Early glucose variability in cardiogenic shock following acute myocardial infarction: a pilot study

Lazzeri, Chiara; Valente, Serafina; Chiostri, Marco; Attanà, Paola; Gensini, Gian Franco

doi:10.1177/1753944715578968

Cited by 6 publications

(4 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…and sepsis (Karetnikova et al, 2016;Lee et al, 2017;The NICE-SUGAR Study Investigators, 2009;Van den Berghe et al, 2001. The same trends have been documented in a few prospective and retrospective observational studies in patients with cardiogenic shock (CS) (Abdin et al, 2018;Kataja et al, 2017;Lazzeri et al, 2015). Similar metabolic derangements also occur in patients with diabetes during acute illness, with surprising lower mortality than in controls without diabetes (Capes et al, 2000;Malmberg et al, 1995;Planer et al, 2013).…”

mentioning

confidence: 75%

“…Hyperglycemia at admission is one of the strongest predictors of short‐term mortality in patients with CS (Abdin et al, 2018; Kataja et al, 2017; Leor et al, 1993; Tada et al, 2006). Peak glycemia is an independent predictor of mortality in STEMI patients that develop CS, and survivors show lower glycemic variability than nonsurvivors (Lazzeri et al, 2015). The retrospective analysis of subgroups in the Intra‐aortic Balloon Pump in Cardiogenic Shock II (IABP‐SHOCK II) confirmed the important prognostic role of impaired glycemic control on the survival of patients with CS (Abdin et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Stress hyperglycemia, cardiac glucotoxicity, and critically ill patient outcomes current clinical and pathophysiological evidence

2021

View full text Add to dashboard Cite

Stress hyperglycemia describes a state of blood glucose deregulation that occurs during a period of acute physiological stress (Dungan et al., 2009; Marik & Bellomo, 2013). It is defined as an episode of hyperglycemia that resolves spontaneously after the dissipation of the acute illness (Dungan et al., 2009). Stress hyperglycemia is characteristically transient and is frequently observed in critically ill patients. Its presence has, however, been positively correlated with ICU mortality. Indeed, several studies have shown that controlling blood glucose fluctuations during catecholamine overload has survival benefits during acute illness such as acute myocardial infarction (AMI), stroke,

show abstract

mentioning

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Stress hyperglycemia, cardiac glucotoxicity, and critically ill patient outcomes current clinical and pathophysiological evidence

2021

View full text Add to dashboard Cite

show abstract

“…In patients hospitalized directly after an acute myocardial infarction (AMI), GV adversely affects myocardial salvage 57 and wall motion severity at the infarct area, increasing the final infarct size after myocardial reperfusion therapy, 58 as well as triggers left ventricular remodeling in the chronic phase. 59 The role of GV has also been studied by Lazzeri et al 60 who proved that glucose oscillations in patients with a cardiogenic shock after ΑΜΙ constitute an independent predictor of mortality. Acute glucose swings after transcatheter aortic valve implantation are correlated with major adverse events 30 days after the procedure, while hypoglycemia is not associated with this outcome.…”

Section: Glycemic Variability and Coronary Syndromesmentioning

confidence: 96%

Short-term Glycemic Variability and Its Association With Macrovascular and Microvascular Complications in Patients With Diabetes

Psoma

Makris

Tselepis

et al. 2022

J Diabetes Sci Technol

View full text Add to dashboard Cite

The introduction of continuous glucose monitoring inaugurated a new era in clinical practice by shifting the characterization of glycemic control from HbA1c to novel metrics. The one that gained widespread attention over the past decades was glycemic variability (GV), which typically refers to peaks and nadirs of blood glucose measured over a given time interval. GV can be dichotomized into two main categories: short-term and long-term. Short-term GV reflects within-day and between-day glycemic oscillations, and its contribution to diabetic complications remains an enigma. In this review, we summarize the available data about short-term GV and its possible association with both microvascular and macrovascular complications, evaluating different pathogenic mechanisms and demonstrating nonpharmaceutical, as well as pharmaceutical, therapeutic interventions.

show abstract

“…sd Increased sd of BG values as a measure of GV is probably associated with increased mortality (moderate certainty) (Supplemental Table 7, http://links.lww.com/ CCX/B288). Pooled mean difference of sd (mmol/L) was 0.51 (95% CI, 0.40-0.62) higher in those who died (5,(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37). Pooled aOR of mortality per 1mmol/L glucose increase was 1.17 (95% CI, 1.05-1.30) and uOR was 1.03 (95% CI, 1.00-1.06) (20,24,32,33,38,39).…”

Section: Risk Of Bias and Quality Assessmentsmentioning

confidence: 99%

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

Hryciw,

Ghossein,

Rochwerg

et al. 2024

Critical Care Explorations

View full text Add to dashboard Cite

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.

show abstract

Early glucose variability in cardiogenic shock following acute myocardial infarction: a pilot study

Cited by 6 publications

References 19 publications

Stress hyperglycemia, cardiac glucotoxicity, and critically ill patient outcomes current clinical and pathophysiological evidence

Stress hyperglycemia, cardiac glucotoxicity, and critically ill patient outcomes current clinical and pathophysiological evidence

Short-term Glycemic Variability and Its Association With Macrovascular and Microvascular Complications in Patients With Diabetes

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

Contact Info

Product

Resources

About