAG was independently associated with 28-day mortality of critically ill patients with diabetes. The predictive power was optimized with addition of SOFA₅.

The Effect of a Liberal Approach to Glucose Control in Critically Ill Patients with Type 2 Diabetes: A multicenter, parallel-group, open-label, randomized clinical trial

Rationale Blood glucose concentrations affect outcomes in critically ill patients but the optimal target blood glucose range in those with type 2 diabetes is unknown. Objective To evaluate the effects of a 'liberal' approach to targeted blood glucose range during intensive care unit (ICU) admission. Methods This mutlicenter, parallel-group, open-label, randomized clinical trial included 419 adult patients with type 2 diabetes expected to be in the ICU on at least three consecutive days. In the intervention group intravenous insulin was commenced at a blood glucose >252 mg/dL and titrated to a target range of 180 to 252 mg/dL. In the comparator group insulin was commenced at a blood glucose >180 mg/dL and titrated to a target range of 108 to 180 mg/dL. The primary outcome was incident hypoglycemia (<72 mg/dL). Secondary outcomes included glucose metrics and clinical outcomes. Main Results At least one episode of hypoglycemia occurred in 10 of 210 (5%) patients assigned the intervention and 38 of 209 (18%) patients assigned the comparator (incident rate ratio: 0.21 (95% CI, 0.09 to 0.49); P<0.001). Those assigned the intervention had greater blood glucose concentrations (daily mean, minimum, maximum), less glucose variability and less relative hypoglycaemia (P<0.001 for all comparisons). By day 90, 62 of 210 (29.5%) in the intervention and 52 of 209 (24.9%) in the comparator group had died (absolute difference 4.6 percentage points (95%CI, -3.9 to 13.2%); P=0.29). Conclusions A liberal approach to blood glucose targets reduced incident hypoglycemia but did not improve patient-centered outcomes. Clinical trial registration available at www.anzctr.org.au, ID: ACTRN12616001135404.

Relationship Between Glucose Time in Range in Diabetic and Non-Diabetic Patients and Mortality in Critically Ill Patients

Background: Shorter time spent in specific blood glucose ranges is associated with mortality benefit in critically ill patients. However, various time in range values are reported, each based on a specific blood glucose range. Objective: To evaluate relationship between percentage of time spent at various blood glucose ranges (TIR) and mortality in critically ill patients. Methods: Single-center, retrospective, cohort study that included adult patients admitted to ICU for at least one day. We evaluated the relationship between TIR at prespecified blood glucose ranges and hospital mortality in diabetic and non-diabetic patients Results: Of the 5287 patients included, 3705 (70.0%) were non-diabetic and 1582 were diabetic (29.9%). Diabetic patients had higher in-hospital mortality rate (15.8%) compared to non-diabetic patients (11.3%), p < 0.0001, and with higher incidence of hyperglycemia (77.8% vs. 39.4%) and hypoglycemia (14.3% vs. 10%) compared to non-diabetic patients, p < 0.0001. The highest median TIR for both diabetic [76% (49.1 − 97.8%)] and non-diabetic patients [100% (92.3--100%)] was at blood glucose range of 70-180 mg/dL. In non-diabetic cohort, the only optimal TIR of 40% at blood glucose range of 70-120 mg/dL was identified. Non-diabetic patients stratified into TIR 70-120 mg/dL > 40% reported significantly lower mortality (7.0%) rate compared to patients with TIR 70-120 mg/dL < 40% (15.7%), OR 0.52, 95% CI 0.27-0.97, adjusted-p = 0.03. In diabetic patients, no relationship was detected between TIR at all predefined glucose ranges and hospital mortality. Conclusion: Critically ill non-diabetic patients who spent at least 40% of time in blood glucose range of 70-120 mg/dL had improved survival. This association was not observed in diabetic patients.

Diabetes mellitus, glycaemic control and severe COVID-19 in the Australian Critical Care Setting – a nested cohort study

Background

Internationally, diabetes mellitus is recognised as a risk factor for severe COVID-19. The relationship between diabetes mellitus and severe COVID-19 has not been reported in the Australian population.

Objective

The objective of this study was to determine the prevalence of and outcomes for patients with diabetes admitted to Australian intensive care units (ICUs) with COVID-19.

Methods

This is a nested cohort study of four ICUs in Melbourne participating in the Short Period Incidence Study of Severe Acute Respiratory Infection (SPRINT-SARI) Australia project. All adult patients admitted to the ICU with COVID-19 from 20 February 2020 to 27 February 2021 were included. Blood glucose and glycated haemoglobin (HbA1c) data were retrospectively collected. Diabetes was diagnosed from medical history or an HbA1c ≥6.5% (48 mmol/mol). Hospital mortality was assessed using logistic regression.

Results

There were 136 patients with median age 58 years [48–68] and median Acute Physiology and Chronic Health Evaluation II (APACHE II) score of 14 [11–19]. Fifty-eight patients had diabetes (43%), 46 patients had stress-induced hyperglycaemia (34%), and 32 patients had normoglycaemia (23%). Patients with diabetes were older, were with higher APACHE II scores, had greater glycaemic variability than patients with normoglycaemia, and had longer hospital length of stay. Overall hospital mortality was 16% (22/136), including nine patients with diabetes, nine patients with stress-induced hyperglycaemia, and two patients with normoglycaemia.

Conclusion

Diabetes is prevalent in patients admitted to Australian ICUs with severe COVID-19, highlighting the need for prevention strategies in this vulnerable population.

Association of Blood Glucose Level and Glycemic Variability With Mortality in Sepsis Patients During ICU Hospitalization

Background

There was considerable debate regarding the effect of mean blood glucose (MBG) and glycemic variability (GV) on the mortality of septic patients. This retrospective cohort study aimed to assess the association between MBG and GV with ICU mortality of sepsis patients and to explore the optimal MBG range.

Methods

Sepsis patients were enrolled from the Medical Information Mart for Intensive Care IV database (MIMIC-IV). MBG and glycemic coefficient of variation (Glu_CV) were, respectively, calculated to represent the overall glycemic status and GV during ICU stay. The associations between MBG, Glu_CV, and ICU mortality of the septic patients were assessed by using multivariate logistic regression in different subgroups and the severity of sepsis. Restricted cubic splines evaluated the optimal MBG target.

Results

A total of 7,104 adult sepsis patients were included. The multivariate logistic regression results showed that increased MBG and Glu_CV were significantly correlated with ICU mortality. The adjusted odds ratios were 1.14 (95% CI 1.09–1.20) and 1.05 (95% CI 1.00–1.12). However, there was no association between hyperglycemia and ICU mortality among diabetes, liver disease, immunosuppression, and hypoglycemia patients. And the impact of high Glu_CV on ICU mortality was not observed in those with diabetes, immunosuppression, liver disease, and non-septic shock. The ICU mortality risk of severe hyperglycemia (≧200 mg/dl) and high Glu_CV (>31.429%), respectively, elevated 2.30, 3.15, 3.06, and 2.37, 2.79, 3.14-folds in mild (SOFA ≦ 3), middle (SOFA 3–7), and severe group (SOFA ≧ 7). The MBG level was associated with the lowest risk of ICU mortality and hypoglycemia between 120 and 140 mg/dl in the subgroup without diabetes. For the diabetic subset, the incidence of hypoglycemia was significantly reduced when the MBG was 140–190 mg/dl, but a glycemic control target effectively reducing ICU mortality was not observed.

Conclusion

MBG and Glu_CV during the ICU stay were associated with all-cause ICU mortality in sepsis patients; however, their harms are not apparent in some particular subgroups. The impact of hyperglycemia and high GV on death increased with the severity of sepsis. The risk of ICU mortality and hypoglycemia in those with no pre-existing diabetes was lower when maintaining the MBG in the range of 120–140 mg/dl.

Association between dysglycemia and mortality by diabetes status and risk factors of dysglycemia in critically ill patients: a retrospective study

AIMS

Dysglycemia, including the three domains hyperglycemia, hypoglycemia, and increased glycemic variability (GV), is associated with high mortality among critically ill patients. However, this association differs by diabetes status, and reports in this regard are limited. This study aimed to evaluate the associations between the three dysglycemia domains and mortality in critically ill patients by diabetes status and determined the contributing factors for dysglycemia.

METHODS

This retrospective study included 958 critically ill patients (admitted to the ICU) with or without DM. Dysglycemia was defined as abnormality of any of the three dimensions. We evaluated the effects of the three domains of glucose control on mortality using binary logistic regression and then adjusted for confounders. The associations between dysglycemia and other variables were investigated using cumulative logistic regression analysis.

RESULT

GV independently and similarly affected mortality in both groups after adjustment for confounders (DM: odds ratio [OR], 1.05; 95% confidence interval [CI]: 1.03-1.08; p <0.001; non-DM: OR, 1.07; 95% CI, 1.03-1.11; p = 0.002). Hypoglycemia was strongly associated with ICU mortality among patients without DM (3.12; 1.76-5.53; p <0.001) and less so among those with DM (1.18; 0.49-2.83; p = 0.72). Hyperglycemia was non-significantly associated with mortality in both groups. However, the effects of dysglycemia seemed cumulative. The factors contributing to dysglycemia included disease severity, insulin treatment, glucocorticoid use, serum albumin level, total parenteral nutrition, duration of diabetes, elevated procalcitonin level, and need for mechanical ventilation and renal replacement therapy.

CONCLUSION

The association between the three dimensions of dysglycemia and mortality varied by diabetes status. Dysglycemia in critical patients is associated with excess mortality; however, glucose management in patients should be specific to the patient's need considering the diabetes status and broader dimensions. The identified factors for dysglycemia could be used for risk assessment in glucose management requirement in critically ill patients, which may improve clinical outcomes.

Effect of glycemic gap upon mortality in critically ill patients with diabetes

AIMS/INTRODUCTION

Hyperglycemia, hypoglycemia, and blood glucose fluctuation are associated with the outcome in critically ill patients, but the target of blood glucose control is debatable especially in patients with diabetes regarding the status of blood glucose control before admission to ICU. This study aimed to investigate the association between the glycemic gap which is calculated as the mean blood glucose level during the first 7 days after admission to ICU minus the A1C-derived average glucose and the outcome of critically ill patients with diabetes.

METHOD

This study was undertaken in two intensive care units (ICUs) with a total of 30 beds. Patients with diabetes who were expected to stay for more than 24 h were enrolled, the HbA1c was tested within 3 days after admission and converted to the A1C-derived average glucose (ADAG) by the equation: ADAG = [(HbA1c * 28.7) - 46.7 ] * 18-1 , arterial blood glucose measurements were four per day routinely during the first 7 days after admission, the APACHE II score within the first 24 h, the mean blood glucose level (MGL), standard deviation (SD), and coefficient of variation (CV) during the first 7 days were calculated for each person, the GAPadm and GAPmean were calculated as the admission blood glucose and MGL minus the ADAG, respectively, the incidence of moderate hypoglycemia (MH) and severe hypoglycemia (SH), the total dosage of glucocorticoids and average daily dosage of insulin within 7 days, the duration of renal replacement therapy (RRT), ventilator-free hours, and non-ICU stay days within 28 days were also collected. The enrolled patients were divided into a survival group and a nonsurvival group according to survival or not at 28 days and 1 year after admission, and the relationship between parameters derived from blood glucose and mortality in the enrolled critically ill patients was explored.

RESULTS

Five hundred and two patients were enrolled and divided into a survival group (n = 310) and a nonsurvival group (n = 192). It was shown that the two groups had a comparable level of HbA1c, the nonsurvivors had a greater APACHE II, MGL, SD, CV, GAPadm , GAPmean , and a higher incidence of hypoglycemia. A lesser duration of ventilator-free, non-ICU stay, and a longer duration of RRT were recorded in the nonsurvival group, who received a lower carbohydrate intake, a higher daily dosage of insulin and glucocorticoid. GAPmean had the greatest predictive power with an AUC of 0.820 (95%CI: 0.781-0.850), the cut-off value was 3.60 mmol/L (sensitivity 78.2% and specificity 77.3%). Patients with a low GAPmean tended to survive longer than the high GAPmean group 1 year after admission.

CONCLUSIONS

Glycemic GAP between the mean level of blood glucose within the first 7 days after admission to ICU and the A1C-derived average glucose was independently associated with a 28 day mortality of critically ill patients with diabetes, the predictive power extended to 1 year. The incidence of hypoglycemia was associated with mortality either.

The impact of a modified carbohydrate formula, and its constituents, on glycaemic control and inflammatory markers: A nested mechanistic sub-study

BACKGROUND

Hyperglycaemia occurs frequently in the critically ill. Dietary intake of advanced glycation end-products (AGEs), specifically Nε-(carboxymethyl)lysine (CML), may exacerbate hyperglycaemia through perturbation of insulin sensitivity. The present study aimed to determine whether the use of nutritional formulae, with varying AGE loads, affects the amount of insulin administered and inflammation.

METHODS

Exclusively tube fed patients (n = 35) were randomised to receive Nutrison Protein Plus Multifibre®, Diason® or Glucerna Select®. Insulin administration was standardised according to protocol based on blood glucose (<10 mmol L^-1 ). Samples were obtained at randomisation and 48 h later. AGEs in nutritional formula, plasma and urine were measured using mass spectrometry. Plasma inflammatory markers were measured using an enzyme-linked immunosorbent assay and multiplex bead-based assays.

RESULTS

AGE concentrations of CML in nutritional formulae were greatest with delivery of Nutrison Protein Plus® (mean [SD]; 6335 pmol mol^-1 [2436]) compared to Diason® (4836 pmol mol^-1 [1849]) and Glucerna Select® (4493 pmol mol^-1 [1829 pmol mol^-1 ]) despite patients receiving similar amounts of energy (median [interquartile range]; 12 MJ [8.2-13.7 MJ], 11.5 MJ [8.3-14.5 MJ], 11.5 MJ [8.3-14.5 MJ]). More insulin was administered with Nutrison Protein Plus® (2.47 units h^-1 [95% confidence interval (CI) = 1.57-3.37 units h^-1 ]) compared to Diason® (1.06 units h^-1 [95% CI = 0.24-1.89 units h^-1 ]) or Glucerna Select® (1.11 units h^-1 [95% CI = 0.25-1.97 units h^-1 ]; p = 0.04). Blood glucose concentrations were similar. There were associations between greater insulin administration and reductions in circulating interleukin-6 (r = -0.46, p < 0.01), tumour necrosis factor-α (r = -0.44, p < 0.05), high sensitivity C-reactive protein (r = -0.42, p < 0.05) and soluble receptor for advanced glycation end-products (r = -0.45, p < 0.01) concentrations.

CONCLUSIONS

The administration of greater AGE load in nutritional formula potentially increases the amount of insulin required to maintain blood glucose within a normal range during critical illness. There was an inverse relationship between exogenous insulin and plasma inflammatory markers.

Glycemic targets in critically ill adults: A mini-review

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

Individualised versus conventional glucose control in critically-ill patients: the CONTROLING study-a randomized clinical trial

Purpose

Hyperglycaemia is an adaptive response to stress commonly observed in critical illness. Its management remains debated in the intensive care unit (ICU). Individualising hyperglycaemia management, by targeting the patient’s pre-admission usual glycaemia, could improve outcome.

Methods

In a multicentre, randomized, double-blind, parallel-group study, critically-ill adults were considered for inclusion. Patients underwent until ICU discharge either individualised glucose control by targeting the pre-admission usual glycaemia using the glycated haemoglobin A1c level at ICU admission (IC group), or conventional glucose control by maintaining glycaemia below 180 mg/dL (CC group). A non-commercial web application of a dynamic sliding-scale insulin protocol gave to nurses all instructions for glucose control in both groups. The primary outcome was death within 90 days.

Results

Owing to a low likelihood of benefit and evidence of the possibility of harm related to hypoglycaemia, the study was stopped early. 2075 patients were randomized; 1917 received the intervention, 942 in the IC group and 975 in the CC group. Although both groups showed significant differences in terms of glycaemic control, survival probability at 90-day was not significantly different (IC group: 67.2%, 95% CI [64.2%; 70.3%]; CC group: 69.6%, 95% CI [66.7%; 72.5%]). Severe hypoglycaemia (below 40 mg/dL) occurred in 3.9% of patients in the IC group and in 2.5% of patients in the CC group (p = 0.09). A post hoc analysis showed for non-diabetic patients a higher risk of 90-day mortality in the IC group compared to the CC group (HR 1.3, 95% CI [1.05; 1.59], p = 0.018).

Conclusion

Targeting an ICU patient’s pre-admission usual glycaemia using a dynamic sliding-scale insulin protocol did not demonstrate a survival benefit compared to maintaining glycaemia below 180 mg/dL.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00134-021-06526-8.

Hyperglycaemia increases mortality risk in non-diabetic patients with COVID-19 even more than in diabetic patients

Aim

Diabetes has been identified as a risk factor for poor outcomes in patients with COVID‐19. We examined the association of hyperglycaemia, both in the presence and absence of pre‐existing diabetes, with severity and outcomes in COVID‐19 patients.

Methods

Data from 74,148 COVID‐19‐positive inpatients with at least one recorded glucose measurement during their inpatient episode were analysed for presence of pre‐existing diabetes diagnosis and any glucose values in the hyperglycaemic range (>180 mg/dl).

Results

Among patients with and without a pre‐existing diabetes diagnosis on admission, mortality was substantially higher in the presence of high glucose measurements versus all measurements in the normal range (70–180 mg/dl) in both groups (non‐diabetics: 21.7% vs. 3.3%; diabetics 14.4% vs. 4.3%). When adjusting for patient age, BMI, severity on admission and oxygen saturation on admission, this increased risk of mortality persisted and varied by diabetes diagnosis. Among patients with a pre‐existing diabetes diagnosis, any hyperglycaemic value during the episode was associated with a substantial increase in the odds of mortality (OR: 1.77, 95% CI: 1.52–2.07); among patients without a pre‐existing diabetes diagnosis, this risk nearly doubled (OR: 3.07, 95% CI: 2.79–3.37).

Conclusion

This retrospective analysis identified hyperglycaemia in COVID‐19 patients as an independent risk factor for mortality after adjusting for the presence of diabetes and other known risk factors. This indicates that the extent of glucose control could serve as a mechanism for modifying the risk of COVID‐19 morality in the inpatient environment.

Protocol for a prospective, international cohort study on the Management and Outcomes of Perioperative Care among European Diabetic Patients (MOPED)

INTRODUCTION

Diabetes is common (about 20 million patients in Europe) and patients with diabetes have more surgical interventions than the general population. There are plausible pathophysiological and clinical mechanisms suggesting that patients with diabetes are at an increased risk of postoperative complications. When postoperative complications occur in the general population, they increase major adverse events and subsequently increase 1-year mortality. This is likely to be worse in patients with diabetes. There is variation in practice guidelines in different countries in the perioperative management of patients with diabetes undergoing major surgery and whether this may affect postoperative outcome has not been investigated on a large scale. Neither is it known whether different strata of preoperative glycaemic control affects outcome.

METHODS AND ANALYSIS

A prospective, observational, international, multicentre cohort study, recruiting 5000 patients with diabetes undergoing elective or emergency surgery in at least n=50 centres. Inclusion criteria are any patient with diabetes undergoing surgery under any substantive anaesthetic technique. Exclusion criteria are not being a confirmed diabetic patient and patients with diabetes undergoing procedures under monitored sedation or local anaesthetic infiltration only. Follow-up duration is 30 days after surgery. Primary outcome is days at home at 30 days. Secondary outcomes are Comprehensive Complications Index, Quality of Recovery (QoR-15) score on Day 1 postoperatively, 30-day mortality, length of hospital stay and incidence of specific major adverse events (Myocardial Infarction (MI), Myocardial Injury after Non-cardiac Surgery (MINS), Acute Kidney Injury (AKI), Postoperative Pulmonary Complications (PPC), Cerebrovascular Accident (CVA), Pulmonary Embolism (PE), DVT, surgical site infection, postoperative pulmonary infection). Tertiary outcomes include time to resumption of normal diabetes therapy, incidence of diabetic ketoacidosis or hypoglycaemia, incidence and duration of use of intravenous insulin infusion therapy and change in diabetic management at 30 days.

ETHICS AND DISSEMINATION

This study will adhere to the principles of the Declaration of Helsinki (amendment 2013) by the World Medical Association and the ICH-Good Clinical Practice (GCP) Guidelines E6(R2). Specific national and local regulatory authority requirements will be followed as applicable. Ethical approval has been granted by the Institutional Review Board of the Mater Misericordiae University Hospital, Dublin, Ireland (Reference: 1/378/2167). As enrolment for this study is ongoing, ethical approval from additional centres is being added continuously. The main results of Management and Outcomes of Perioperative Care among European Diabetic Patients and its substudies will be published in peer-reviewed international medical journals and presented at Euroanaesthesia congress and other international and national meetings.

TRIAL REGISTRATION NUMBER

NCT04511312.

The relationship between inpatient hyperglycaemia and mortality is modified by baseline glycaemic status

AIMS

There is a well-established association between inpatient hyperglycaemia and mortality. However, evidence is inconsistent regarding whether this association is differential among those with and without type 2 diabetes mellitus (T2DM). Most studies are based on convenience samples or are unable to adjust for comorbidities. We examined whether the association between hyperglycaemia and 30-day mortality was modified by baseline glycaemic status.

MATERIALS AND METHODS

This was a retrospective cohort study of 174,671 eligible hospitalized individuals between 2012 and 2015. Thirty-day mortality was assessed during the first inpatient stay up to 30 days post discharge. The adjusted association between hyperglycaemia and mortality was assessed with logistic regression models. Then, four interaction terms were entered into the model to assess if the association between hyperglycaemia and mortality differed by baseline glycaemic status.

RESULTS

The multivariate model demonstrated a 2.18-fold risk of mortality associated with hyperglycaemia (odds ratio [OR] [95%CI]: 2.19 [2.08-2.31]). Adding the interaction terms between hyperglycaemia and baseline glycaemic status the ORs of 30-day mortality were 1.41 (1.25-1.60) in non-T2DM status, 1.32 (1.16-1.51) in pre-diabetes status and 1.30 (1.04-1.62) in unscreened status, as compared to T2DM status with hyperglycaemia.

CONCLUSIONS

Hyperglycaemia is positively associated with mortality and both those without and with controlled T2DM are at highest risk. These findings may help medical staff identify potential increased risk of mortality upon hospital entry and discharge, and direct further research to assess how hyperglycaemia control and proactive deterioration prevention throughout the entire inpatient stay may prevent adverse outcomes.

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.

Admission Blood Glucose in the Emergency Department is Associated with Increased In-Hospital Mortality in Nontraumatic Critically Ill Patients

BACKGROUND

Abnormal admission blood glucose was reported as a useful predictor of outcome in critically ill patients.

OBJECTIVES

To identify patients at higher risk, this study aimed to evaluate the relationship between admission blood glucose levels and patient mortality during the management of nontraumatic critically ill patients in the emergency department (ED).

METHODS

In this prospective, single-center observational study in a German university ED, all adult patients admitted to the resuscitation room of the ED were included between September 1, 2014 and August 31, 2015. Directly after resuscitation room admission, blood samples for admission blood glucose were taken, and adult patients were divided into groups according to predefined cut-offs between the admission blood glucose. Study endpoint was in-hospital mortality.

RESULTS

During the study period, 532 patients were admitted to the resuscitation room. The data of 523 patients (98.3%) were available for analysis. The overall in-hospital mortality was 34.2%. In comparison with an in-hospital mortality of 25.2% at an admission blood glucose of 101-136 mg/dL (n = 107), admission blood glucose of ≤ 100 mg/dL (n = 25, odds ratio [OR] 6.30, 95% confidence interval [CI] 2.44-16.23, p < 0.001), 272-361 mg/dL (n = 63, OR 2.53, 95% CI 1.31-4.90, p = 0.007), and ≥ 362 mg/dL (n = 44, OR 2.96, 95% CI 1.42-6.18, p = 0.004) were associated with a higher mortality.

CONCLUSIONS

Abnormal admission blood glucose is associated with a high in-hospital mortality. Admission blood glucose is an inexpensive and rapidly available laboratory parameter that may predict mortality and help to identify critically ill patients at risk in a general nontraumatic critically ill ED patient cohort. The breakpoint for in-hospital mortality may be an admission blood glucose ≤ 100 and ≥ 272 mg/dL.

Association of specialized enteral nutrition with glycemic control and clinical outcomes in critically ill patients: A meta-analysis of randomized controlled trials

OBJECTIVE

To evaluate the association of glycemic-control formulae (GCF) with measurements of glycemic control and clinical outcomes compared to standard enteral formulae (SF) in critically ill patients.

DATA SOURCES

MEDLINE, EMBASE, Scopus and the Cochrane Central Register of Controlled Trials were searched from inception up to January, 2021.

STUDY SELECTION

RCTs that assessed the effects of GCF relative to SF in adult critically ill patients.

DATA EXTRACTION

Measurements of glycemic control were the primary outcomes. Secondary outcomes included insulin requirements, mechanical ventilation (MV), length of intensive care unit (ICU) stay and mortality. Two authors independently extracted data and assessed risk of bias using the Cochrane's RoB 2 tool and the GRADE approach was used to assess the quality of evidence.

DATA SYNTHESIS

Ten studies (12 reports, 685 patients) were included. The use of GCFs was associated with lower blood glucose (WMD, -16.06 mg/dL; 95% CI -23.48 to -8.63; I² = 47%) and lower daily administered insulin (WMD, -7.20 IU; 95% CI -13.92 to -0.48; I² = 53%). Glycemic variability, measured by the coefficient of variation, was also associated with the use of GCFs (WMD, -6.84%; 95% CI, -13.57 to -0.11; I² = 95%). In contrast, analyses for length of ICU stay (WMD, -0.12, 95% CI -1.77 to 1.52; I² = 0%), duration of MV (WMD, -0.34 days; 95% CI, -1.72 to 1.04; I² = 0%) and mortality (RR, 1.13; 95% CI 0.82 to 1.56; I² = 0%) were not statistically significant. Quality of evidence ranged from low to very low, and only one study was judged as at low risk of bias.

CONCLUSIONS

In this meta-analysis, GCFs were significantly associated with lower insulin requirements and improved glycemic control. Although results for clinical outcomes were not statistically significant, there is insufficient evidence to confirm or exclude important differences due to serious imprecision in the effect estimates and overall low quality of evidence. The effects of GCFs on clinical outcomes require confirmation in larger randomized trials.

The prognostic role of hyperglycemia and glucose variability in covid-related acute respiratory distress Syndrome

AIMS

Due to heterogeneity on the prognostic role of glucose values and glucose variability in Novel Coronavirus (COVID) disease, we aimed at assessing the prognostic role for Intensive Care Unit (ICU) death of admission hyperglycaemia, peak glycemia and glucose variability in critically ill COVID patients: METHODS: 83 patients consecutively admitted for COVID-related Acute Respiratory Distress Syndrome (ARDS) from from 1st March to 1st October 2020.

RESULTS

Non survivors were older, with more comorbidities and a more severe disease. Corticosteroids were used in the majority of patients (54/83, 65%) with no difference between survivors and non survivors. Mean blood glucose values, (during the first 24 and 48 h, respectively), were comparable between the two subgroups, as well as SD 24 and CV 24. During the first 48 h, survivors showed significantly lower values of SD 48 (p < 0.001) and CV 48, respectively (p < 0.001) than non survivors.

CONCLUSIONS

in consecutive COVID-related ARDS patients admitted to ICU hyperglycemia (>180 mg/dl) is more common in non survivors who also showed a significantly higher glucose variability in the first 48 h since ICU admission. Our findings point to the clinical significance of in-ICU glucose control in severe COVID patients.

GlucoSTRESS - A project to optimize glycemic control in a level C (III) Portuguese intensive care unit

Objective

To double the percentage of time within the 100 - 180mg/dL blood glucose range in the first three months following a phased implementation of a formal education program, and then, of an insulin therapy protocol, without entailing an increased incidence of hypoglycemia.

Methods

The pre-intervention glycemic control was assessed retrospectively. Next, were carried out the implementation of a formal education program, distribution of manual algorithms for intravenous insulin therapy - optimized by the users, based on the modified Yale protocol - and informal training of the nursing staff. The use of electronic blood glucose control systems was supported, and the results were recorded prospectively.

Results

The first phase of the program (formal education) lead to improvement of the time within the euglycemic interval (28% to 37%). In the second phase, euglycemia was achieved 66% of the time, and the incidence of hypoglycemia was decreased. The percentage of patients on intravenous insulin infusion at 48 hours from admission increased from 6% to 35%.

Conclusion

The phased implementation of a formal education program, fostering the use of electronic insulin therapy protocols and dynamic manuals, received good adherence and has shown to be safe and effective for blood glucose control in critically ill patients, with a concomitant decrease in hypoglycemia.

The association of diabetes and hyperglycemia with sepsis outcomes: a population-based cohort analysis

The independent association of diabetes and hyperglycemia on the outcomes of sepsis remains unclear. We conducted retrospective cohort analyses of outcomes among patients with community-onset sepsis admitted to Shamir Medical Center, Israel (08-12/2016). Statistical associations were queried by Cox and logistic regressions, controlled for by matched propensity score analyses. Among 1527 patients with community-onset sepsis, 469 (30.7%) were diabetic. Diabetic patients were significantly older, with advanced complexity of comorbidities, and were more often exposed to healthcare environments. Despite statistically significant univariable associations with in-hospital and 90-day mortality, the adjusted Hazard Ratios (aHR) were 1.21 95% CI 0.8-1.71, p = 0.29 and 1.13 95% CI 0.86-1.49, p = 0.37, respectively. However, hyperglycemia at admission (i.e., above 200 mg/dl (was independently associated with: increased in-hospital mortality, aHR 1.48 95% CI 1.02-2.16, p = 0.037, 30-day mortality, aHR 1.8 95% CI 1.12-2.58, p = 0.001), and 90-day mortality, aHR 1.68 95% CI 1.24-2.27, p = 0.001. This association was more robust among diabetic patients than those without diabetes. In this study, diabetes was not associated with worse clinical outcomes in community-onset sepsis. However, high glucose levels at sepsis onset are independently associated with a worse prognosis, particularly among diabetic patients. Future trials should explore whether glycemic control could impact the outcomes and should be part of the management of sepsis, among the general adult septic population.

Survivors of Intensive Care With Type 2 Diabetes and the Effect of Shared-Care Follow-Up Clinics: The SWEET-AS Randomized Controlled Pilot Study

BACKGROUND

Follow-up clinics after ICU admission have demonstrated limited benefit. However, existing trials have evaluated heterogeneous cohorts and used physicians who had limited training in outpatient care.

RESEARCH QUESTION

What are the effects of a "shared-care" intensivist-endocrinologist clinic for ICU survivors with type 2 diabetes on process measures and clinical outcomes 6 months after hospital discharge, and is it feasible to conduct a larger trial?

STUDY DESIGN AND METHODS

This was a prospective, randomized, single-center pilot study with blinded outcome assessment. Patients with type 2 diabetes, who required ≥ 5 days of ICU care (mixed medical-surgical ICU) and survived to ICU discharge, were eligible. Participants were randomized to attendance at the shared-care clinic 1 month after hospital discharge or usual care. Six months after hospital discharge, participants were assessed for outcomes including glycated hemoglobin, neuropathy, nephropathy, quality of life, return to employment, frailty, and health-care use. The primary outcome was participant recruitment and retention.

RESULTS

During an 18-month period, 42 of 82 eligible patients (51%) were recruited. Four participants (10%) withdrew before assessment at 6 months and 11 (26%) died. At 6 months, only 18 of 38 participants who did not withdraw (47%) were living independently without support, and 24 (63%) required at least one subsequent hospital admission. In the intervention group (n = 21), 16 (76%) attended the clinic. Point estimates did not indicate that the intervention improved glycated hemoglobin (+5.6 mmol/mol; 95% CI, -6.3 to 17; P = .36) or quality of life (36-Item Short Form Survey physical summary score, 32 [9] vs. 32 [7]; P = 1.0).

INTERPRETATION

Outcomes for ICU survivors with type 2 diabetes are poor. Because of low participation and high mortality, a larger trial of a shared-care follow-up clinic in this cohort, using the present design, does not appear feasible.

TRIAL REGISTRY

Australian New Zealand Clinical Trials Registry (ANZCTR); No.: ACTRN12616000206426; URL: www.anzctr.org.au.