Glycaemic Variability and Hyperglycaemia as Prognostic Markers of Major Cardiovascular Events in Diabetic Patients Hospitalised in Cardiology Intensive Care Unit for Acute Heart Failure

The Impact of Acute Heart Failure on Frailty Degree and Outcomes in Elderly Patients with Severe Aortic Stenosis and Chronic Heart Failure with Preserved Ejection Fraction

Frailty degree plays a critical role in the decision-making and outcomes of elderly patients with severe aortic stenosis (AS). Acute heart failure (AHF) results in a severely worse clinical hemodynamic status in this population. This study aimed to evaluate the impact of AHF on frailty degree and outcomes in older patients referred for tailored interventional treatment due to AS. A total of 109 patients (68% female; mean age 83.3 ± 5.4), evaluated by a multidisciplinary path for "frailty-based management" of valve disease, were divided into two groups, one with (AHF+) and one without AHF (AHF-) and preserved ejection fraction (mean value EF: 57.4 ± 8.6). AHF occurred a mean value of 55 days before geriatric, clinical, and surgical assessment. A follow-up for all-cause mortality and readmission was conducted at 20 months. AHF+ patients showed a higher frequency of advanced frailty (53.3% vs. 46.7%, respectively), rehospitalization (35.5% vs. 12.8; p = 0.007), and death (41.9% vs. 12.8%; p < 0.001). In stepwise logistic regression analysis, AHF emerged as an independent risk factor for advanced frailty (OR: 3.8 CI 1.3-10.7; p = 0.01) and hospital readmission (OR: 3.6 CI 1.1-11.6; p = 0.03). In addition, preceding AHF was an independent determinant associated with a higher risk of mortality (HR 2.65; CI 95% 1.04-6.74; p-value 0.04). AHF is independently associated with advanced frailty and poor outcomes in elderly patients with severe AS. So, this population needs careful clinical and geriatric monitoring and the implementation of interventional therapy for AS in the early stages of frailty to avoid the occurrence of AHF and poor outcomes.

Impact of acute glycemic variability on short-term outcomes in patients with ST-segment elevation myocardial infarction: a multicenter population-based study

BACKGROUND

Given the increasing attention to glycemic variability (GV) and its potential implications for cardiovascular outcomes. This study aimed to explore the impact of acute GV on short-term outcomes in Chinese patients with ST-segment elevation myocardial infarction (STEMI).

METHODS

This study enrolled 7510 consecutive patients diagnosed with acute STEMI from 274 centers in China. GV was assessed using the coefficient of variation of blood glucose levels. Patients were categorized into three groups according to GV tertiles (GV1, GV2, and GV3). The primary outcome was 30-day all-cause death, and the secondary outcome was major adverse cardiovascular events (MACEs). Cox regression analyses were conducted to determine the independent correlation between GV and the outcomes.

RESULTS

A total of 7136 patients with STEMI were included. During 30-days follow-up, there was a significant increase in the incidence of all-cause death and MACEs with higher GV tertiles. The 30-days mortality rates were 7.4% for GV1, 8.7% for GV2 and 9.4% for GV3 (p = 0.004), while the MACEs incidence rates was 11.3%, 13.8% and 15.8% for the GV1, GV2 and GV3 groups respectively (p < 0.001). High GV levels during hospitalization were significantly associated with an increased risk of 30-day all-cause mortality and MACEs. When analyzed as a continuous variable, GV was independently associated with a higher risk of all-cause mortality (hazard ratio [HR] 1.679, 95% confidence Interval [CI] 1.005-2.804) and MACEs (HR 2.064, 95% CI 1.386-3.074). Additionally, when analyzed as categorical variables, the GV3 group was found to predict an increased risk of MACEs, irrespective of the presence of diabetes mellitus (DM).

CONCLUSION

Our study findings indicate that a high GV during hospitalization was significantly associated with an increased risk of 30-day all-cause mortality and MACE in Chinese patients with STEMI. Moreover, acute GV emerged as an independent predictor of increased MACEs risk, regardless of DM status.

Blood glucose fluctuation and in-hospital mortality among patients with acute myocardial infarction: eICU collaborative research database

BACKGROUND

To assess the relationship between glycemic variability, glucose fluctuation trajectory and the risk of in-hospital mortality in patients with acute myocardial infarction (AMI).

METHODS

This retrospective cohort study included AMI patients from eICU Collaborative Research Database. In-hospital mortality of AMI patients was primary endpoint. Blood glucose levels at admission, glycemic variability, and glucose fluctuation trajectory were three main study variables. Blood glucose levels at admission were stratified into: normal, intermediate, and high. Glycemic variability was evaluated using the coefficient of variation (CV), divided into four groups based on quartiles: quartile 1: CV≤10; quartile 2: 1030. Univariate and multivariate Cox regression models to assess the relationship between blood glucose levels at admission, glycemic variability, glucose fluctuation trajectory, and in-hospital mortality in patients with AMI.

RESULTS

2590 participants were eventually included in this study. There was a positive relationship between high blood glucose level at admission and in-hospital mortality [hazard ratio (HR) = 1.42, 95%confidence interval (CI): 1.06-1.89]. The fourth quartile (CV>30) of CV was associated with increased in-hospital mortality (HR = 2.06, 95% CI: 1.25-3.40). The findings indicated that only AMI individuals in the fourth quartile of glycemic variability, exhibited an elevated in-hospital mortality among those with normal blood glucose levels at admission (HR = 2.33, 95% CI: 1.11-4.87). Additionally, elevated blood glucose level was a risk factor for in-hospital mortality in AMI patients.

CONCLUSION

Glycemic variability was correlated with in-hospital mortality, particularly among AMI patients who had normal blood glucose levels at admission. Our study findings also suggest early intervention should be implemented to normalize high blood glucose levels at admission of AMI.

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.

Long-term glycemic variability predicts compromised development of heart failure with improved ejection fraction: a cohort study

Background

A substantial portion of heart failure (HF) patients adherent to guideline-directed medical therapies have experienced improved ejection fraction (EF), termed HFimpEF. Glycemic variability (GV) has emerged as a critical cardiometabolic factor. However, the relation between long-term GV and the incidence of HFimpEF is still unclear.

Methods

A total of 591 hospitalized HF patients with reduced EF (HFrEF, EF≤ 40%) admitted from January 2013 to December 2020 were consecutively enrolled. Repeat echocardiograms were performed at baseline and after around 12 months. The incidence of HFimpEF, defined as (1) an absolute EF improvement ≥10% and (2) a second EF > 40% and its association with long-term fasting plasma glucose (FPG) variability were analyzed.

Results

During a mean follow-up of 12.2 ± 0.6 months, 218 (42.0%) patients developed HFimpEF. Multivariate analysis showed FPG variability was independently associated with the incidence of HFimpEF after adjustment for baseline HbA1c, mean FPG during follow-up and other traditional risk factors (odds ratio [OR] for highest vs. lowest quartile of CV of FPG: 0.487 [95% CI 0.257~0.910]). Evaluation of GV by alternative measures yielded similar results. Subgroup analysis revealed that long-term GV was associated with HFimpEF irrespective of glycemic levels and diabetic conditions.

Conclusions

This study reveals that greater FPG variability is associated with compromised development of HFimpEF. A more stable control of glycemic levels might provide favorable effects on myocardial functional recovery in HF patients even without diabetes.

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.

Association between dysglycemia and the Charlson Comorbidity Index among hospitalized patients with diabetes

AIM

Inpatient dysglycemia has been linked to short-term mortality, but longer-term mortality data are lacking. Our aim was to evaluate the association between inpatient dysglycemia and one-year mortality risk.

METHODS

Retrospective chart review of adults with diabetes hospitalized between 2015 and 2019. The Charlson Comorbidity Index (CCI) was used to estimate 1-year mortality risk, stratified into low (CCI ≤ 5) and high risk (CCI ≥6). Simple and multivariable logistic regression was used to evaluate the association between dysglycemic measures and high mortality risk.

RESULTS

Among 22,639 unique admissions, BG ≥ 180, ≥300, ≤70, <54 and <40 mg/dL were associated with adjusted odds of 1.43 (95 % CI, 1.33, 1.54), 1.58 (95 % CI, 1.48, 1.68), 2.16 (95 % CI, 2.01, 2.32), 2.58 (95 % CI, 2.32, 2.86), and 2.56 (95 % CI, 2.19, 2.99) for high mortality risk, respectively. Older age and Black race were positively associated with hyperglycemia and hypoglycemia. Myocardial infarction, congestive heart failure (CHF), and moderate to severe liver disease were most strongly associated with hyperglycemia, while renal disease, CHF, peripheral vascular disease, and peptic ulcer disease were most strongly associated with hypoglycemia.

CONCLUSIONS

Inpatient hypoglycemia and hyperglycemia were both positively associated with higher one-year mortality risk, with stronger magnitude of association observed for hypoglycemia. The association appears to be mediated mainly by presence of diabetes-related complications.