Effect of stress-induced hyperglycemia on long-term mortality in non-diabetic patients with acute type A aortic dissection: a retrospective analysis.

BACKGROUND: Acute Type A Aortic Dissection (AAAD) is one of the most life-threatening diseases, often associated with transient hyperglycemia induced by acute physiological stress. The impact of stress-induced hyperglycemia on the prognosis of ST-segment elevation myocardial infarction has been reported. However, the relationship between stress-induced hyperglycemia and the prognosis of AAAD patients remains uncertain. METHODS: The clinical data of 456 patients with acute type A aortic dissection were retrospectively reviewed. Patients were divided into two groups based on their admission blood glucose. Cox model regression analysis was performed to assess the relationship between stress-induced hyperglycemia and the 30-day and 1-year mortality rates of these patients. RESULTS: Among the 456 patients, 149 cases (32.7%) had AAAD combined with stress-induced hyperglycemia (SIH). The results of the multifactor regression analysis of the Cox model indicated that hyperglycemia (RR = 1.505, 95% CI: 1.046-2.165, p = 0.028), aortic coarctation involving renal arteries (RR = 3.330, 95% CI: 2.237-4.957, p < 0.001), aortic coarctation involving superior mesenteric arteries (RR = 1.611, 95% CI: 1.056-2.455, p = 0.027), and aortic coarctation involving iliac arteries (RR = 2.034, 95% CI: 1.364-3.035, p = 0.001) were independent influences on 1-year postoperative mortality in AAAD patients. CONCLUSION: The current findings indicate that stress-induced hyperglycemia measured on admission is strongly associated with 1-year mortality in patients with AAAD. Furthermore, stress-induced hyperglycemia may be related to the severity of the condition in patients with AAAD.

Prognostic significance of the stress hyperglycemia ratio and admission blood glucose in diabetic and nondiabetic patients with spontaneous intracerebral hemorrhage.

BACKGROUND: The role of stress hyperglycemia ratio (SHR) on the prognosis of spontaneous intracerebral hemorrhage (ICH) in patients with different diabetic status has not been elucidated. This study aimed to evaluate the prognostic value of SHR and admission blood glucose (ABG) for the short- and long-term mortality in diabetic and nondiabetic populations with ICH. METHOD: Participants with ICH were retrospectively retrieved from the Medical Information Mart for Intensive Care (MIMIC-IV). The primary outcome was all-cause 30-day and 1-year mortality. The association of SHR and ABG with the primary outcomes in diabetic and nondiabetic cohorts were assessed by Cox proportional hazard regression. RESULTS: Overall, 1029 patients with a median age of 71.09 (IQR: 60.05-81.97) were included. Among them, 548 (53%) individuals were male, and 95 (19%) as well as 323 (31%) ones experienced the 30-day and 1-year mortality, respectively. After adjusting for confounding variables, individuals in quintile 5 of SHR had significantly higher risk of the 30-day and 1-year mortality than those in quintile 1 in the whole cohort (30-day mortality: HR 3.33, 95%CI 2.01-5.51; 1-year mortality: HR 2.09, 95% CI 1.46-3.00) and in nondiabetic patients (30-day mortality: HR 4.55, 95%CI 2.33-8.88; 1-year mortality: HR 3.06, 95%CI 1.93-4.86), but no significant difference was observed in diabetic patients. Similar results were observed for ABG as a categorical variable. As continuous variable, SHR was independently correlated with the 30-day and 1-year mortality in both of the diabetic and nondiabetic cohorts (30-day mortality: HR 2.63, 95%CI 1.50-4.60. 1-year mortality: HR 2.12, 95%CI 1.33-3.39), but this correlation was only observed in nondiabetic cohort for ABG (HR 1.00, 95%CI 0.99-1.01 for both of the 30-day and 1-year mortality). Moreover, compared with ABG, SHR can better improve the C-statistics of the original models regarding the 30-day and 1-year outcomes, especially in patients with diabetes (p < 0.001 in all models). CONCLUSION: SHR might be a more useful and reliable marker than ABG for prognostic prediction and risk stratification in critically ill patients with ICH, especially in those with diabetes.

Malglycemia in the critical care setting. Part III: Temporal patterns, relative potencies, and hospital mortality.

INTRODUCTION: The relationship between critical care mortality and combined impact of malglycemia remains undefined. METHODS: We assessed the risk-adjusted relationship (n = 4790) between hospital mortality with malglycemia, defined as hypergycemia (hours Glycemic Ratio ≥ 1.1, where GR is quotient of mean ICU blood glucose (BG) and estimated average BG), absolute hypoglycemia (hours BG < 70 mg/dL) and relative hypoglycemia (excursions GR < 0.7 in those with HbA1c ≥ 8%). RESULTS: Each malglycemia was independently associated with mortality - hyperglycemia (OR 1.0020/h, 95%CI 1.0009-1.0031, p = 0.0004), absolute hypoglycemia (OR 1.0616/h, 95%CI 1.0190-1.1061, p = 0.0043), and relative hypoglycemia (OR 1.2813/excursion, 95%CI 1.0704-1.5338, p = 0.0069). Absolute (7.4%) and relative hypoglycemia (6.7%) exposure dominated the first 24 h, decreasing thereafter. While hyperglycemia had lower risk association with mortality, it was persistently present across the length-of-stay (68-76% incidence daily), making it the dominant form of malglycemia. Relative contributions in the first five days from hyperglycemia, absolute hypoglycemia and relative hypoglycemia were 60%, 21% and 19% respectively. CONCLUSIONS: Absolute and relative hypoglycemia occurred largely in the first 24 h. Relative to all hypoglycemia, the associated mortality from the seemingly less potent but consistently more prevalent hyperglycemia steadily accumulated with increasing length-of-stay. This has important implications for interpretation of study results.

Malglycemia in the critical care setting. Part II: Relative and absolute hypoglycemia.

INTRODUCTION: The relationship between critical care mortality and hypoglycemia, both relative (>30% below average preadmission glycemia) and absolute (blood glucose (BG) <70 mg/dL (<10 mmol/L)) requires further definition. METHODS: We assessed the risk-adjusted relationship between hospital mortality with relative hypoglycemia using the Glycemic Ratio (GR), and with absolute hypoglycemia using BG in a retrospective cohort investigation (n = 4790). RESULTS: Relative hypoglycemia excursions below GR 0.7 with a of 24-h non-exposure period between excursions in those with HbA1c ≥ 8% were independently associated with mortality (n = 373, OR 2.49, 95% CI 1.54-4.04, p = 0.0002) but not those with HbA1c < 8% (n = 4417, OR 0.98 95% CI 0.89-1.08, p = 0.70). Hours below GR 0.7 (1.0037, 0.9995-1.0080, 0.0846) or minimum GR (0.0896, 0.0030-2.6600, 0.1632) were not independently associated with outcome. Absolute hypoglycemia occurred across the HbA1c spectrum in a U-shaped pattern. There was no difference in mortality associated with exposure to BG < 70 mg/dL for HbA1c ≥ 6.5% vs <6.5% (29.7% vs 24.3%, p = 0.77). Hours below 70 mg/dL demonstrated strongest association with outcome, while minimum BG, and excursions below 70 mg/dL were also independently associated. CONCLUSIONS: Relative hypoglycemia represented by excursions below GR 0.7 in those with HbA1c ≥ 8% occurred commonly and was independently associated with mortality. Absolute hypoglycemia had similar association with mortality regardless of HbA1c.

Impact of stress hyperglycemia ratio, derived from glycated albumin or hemoglobin A1c, on mortality among ST-segment elevation myocardial infarction patients.

BACKGROUND: Stress hyperglycemia ratio (SHR), associated with adverse outcomes in patients with ST-segment elevation myocardial infarction (STEMI), has several definitions. This study aims to assess the prognostic value of SHR, derived from hemoglobin A1c (HbA1c) or glycated albumin (GA), to mortality. METHODS: The study comprised 1,643 STEMI patients who underwent percutaneous coronary intervention (PCI) in two centers. SHR1 was calculated using fasting blood glucose (FBG)/GA, while SHR2 was calculated using the formula FBG/(1.59*HbA1c-2.59). The primary endpoints were in-hospital death and all-cause mortality, with a median follow-up duration of 1.56 years. RESULTS: Higher SHR1 and SHR2 values are associated with increased risks of in-hospital death and all-cause mortality. Each standard deviation increase in SHR1 corresponded to a 39% and 22% escalation in in-hospital death and all-cause mortality, respectively. The respective increases for SHR2 were 51% and 26%. Further examinations validated these relationships as linear. Additionally, the areas under the curve (AUC) for in-hospital death were not significantly different between SHR1 and SHR2 (p > 0.05). Incorporating SHR1 or SHR2 into the base model significantly improved the discrimination and risk reclassification for in-hospital and all-cause mortality. A subgroup analysis revealed that the effects of SHR1 and SHR2 were more pronounced in patients with hypercholesteremia. CONCLUSION: SHR1 and SHR2 have emerged as robust and independent prognostic markers for STEMI patients undergoing PCI. The SHR calculation based on either HbA1c or GA can provide additional predictive value for mortality beyond traditional risk factors, helping to identify high-risk STEMI patients.

Association between diabetes and stress-induced hyperglycemia with skeletal muscle gene expression of INSR in critically ill patients: A prospective cohort study.

This study aimed to investigate the association between diabetes and stress-induced hyperglycemia with skeletal muscle gene expression of INSR of critically ill patients. Skeletal muscle biopsies were prospectively taken from the vastus muscle, and the expression level of INSR was analyzed using RT-qPCR. Fifty patients were included from April 2018 to September 2018. No significant differences in skeletal muscle gene expression were found between patients with or without diabetes. Similarly, there were no differences in gene expression between groups according to the presence of hypoglycemia 〈 70 mg/dl or hyperglycemia 〉 140 mg/dl. Patients with glycemic variability ≥ 40 mg/dl exhibited a downregulation of INSR compared to those with glycemic variability < 40 mg/dl (1.3 [0.01-5] vs. 2.1 [0.7 - 3.4] fold-changes, P = 0.045). The same pattern was observed when glycemic gap threshold of 80 mg/dl was used (1.4 [0.25-5] vs 1 [0.01 - 2.3] fold-changes in patients with glycemic gap < 80 mg/dl and glycemic gap ≥ 80 mg/dl respectively, P = 0.015). In conclusion, INSR was downregulated in the skeletal muscle of critically ill patients with stress-induced hyperglycemia.

[Predictive value of stress-induced hyperglycemia on 28 d risk of all-cause death in intensive care patients].

OBJECTIVE: To investigate the relationship between stress glucose elevation and the risk of 28 d all-cause mortality in intensive care unit (ICU) patients, and to compare the predictive efficacy of different stress glucose elevation indicators. METHODS: ICU patients who met the inclusion and exclusion criteria in the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database were used as the study subjects, and the stress glucose elevation indicators were divided into Q1 (0-25%), Q2 (>25%- 75%), and Q3 (>75%-100%) groups, with whether death occurred in the ICU and the duration of treatment in the ICU as outcome variables, and demographic characteristics, laboratory indicators, and comorbidities as covariates, Cox regression and restricted cubic splines were used to explore the association between stress glucose elevation and the risk of 28 d all-cause death in ICU patients; and subject work characteristics [receiver operating characteristic (ROC) and the area under curve (AUC)] were used to evaluate the predictive efficacy of different stress glucose elevation indicators, The stress hyperglycemia indexes included: stress hyperglycemia ratio (SHR1, SHR2), glucose gap (GG); and the stress hyperglycemia index was further incorporated into the Oxford acute severity of illness score (OASIS) to investigate the predictive efficacy of the improved scores: the AUC was used to assess the score discrimination, and the larger the AUC indicated, the better score discrimination. The Brier score was used to evaluate the calibration of the score, and a smaller Brier score indicated a better calibration of the score. RESULTS: A total of 5 249 ICU patients were included, of whom 7.56% occurred in ICU death. Cox regression analysis after adjusting for confounders showed that the HR (95%CI) for 28 d all-cause mortality in the ICU patients was 1.545 (1.077-2.217), 1.602 (1.142-2.249) and 1.442 (1.001-2.061) for the highest group Q3 compared with the lowest group Q1 for SHR1, SHR2 and GG, respectively, and The risk of death in the ICU patients increased progressively with increasing indicators of stressful blood glucose elevation (Ptrend < 0.05). Restricted cubic spline analysis showed a linear relationship between SHR and the 28 d all-cause mortality risk (P>0.05). the AUC of SHR2 and GG was significantly higher than that of SHR1: AUCSHR2=0.691 (95%CI: 0.661-0.720), AUCGG=0.685 (95%CI: 0.655-0.714), and AUCSHR1=0.680 (95%CI: 0.650-0.709), P < 0.05. The inclusion of SHR2 in the OASIS scores significantly improved the discrimination and calibration of the scores: AUCOASIS=0.820 (95%CI: 0.791-0.848), AUCOASIS+SHR2=0.832 (95%CI: 0.804-0.859), P < 0.05; Brier scoreOASIS=0.071, Brier scoreOASIS+SHR2=0.069. CONCLUSION: Stressful glucose elevation is strongly associated with 28 d all-cause mortality risk in ICU patients and may inform clinical management and decision making in intensive care patients.

Incidence of Stress-Induced Hyperglycemia in Acute Ischemic Stroke: A Systematic Review and Meta-Analysis.

The aim of this study was to systematically evaluate the incidence of stress-induced hyperglycemia (SIH) in acute ischemic stroke (AIS). Studies that reported SIH incidence in AIS and examined risk factors for SIH and non-SIH patients were systematically searched in PubMed, Embase, Cochrane Library, and Web of Science from the inception of each database to December 2021. Article screening and data extraction were performed by two independent reviewers according to the inclusion and exclusion criteria. The quality of the included studies was assessed using the Newcastle-Ottawa Scale (NOS), and meta-analysis was performed using Stata. A total of 13 studies involving 4552 patients (977 in the SIH group and 3575 in the non-SIH group) were included. Meta-analysis showed that the incidence of SIH was 24% (95% CI: 21-27%) in the total population, 33% (14-52%) in North America, 25% (20-29%) in Europe, and 21% (12-29%) in Asia. Subgroup analysis by year of publication revealed that the pooled incidence of SIH was 27% (22-32%) in studies published before 2010 and 19% (14-24%) in those published after 2010. SIH is relatively common in AIS and poses a serious public health problem. Therefore, more emphasis should be placed on the prevention and control of SIH in AIS.

A Review of Hyperglycemia in COVID-19.

Diabetes mellitus (DM) is one of the most common chronic metabolic disorders worldwide, which increases the risk of common and opportunistic infections. Following the coronavirus disease 2019 (COVID-19) pandemic, a higher incidence rate, more severe forms of the disease, and exacerbation of hyperglycemia and its complications have been observed in patients with DM. Moreover, stress-induced hyperglycemia has been observed in many hospitalized nondiabetic patients after contracting COVID-19. Hyperglycemia worsens prognosis in both diabetic and nondiabetic patients. In this study, the mechanism of new-onset or exacerbation of hyperglycemia, the effect of the treatments used for COVID-19 on hyperglycemia, the importance and appropriate method of blood glucose (blood sugar (BS)) control during the disease, and the possible fate of new-onset hyperglycemia after recovery from COVID-19 to some extent is expressed.

Malglycemia in the critical care setting. Part I: Defining hyperglycemia in the critical care setting using the glycemic ratio.

INTRODUCTION: Stress-induced hyperglycemia (SIH) is conventionally represented by Blood Glucose (BG) although recent evidence indicates the Glycemic Ratio (GR, quotient of mean BG and estimated preadmission BG) is a superior prognostic marker. We assessed the association between in-hospital mortality and SIH, using BG and GR in an adult medical-surgical ICU. METHODS: We included patients with hemoglobin A1c (HbA1c) and minimum four BGs in a retrospective cohort investigation (n = 4790). RESULTS: A critical SIH threshold of GR 1.1 was identified. Mortality increased with increasing exposure to GR ≥ 1.1 (r2 = 0.94, p = 0.0007). Duration of exposure to BG ≥ 180 mg/dL demonstrated a less robust association with mortality (r2 = 0.75, p = 0.059). In risk-adjusted analyses, hours GR ≥ 1.1 (OR 1.0014, 95%CI (1.0003-1.0026), p = 0.0161) and hours BG ≥ 180 mg/dL (OR 1.0080, 95%CI (1.0034-1.0126), p = 0.0006) were associated with mortality. In the cohort with no exposure to hypoglycemia however, only hours GR ≥ 1.1 was associated with mortality (OR 1.0027, 95%CI (1.0012-1.0043), p = 0.0007), not BG ≥ 180 mg/dL (OR 1.0031, 95%CI (0.9949-1.0114), p = 0.50) and this relationship remained intact for those who never experienced BG outside the 70-180 mg/dL range (n = 2494). CONCLUSIONS: Clinically significant SIH commenced above GR 1.1. Mortality was associated with hours of exposure to GR ≥ 1.1 which was a superior marker of SIH compared to BG.

Large vessel occlusion stroke outcomes in diabetic vs. non-diabetic patients with acute stress hyperglycemia.

Objective: This study assesses whether stress-induced hyperglycemia is a predictor of poor outcome at 3 months for patients with acute ischemic stroke (AIS) treated by endovascular treatment (EVT) and impacted by their previous blood glucose status. Methods: This retrospective study collected data from 576 patients with AIS due to large vessel occlusion (LVO) treated by EVT from March 2019 to June 2022. The sample was composed of 230 and 346 patients with and without diabetes mellitus (DM), respectively, based on their premorbid diabetic status. Prognosis was assessed with modified Rankin Scale (mRS) at 3-month after AIS. Poor prognosis was defined as mRS>2. Stress-induced hyperglycemia was assessed by fasting glucose-to-glycated hemoglobin ratio (GAR). Each group was stratified into four groups by quartiles of GAR (Q1-Q4). Binary logistic regression analysis was used to identify relationship between different GAR quartiles and clinical outcome after EVT. Results: In DM group, a poor prognosis was seen in 122 (53%) patients and GAR level was 1.27 ± 0.44. These variables were higher than non-DM group and the differences were statistically significant (p < 0.05, respectively). Patients with severe stress-induced hyperglycemia demonstrated greater incidence of 3-month poor prognosis (DM: Q1, 39.7%; Q2, 45.6%; Q3, 58.6%; Q4, 68.4%; p = 0.009. Non-DM: Q1, 31%; Q2, 32.6%; Q3, 42.5%; Q4, 64%; p < 0.001). However, the highest quartile of GAR was independently associated with poor prognosis at 3 months (OR 3.39, 95% CI 1.66-6.96, p = 0.001), compared to the lowest quartile in non-DM patients after logistic regression. This association was not observed from DM patients. Conclusion: The outcome of patients with acute LVO stroke treated with EVT appears to be influenced by premorbid diabetes status. However, the poor prognosis at 3-month in patients with DM is not independently correlated with stress-induced hyperglycemia. This could be due to the long-term damage of persistent hyperglycemia and diabetic patients' adaptive response to stress following acute ischemic damage to the brain.

Stress-induced Hyperglycemia Ratio as an Independent Risk Factor of In-hospital Mortality in Nonresuscitation Intensive Care Units: A Retrospective Study.

PURPOSE: To determine whether the stress-induced hyperglycemia ratio (SHR) is independently associated with in-hospital mortality in critically ill patients in nonresuscitation ICUs. METHODS: In this retrospective cohort study, clinical- and laboratory-related data from patients first admitted to nonresuscitation ICUs were extracted from an open-access database of >50,000 ICU admissions. Patients were assigned to one of two groups according to an SHR threshold of 1.1. The primary end point of this study was the in-hospital mortality rate. The associations between SHR and length of stay in the ICU and hospital, duration of mechanical ventilation use, and vasopressor use were secondary end points. Logistic regression models were established in the analysis of in-hospital mortality risk, and areas under the receiver operating characteristic curve (AUC) were analyzed to investigate the association between the primary end point and SHR used alone or together with the Simplified Acute Physiology Scale (SAPS) II score. The Youden index, specificity, and sensitivity of SHR and SAPS-II were also assessed. FINDINGS: In this study, 1859 patients were included, 187 of whom (10.06%) died during hospitalization. The group with an SHR of ≥1.1 had a greater in-hospital mortality rate (13.7% vs 7.4%; P < 0.001), longer length of stay both in the ICU and in the hospital, a longer duration of mechanical ventilation use, and a greater rate of vasopressor use. On adjustment for multivariate risk, a 0.1-point increment in SHR was significantly associated with in-hospital mortality (OR = 1.08; 95% CI, 1.00-1.16; P = 0.036). The AUC of the association between risk and the SAPS-II score was significantly greater than that with SHR (0.797 [95% CI, 0.576-0.664] vs 0.620 [95% CI, 0.764-0.830]; P < 0.001). The AUC with SAPS-II + SHR was significantly greater than that with SAPS-II used alone (0.802 [95% CI, 0.770-0.835] vs 0.797 [95% CI, 0.764-0.830]; P = 0.023). The Youden index, specificity, and sensitivity of SAPS-II + SHR were 0.473, 0.703, and 0.770, respectively. IMPLICATIONS: Stress-induced hyperglycemia, as evaluated using the SHR, was associated with increased in-hospital mortality and worse clinical outcomes in these critically ill patients in nonresuscitation ICUs. SHR was an independent risk factor for in-hospital mortality, and when used together with the SAPS-II, added to the capacity to predict mortality in these patients in nonresuscitation ICUs. Prospective data are needed to validate the capacity of SHR in predicting in-hospital mortality in patients in the nonresuscitation ICU.

Diabetic and stress-induced hyperglycemia in spontaneous intracerebral hemorrhage: A multicenter prospective cohort (CHEERY) study.

INTRODUCTION: Admission hyperglycemia is a common finding after spontaneous intracerebral hemorrhage (ICH) secondary to pre-existing diabetes mellitus (DM) or stress-induced hyperglycemia (SIH). Studies of the causal relationship between SIH and ICH outcomes are rare. AIM: We aimed to identify whether SIH or pre-existing DM was the cause of admission hyperglycemia associated with ICH outcomes. METHODS: Admission glycosylated hemoglobin (HbA1c), glucose levels, and comorbidity data from the prospective, multicenter cohort, Chinese Cerebral Hemorrhage: Mechanisms and Intervention Study (CHEERY), were collected and analyzed. According to different admission blood glucose and HbA1c levels, patients were divided into nondiabetic normoglycemia (NDN), diabetic normoglycemia (DN), diabetic hyperglycemia (DH), and SIH groups. Modified Poisson regression models were used to analyze ICH outcomes in the different groups. RESULTS: In total, 1372 patients were included: 388 patients with admission hyperglycemia, 239 with DH, and 149 with SIH. In patients with hyperglycemia, SIH was associated with a higher risk of pulmonary infection [risk ratios (RR): 1.477, 95% confidence interval (CI): 1.004-2.172], 30-day (RR: 1.068, 95% CI: 1.009-1.130) and 90-day mortality after ICH (RR: 1.060, 95% CI: 1.000-1.124). CONCLUSIONS: Admission hyperglycemia is a common finding after ICH, and SIH is a sensitive predictor of the risk of pulmonary infection and all-cause death after ICH.

[Risk of postoperative complications in hyperglycemic conditions]. / Risk razvitiya posleoperatsionnykh oslozhnenii pri giperglikemicheskikh sostoyaniyakh.

The authors consider the influence of carbohydrate metabolism disorders on postoperative period. Data on the influence of diabetes mellitus on morbidity are summarized. Mechanisms and significance of stress-induced hyperglycemia are described. The authors also discuss modern approaches to the treatment of hyperglycemic conditions in perioperative period.

Predictive value of stress-induced hyperglycemia on 28 d risk of all-cause death in intensive care patients / 北京大学学报(医学版)

OBJECTIVE@#To investigate the relationship between stress glucose elevation and the risk of 28 d all-cause mortality in intensive care unit (ICU) patients, and to compare the predictive efficacy of different stress glucose elevation indicators.@*METHODS@#ICU patients who met the inclusion and exclusion criteria in the Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) database were used as the study subjects, and the stress glucose elevation indicators were divided into Q1 (0-25%), Q2 (>25%- 75%), and Q3 (>75%-100%) groups, with whether death occurred in the ICU and the duration of treatment in the ICU as outcome variables, and demographic characteristics, laboratory indicators, and comorbidities as covariates, Cox regression and restricted cubic splines were used to explore the association between stress glucose elevation and the risk of 28 d all-cause death in ICU patients; and subject work characteristics [receiver operating characteristic (ROC) and the area under curve (AUC)] were used to evaluate the predictive efficacy of different stress glucose elevation indicators, The stress hyperglycemia indexes included: stress hyperglycemia ratio (SHR1, SHR2), glucose gap (GG); and the stress hyperglycemia index was further incorporated into the Oxford acute severity of illness score (OASIS) to investigate the predictive efficacy of the improved scores: the AUC was used to assess the score discrimination, and the larger the AUC indicated, the better score discrimination. The Brier score was used to evaluate the calibration of the score, and a smaller Brier score indicated a better calibration of the score.@*RESULTS@#A total of 5 249 ICU patients were included, of whom 7.56% occurred in ICU death. Cox regression analysis after adjusting for confounders showed that the HR (95%CI) for 28 d all-cause mortality in the ICU patients was 1.545 (1.077-2.217), 1.602 (1.142-2.249) and 1.442 (1.001-2.061) for the highest group Q3 compared with the lowest group Q1 for SHR1, SHR2 and GG, respectively, and The risk of death in the ICU patients increased progressively with increasing indicators of stressful blood glucose elevation (Ptrend < 0.05). Restricted cubic spline analysis showed a linear relationship between SHR and the 28 d all-cause mortality risk (P>0.05). the AUC of SHR2 and GG was significantly higher than that of SHR1: AUCSHR2=0.691 (95%CI: 0.661-0.720), AUCGG=0.685 (95%CI: 0.655-0.714), and AUCSHR1=0.680 (95%CI: 0.650-0.709), P < 0.05. The inclusion of SHR2 in the OASIS scores significantly improved the discrimination and calibration of the scores: AUCOASIS=0.820 (95%CI: 0.791-0.848), AUCOASIS+SHR2=0.832 (95%CI: 0.804-0.859), P < 0.05; Brier scoreOASIS=0.071, Brier scoreOASIS+SHR2=0.069.@*CONCLUSION@#Stressful glucose elevation is strongly associated with 28 d all-cause mortality risk in ICU patients and may inform clinical management and decision making in intensive care patients.

Impact of glycemic gap on 30-day adverse outcomes in patients with acute ST-segment elevation myocardial infarction.

BACKGROUND AND AIMS: Stress-induced hyperglycemia (SIH) generally occurs in critical illness. Recently, glycemic gap (GAP) has been considered to be a superior indicator of SIH. However, data on the association between GAP and prognosis in ST-segment elevation myocardial infarction (STEMI) is limited. This observational study aimed to estimate the prognostic value of GAPmean, defined as the difference between mean blood glucose level (MGL) within 24 h after admission and A1c-derived average glucose (ADAG), in patients with acute STEMI. METHODS: A total of 4952 patients with acute STEMI were included in the final analysis, and they were divided into four groups according to GAPmean quartiles and diabetes mellitus (DM). The primary outcomes were all-cause mortality and major adverse cardiovascular events (MACEs). Cox proportional hazards regression analysis and net reclassification improvement (NRI) analysis were performed. RESULTS: At 30 days of follow-up, 324 (6.5%) deaths and 569 (11.5%) MACEs occurred. With the elevation of GAPmean, the incidence of all-cause mortality (4.0%, 5.6%, 6.5%, and 10.1%) and MACEs (7.3%, 9.6%, 11.4%, and 17.7%) significantly increased. Receiver operating characteristic curve analysis demonstrated that GAPmean was superior to admission blood glucose (ABG) and GAPadm (defined as the difference between ABG and ADAG) to detect adverse outcomes. Multivariate Cox regression analysis revealed that elevated GAPmean was independently associated with all-cause death and MACEs. With the first quartile as a reference, the hazards ratios (HRs) for all-cause death in the second, third, and fourth quartiles were 1.49 (95% CI 1.02-2.18), 1.58 (95% CI 1.09-2.30), and 2.11 (95% CI 1.48-3.02), respectively, and the HRs for MACEs were 1.40 (95% CI 1.05-1.86), 1.60 (95% CI 1.21-2.11), and 2.17 (95% CI 1.66-2.83), respectively, which were independent of DM status. Continuous NRI analysis revealed that GAPmean significantly improved risk stratification for all-cause mortality and MACEs by 21.6% and 19.8%, respectively. CONCLUSIONS: The glycemic gap between MGL within 24 h after admission and ADAG was independently associated with 30-day all-cause mortality and MACEs in patients with acute STEMI, which was not affected by DM status. Further, the glycemic gap provided incremental accuracy in the risk stratification of STEMI.

Stress Induced Hyperglycemia in Early Childhood as a Clue for the Diagnosis of NEUROD1-MODY

Maturity-onset diabetes of young 'MODY' Type 6 is a rare form of monogenic diabetes caused by mutations in Neuronal differentiation 1 (NEUROD1). Clinical features vary in a large spectrum in terms of age and BMI at diagnosis. Here, we reported the youngest patient with a NEUROD1 variant to the best of our knowledge. A 2.1-year-old girl was referred to pediatric endocrinology clinic for elevated fasting blood glucose (BG) (104 mg/dL) which was detected at another center where she had been evaluated for loss of appetite. Her maternal aunt and uncle had been diagnosed with type 2 diabetes mellitus (DM) at the age of 40 and 45 years; they were obese (BMI: 30.2 and 30.6 kg/m2). At the age of 3.7 years old, she was hospitalized for buccal cellulitis and plasma glucose concentration was 239 mg/dL at admission. Targeted next-generation sequencing (NGS) was performed considering the stress induced hyperglycemia without serious illness, negative islet cell antibodies and insulin autoantibodies, age at the presentation, and family history of DM. NGS analysis revealed a previously reported heterozygous missense variant in NEUROD1. Segregation studies showed that the identified variant was inherited from her 44-year-old mother with a BMI of 27.2 kg/m2 and a normal oral glucose tolerance test (OGTT). Heterozygous NEUROD1 mutations cause low-penetrant diabetes that is heterogeneous in terms of clinical features as some patients fulfill the classic MODY definition and others are mimicking type 2 DM. Clinical manifestations and family history should be carefully evaluated in patients with stress induced hyperglycemia to identify candidate cases for molecular testing, and proper follow-up should be initiated in affected individuals.

Association of stress induced hyperglycemia with angiographic findings and clinical outcomes in patients with ST-elevation myocardial infarction.

BACKGROUND: Stress induced hyperglycemia (SIH) is common among patients with ST-elevation myocardial infarction (STEMI), even in patients without diabetes mellitus. However, evidence regarding its role on the angiographic outcomes and the prognosis of patients presenting with STEMI is scarce. METHODS: This study included 309 consecutively enrolled STEMI patients undergoing primary percutaneous coronary intervention (pPCI). Patients were diagnosed with SIH if blood glucose on admission was > 140 mg/dl. Also, patients had to fast for at least 8 hours before blood sampling. The objective was to assess whether SIH was associated with major adverse cardiovascular and cerebrovascular (MACCE) events and explore its relationship with angiographic predictors of worse prognosis such as poor initial TIMI flow, intracoronary thrombus burden, distal embolization, and presence of residual thrombus after pPCI. RESULTS: SIH in diabetic and non-diabetic patients was associated with a higher incidence of LTB (aOR = 2.171, 95% CI 1.27-3.71), distal embolization (aOR = 2.71, 95% CI 1.51-4.86), and pre-procedural TIMI flow grade = 0 (aOR = 2.69, 95% CI 1.43-5.04) after adjusting for relevant clinical variables. Importantly, during a median follow-up of 1.7 years STEMI patients with SIH with or without diabetes experienced increased occurrence of MACCE both in univariate (HR = 1.92, 95% CI 1.19-3.01) and multivariate analysis (aHR = 1.802, 95% CI 1.01-3.21). CONCLUSIONS: SIH in STEMI patients with or without diabetes was independently associated with increased MACCE. This could be attributed to the fact that SIH was strongly correlated with poor pre-procedural TIMI flow, LTB, and distal embolization. Large clinical trials need to validate SIH as an independent predictor of adverse angiographic and clinical outcomes to provide optimal individualized care for patients with STEMI.

Glycemic control in critically ill patients with or without diabetes.

BACKGROUND: Early randomized controlled trials have demonstrated the benefits of tight glucose control. Subsequent NICE-SUGAR study found that tight glucose control increased mortality. The optimal glucose target in diabetic and nondiabetic patients remains unclear. This study aimed to evaluate the relationship between blood glucose levels and outcomes in critically ill patients with or without diabetes. METHODS: This was a retrospective analysis of the eICU database. Repeat ICU stays, ICU stays of less than 2 days, patients transferred from other ICUs, those with less than 2 blood glucose measurements, and those with missing data on hospital mortality were excluded. The primary outcome was hospital mortality. Generalised additive models were used to model relationship between glycemic control and mortality. Models were adjusted for age, APACHE IV scores, body mass index, admission diagnosis, mechanical ventilation, and use of vasopressor or inotropic agents. RESULTS: There were 52,107 patients in the analysis. Nondiabetes patients exhibited a J-shaped association between time-weighted average glucose and hospital mortality, while this association in diabetes patients was right-shifted and flattened. Using a TWA glucose of 100 mg/dL as the reference value, the adjusted odds ratio (OR) of TWA glucose of 140 mg/dL was 3.05 (95% confidence interval (CI) 3.03-3.08) in nondiabetes and 1.14 (95% CI 1.08-1.20) in diabetes patients. The adjusted OR of TWA glucose of 180 mg/dL were 4.20 (95% CI 4.07-4.33) and 1.49 (1.41-1.57) in patients with no diabetes and patients with diabetes, respectively. The adjusted ORs of TWA glucose of 80 mg/dL compared with 100 mg/dL were 1.74 (95% CI 1.57-1.92) in nondiabetes and 1.36 (95% CI 1.12-1.66) in patients with diabetes. The glucose ranges associated with a below-average risk of mortality were 80-120 mg/dL and 90-150 mg/dL for nondiabetes and diabetes patients, respectively. Hypoglycemia was associated with increased hospital mortality in both groups but to a lesser extent in diabetic patients. Glucose variability was positively associated with hospital mortality in nondiabetics. CONCLUSIONS: Time-weighted average glucose, hypoglycemia, and glucose variability had different impacts on clinical outcomes in patients with and without diabetes. Compared with nondiabetic patients, diabetic patients showed a more blunted response to hypo- and hyperglycemia and glucose variability. Glycemic control strategies should be reconsidered to avoid both hypoglycemia and hyperglycemia.