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

Are we Ready for Real-Time Continuous Glucose Monitoring in the Hospital Setting? Benefits, Challenges, and Practical Approaches for Implementation : Case Vignette: Remote Real-Time Continuous Glucose Monitoring for Hospitalized Care in Quincy Koala

PURPOSE OF REVIEW

While preliminary evidence for use of real-time continuous glucose monitoring (rtCGM) in the hospital setting is encouraging, challenges with currently available devices and technology will need to be overcome as part of real-world integration. This paper reviews the current evidence and guidelines regarding use of rtCGM in the hospital and suggests a practical approach to implementation.

RECENT FINDINGS

There is now a considerable body of real-world evidence on the benefits of reducing dysglycemia in the hospital using both traditional point-of-care (POC) glucose testing and rtCGM. Benefits of rtCGM include decreased frequency of hypo- and hyperglycemia with reduced need of frequent POC checks and it is both feasible and well-accepted by nursing staff and providers. If expansion to additional sites is to be considered, practical solutions will need to be offered. Recommendations for an operational workflow and tools are described to guide implementation in the non-ICU setting. Further testing in randomized controlled trials and real-world dissemination and implementation designs is needed, together with industry and technology collaborations, to further streamline the integration into health systems.

Vitamin C for all?

PURPOSE OF REVIEW

Vitamin C can be a potential adjunctive treatment option for critically ill individuals due to its pleiotropic effects as electron donor in many enzymatic reactions throughout the body. Recently, several important randomized controlled trials (RCTs) investigating vitamin C in critically ill patients have been published.

RECENT FINDINGS

Two recent large RCTs administering high-dose vitamin C to patients with sepsis and COVID-19 showed signs of harm. Though performed at high standard, these trials had several limitations. Recent studies in cardiac surgery and burns showed decreased cardiac enzymes and improved clinical outcomes after cardiac surgery, and decreased fluid requirements, reduced wound healing time and in-hospital mortality after burns. Vitamin C may hold benefit in the management of other ischemia/reperfusion injury populations, including postcardiac arrest patients and after solid organ transplantation. Currently, covering basal vitamin C requirements during critical illness is recommended, though the exact dose remains to be determined.

SUMMARY

Future work should address optimal vitamin C timing, since early versus late drug administration are likely distinct, and duration of therapy, where withdrawal-induced injury is possible. Additionally accurate assessment of body stores with determination of individual vitamin requirements is crucial to ascertain patient and subgroups most likely to benefit from vitamin C.

A Study on the Incidence and Impact of Dysglycemia in Non-diabetic Sepsis Patients

Context Dysglycemia is common in severe sepsis and is associated with a poor prognosis. There is a limited amount of research on stress-induced dysglycemia in non-diabetic sepsis patients. Aim This study aims to estimate the incidence of dysglycemia among non-diabetic patients presenting with sepsis at the Emergency Department and to determine its correlation with gender, age, APACHE II (Acute Physiology and Chronic Health Evaluation) scores, diagnosis, and duration of hospital stay. Materials and methods The study was conducted at a medical college hospital in Kochi from January 1, 2023, to December 31, 2023. A minimum sample size of 77 was derived after a pilot study, with a 95% confidence interval and 10% allowable error. A total of 100 non-diabetic sepsis patients meeting the inclusion and exclusion criteria were analyzed with regard to gender, age, diagnosis, glycemic status (hypo/hyper/normoglycemic), APACHE II scores, and hospital stay duration. Statistical analysis was performed using IBM SPSS Statistics for Windows, Version 20 (Released 2011; IBM Corp., Armonk, New York) software. Categorical variables were expressed as frequency and percentage. Continuous variables were presented as mean ± SD (standard deviation) and median (Q1-Q3). To test the statistical significance of the association between the presence of various factors (gender, age, diagnosis) and dysglycemia, the chi-square test was used. To test the statistical significance of the difference in the mean age and APACHE II score values with dysglycemia, an independent sample t-test was used. To test the statistical significance of the difference in the median hospital stay with dysglycemia, the Whitney U test was used. Data were represented as mean ± SD, and a p-value of <0.05 was considered to be statistically significant. Results The incidence of dysglycemia in the inclusion group was 49% (hypoglycemia in 16% and hyperglycemia in 33% of cases), and it increased with age (p=0.002). The majority of the dysglycemic patients fell into the age group >40 years. Dysglycemia was 54.8% in pneumonia and 66.7% in gastrointestinal sepsis ( p=0.138). Dysglycemia increased with an increase in APACHE II scores (p=0.017). The median hospital stay was almost the same in both normoglycemics and dysglycemics. Conclusion Dysglycemia is a frequent complication in non-diabetic patients with sepsis. It increased with age and APACHE II score, but it does not prolong the duration of hospital stay, nor is it associated with the diagnosis.

Key influences on dysglycemia across Fujian's urban-rural divide

BACKGROUND

Screening and treatment of dysglycemia (prediabetes and diabetes) represent significant challenges in advancing the Healthy China initiative. Identifying the crucial factors contributing to dysglycemia in urban-rural areas is essential for the implementation of targeted, precise interventions.

METHODS

Data for 26,157 adults in Fujian Province, China, were collected using the Social Factors Special Survey Form through a multi-stage random sampling method, wherein 18 variables contributing to dysglycemia were analyzed with logistic regression and the random forest model.

OBJECTIVE

Investigating urban-rural differences and critical factors in dysglycemia prevalence in Fujian, China, with the simultaneous development of separate predictive models for urban and rural areas.

RESULT

The detection rate of dysglycemia among adults was 35.26%, with rates of 34.1% in urban areas and 35.8% in rural areas. Common factors influencing dysglycemia included education, age, BMI, hypertension, and dyslipidemia. For rural residents, higher income (OR = 0.80, 95% CI [0.74, 0.87]), average sleep quality (OR = 0.89, 95% CI [0.80, 0.99]), good sleep quality (OR = 0.89, 95% CI [0.80, 1.00]), and high physical activity (PA) (OR = 0.87, 95% CI [0.79, 0.96]) emerged as protective factors. Conversely, a daily sleep duration over 8 hours (OR = 1.46, 95% CI [1.03, 1.28]) and middle income (OR = 1.12, 95% CI [1.03, 1.22]) were specific risk factors. In urban areas, being male (OR = 1.14, 95% CI [1.02, 1.26]), cohabitation (OR = 1.18, 95% CI [1.02, 1.37]), and central obesity (OR = 1.35, 95% CI [1.19, 1.53]) were identified as unique risk factors. Using logistic regression outcomes, a random forest model was developed to predict dysglycemia, achieving accuracies of 75.35% (rural) and 76.95% (urban) with ROC areas of 0.77 (rural) and 0.75 (urban).

CONCLUSION

This study identifies key factors affecting dysglycemia in urban and rural Fujian residents, including common factors such as education, age, BMI, hypertension, and dyslipidemia. Notably, rural-specific protective factors are higher income and good sleep quality, while urban-specific risk factors include being male and central obesity. These findings support the development of targeted prevention and intervention strategies for dysglycemia, tailored to the unique characteristics of urban and rural populations.

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.

Tight Versus Liberal Blood Glucose Control in Patients With Diabetes in the ICU: A Meta-Analysis of Randomized Controlled Trials

Introduction: Glycemia is an important factor among critically ill patients in the intensive care unit (ICU). There is conflicting evidence on the preferred strategy of blood glucose control among patients with diabetes in the ICU. We aimed to conduct a meta-analysis comparing tight with liberal blood glucose in critically ill patients with diabetes in the ICU. Methods: We systematically searched PubMed, Embase, and Cochrane Central for randomized controlled trials (RCTs) comparing tight versus liberal blood glucose control in critically ill patients with diabetes from inception to December 2023. We pooled odds-ratios (OR) and 95% confidence intervals (CI) with a random-effects model for binary endpoints. We used the Review Manager 5.17 and R version 4.3.2 for statistical analyses. Risk of bias assessment was performed with the Cochrane tool for randomized trials (RoB2). Results: Eight RCTs with 4474 patients were included. There was no statistically significant difference in all-cause mortality (OR 1.11; 95% CI 0.95-1.28; P = .18; I² = 0%) between a tight and liberal blood glucose control. RoB2 identified all studies at low risk of bias and funnel plot suggested no evidence of publication bias. Conclusion: In patients with diabetes in the ICU, there was no statistically significant difference in all-cause mortality between a tight and liberal blood glucose control. PROSPERO registration: CRD42023485032.

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis

OBJECTIVES

To perform a systematic review and meta-analysis to evaluate the association of various measures of glycemic variability, including time-domain and complexity-domain, with short-term mortality in patients with critical illness.

DATA SOURCES

We searched Embase Classic +, MEDLINE, and the Cochrane Database of Systematic Reviews from inception to November 3, 2023.

STUDY SELECTION

We included English language studies that assessed metrics of glycemic variation or complexity and short-term mortality in patients admitted to the ICU.

DATA EXTRACTION

Two authors performed independent data abstraction and risk-of-bias assessments. We used a random-effects model to pool binary and continuous data and summarized estimates of effect using odds ratios and mean difference. We used the Quality in Prognosis Studies tool to assess risk of bias and the Grading of Recommendations, Assessment, Development and Evaluations to assess certainty of pooled estimates.

DATA SYNTHESIS

We included 41 studies (n = 162,259). We demonstrate that increased sd, coefficient of variance, glycemic lability index, and decreased time in range are probably associated with increased mortality in critically ill patients (moderate certainty) and that increased mean absolute glucose, mean amplitude of glycemic excursion, and detrended fluctuation analysis may be associated with increased mortality (low certainty).

CONCLUSIONS

We found a consistent association between increased measures of glycemic variability and higher short-term mortality in patient with critical illness. Further research should focus on standardized measurements of glycemic variation and complexity, along with their utility as therapeutic targets and prognostic markers.

Association of glycemic variability with death and severe consciousness disturbance among critically ill patients with cerebrovascular disease: analysis of the MIMIC-IV database

BACKGROUND

The association of glycemic variability with severe consciousness disturbance and in-hospital all-cause mortality in critically ill patients with cerebrovascular disease (CVD) remains unclear, This study aimed to investigate the association of glycemic variability with cognitive impairment and in-hospital death.

METHOD

We extracted all blood glucose measurements of patients diagnosed with CVD from the Medical Information Mart for Intensive Care IV (MIMIC-IV). Glycemic variability was defined as the coefficient of variation (CV), which was determined using the ratio of standard deviation and the mean blood glucose levels. Cox hazard regression models were applied to analyze the link between glycemic variability and outcomes. We also analyzed non-linear relationship between outcome indicators and glycemic variability using restricted cubic spline curves.

RESULTS

The present study included 2967 patients diagnosed with cerebral infarction and 1842 patients diagnosed with non-traumatic cerebral hemorrhage. Log-transformed CV was significantly related to cognitive impairment and in-hospital mortality, as determined by Cox regression. Increasing log-transformed CV was approximately linearly with the risk of cognitive impairment and in-hospital mortality.

CONCLUSION

High glycemic variability was found to be an independent risk factor for severe cognitive decline and in-hospital mortality in critically ill patients with CVD. Our study indicated that enhancing stability of glycemic variability may reduced adverse outcomes in patients with severe CVD.

Glycemic variability and in-hospital death of critically ill patients and the role of ventricular arrhythmias

BACKGROUND

Abnormal glycemic variability is common in the intensive care unit (ICU) and is associated with increased in-hospital mortality and major adverse cardiovascular events, but little is known about whether adverse outcomes are partly mediated by ventricular arrhythmias (VA). We aimed to explore the association between glycemic variability and VA in the ICU and whether VA related to glycemic variability mediate the increased risk of in-hospital death.

METHODS

We extracted all measurements of blood glucose during the ICU stay from The Medical Information Mart for Intensive Care IV (MIMIC-IV) database version 2.0. Glycemic variability was expressed by the coefficient of variation (CV), which was calculated by the ratio of standard deviation (SD) and average blood glucose values. The outcomes included the incidence of VA and in-hospital death. The KHB (Karlson, KB & Holm, A) is a method to analyze the mediation effect for nonlinear models, which was used to decompose the total effect of glycemic variability on in-hospital death into a direct and VA-mediated indirect effect.

RESULTS

Finally, 17,756 ICU patients with a median age of 64 years were enrolled; 47.2% of them were male, 64.0% were white, and 17.8% were admitted to the cardiac ICU. The total incidence of VA and in-hospital death were 10.6% and 12.8%, respectively. In the adjusted logistic model, each unit increase in log-transformed CV was associated with a 21% increased risk of VA (OR 1.21, 95% CI: 1.11-1.31) and a 30% increased risk (OR 1.30, 95% CI: 1.20-1.41) of in-hospital death. A total of 3.85% of the effect of glycemic variability on in-hospital death was related to the increased risk of VA.

CONCLUSION

High glycemic variability was an independent risk factor for in-hospital death in ICU patients, and the effect was caused in part by an increased risk of VA.

Systemic Glycemic Variation Predicts Mortality of Acute Ischemic Stroke After Mechanical Thrombectomy: A Prospective Study Using Continuous Glucose Monitoring

Objective

We investigated the association of glycemic variation with the clinical outcomes of large vessel occlusion (LVO) induced acute ischemic stroke (AIS) after mechanical thrombectomy (MT).

Methods

We recruited consecutive ischemic patients with stroke. Glucose levels were assessed through continuous glucose monitoring in 70 patients with AIS who had undergone MT. Metrics including percentages of time of glucose levels above the range, the hypoglycemic range, and the time within the range, coefficient of variation, standard deviation (SD), mean of daily differences, mean amplitude of glycemic excursion, largest amplitude of glycemic excursion, high blood glucose index, and low blood glucose index. The outcomes of this observational study were in-hospital mortality, neurological improvement during hospitalization, functional independence, and mortality at follow-up (3 months). The associations of the blood glucose metrics with outcomes were analyzed.

Results

The average period of glucose monitoring was 3.5 days, and serum glucose was recorded 728 times after MT for each person. The glycemic variation expressed in SDs was independently associated with in-hospital mortality [odds ratio (OR): 2.8, 95% confidence interval (CI): 1.276–6.145, p = 0.01] and the 3-month mortality (OR: 2.107, 95% CI: 1.013–4.382, p = 0.046) after adjusting for potential confounders. There was no association of glycemic variation with the 3-month clinical functional independence.

Conclusions

Increased systemic glycemic variation was associated with higher odds of mortality of LVO-AIS after MT.

Clinical Trial Registration

http://www.chictr.org.cn/showproj.aspx?proj=21016, identifier: ChiCTR-OOC-17012378.