Relative Hyperglycemia Is an Independent Determinant of In-Hospital Mortality in Patients With Critical Illness

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.

Accuracy of a Continuous Glucose Monitor in the Intensive Care Unit: A Proposed Accuracy Standard and Calibration Protocol for Inpatient Use

Background and Aims: Guidelines now recommend inpatient continuous glucose monitor (CGM) use with confirmatory blood glucose measurements. However, the Food and Drug Administration has not yet officially approved CGM for inpatient use in large part because its accuracy has not been established in this setting. We tested the accuracy of the Dexcom G6 (G6) in 28 adults on an insulin infusion in a medical-surgical intensive care unit with 1064 matched CGM and arterial point-of-care pairs. Methods: The participants were on average 57.29 (SD 2.39) years, of whom 13 had a prior diagnosis of diabetes and 14 were admitted for a surgical diagnosis. The first 19 participants received the G6 without calibration and had a mean absolute relative difference (MARD) of 13.19% (IQR 5.11, 19.03) across 659 matched pairs, which just meets the critical care expert recommendation of MARD <14%. We then aimed to improve accuracy for the subsequent 9 participants using a calibration protocol. Results: The MARD for calibrated participants was 9.65% (3.03, 13.33), significantly lower than for uncalibrated participants (P < 0.001). Calibration also demonstrated excellent safety with 100% of values within the Clarke Error Grid zones A and B compared with 99.07% without calibration. Our protocol achieved the lowest MARD and safest CEG profile in the critical care setting and well exceeds the critical care expert recommendations. Our large sample of heterogenous critically ill patients also reached comparable accuracy to the MARD of 9% for G6 in outpatients. We believe our calibration protocol will allow G6 to be used with sufficient accuracy in inpatients.

Glucose evaluation and management in the ICU (GEM-ICU): Protocol for a bi-centre cohort study

INTRODUCTION

Hyperglycaemia is common in intensive care unit (ICU) patients. Glycaemic monitoring and effective glycaemic control with insulin are crucial in the ICU to improve patient outcomes. However, glycaemic control and insulin use vary between ICU patients and hypo- and hyperglycaemia occurs. Therefore, we aim to provide contemporary data on glycaemic control and management, and associated outcomes, in adult ICU patients. We hypothesise that the occurrence of hypoglycaemia in acutely admitted ICU patients is lower than that of hyperglycaemia.

METHODS

We will conduct a bi-centre cohort study of 300 acutely admitted adult ICU patients. Routine data will be collected retrospectively at baseline (ICU admission) and daily during ICU stay up to a maximum of 30 days. The primary outcome will be the number of patients with hypoglycaemia during their ICU stay. Secondary outcomes will be occurrence of severe hypoglycaemia, occurrence of hyperglycaemia, time below blood glucose target range, time above target range, all-cause mortality at Day 30, number of days alive without life support at Day 30 and number of days alive and out of hospital at Day 30. Process outcomes include the number of in-ICU days, glucose measurements (number of measurements and method) and use of insulin (including route of administration and dosage). All statistical analyses will be descriptive.

CONCLUSIONS

This cohort study will provide a contemporary overview of glucose evaluation and management practices in adult ICU patients and, thus, highlight potential areas for improvement through future clinical trials in this area.

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 Glycemic Ratio Is Strongly and Independently Associated With Mortality in the Critically Ill

BACKGROUND

Interventional studies investigating blood glucose (BG) management in intensive care units (ICU) have been inconclusive. New insights are needed. We assessed the ability of a new metric, the Glycemic Ratio (GR), to determine the relationship of ICU glucose control relative to preadmission glycemia and mortality.

METHODS

Retrospective cohort investigation (n = 4790) in an adult medical-surgical ICU included patients with minimum four BGs, hemoglobin (Hgb), and hemoglobin A1c (HbA1c). The GR is the quotient of mean ICU BGs (mBG) and estimated preadmission BG, derived from HbA1c.

RESULTS

Mortality displayed a J-shaped curve with GR (nadir GR 0.9), independent of background glycemia, consistent for HbA1c <6.5% vs >6.5%, and Hgb >10 g/dL vs <10 g/dL and medical versus surgical. An optimal range of GR 0.80 to 0.99 was associated with decreased mortality compared with GR above and below this range. The mBG displayed a linear relationship with mortality at lower HbA1c but diminished for HbA1c >6.5%, and dependent on preadmission glycemia. In adjusted analysis, GR remained associated with mortality (odds ratio = 2.61, 95% confidence interval = 1.48-4.62, P = .0012), but mBG did not (1.004, 1.000-1.009, .059). A single value on admission was not independently associated with mortality.

CONCLUSIONS

The GR provided new insight into malglycemia that was not apparent using mBG, or an admission value. Mortality was associated with acute change from preadmission glycemia (GR). Further assessment of the impact of GR deviations from the nadir in mortality at GR 0.80 to 0.99, as both relative hypo- and hyperglycemia, and as duration of exposure and intensity, may further define the multifaceted nature of malglycemia.

Performance comparison of stress hyperglycemia ratio for predicting fatal outcomes in patients with thrombolyzed acute ischemic stroke

BACKGROUND

The stress hyperglycemia ratio (SHR), a newly developed metric, is used to assess adverse outcomes in patients with acute ischemic stroke (AIS). However, the relationship between SHR and fatal outcomes (in-hospital mortality [IHM], malignant cerebral edema [MCE], symptomatic intracerebral hemorrhage [sICH], 3-month mortality, and poor functional outcome) in AIS patients receiving recombinant tissue plasminogen activator (rt-PA) treatment is unclear, and determining the optimal threshold remains incomplete.

MATERIALS AND METHODS

We retrospectively enrolled a total of 345 AIS patients treated with rt-PA during 2015-2022 and collected data on various glucose metrics, including different types of SHR, glycemic gap (GG), random plasma glucose (RPG), fasting plasma glucose (FPG), and hemoglobin A1c (HbA1c). SHR and GG were calculated using these equations: SHR1, [FPG]/[HbA1c]; SHR2, [admission RPG]/[HbA1c]; SHR3, FPG/[(1.59 × HbA1c)-2.59]; SHR4, [admission RPG]/[(1.59 × HbA1c)-2.59]; GG, admission RPG - [(1.59 × HbA1c)-2.59]. We used multivariable logistic regression analysis (MVLR) to identify the association between different glucose metrics and outcomes while comparing their predictive values.

RESULTS

SHR1 had the greatest predictive power and a more significant correlation with fatal outcomes than other continuous glucose metrics. The area under the curve of the SHR1 for IHM, MCE, and sICH, 3-month mortality, and poor functional outcome were 0.75, 0.77, 0.77, 0.76, and 0.73, respectively. SHR1 (per 1-point increases) was independently associated with IHM (Odds ratios [ORs] = 5.80; 95% CI [1.96, 17.17]; p = 0.001), MCE (ORs = 4.73; 95% CI [1.71, 13.04]; p = 0.003), sICH (ORs = 4.68, 95% CI [1.48-14.82]; p = 0.009), 3-month mortality (ORs = 10.87; 95% CI [3.56, 33.21]; p<0.001), and 3-month poor functional outcome (ORs = 8.05; 95% CI [2.77, 23.39]; p<0.001) after adjustment in MVLR. In subgroup analysis, elevated SHR1 was associated with fatal outcomes in patients with non-diabetes, SBP≥ 180 mmHg, and NIHSS <16.

CONCLUSION

SHR1 demonstrates an independent association with fatal outcomes in AIS patients treated with rt-PA, exhibiting superior predictive ability over other glucose metrics.

Association between stress hyperglycemia ratio and prognosis in acute ischemic stroke: a systematic review and meta-analysis

BACKGROUND

Stress hyperglycemia is a relatively transient increase in blood glucose in response to inflammation of the body and neurohormonal disorders. It is still debated whether stress hyperglycemia ratio (SHR) in the acute phase, a new indicator of stress hyperglycemia, is related to poor prognosis in acute ischemic stroke (AIS) patients. This meta-analysis provides insight into the connection between SHR and prognosis in AIS patients.

METHODS

We screened all potentially relevant studies using a comprehensive database search. The standardized mean difference (SMD) and 95% confidence interval (CI) were utilized to investigate the relationship between SHR in the acute phase and the prognosis of AIS.

RESULTS

The pooled results revealed that AIS patients with poor prognoses had significantly higher SHR values than those with good prognoses (SMD = 0.56, 95%CI: 0.37-0.75, p<0.001). Subgroup analysis indicated that study design and differences in post-stroke treatment might be the sources of heterogeneity in this meta-analysis.

CONCLUSIONS

High SHR in the acute period is related to poor prognosis after AIS. SHR may be a new predictor of poor outcomes in AIS patients.

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.

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 implications of stress hyperglycemia ratio in patients with myocardial infarction with nonobstructive coronary arteries

BACKGROUND

The role of stress hyperglycemia in acute myocardial infarction (AMI) has long been emphasized. Recently, the stress hyperglycemia ratio (SHR), a novel index reflecting an acute glycemia rise, has shown a good predictive value in AMI. However, its prognostic power in myocardial infarction with nonobstructive coronary arteries (MINOCA) remains unclear.

METHODS

In a prospective cohort of 1179 patients with MINOCA, relationships between SHR levels and outcomes were analyzed. SHR was defined as acute-to-chronic glycemic ratio using admission blood glucose (ABG) and glycated hemoglobin. The primary endpoint was defined as major adverse cardiovascular events (MACE), including all-cause death, nonfatal MI, stroke, revascularization, and hospitalization for unstable angina or heart failure. Survival analyses and receiver-operating characteristic (ROC) curve analyses were performed.

RESULTS

Over the median follow-up of 3.5 years, the incidence of MACE markedly increased with higher SHR tertile levels (8.1%, 14.0%, 20.5%; p < 0.001). At multivariable Cox analysis, elevated SHR was independently associated with an increased risk of MACE (HR 2.30, 95% CI: 1.21-4.38, p = 0.011). Patients with rising tertiles of SHR also had a significantly higher risk of MACE (tertile 1 as reference; tertile 2: HR 1.77, 95% CI: 1.14-2.73, p = 0.010; tertile 3: HR 2.64, 95% CI: 1.75-3.98, p < 0.001). SHR remained a robust predictor of MACE in patients with and without diabetes; whereas ABG was no longer associated with the MACE risk in diabetic patients. SHR showed an area under the curve of 0.63 for MACE prediction. By incorporating SHR to TIMI risk score, the combined model further improved the discrimination for MACE.

CONCLUSIONS

The SHR independently confers the cardiovascular risk after MINOCA, and may serve as a better predictor than glycemia at admission alone, particularly in those with diabetes.KEY MESSAGESStress hyperglycemia ratio (SHR) is independently associated with the prognosis in a distinct population with myocardial infarction with nonobstructive coronary arteries (MINOCA).SHR is a better predictor of prognosis than admission glycemia alone, especially in diabetic patients with MINOCA.SHR may serve as a prognostic marker for risk stratification as well as a potential target for tailored glucose-lowering treatment in MINOCA.

Dysglycemias in patients admitted to ICUs with severe acute respiratory syndrome due to COVID-19 versus other causes - a cohort study

BACKGROUND

Dysglycemias have been associated with worse prognosis in critically ill patients with COVID-19, but data on the association of dysglycemia with COVID-19 in comparison with other forms of severe acute respiratory syndrome are lacking. This study aimed to compare the occurrence of different glycemic abnormalities in patients with severe acute respiratory syndrome and COVID-19 admitted to intensive care units versus glycemic abnormalities in patients with severe acute respiratory syndrome from other causes, to evaluate the adjusted attributable risk associated with COVID-19 and dysglycemia and to assess the influence of these dysglycemias on mortality.

METHODS

We conducted a retrospective cohort of consecutive patients with severe acute respiratory syndrome and suspected COVID-19 hospitalized in intensive care units between March 11 and September 13, 2020, across eight hospitals in Curitiba-Brazil. The primary outcome was the influence of COVID-19 on the variation of the following parameters of dysglycemia: highest glucose level at admission, mean and highest glucose levels during ICU stay, mean glucose variability, percentage of days with hyperglycemia, and hypoglycemia during ICU stay. The secondary outcome was the influence of COVID-19 and each of the six parameters of dysglycemia on hospital mortality within 30 days from ICU admission.

RESULTS

The sample consisted of 841 patients, of whom 703 with and 138 without COVID-19. Comparing patients with and without COVID-19, those with COVID-19 had significantly higher glucose peaks at admission (165 mg/dL vs. 146 mg/dL; p = 0.002) and during ICU stay (242 mg/dL vs. 187md/dL; p < 0.001); higher mean daily glucose (149.7 mg/dL vs. 132.6 mg/dL; p < 0.001); higher percentage of days with hyperglycemia during ICU stay (42.9% vs. 11.1%; p < 0.001); and greater mean glucose variability (28.1 mg/dL vs. 25.0 mg/dL; p = 0.013). However, these associations were no longer statistically significant after adjustment for Acute Physiology and Chronic Health Evaluation II scores, Sequential Organ Failure Assessment scores, and C-reactive protein level, corticosteroid use and nosocomial infection. Dysglycemia and COVID-19 were each independent risk factors for mortality. The occurrence of hypoglycemia (< 70 mg/dL) during ICU stay was not associated with COVID-19.

CONCLUSION

Patients with severe acute respiratory syndrome due to COVID-19 had higher mortality and more frequent dysglycemia than patients with severe acute respiratory syndrome due to other causes. However, this association did not seem to be directly related to the SARS-CoV-2 infection.

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.

Does hyperglycemia affect arginine metabolites in critically ill patients? A prospective cohort and in vitro study

BACKGROUND

Changes in the arginine metabolites asymmetric dimethyl-L-arginine (ADMA) and L-homoarginine and acute blood glucose concentrations have been shown to cause endothelial dysfunction and be independently associated with mortality in Intensive Care Unit (ICU) patients. The aim of this study was to investigate whether hyperglycemia potentially modulates these arginine metabolite concentrations to provide a mechanism that may link hyperglycemia and mortality in this patient group.

METHODS

A clinical and in vitro study were undertaken. Glucose, glycosylated hemoglobin-A1c (HbA1c) and the stress hyperglycemia ratio (SHR) (to quantify absolute, chronic and relative hyperglycemia respectively) were measured in 1155 acutely unwell adult patients admitted to a mixed medical-surgical ICU. SHR was calculated by dividing the admission glucose by the estimated average glucose over the last 3 months, which was derived from HbA1c. ADMA and L-homoarginine were measured in a plasma sample collected at admission to ICU by liquid chromatography tandem mass spectrometry. The activity of dimethylarginine-dimethylaminohydrolase 1 (DDAH1), the main enzyme regulating ADMA concentrations, was assessed at varying glucose concentrations in vitro by quantifying the conversion of ADMA to citrulline in HEK293 cells that overexpress DDAH1.

RESULTS

In the clinical study, plasma ADMA was not significantly associated with any measure of hyperglycemia. L-homoarginine was positively associated with glucose (β = 0.067, p = 0.018) and SHR (β = 0.107, p < 0.001) after correction for glomerular filtration rate. However, as L-homoarginine is a negative predictor of mortality, the direction of these associations are the opposite of those expected if hyperglycemia was affecting mortality via changes in L-homoarginine. In vitro DDAH1 activity was not significantly influenced by glucose concentrations (p = 0.506).

CONCLUSION

In critically ill patients the association between relative hyperglycemia and mortality is not mediated by changes in ADMA or L-homoarginine. Trial registration ANZCTR Trial ID ACTRN12615001164583.

The association between serum albumin and long length of stay of patients with acute heart failure: A retrospective study based on the MIMIC-IV database

BACKGROUND

The purpose of this article is to assess the relationship between serum albumin level and long length of stay (LOS) of inpatients with acute heart failure (AHF) in the intensive care unit (ICU).

METHODS

We retrospectively analyzed data of 2280 patients with AHF from the medical information mart for intensive care IV (the MIMIC-IV) database. Multivariate logistic regression was performed to evaluate the association between serum albumin and long LOS, and the development of the predictive model was based on independent predictors of long LOS.

RESULTS

According to the statistical results, A negative linear relationship was presented between albumin and long LOS of AHF patients in the ICU (P for trend <0.001), and serum albumin could predict long LOS (AUC 0.649, 95%CI 0.616-0.683, P <0.001). Based on independent predictors, including respiratory failure (OR 1.672, 95%CI 1.289-2.169, P<0.001), WBC (OR 1.046, 95%CI 1.031-1.061, P<0.001), creatinine (OR 1.221, 95%CI 1.098-1.257, P<0.001), glucose (OR 1.010, 95%CI 1.007-1.012, P<0.001), lactic acid (OR 1.269, 95%CI 1.167-1.381, P<0.001), and albumin (OR 0.559, 95%CI 0.450-0.695, P<0.001), identified by multivariable logistic regression analysis, we developed the nomogram to predict the probability of long LOS of AHF patients in the ICU. The nomogram accurately predicted the probability of long LOS (AUC 0.740, 95%CI 0.712-0.768, P<0.001). The calibration suggested the predictive probability was highly consistent with the actual probability of long LOS. Decision curve analysis (DCA) also suggested that the nomogram was applicable in the clinic.

CONCLUSION

Serum albumin level was negatively associated with LOS among AHF patients. The predictive model based on serum albumin has predictive value for evaluating the length of stay in AHF patients.

Association between the stress hyperglycemia ratio and severity of coronary artery disease under different glucose metabolic states

BACKGROUND

Stress hyperglycemia ratio (SHR) is significantly related to adverse cardiovascular clinical outcomes and increased in-hospital mortality. However, the relationship between SHR and coronary artery disease (CAD) severity has hitherto not been reported. This study sought to clarify the relationship between the SHR and CAD severity of individuals with different glucose metabolic statuses.

METHODS

A retrospective analysis was performed on 987 patients who underwent coronary angiography (CAG) from October 2020 to May 2022. Based on CAG results, patients were divided into single-vessel CAD and multi-vessel CAD groups. All subjects were stratified into three groups according to the tertiles of the SHR (T1 group: SHR < 0.930; T2 group: 0.930 ≤ SHR < 1.154; T3 group: 1.154 ≤ SHR). Moreover, according to glucose metabolism status, study subjects were divided into normal glucose regulation (NGR), pre-diabetes mellitus (pre-DM) and diabetes mellitus (DM) groups. Finally, the correlation between SHR and CAD severity was analyzed by logistic regression analysis and receiver operating characteristic (ROC) curve.

RESULTS

The results showed significantly higher SHR in the multi-vessel CAD group than in the single-vessel group. Logistic regression analysis showed that SHR was an independent risk factor for multi-vessel CAD when used as a continuous variable (OR, 4.047; 95% CI 2.137-7.663; P < 0.001). After adjusting for risk factors, the risk of multi-vessel CAD in the T2 and T3 groups was 1.939-fold (95% CI 1.341-2.804; P < 0.001) and 1.860-fold (95% CI 1.272-2.719; P = 0.001) higher than in the T1 group, respectively. The area under the curve (AUC) of ROC plots was 0.613 for SHR. In addition, SHR was significantly correlated with an increased risk of multi-vessel CAD in the pre-DM and DM groups.

CONCLUSIONS

Our study indicated that SHR was significantly correlated with the risk of multi-vessel CAD and predicted CAD severity, especially in pre-DM and DM patients.

The association between hemoglobin A1c and all-cause mortality in the ICU: A cross-section study based on MIMIC-IV 2.0

BACKGROUND

Hyperglycemia has been reported to be associated with the outcomes of patients in the intensive care unit (ICU). However, the relationship between hemoglobin A1c (HbA1c) and long-term or short-term mortality in the ICU is still unknown. This study used the Medical Information Mart for Intensive Care (MIMIC)-IV database to investigate the relationship between HbA1c and long-term or short-term mortality among ICU patients without a diabetes diagnosis.

METHODS

A total of 3,154 critically ill patients without a diabetes diagnosis who had HbA1c measurements were extracted and analyzed from the MIMIC-IV. The primary outcome was 1-year mortality, while the secondary outcomes were 30-day mortality and 90-day mortality after ICU discharge. HbA1c levels were classified into four levels according to three HbA1c values (5.0%, 5.7%, and 6.5%). The Cox regression model was used to investigate the relationship between the highest HbA1c measurement and mortality. Finally, this correlation was validated using the XGBoost machine learning model and Cox regression after propensity score matching (PSM).

RESULTS

The study eventually included 3,154 critically ill patients without diabetes who had HbA1c measurements in the database. HbA1c levels of below 5.0% or above 6.5% were significantly associated with 1-year mortality after adjusting for covariates in Cox regression (HR: 1.37; 95% CI: 1.02-1.84 or HR: 1.62; 95% CI: 1.20-2.18). In addition, HbA1c 6.5% was linked to 30-day mortality (HR: 1.81; 95% CI: 1.21-2.71) and 90-day mortality (HR: 1.62; 95% CI: 1.14-2.29). The restricted cubic spline demonstrated a U-shaped relationship between HbA1c levels and 1-year mortality. The AUCs of the training and testing datasets in the XGBoost model were 0.928 and 0.826, respectively, while the SHAP plot revealed that HbA1c was somewhat important for the 1-year mortality. Higher HbA1c levels in Cox regression were still significantly associated with 1-year mortality after PSM for other factors.

CONCLUSIONS

The 1-year mortality, 30-day mortality, and 90-day mortality rates for critically ill patients after discharge from ICU are significantly associated with HbA1c. HbA1c < 5.0% and ≥6.5% would increase 30-day, 90-day, and 1-year mortality, while levels between 5.0% and 6.5% of HbA1c did not significantly affect these outcomes.

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.

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.

Control of blood glucose levels by an artificial pancreas in patients with severe coronavirus disease 2019 pneumonia

BACKGROUND

Many patients with severe coronavirus disease 2019 (COVID-19) pneumonia experience hyperglycemia. It is often difficult to control blood glucose (BG) levels in such patients using standard intravenous insulin infusion therapy. Therefore, we used an artificial pancreas. This study aimed to compare the BG status of the artificial pancreas with that of standard therapy.

METHODS

Fifteen patients were included in the study. BG values and the infusion speed of insulin and glucose by the artificial pancreas were collected. Arterial BG and administration rates of insulin, parenteral sugar, and enteral sugar were recorded during the artificial pancreas and standard therapy. The target BG level was 200 mg/dl.

RESULTS

Arterial BG was highly correlated with BG data from the artificial pancreas. A higher BG slightly increased the difference between the BG data from the artificial pancreas and arterial BS. No significant difference in arterial BG was observed between the artificial pancreas and standard therapy. However, the standard deviation with the artificial pancreas was smaller than that under standard therapy (p < 0.0001). More points within the target BG range were achieved with the artificial pancreas (180-220 mg/dl) than under standard therapy. The hyperglycemic index of the artificial pancreas (8.7 ± 15.6 mg/dl) was lower than that of standard therapy (16.0 ± 21.5 mg/dl) (p = 0.0387). No incidence of hypoglycemia occurred under the artificial pancreas.

CONCLUSIONS

The rate of achieving target BG was higher using artificial pancreas than with standard therapy. An artificial pancreas helps to control BG in critically ill patients.

Quantification of stress-induced hyperglycaemia associated with key diagnostic categories using the stress hyperglycaemia ratio

AIM

Stress-induced hyperglycaemia (SIH) is the acute increase from preadmission glycaemia and is associated with poor outcomes. Early recognition of SIH and subsequent blood glucose (BG) management improves outcomes, but the degree of SIH provoked by distinct diagnostic categories remains unknown. Quantification of SIH is now possible using the stress hyperglycaemia ratio (SHR), which measures the proportional change from preadmission glycaemia, based on haemoglobin A_1c (HbA_1c ).

METHODS

We identified eligible patients for eight medical (n = 892) and eight surgical (n = 347) categories. Maximum BG from the first 24 h of admission for medical, or postoperatively for surgical patients was used to calculate SHR.

RESULTS

Analysis of variance indicated differing SHR and BG within both the medical (p < 0.0001 for both) and surgical cohort (p < 0.0001 for both). Diagnostic categories were associated with signature levels of SHR that varied between groups. Medically, SHR was greatest for ST-elevation myocardial infarction (1.22 ± 0.33) and sepsis (1.37 ± 0.43). Surgically, SHR was greatest for colectomy (1.62 ± 0.48) and cardiac surgeries (coronary artery graft 1.56 ± 0.43, aortic valve replacement 1.71 ± 0.33, and mitral valve replacement 1.75 ± 0.34). SHR values remained independent of HbA_1c , with no difference for those with HbA_1c above or below 6.5% (p > 0.11 for each). BG however was highly dependent on HbA_1c , invariably elevated in those with HbA_1c  ≥ 6.5% (p < 0.001 for each), and unreliably reflected SIH.

CONCLUSION

The acute stress response associated with various medical and surgical categories is associated with signature levels of SIH. Those with higher expected SHR are more likely to benefit from early SIH management, especially major surgery, which induced SIH typically 40% greater than medical cohorts. SHR equally recognised the acute change in BG from baseline across the full HbA_1c spectrum while BG did not and poorly reflected SIH.

Is it time to personalise glucose targets during critical illness?

PURPOSE OF REVIEW

Dysglycaemia complicates most critical care admissions and is associated with harm, yet glucose targets, particularly in those with preexisting diabetes, remain controversial. This review will summarise advances in the literature regarding personalised glucose targets in the critically ill.

RECENT FINDINGS

Observational data suggest that the degree of chronic hyperglycaemia in critically ill patients with diabetes attenuates the relationship between mortality and several metrics of dysglycaemia, including blood glucose on admission, and mean blood glucose, glycaemic variability and hypoglycaemia in the intensive care unit. The interaction between acute and chronic hyperglycaemia has recently been quantified with novel metrics of relative glycaemia including the glycaemic gap and stress hyperglycaemia ratio. Small pilot studies provided preliminary data that higher blood glucose thresholds in critically ill patients with chronic hyperglycaemia may reduce complications of intravenous insulin therapy as assessed with biomakers. Although personalising glycaemic targets based on preexisting metabolic state is an appealing concept, the recently published CONTROLLING trial did not identify a mortality benefit with individualised glucose targets, and the effect of personalised glucose targets on patient-centred outcomes remains unknown.

SUMMARY

There is inadequate data to support adoption of personalised glucose targets into care of critically ill patients. However, there is a strong rationale empowering future trials utilising such an approach for patients with chronic hyperglycaemia.

Influence of Optimal Management of Hyperglycemia and Intensive Nursing on Blood Glucose Control Level and Complications in Patients with Postoperative Cerebral Hemorrhage

Background

Cerebral hemorrhage, also known as hemorrhagic stroke, is a common clinical cerebrovascular disease, accounting for about 10%-30% of stroke, with high morbidity and mortality.

Objective

To observe the effect of optimal management of hyperglycemia and intensive nursing on blood glucose control level and complications in patients with postoperative cerebral hemorrhage.

Methods

One hundred and eight patients with postoperative cerebral hemorrhage comorbid with stress hyperglycemia admitted to our neurosurgery department from February 2019 to February 2022 were selected and divided into a general group of 54 cases and an optimized group of 54 cases by simple random method. The general group was managed with conventional care, while the optimized group developed optimized management of hyperglycemia for intensive care. The indexes related to blood glucose control, electrolytes, National Institutes of Health Stroke Scale (NIHSS) scores, Barthel Index (BI) scores, and time to achieve blood glucose standard, insulin pumping time, patient satisfaction, and prognosis were compared between the two groups.

Results

Before intervention, there was no statistical significance in the comparison of blood glucose control-related indicators and electrolytes between the two groups (P > 0.05). After 7 d and 14 d of intervention, the fasting blood glucose and 2 h postprandial blood glucose in the two groups were lower than before, while K+ and Na+ were higher than before (P < 0.05). The blood glucose indexes at the same time point in the optimized group were found to be lower than those in the general group by statistical analysis, but electrolytes were not statistically significant when compared with the general group (P > 0.05). In the optimized group, the time to achieve blood glucose standard (6.59 ± 1.94) d and insulin pumping time (7.14 ± 1.89) d were shorter than those in the general group [(7.48 ± 2.12) d and (8.58 ± 2.14) d], insulin dosage (748.85 ± 63.61) U was less than that in the general group (923.54 ± 84.14) U, and the incidence of hypoglycemia (3.70%) was lower than that in the general group (16.67%), and the satisfaction rate (92.59%) was higher than that of the general group (77.78%), which was statistically significant (P < 0.05). Before intervention, there was no significant difference in NIHSS score and BI score between the two groups (P > 0.05). After 7 d and 14 d of intervention, the NIHSS scores of the two groups were lower than before, while the BI scores were higher than before, and the NIHSS scores of the optimized group at the same time point were all lower than those of the general group, and the BI scores were higher than those of the general group (P < 0.05). The incidence of pulmonary infection (11.11%) and rebleeding (7.41%) in the optimized group were lower than those in the general group (25.93% and 22.22%), while deep vein thrombosis, multiple organ dysfunction syndrome (MODS), and death within 28 d was not statistically significant when compared with the general group (P > 0.05).

Conclusion

Optimal management of hyperglycemia and intensive nursing can effectively control the blood sugar level of patients after cerebral hemorrhage, reducing insulin dosage, and the occurrence of hypoglycemia, pulmonary infection, and rebleeding.

Association between time in range of relative normoglycemia and in-hospital mortality in critically ill patients: a single-center retrospective study

The aim of this single-center retrospective study was to investigate the association between the time in range (TIR) of relative normoglycemia (RN) and in-hospital mortality. We defined RN as measured blood glucose in the range of 70–140% of A1C-derived average glucose and absolute normoglycemia (AN) as 70–140 mg/dL. We conducted multivariate logistic regression analyses to examine the association between TIR of RN > 80% or TIR of AN > 80% up to 72 h after ICU admission and in-hospital mortality (Model 1 and Model 2, respectively). The discrimination of the models was assessed using the area under the receiver operating characteristic curve (AUROC). Among 328 patients, 35 died in hospital (11%). Model 1 showed that TIR of RN > 80% was associated with reduced in-hospital mortality (adjusted OR 0.16; 95% CI 0.06–0.43; P < 0. 001); however, Model 2 showed that the TIR of AN > 80% was not. The AUROC of Model 1 was significantly higher than that of Model 2 (0.84 [95% CI 0.77–0.90] vs. 0.79 [0.70–0.87], P = 0.008).Our findings provide a foundation for further studies exploring individualized glycemic management in ICUs.

Association between stress hyperglycemia on admission and unfavorable neurological outcome in OHCA patients receiving ECPR

BACKGROUND

Stress hyperglycemia is a normal response to stress and has been associated with outcomes in out-of-hospital cardiac arrest (OHCA) patients. However, this association remained unknown in OHCA patients receiving extracorporeal cardiopulmonary resuscitation (ECPR). This study aimed to examine the association between degree of stress hyperglycemia on admission and neurological outcomes at discharge in OHCA patients receiving ECPR.

PATIENTS AND METHODS

This was a retrospective cohort study of adult OHCA patients receiving ECPR between 2011 and 2021. Patients were classified into three groups: absence of stress hyperglycemia (blood glucose level on admission < 200 mg/dL), moderate stress hyperglycemia (200-299 mg/dL), and severe stress hyperglycemia (≥ 300 mg/dL). The primary outcome was unfavorable neurological outcome (Cerebral Performance Category: 3-5) at discharge.

RESULTS

This study included 160 patients; unfavorable neurological outcomes totaled 79.4% (n = 127). There were 23, 52, and 85 patients in the absence, moderate, and severe stress hyperglycemia groups, respectively. Of each group, unfavorable neurological outcomes constituted 91.3%, 71.2%, and 81.2%, respectively. Multivariable analysis showed that, compared with moderate stress hyperglycemia, absence of stress hyperglycemia on admission was significantly associated with unfavorable neurological outcome at discharge (odds ratio [OR], 4.70; 95% confidence interval [CI], 1.07-33.35; p = 0.039).

CONCLUSION

Compared with moderate stress hyperglycemia on admission, absence of stress hyperglycemia showed significant association with unfavorable neurological outcome at discharge in OHCA patients receiving ECPR.

The Role of the Diabetes Care and Education Specialist in the Hospital Setting

It is the position of Association of Diabetes Care & Education Specialists that all inpatient interdisciplinary teams include a diabetes care and education specialist to lead or support quality improvement initiatives that affect persons hospitalized with diabetes and/or hyperglycemia. This encompasses not only patient, family, and caregiver education but also education of interdisciplinary team members and achievement of diabetes-related organizational quality metrics and performance outcomes.

Association between stress hyperglycemia ratio and delirium in older hospitalized patients: a cohort study

Background

It remains unclear whether stress hyperglycemia is associated with delirium. We performed this cohort study to determine the association between stress hyperglycemia and delirium.

Methods

We consecutively enrolled patients aged ≥70 years who were admitted to the Geriatric Department of West China Hospital between March 2016 and July 2017. Stress hyperglycemia ratio (SHR) was calculated as fasting blood glucose divided by estimated average glucose derived from glycosylated hemoglobin (HbA1c) and was classified into three tertiles. Delirium was screened within 24 h of admission and three times daily thereafter, using the confusion assessment method. The Cox proportional hazards models were used to assess the association of SHR with delirium.

Results

Among 487 included patients (mean age 83.0 years, 72.0% male), 50 (10.3%) patients experienced delirium during hospitalization. Compared to the second tertile, both the lowest and the highest SHR tertiles were independently associated with delirium (hazard ratio [HR] 3.71, 95% confidence interval [CI] 1.45-9.51; and HR 2.97, 95% CI 1.29-6.81, respectively). Similar results were found after further adjusting for statin comedication. Multiple-adjusted restricted cubic splines revealed a nonlinear relationship between SHR and delirium (P_nonlinearity=0.04). Adding SHR to conventional risk factors improved the risk prediction of delirium (net reclassification index 0.39, P=0.01; integrated discrimination improvement 0.07, P=0.03). Subgroup analyses indicated that the relationship between SHR and delirium was more apparent in patients with HbA1c <6.5%, with significantly higher HR in the first (3.65, 95% CI 1.11-11.97) and third (3.13, 95% CI 1.13-8.72) SHR tertiles compared to the second tertile, while there was no significant association between SHR and delirium in those with HbA1c ≥6.5%.

Conclusions

Both lower and higher SHR were associated with increased risk of delirium but only in patients with HbA1c <6.5%. Admission SHR may serve as a promising predictor of delirium, and incorporating this biomarker into prediction algorithms might have potential clinical utility in aiding delirium risk stratification, especially in those with HbA1c <6.5%.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02935-6.

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.

Association of Stress Hyperglycemia Ratio With Acute Ischemic Stroke Outcomes Post-thrombolysis

Background and Purpose: The association between stress hyperglycemia and clinical outcomes in patients with acute ischemic stroke treated with intravenous thrombolysis (IVT) is uncertain. We sought to analyze the association between the stress hyperglycemia ratio (SHR) using different definitions and clinical outcomes in acute patients with ischemic stroke undergoing IVT.

Methods: A total of 341 patients with ischemic stroke receiving IVT were prospectively enrolled in this study. The SHR was evaluated using different equations: SHR1, fasting glucose (mmol/L)/glycated hemoglobin (HbA1c) (%); SHR2, fasting glucose (mmol/L)/[(1.59 × HbA1c)−2.59]; SHR3, admission blood glucose (mmol/L)/[(1.59 × HbA1c)−2.59]. A poor functional outcome was defined as a modified Rankin scale score of 3–6 at 3 months. Multivariate logistic regression analysis was used to identify the relationship between different SHRs and clinical outcomes after IVT.

Results: A total of 127 (37.2%) patients presented with poor functional outcomes at 3 months. The predictive value of SHR1 for poor functional outcomes was better than that of SHR2 and SHR3 in receiver operating characteristic analyses. On multivariate analysis, SHR1 [odds ratio (OR) 14.639, 95% CI, 4.075–52.589; P = 0.000] and SHR2 (OR, 19.700; 95% CI; 4.475–86.722; P = 0.000) were independently associated with an increased risk of poor functional outcome but not SHR3.

Conclusions: Our study confirmed that the SHR, as measured by SHR1 and SHR2, is independently associated with worse clinical outcomes in patients with ischemic stroke after intravenous thrombolysis. Furthermore, SHR1 has a better predictive performance for outcomes than other SHR definitions.

Stress hyperglycemia is associated with in-hospital mortality in patients with diabetes and acute ischemic stroke

Background and Objective

Stress hyperglycemia may occur in diabetic patients with acute severe cerebrovascular disease, but the results regarding its association with stroke outcomes are conflicting. This study aimed to examine the association between stress‐induced hyperglycemia and the occurrence of in‐hospital death in patients with diabetes and acute ischemic stroke.

Research Design and Methods

All data were from the Chinese Stroke Center Alliance (CSCA) database and were collected between 2016 and 2018 from >300 centers across China. Patients’ demographics, clinical presentation, and laboratory data were extracted from the database. The primary endpoint was in‐hospital death. The ratio of fasting blood glucose (FBG) to HbA1c was calculated, that is, the stress‐induced hyperglycemia ratio (SHR), to determine stress hyperglycemia following acute ischemic stroke.

Results

A total of 168,381 patients were included. The mean age was 66.2 ± 10.7, and 77,688 (43.0%) patients were female. The patients were divided into two groups: survivors (n = 167,499) and non‐survivors (n = 882), as well as into four groups according to their SHR quartiles (n = 42,090–42,099/quartile). There were 109 (0.26%), 142 (0.34%), 196 (0.47%), and 435 (1.03%) patients who died in the Q1, Q2, Q3, and Q4 quartiles, respectively. Compared with Q1 patients, the death risk was higher in Q4 patients (odds ratio (OR) = 4.02) (adjusted OR = 1.80, 95% confidence interval [CI] = 1.10–2.92, p = 0.018 after adjustment for traditional cardiovascular risk factors). The ROC analyses showed that SHR (AUC = 0.667, 95% CI: 0.647–0.686) had a better predictive value for mortality than that of fasting blood glucose (AUC = 0.633, 95% CI: 0.613–0.652) and HbA1c (AUC = 0.523, 95% CI: 0.504–0.543).

Conclusions

The SHR may serve as an accessory parameter for the prognosis of patients with diabetes after acute ischemic stroke. Hyperglycemia in stroke patients with diabetes mellitus is associated with a higher risk of in‐hospital death.

Comparison of two glucose-monitoring systems for use in horses

OBJECTIVE

To determine the accuracy of 2 interstitial glucose-monitoring systems (GMSs) for use in horses compared with a point-of-care (POC) glucometer and standard laboratory enzymatic chemistry method (CHEM).

ANIMALS

8 clinically normal adult horses.

PROCEDURES

One of each GMS device (Dexcom G6 and Freestyle Libre 14-day) was placed on each horse, and blood glucose concentration was measured via POC and CHEM at 33 time points and compared with simultaneous GMS readings. An oral glucose absorption test (OGAT) was performed on day 2, and glucose concentrations were measured and compared.

RESULTS

Glucose concentrations were significantly correlated with one another between all devices on days 1 to 5. Acceptable agreement was observed between Dexcom G6 and Freestyle Libre 14-day when compared with CHEM on days 1, 3, 4, and 5 with a combined mean bias of 10.45 mg/dL and 1.53 mg/dL, respectively. During dextrose-induced hyperglycemia on day 2, mean bias values for Dexcom G6 (10.49 mg/dL) and FreeStyle Libre 14-day (0.34 mg/dL) showed good agreement with CHEM.

CLINICAL RELEVANCE

Serial blood glucose measurements are used to diagnose or monitor a variety of conditions in equine medicine; advances in near-continuous interstitial glucose monitoring allow for minimally invasive glucose assessment, thereby reducing stress and discomfort to patients. Data from this study support the use of the Dexcom G6 and Freestyle Libre 14-day interstitial glucose-monitoring systems to estimate blood glucose concentrations in horses.

A comparison of the stress hyperglycemia ratio, glycemic gap, and glucose to assess the impact of stress-induced hyperglycemia on ischemic stroke outcome

BACKGROUND

The aim of this study is to compare metrics specific for stress-induced hyperglycemia (SIH) with glucose for predicting ischemic stroke outcome.

METHODS

This observational retrospective study (n = 300) included patients acutely hospitalized for ischemic stroke over a 3.8-year period. We assessed the association between acute ischemic stroke outcome with the stress hyperglycemia ratio (SHR, relative increase in glycemia) and glycemic gap (GG, absolute increase in glycemia) using admission values and 5-day maximum values, along with incidence of poor outcome above recognized clinical thresholds of glucose 10 mmol/L, SHR 1.14, and GG 2.5 mmol/L.

RESULTS

At admission, only SHR was associated with outcome after adjustment for clinical covariates (odds ratio [OR] = 2.88; 95% CI: 1.05-7.91; P = .041), while glucose or GG were not. Admission SHR ≥ 1.14 was also an indicator of poor outcome (39.1% vs 23.4%, P = .016), but not glucose ≥10 mmol/L or GG ≥ 2.5 mmol/L. All 5-day maximum glucose metrics were associated with outcome, as was any SHR ≥ 1.14 (40.9% vs 20.1%, P < .001) or GG ≥ 2.5 mmol/L (42.9% vs 23.4%, P = .011), but not glucose ≥10 mmol/L. Increased comorbidity was strongly associated with worse outcome (P < .001) in all models.

CONCLUSIONS

SHR provided the best prognostic insight at admission to assess the relationship between SIH and ischemic stroke outcome. Absolute glucose levels failed to account for natural interpatient variation in background glycemia and provided little prognostic insight. To assess the impact of SIH, future interventional studies need to be designed using designated markers of SIH such as SHR in preference to absolute glucose.

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.

Development and Validation of a Simple-to-Use Nomogram for Predicting In-Hospital Mortality in Patients With Acute Heart Failure Undergoing Continuous Renal Replacement Therapy

Background: Patients with acute heart failure (AHF) who require continuous renal replacement therapy (CRRT) have a high risk of in-hospital mortality. It is clinically important to screen high-risk patients using a model or scoring system. This study aimed to develop and validate a simple-to-use nomogram consisting of independent prognostic variables for the prediction of in-hospital mortality in patients with AHF undergoing CRRT.

Methods: We collected clinical data for 121 patients with a diagnosis of AHF who underwent CRRT in an AHF unit between September 2011 and August 2020 and from 105 patients in the medical information mart for intensive care III (MIMIC-III) database. The nomogram model was created using a visual processing logistic regression model and verified using the standard method.

Results: Patient age, days after admission, lactic acid level, blood glucose concentration, and diastolic blood pressure were the significant prognostic factors in the logistic regression analyses and were included in our model (named D-GLAD) as predictors. The resulting model containing the above-mentioned five factors had good discrimination ability in both the training group (C-index, 0.829) and the validation group (C-index, 0.740). The calibration and clinical effectiveness showed the nomogram to be accurate for the prediction of in-hospital mortality in both the training and validation cohort when compared with other models. The in-hospital mortality rates in the low-risk, moderate-risk, and high-risk groups were 14.46, 40.74, and 71.91%, respectively.

Conclusion: The nomogram allowed the optimal prediction of in-hospital mortality in adults with AHF undergoing CRRT. Using this simple-to-use model, the in-hospital mortality risk can be determined for an individual patient and could be useful for the early identification of high-risk patients. An online version of the D-GLAD model can be accessed at https://ahfcrrt-d-glad.shinyapps.io/DynNomapp/.

Clinical Trial Registration:www.ClinicalTrials.gov, identifier: NCT0751838.

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.

Birkenfeld A, Sponholz C, A. Müller U, von Loeffelholz C. Blood Sugar Targets in Surgical Intensive Care—Management and Special Considerations in Patients With Diabetes

BACKGROUND

30-80% of patients being treated in intensive care units in the perioperative period develop hyperglycemia. This stress hyperglycemia is induced and maintained by inflammatory-endocrine and iatrogenic stimuli and generally requires treatment. There is uncertainty regarding the optimal blood glucose targets for patients with diabetes mellitus.

METHODS

This review is based on pertinent publications retrieved by a selective search in PubMed and Google Scholar.

RESULTS

Patients in intensive care with pre-existing diabetes do not benefit from blood sugar reduction to the same extent as metabolically healthy individuals, but they, too, are exposed to a clinically relevant risk of hypoglycemia. A therapeutic range from 4.4 to 6.1 mmol/L (79-110 mg/dL) cannot be justified for patients with diabetes mellitus. The primary therapeutic strategy in the perioperative setting should be to strictly avoid hypoglycemia. Neurotoxic effects and the promotion of wound-healing disturbances are among the adverse consequences of hyperglycemia. Meta-analyses have shown that an upper blood sugar limit of 10 mmol/L (180 mg/dL) is associated with better outcomes for diabetic patients than an upper limit of less than this value. The target range of 7.8-10 mmol/L (140-180 mg/dL) proposed by specialty societies for hospitalized patients with diabetes seems to be the best compromise at present for optimizing clinical outcomes while avoiding hypoglycemia. The method of choice for achieving this goal in intensive care medicine is the continuous intravenous administration of insulin, requirng standardized, high-quality monitoring conditions.

CONCLUSION

Optimal blood sugar control for diabetic patients in intensive care meets the dual objectives of avoiding hypoglycemia while keeping the blood glucose concentration under 10 mmol/L (180 mg/dL). Nutrition therapy in accordance with the relevant guidelines is an indispensable pre - requisite.

Association Between Stress Hyperglycemia Ratio and In-hospital Outcomes in Elderly Patients With Acute Myocardial Infarction

Backgrounds: Emerging evidence suggests that stress hyperglycemia ratio (SHR), an index of relative stress hyperglycemia, is of great prognostic value in acute myocardial infarction (AMI), but current evidence is limited in elderly patients. In this study, we aimed to assess whether SHR is associated with in-hospital outcomes in elderly patients with AMI.

Methods: In this retrospective study, patients who were aged over 75 years and diagnosed with AMI were consecutively enrolled from 2015, January 1st to 2019, December 31th. Admission blood glucose and glycosylated hemoglobin (HbA1C) during the index hospitalization were used to calculate SHR. Restricted quadratic splines, receiver-operating curves, and logistic regression were performed to evaluate the association between SHR and in-hospital outcomes, including in-hospital all-cause death and in-hospital major adverse cardiac and cerebrovascular events (MACCEs) defined as a composite of all-cause death, cardiogenic shock, reinfarction, mechanical complications of MI, stroke, and major bleeding.

Results: A total of 341 subjects were included in this study. Higher SHR levels were observed in patients who had MACCEs (n = 69) or death (n = 44) during hospitalization. Compared with a SHR value below 1.25, a high SHR was independently associated with in-hospital MACCEs (odds ratio [OR]: 2.945, 95% confidence interval [CI]: 1.626–5.334, P < 0.001) and all-cause death (OR: 2.871 95% CI: 1.428–5.772, P = 0.003) in univariate and multivariate logisitic analysis. This relationship increased with SHR levels based on a non-linear dose-response curve. In contrast, admission glucose was only associated with clinical outcomes in univariate analysis. In subgroup analysis, high SHR was significantly predictive of worse in-hospital clinical outcomes in non-diabetic patients (MACCEs: 2.716 [1.281–5.762], P = 0.009; all-cause death: 2.394 [1.040–5.507], P = 0.040), but the association was not significant in diabetic patients.

Conclusion: SHR might serve as a simple and independent indicator of adverse in-hospital outcomes in elderly patients with AMI, especially in non-diabetic population.

The Interaction of Acute and Chronic Glycemia on the Relationship of Hyperglycemia, Hypoglycemia, and Glucose Variability to Mortality in the Critically Ill

OBJECTIVES

To determine the relationship between preadmission glycemia, reflected by hemoglobin A1c level, glucose metrics, and mortality in critically ill patients.

DESIGN

Retrospective cohort investigation.

SETTING

University affiliated adult medical-surgical ICU.

PATIENTS

The investigation included 5,567 critically ill patients with four or more blood glucose tests and hemoglobin A1c level admitted between October 11, 2011 and November 30, 2019. The target blood glucose level was 90-120 mg/dL for patients admitted before September 14, 2014 (n = 1,614) and 80-140 mg/dL or 110-160 mg/dL for patients with hemoglobin A1c less than 7% or greater than or equal to 7% (n = 3,953), respectively, subsequently.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Patients were stratified by hemoglobin A1c: less than 6.5.(n = 4,406), 6.5-7.9% (n = 711), and greater than or equal to 8.0% (n = 450). Increasing hemoglobin A1c levels were associated with significant increases in mean glycemia, glucose variability, as measured by coefficient of variation, and hypoglycemia (p for trend < 0.0001, < 0.0001, and 0.0010, respectively). Among patients with hemoglobin A1c less than 6.5%, mortality increased as mean glycemia increased; however, among patients with hemoglobin A1c greater than or equal to 8.0%, the opposite relationship was observed (p for trend < 0.0001 and 0.0027, respectively). Increasing glucose variability was independently associated with increasing mortality only among patients with hemoglobin A1c less than 6.5%. Hypoglycemia was independently associated with higher mortality among patients with hemoglobin A1c less than 6.5% and 6.5-7.9% but not among those with hemoglobin A1c greater than or equal to 8.0%. Mean blood glucose 140-180 and greater than or equal to 180 mg/dL were independently associated with higher mortality among patients with hemoglobin A1c less than 6.5% (p < 0.0001 for each). Among patients with hemoglobin A1c greater than or equal to 8.0% treated in the second era, mean blood glucose greater than or equal to 180 mg/dL was independently associated with decreased risk of mortality (p = 0.0358).

CONCLUSIONS

Preadmission glycemia, reflected by hemoglobin A1c obtained at the onset of ICU admission, has a significant effect on the relationship of ICU glycemia to mortality. The different responses to increasing mean glycemia support a personalized approach to glucose control practices in the ICU.

Effects of Stress Hyperglycemia on Short-Term Prognosis of Patients Without Diabetes Mellitus in Coronary Care Unit

Background: Diabetes mellitus (DM) has a high morbidity and mortality worldwide, and it is a risk factor for cardiovascular diseases. Non-diabetic stress hyperglycemia is common in severely ill patients, and it could affect prognosis. This study aimed to analyze the influence of different blood glucose levels on prognosis from the perspective of stress hyperglycemia by comparing them with normal blood glucose levels and those of patients with DM.

Methods: A retrospective study of 1,401 patients in coronary care unit (CCU) from the critical care database called Medical Information Mart for Intensive Care IV was performed. Patients were assigned to the following groups 1–4 based on their history of DM, random blood glucose, and HbA1c levels: normal blood glucose group, moderate stress hyperglycemia group, severe stress hyperglycemia group and DM group. The main outcome of this study was 30- and 90-day mortality rates. The associations between groups and outcomes were analyzed using Kaplan–Meier survival analysis, Cox proportional hazard regression model and competing risk regression model.

Results: A total of 1,401 patients in CCU were enrolled in this study. The Kaplan–Meier survival curve showed that group 1 had a higher survival probability than groups 3 and 4 in terms of 30- and 90-day mortalities. After controlling the potential confounders in Cox regression, groups 3 and 4 had a statistically significant higher risk of both mortalities than group 1, while no difference in mortality risk was found between groups 2 and 1. The hazard ratios [95% confidence interval (CI)] of 30- and 90-day mortality rates for group 3 were 2.77(1.39,5.54) and 2.59(1.31,5.12), respectively, while those for group 4 were 1.92(1.08,3.40) and 1.94(1.11,3.37), respectively.

Conclusions: Severe stress hyperglycemia (≥200 mg/dL) in patients without DM in CCU may increase the risk of short-term death, which is greater than the prognostic effect in patients with diabetes. Patients with normal blood glucose levels and moderate stress hyperglycemia (140 mg/dL ≤ RBG <200 mg/dL) had no effect on short-term outcomes in patients with CCU.

A single arm trial using passive simulated jogging for blunting acute hyperglycemia

Glycemic fluctuations increase oxidative stress, promote endothelial dysfunction and cardiovascular disease. Reducing glycemic fluctuations is beneficial. We previously reported that a portable motorized passive simulated jogging device, (JD) reduces 24 h glycemic indices in type 2 and non-diabetic subjects. This study evaluates effectiveness and feasibility of JD in blunting large glycemic fluctuation induced by an oral glucose tolerance test (OGTT). The study was performed in 10 adult participants mean age 41.3 ± 13.5 year using interstitial glucose monitor (IG). Each participant fasted for 8 h. followed by an OGTT (Pre-JD), thereafter JD was used for 90 min per day for 7 days, without change to diet or activities of daily living. A repeat OGTT (Post-JD) was performed after completion. The integrated area under the curve (iAUC_2h–4h) was computed for the OGTT Pre-JD and Post-JD. Seven days of JD blunted the glucose fluctuation produced by OGTT. JD decreased AUC_2h by 17 ± 4.7% and iAUC_4h by 15 ± 5.9% (p < 0.03). In healthy mostly obese participants 7 days of JD blunts the hyperglycemic response produced by an OGTT. JD may be an adjunct to current glycemic management, it can be applied in different postures for those who cannot (due to physical or cognitive limitations) or will not exercise.

Trial registration:ClinicalTrials.gov NCT03550105 (08-06-2018).

Systemic Corticosteroids and Mortality in Severe and Critical COVID-19 Patients in Wuhan, China

BACKGROUND

Systemic corticosteroids are now recommended in many treatment guidelines, although supporting evidence is limited to 1 randomized controlled clinical trial (RECOVERY).

OBJECTIVE

To identify whether corticosteroids were beneficial to COVID-19 patients.

METHODS

A total of 1514 severe and 249 critical hospitalized COVID-19 patients from 2 medical centers in Wuhan, China. Multivariable Cox models, Cox model with time-varying exposure and propensity score analysis (inverse-probability-of-treatment-weighting [IPTW] and propensity score matching [PSM]) were used to estimate the association of corticosteroid use with risk of in-hospital mortality in severe and critical cases.

RESULTS

Corticosteroids were administered in 531 (35.1%) severe and 159 (63.9%) critical patients. Compared to the non-corticosteroid group, systemic corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality in either severe cases (HR = 1.77; 95% CI, 1.08-2.89; P = 0.023), or critical cases (HR = 2.07; 95% CI, 1.08-3.98; P = 0.028). Findings were similar in time-varying Cox analysis. For patients with severe COVID-19 at admission, corticosteroid use was not associated with improved or harmful outcome in either PSM or IPTW analysis. For critical COVID-19 patients at admission, results were consistent with multivariable Cox model analysis.

CONCLUSION

Corticosteroid use was not associated with beneficial effect in reducing in-hospital mortality for severe or critical cases in Wuhan. Absence of the beneficial effect in our study in contrast to that observed in the RECOVERY clinical trial may be due to biases in observational data, in particular prescription by indication bias, differences in clinical characteristics of patients, choice of corticosteroid used, timing of initiation of treatment, and duration of treatment.

Insufficient hyperfibrinolysis in COVID-19: a systematic review of thrombolysis based on meta-analysis and meta-regression

Background How aberrant fibrinolysis influences the clinical progression of COVID-19 presents a clinicopathological dilemma challenging intensivists. To investigate whether abnormal fibrinolysis is a culprit or protector or both, we associated elevated plasma D-dimer with clinical variables to identify a panoramic view of the derangements of fibrinolysis that contribute to the pathogenesis of COVID-19 based on studies available in the literature. Methods We performed this systematic review based on both meta-analysis and meta-regression to compute the correlation of D-dimer at admission with clinical features of COVID-19 patients in retrospective studies or case series. We searched the databases until Aug 18, 2020, with no limitations by language. The first hits were screened, data extracted, and analyzed in duplicate. We did the random-effects meta-analyses and meta-regressions (both univariate and multivariate). D-dimer associated clinical variables and potential mechanisms were schematically reasoned and graphed. Findings Our search identified 42 observational, or retrospective, or case series from six countries (n=14,862 patients) with all races and ages from 1 to 98-year-old. The weighted mean difference of D-dimer was 0.97 μg/mL (95% CI 0.65, 1.29) between relatively mild (or healthy control) and severely affected groups with significant publication bias. Univariate meta-regression identified 58 of 106 clinical variables were associated with plasma D-dimer levels, including 3 demographics, 5 comorbidies, 22 laboratory tests, 18 organ injury biomarkers, 8 severe complications, and 2 outcomes (discharge and death). Of these, 11 readouts were negatively associated with the level of plasma D-dimer. Further, age and gender were confounding factors for the identified D-dimer associated variables. There were 22 variables independently correlated with the D-dimer level, including respiratory rate, dyspnea plasma K+, glucose, SpO2, BUN, bilirubin, ALT, AST, systolic blood pressure, and CK. We thus propose that "insufficient hyperfibrinolysis (fibrinolysis is accelerated but unable to prevent adverse clinical impact for clinical deterioration COVID-19)" as a peculiar mechanism. Interpretation The findings of this meta-analysis- and meta-regression-based systematic review supports elevated D-dimer as an independent predictor for mortality and severe complications. D-dimer-associated clinical variables draw a landscape integrating the aggregate effects of systemically suppressive and locally (i.e., in the lung) hyperactive derangements of fibrinolysis. D-dimer and associated clinical biomarkers and conceptually parameters could be combined for risk stratification, potentially for tracking thrombolytic therapy or alternative interventions.

Mortality Predictors and Associated Factors in Patients in the Intensive Care Unit: A Cross-Sectional Study

BACKGROUND

Mortality in the intensive care unit (ICU) has been associated to an array of risk factors. Identification of risk factors potentially contribute to predict and reduce mortality rates in the ICU. The objectives of the study were to determine the prevalence and the factors associated with the mortality and to analyze the survival.

METHOD

A cross-sectional study conducted in two clinical and surgical ICU in the state of Sergipe, northeastern Brazil. We enrolled 316 patients with at least 48 h of hospitalization, minimum age of 18 years old, sedated or weaned, with RASS ≥ -3, between July 2017 and April 2018. We categorized data in (1) age and gender, (2) clinical condition, and (3) prevalence of delirium. Data from enrolled patients were collected from enrollment until death or ICU discharge. Patients' outcomes were categorized in (1) death and (2) nondeath (discharge).

RESULTS

Twenty-one percent of participants died. Age (53 ± 17 years vs. 45 ± 18 years, p < 0.01), electrolyte disturbance (30.3% vs 18.1%, p=0.029), glycemic index (33.3% vs 18.2%, p=0.008), tube feeding (83.3% vs 67.1%, p=0.01), mechanical ventilation (50% vs 35.7%, p=0.035), sedation with fentanyl (24.2 vs 13.6, p=0.035), use of insulin (33.8% vs 21.7%, p=0.042), and higher Charlson score (2.61 vs 2.17, p=0.041) were significantly associated with death on the adjusted model. However, the regression model indicated that patients admitted from the emergency (HR = 0.40, p=0.006) and glycemic index alterations (HR = 1.68, p=0.047) were associated with mortality. There was no statistically significant difference (p=0.540) in survival between patients with and without delirium, based on the survival analysis and length of hospitalization.

CONCLUSION

The prevalence of death was 21%, and age, electrolyte disturbance, glycemic index, tube feeding, mechanical ventilation, sedation with fentanyl, use of insulin, and higher Charlson score were associated with mortality.

Stress Hyperglycemia and Mortality in Subjects With Diabetes and Sepsis

Objectives:

Poor glycemic control is associated with mortality in critical patients with diabetes. The aim of the study was to assess the predicting value of stress hyperglycemia in patients with diabetes following hospital admission for sepsis.

Design:

Retrospective observational study.

Setting:

Adult, emergency department, and critical care in a district hospital.

Patients:

In a 10-year retrospective analysis of sepsis-related hospitalizations in the emergency department, we carried out a secondary analysis of 915 patients with diabetes (males, 54.0%) in whom both fasting glucose at entry and glycosylated hemoglobin were available.

Interventions:

None.

Measurements and Main Results:

Patients’ mean age was 79.0 (sd 11.0), glucose at admission was 174.0 mg/dL (74.3 mg/dL), and glycosylated hemoglobin was 7.7% (1.7%). Stress hyperglycemia was defined by the stress hyperglycemia ratio, that is, fasting glucose concentration at admission divided by the estimated average glucose derived from glycosylated hemoglobin. A total of 305 patients died (33.3%) in hospital. Factors associated with in-hospital case fatality rate were tested by multivariable logistic model. Ten variables predicting outcomes in the general population were confirmed in the presence of diabetes (male sex, older age, number of organ dysfunction diagnoses, in particular cardiovascular dysfunction, infection/parasitic, circulatory, respiratory, digestive diseases diagnosis, and Charlson Comorbidity Index). In addition, also glycemic control (glycosylated hemoglobin: odds ratio, 1.17; 95% CI, 1.15–1.40) and stress hyperglycemia (stress hyperglycemia ratio: 5.25; 3.62–7.63) were significant case fatality rate predictors. High stress hyperglycemia ratio (≥ 1.14) significantly increased the discriminant capacity (area under the receiver operating characteristic curve, 0.864; se, 0.013; p < 0.001).

Conclusions:

Stress hyperglycemia, even in the presence of diabetes, is predictive of mortality following admission for sepsis. Stress hyperglycemia ratio may be used to refine prediction of an unfavorable outcome.

Elevation of blood glucose level predicts worse outcomes in hospitalized patients with COVID-19: a retrospective cohort study

INTRODUCTION

With intense deficiency of medical resources during COVID-19 pandemic, risk stratification is of strategic importance. Blood glucose level is an important risk factor for the prognosis of infection and critically ill patients. We aimed to investigate the prognostic value of blood glucose level in patients with COVID-19.

RESEARCH DESIGN AND METHODS

We collected clinical and survival information of 2041 consecutive hospitalized patients with COVID-19 from two medical centers in Wuhan. Patients without available blood glucose level were excluded. We performed multivariable Cox regression to calculate HRs of blood glucose-associated indexes for the risk of progression to critical cases/mortality among non-critical cases, as well as in-hospital mortality in critical cases. Sensitivity analysis were conducted in patient without diabetes.

RESULTS

Elevation of admission blood glucose level was an independent risk factor for progression to critical cases/death among non-critical cases (HR=1.30, 95% CI 1.03 to 1.63, p=0.026). Elevation of initial blood glucose level of critical diagnosis was an independent risk factor for in-hospital mortality in critical cases (HR=1.84, 95% CI 1.14 to 2.98, p=0.013). Higher median glucose level during hospital stay or after critical diagnosis (≥6.1 mmol/L) was independently associated with increased risks of progression to critical cases/death among non-critical cases, as well as in-hospital mortality in critical cases. Above results were consistent in the sensitivity analysis in patients without diabetes.

CONCLUSIONS

Elevation of blood glucose level predicted worse outcomes in hospitalized patients with COVID-19. Our findings may provide a simple and practical way to risk stratify COVID-19 inpatients for hierarchical management, particularly where medical resources are in severe shortage during the pandemic.