Compromised cardiac autonomic function in non-diabetic subjects with 1 h post-load hyperglycemia: a cross-sectional study.

BACKGROUND: A compromised cardiac autonomic function has been found in subjects with insulin resistance related disorders such as obesity, impaired glucose tolerance (IGT) and type 2 diabetes and confers an increased risk of adverse cardiovascular outcomes. Growing evidence indicate that 1 h plasma glucose levels (1hPG) during an oral glucose tolerance test (OGTT) ≥ 155 mg/dl identify amongst subjects with normal glucose tolerance (NGT) a new category of prediabetes (NGT 1 h-high), harboring an increased risk of cardiovascular organ damage. In this study we explored the relationship between 1 h post-load hyperglycemia and cardiac autonomic dysfunction. METHODS: Presence of cardiac autonomic neuropathy (CAN) defined by cardiovascular autonomic reflex tests (CARTs) and heart rate variability (HRV), assessed by 24-h electrocardiography were evaluated in 88 non-diabetic subjects subdivided on the basis of OGTT data in: NGT with 1 h PG < 155 mg/dl (NGT 1 h-low), NGT 1 h-high and IGT. RESULTS: As compared to subjects with NGT 1 h-low, those with NGT 1 h-high and IGT were more likely to have CARTs defined CAN and reduced values of the 24 h time domain HVR parameters including standard deviation of all normal heart cycles (SDNN), standard deviation of the average RR interval for each 5 min segment (SDANN), square root of the differences between adjacent RR intervals (RMSSD), percentage of beats with a consecutive RR interval difference > 50 ms (PNN50) and Triangular index. Univariate analyses showed that 1hPG, but not fasting and 2hPG, was inversely associated with all the explored HVR parameters and positively with CARTs determined presence of CAN. In multivariate regression analysis models including several confounders we found that 1hPG was an independent contributor of HRV and presence of CAN. CONCLUSION: Subjects with 1hPG ≥ 155 mg/dl have an impaired cardiac autonomic function.

Relationship between hyperglycemia and intraocular pressure, corneal biomechanics, and corneal topography during the oral glucose tolerance test in nondiabetic patients.

PURPOSE: Altered corneal biomechanics in patients with diabetes may affect intraocular pressure (IOP) measurements. Although a relationship between IOP and glucose levels has been reported in diabetic and nondiabetic patients, the mechanism by which hyperglycemia influences IOP is unclear. The aim of this study was to determine the effects of hyperglycemia on IOP, corneal biomechanics, and anterior segment parameters during the oral glucose tolerance test (OGTT) in nondiabetic patients. METHODS: Twenty-one patients without DM who underwent OGTT were included in this study. A complete ophthalmologic examination was performed before the test. Blood glucose, insulin level, IOP (iCare rebound tonometer), Ocular Response Analyzer, and corneal topography (Pentacam) measurements were obtained at 0, 1, and 2 h during the OGTT. Data from the patients' right eyes were included in the analysis. RESULTS: The mean age of the patients was 46.9 ± 11.0 years. There was a statistically significant difference in IOP between 1 and 2 h (p = 0.03) and a clinically significant difference between 0 and 1 h (p = 0.06). Corneal resistance factor was lower at 2 h than 1 h (p = 0.03), while central cornea thickness was increased at 1 h (p = 0.01) and 2 h (p = 0.05) compared to 0 h. There was positive partial correlation between hyperglycemia and IOP at 1 h (p = 0.049, r = 0.67). CONCLUSION: The positive partial correlation between IOP and glucose level suggests that acute hyperglycemia may lead to increased IOP. However, further research is needed to explain the mechanism of IOP elevation in the hyperglycemic phase during OGTT.

Development and validation of a machine learning-based model to predict isolated post-challenge hyperglycemia in middle-aged and elder adults: Analysis from a multicentric study.

INTRODUCTION: Due to the high cost and complexity, the oral glucose tolerance test is not adopted as the screening method for identifying diabetes patients, which leads to the misdiagnosis of patients with isolated post-challenge hyperglycemia (IPH), that is., patients with normal fasting plasma glucose (<7.0 mmoL/L) and abnormal 2-h postprandial blood glucose (≥11.1 mmoL/L). We aimed to develop a model to differentiate individuals with IPH from the normal population. METHODS: Data from 54301 eligible participants were obtained from the Risk Evaluation of Cancers in Chinese Diabetic Individuals: a longitudinal (REACTION) study in China. Data from 37740 participants were used to develop the diagnostic system. External validation was performed among 16561 participants. Three machine learning algorithms were used to create the predictive models, which were further evaluated by various classification algorithms to establish the best predictive model. RESULTS: Ten features were selected to develop an IPH diagnosis system (IPHDS) based on an artificial neural network. In external validation, the AUC of the IPHDS was 0.823 (95% CI 0.811-0.836), which was significantly higher than the AUC of the Taiwan model [0.799 (0.786-0.813)] and that of the Chinese Diabetes Risk Score model [0.648 (0.635-0.662)]. The IPHDS model had a sensitivity of 75.6% and a specificity of 74.6%. This model outperformed the Taiwan and CDRS models in subgroup analyses. An online site with instant predictions was deployed at https://app-iphds-e1fc405c8a69.herokuapp.com/. CONCLUSIONS: The proposed IPHDS could be a convenient and user-friendly screening tool for diabetes during health examinations in a large general population.

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.

Supervised Machine Learning-Based Models for Predicting Raised Blood Sugar.

Raised blood sugar (hyperglycemia) is considered a strong indicator of prediabetes or diabetes mellitus. Diabetes mellitus is one of the most common non-communicable diseases (NCDs) affecting the adult population. Recently, the prevalence of diabetes has been increasing at a faster rate, especially in developing countries. The primary concern associated with diabetes is the potential for serious health complications to occur if it is not diagnosed early. Therefore, timely detection and screening of diabetes is considered a crucial factor in treating and controlling the disease. Population screening for raised blood sugar aims to identify individuals at risk before symptoms appear, enabling timely intervention and potentially improved health outcomes. However, implementing large-scale screening programs can be expensive, requiring testing, follow-up, and management resources, potentially straining healthcare systems. Given the above facts, this paper presents supervised machine-learning models to detect and predict raised blood sugar. The proposed raised blood sugar models utilize diabetes-related risk factors including age, body mass index (BMI), eating habits, physical activity, prevalence of other diseases, and fasting blood sugar obtained from the dataset of the STEPwise approach to NCD risk factor study collected from adults in the Palestinian community. The diabetes risk factor obtained from the STEPS dataset was used as input for building the prediction model that was trained using various types of supervised learning classification algorithms including random forest, decision tree, Adaboost, XGBoost, bagging decision trees, and multi-layer perceptron (MLP). Based on the experimental results, the raised blood sugar models demonstrated optimal performance when implemented with a random forest classifier, yielding an accuracy of 98.4%. Followed by the bagging decision trees, XGBoost, MLP, AdaBoost, and decision tree with an accuracy of 97.4%, 96.4%, 96.3%, 95.2%, and 94.8%, respectively.

Anthropometry for predicting cardiometabolic disease risk factors in adolescents.

OBJECTIVE: Early screening prevents chronic diseases by identifying at-risk adolescents through anthropometric measurements, but predictive value in diverse groups is uncertain. METHODS: A cross-sectional analysis of 12- to 19-year-old individuals from the 2017-2018 National Health and Nutrition Examination Survey (NHANES) assessed the predictive ability of BMI percentile, total body fat percentage, waist circumference (WC), and waist-hip ratio (WHR) for four cardiometabolic risk factors across race and ethnicity groups using receiver operating characteristic curves. RESULTS: The unweighted sample (N = 1194; 51.2% male individuals; 23.7% Hispanic, 13.2% non-Hispanic Black [NHB], 51.1% non-Hispanic White [NHW], 12.0% other/multirace) had a weighted prevalence of elevated blood pressure of 2.7%, hyperglycemia of 36.8%, hypertriglyceridemia of 4.8%, and low high-density lipoprotein (HDL) cholesterol of 15%. WHR (area under the curve [AUC] = 0.77), WC (AUC = 0.77), and BMI percentile (AUC = 0.73) outperformed total body fat percentage (AUC = 0.56) in predicting elevated blood pressure (p < 0.001 for all). BMI percentile was more accurate than total body fat percentage in predicting hypertriglyceridemia (AUC = 0.70 vs. 0.59; p = 0.02) and low HDL cholesterol (AUC = 0.69 vs. 0.59; p < 0.001). Race and ethnicity-based predictions varied: NHW adolescents had the highest AUC (0.89; p < 0.01) for elevated blood pressure prediction compared with Hispanic and NHB adolescents (AUC = 0.77 for both). Total body fat percentage was more accurate in predicting low HDL cholesterol among Hispanic versus NHW adolescents (AUC = 0.73 vs. 0.58; p = 0.04). CONCLUSIONS: WHR, WC, and BMI percentile are better predictors of cardiometabolic risk factors in adolescents than total body fat percentage. Predictive abilities differed by race and ethnicity, highlighting the importance of tailored risk assessment strategies.

Diagnosis and Treatment of Hyperglycemia in Pregnancy: Type 2 Diabetes Mellitus and Gestational Diabetes.

Hyperglycemia in pregnancy due to pre-existing Type 2 diabetes mellitus (T2DM) and gestational diabetes mellitus (GDM) is rising globally with increasing rates of risk factors for metabolic disease. This review summarizes current evidence and recommendations from national and international guidelines for diagnosis and management of T2DM and GDM to optimize maternal and neonatal outcomes.

Acute-to-chronic glycemic ratio as an outcome predictor in ischemic stroke in patients with and without diabetes mellitus.

OBJECTIVE: Elevated plasma glucose levels are common in patients suffering acute ischemic stroke (AIS), and acute hyperglycemia has been defined as an independent determinant of adverse outcomes. The impact of acute-to-chronic glycemic ratio (ACR) has been analyzed in other diseases, but its impact on AIS prognosis remains unclear. The main aim of this study was to assess whether the ACR was associated with a 3-month poor prognosis in patients with AIS. RESEARCH, DESIGN AND METHODS: Retrospective analysis of patients admitted for AIS in Hospital del Mar, Barcelona. To estimate the chronic glucose levels (CGL) we used the formula eCGL= [28.7xHbA1c (%)]-46.7. The ACR (glycemic at admission / eCGL) was calculated for all subjects. Tertile 1 was defined as: 0.28-0.92, tertile 2: 0.92-1.13 and tertile 3: > 1.13. Poor prognosis at 3 months after stroke was defined as mRS score 3-6. RESULTS: 2.774 subjects with AIS diagnosis were included. Age, presence of diabetes, previous disability (mRS), initial severity (NIHSS) and revascularization therapy were associated with poor prognosis (p values < 0.05). For each 0.1 increase in ACR, there was a 7% increase in the risk of presenting a poor outcome. The 3rd ACR tertile was independently associated with a poor prognosis and mortality. In the ROC curves, adding the ACR variable to the classical clinical model did not increase the prediction of AIS prognosis (0.786 vs. 0.781). CONCLUSIONS: ACR was positively associated with a poor prognosis and mortality at 3-months follow-up after AIS. Subjects included in the 3rd ACR tertile presented a higher risk of poor prognosis and mortality. Baseline glucose or ACR did not add predictive value in comparison to only using classical clinical variables.

Additive effect of admission hyperglycemia on left ventricular stiffness in patients following acute myocardial infarction verified by CMR tissue tracking.

BACKGROUND: Stress hyperglycemia occurs frequently in patients following acute myocardial infarction (AMI) and may aggravate myocardial stiffness, but relevant evidence is still lacking. Accordingly, this study aimed to examine the impact of admission stress hyperglycemia on left ventricular (LV) myocardial deformation in patients following AMI. METHODS: A total of 171 patients with first AMI (96 with normoglycemia and 75 with hyperglycemia) underwent cardiac magnetic resonance (CMR) examination were included. AMI patients were classified according to admission blood glucose level (aBGL): < 7.8 mmol/L (n = 96), 7.8-11.1 mmol/L (n = 41) and ≥ 11.1 mmol/L (n = 34). LV strains, including global radial/circumferential/longitudinal peak strain (PS)/peak systolic strain rate (PSSR)/peak diastolic strain rate (PDSR), were measured and compared between groups. Further, subgroup analyses were separately conducted for AMI patients with and without diabetes. Multivariate analysis was employed to assess the independent association between aBGL and LV global PS in AMI patients. RESULTS: LV global PS, PSSR and PDSR were decreased in radial, circumferential and longitudinal directions in hyperglycemic AMI patients compared with normoglycemic AMI patients (all P < 0.05). These differences were more obvious in patients with diabetes than those without diabetes. AMI patients with aBGL between 7.8 and 11.1 mmol/L demonstrated significant decreased radial and longitudinal PS, radial PSSR, and radial and longitudinal PDSR than those with aBGL < 7.8 mmol/L (all P < 0.05). AMI patients with aBGL ≥ 11.1 mmol/L showed significantly decreased PS, PSSR and PDSR in all three directions than those with aBGL < 7.8 mmol/L, and decreased longitudinal PSSR than those with aBGL between 7.8 and 11.1 (all P < 0.05). Further, aBGL was significantly and independently associated with radial (ß = - 0.166, P = 0.003) and longitudinal (ß = 0.143, P = 0.008) PS. CONCLUSIONS: Hyperglycemia may exacerbate LV myocardial stiffness in patients experienced first AMI, leading to reduction in LV strains. aBGL was an independent indicator of impaired LV global PS in AMI patients. Blood glucose monitoring is more valuable for AMI patients with diabetes.

High stress hyperglycemia ratio predicts adverse clinical outcome in patients with coronary three-vessel disease: a large-scale cohort study.

BACKGROUND: Coronary three-vessel disease (CTVD) accounts for one-third of the overall incidence of coronary artery disease, with heightened mortality rates compared to single-vessel lesions, including common trunk lesions. Dysregulated glucose metabolism exacerbates atherosclerosis and increases cardiovascular risk. The stress hyperglycemia ratio (SHR) is proposed as an indicator of glucose metabolism status but its association with cardiovascular outcomes in CTVD patients undergoing percutaneous coronary intervention (PCI) remains unclear. METHODS: 10,532 CTVD patients undergoing PCI were consecutively enrolled. SHR was calculated using the formula: admission blood glucose (mmol/L)/[1.59×HbA1c (%)-2.59]. Patients were divided into two groups (SHR Low and SHR High) according to the optimal cutoff value of SHR. Multivariable Cox regression models were used to assess the relationship between SHR and long-term prognosis. The primary endpoint was cardiovascular (CV) events, composing of cardiac death and non-fatal myocardial infarction (MI). RESULTS: During the median follow-up time of 3 years, a total of 279 cases (2.6%) of CV events were recorded. Multivariable Cox analyses showed that high SHR was associated with a significantly higher risk of CV events [Hazard Ratio (HR) 1.99, 95% Confidence interval (CI) 1.58-2.52, P < 0.001). This association remained consistent in patients with (HR 1.50, 95% CI 1.08-2.10, P = 0.016) and without diabetes (HR 1.97, 95% CI 1.42-2.72, P < 0.001). Additionally, adding SHR to the base model of traditional risk factors led to a significant improvement in the C-index, net reclassification and integrated discrimination. CONCLUSIONS: SHR was a significant predictor for adverse CV outcomes in CTVD patients with or without diabetes, which suggested that it could aid in the risk stratification in this particular population regardless of glucose metabolism status.

A Rare Case of Hyperglycemia, Ketoacidosis, and Central Facial Paralysis in a Newly-Diagnosed Diabetic Woman.

BACKGROUND Diabetes mellitus is a chronic disease that occurs when the pancreas does not produce enough insulin or when the body is unable to effectively use the insulin it produces. Uncontrolled diabetes mellitus is usually associated with neurological manifestations, such as hemichorea, focal epileptic seizures, peripheral neuropathy, and peripheral facial paralysis. This report describes a 59-year-old woman presenting with hyperglycemia and ketoacidosis due to newly diagnosed diabetes mellitus, as well as a temporary episode of central facial paralysis, which regressed within a few days after medical treatment and metabolic correction. CASE REPORT A 59-year-old patient with hypertension and a family history of diabetes mellitus presented with polyuro-polydipsic syndrome and signs of metabolic ketoacidosis, with an elevated anion gap, compatible with newly discovered type 1 diabetes mellitus. Six hours after admission, we noted the abrupt onset of left central facial paralysis, with no brain damage shown on magnetic resonance imaging. Initially, the diagnosis was transient ischemic attack. After a second, normal cerebral magnetic resonance image on the fourth day, and clinical improvement on the fifth day after metabolic correction by insulin therapy and rehydration, the diagnosis of a regressive central facial paralysis was retained. CONCLUSIONS Central facial paralysis in diabetic ketoacidosis is a rare neuroendocrine entity. The pathophysiological mechanisms that can explain the occurrence of central facial paralysis are not yet described and require further investigation. This report highlights the importance of diagnosis, early management of hyperglycemia and diabetic ketoacidosis, and reversibility of central facial paralysis after treatment.

Ambulance clinician use of capillary blood ketone meters to improve emergency hyperglycaemia care: A stepped-wedged controlled, mixed-methods feasibility study.

AIM: To determine whether it was feasible, safe and acceptable for ambulance clinicians to use capillary blood ketone meters for 'high-risk' diabetic ketoacidosis (DKA) recognition and fluid initiation, to inform the need for a full-powered, multi-centre trial. METHODS: Adopting a stepped-wedge controlled design, participants with hyperglycaemia (capillary blood glucose >11.0 mmol/L) or diabetes and unwell were recruited. 'High-risk' DKA intervention participants (capillary blood ketones ≥3.0 mmol/L) received paramedic-led fluid therapy. Participant demographic and clinical data were collated from ambulance and hospital care records. Twenty ambulance and Emergency Department clinicians were interviewed to understand their hyperglycaemia and DKA care experiences. RESULTS: In this study, 388 participants were recruited (Control: n = 203; Intervention: n = 185). Most presented with hyperglycaemia, and incidence of type 1 and type 2 diabetes was 18.5% and 74.3%, respectively. Ketone meter use facilitated 'high-risk' DKA identification (control: 2.5%, n = 5; intervention: 6.5%, n = 12) and was associated with improved hospital pre-alerting. Ambulance clinicians appeared to have a high index of suspicion for hospital-diagnosed DKA participants. One third (33.3%; n = 3) of Control and almost half (45.5%; n = 5) of Intervention DKA participants received pre-hospital fluid therapy. Key interview themes included clinical assessment, ambulance DKA fluid therapy, clinical handovers; decision support tool; hospital DKA management; barriers to hospital DKA care. CONCLUSIONS: Ambulance capillary blood ketone meter use was deemed feasible, safe and acceptable. Opportunities for improved clinical decision making, support and safety-netting, as well as in-hospital DKA care, were recognised. As participant recruitment was below progression threshold, it is recommended that future-related research considers alternative trial designs. CLINICALTRIALS: gov: NCT04940897.

Accuracy of acute hyperglycemia as a biomarker of severe brain damage in children with traumatic brain injury.

PURPOSE: Biomarkers are substances measured at the systemic level to evaluate organic responses in certain situations, establishing diagnoses, disease staging, and prognosis. Blood glucose is a biomarker recognized as a predictor of prognosis in children victims of traumatic brain injury (TBI). The scope of this study was to identify the accuracy of blood glucose as a biomarker of severe brain injury. METHODS: A retrospective analytical study was conducted through the consecutive review of medical records of children and teenage victims of TBI who underwent neurological surgery between 2016 and 2023 in a level 1 trauma center. Two groups were compared: children with Glasgow Coma Scale (GCS) score ≤ 8 and children with GCS > 8. We calculated the predictive values to define the accuracy of blood glucose as a biomarker of brain injury. RESULTS: Ninety-two medical records were included for analysis. Hyperglycemia predominated in cases with GCS ≤ 8 (48% vs 3%; p < 0.0001; OR, 30; 95% CI, 5.9902-150.2448). The glycemic measurement considering the cutoff point of 200 mg/dL or 11.1 mmol/L showed a specificity of 97%, a positive predictive value of 86%, an accuracy of 84%, and a likelihood ratio for a positive test of 16. CONCLUSION: Victims with GCS ≤ 8 are 16 times more likely to develop acute hyperglycemia after TBI when compared to those with GCS > 8. Blood glucose is a biomarker with an accuracy of 84% to predict severe brain injury, considering the cutoff point of 200 mg/dL or 11.1 mmol/L.

Modifiable self-management practices impact nocturnal and morning glycaemia in type 1 diabetes.

AIMS: To identify risk factors for nocturnal/morning hypo- and hyperglycaemia in type 1 diabetes. METHODS: Data on self-management practices were obtained from 3-day records. We studied the associations between self-management practices on the first recording day and the self-reported blood glucose (BG) concentrations on the subsequent night/morning. RESULTS: Of the 1025 participants (39 % men, median age 45 years), 4.4 % reported nocturnal hypoglycaemia (<3.9 mmol/l), 9.8 % morning hypoglycaemia, 51.5 % morning euglycaemia, and 34.3 % morning hyperglycaemia (≥8.9 mmol/l). Within hypoglycaemic range, insulin pump use was associated with higher nocturnal BG concentration (B=0.486 [95 % Confidence Interval=0.121-0.852], p=0.009). HbA1c was positively (0.046 [0.028-0.065], p<0.001), while antecedent fibre intake (-0.327 [-0.543 - -0.111], p=0.003) and physical activity (PA) (-0.042 [-0.075 - -0.010], p=0.010) were inversely associated with morning BG concentration. The odds of morning hypoglycaemia were increased by previous day hypoglycaemia (OR=2.058, p=0.002) and alcohol intake (1.031, p=0.001). Previous day PA (0.977, p=0.031) and fibre intake (0.848, p=0.017) were inversely, while HbA1c (1.027, p<0.001) was positively associated with the risk of morning hyperglycaemia. CONCLUSIONS: Alcohol avoidance may prevent nocturnal hypoglycaemia, while PA and fibre intake may reduce hyperglycaemia risk. Avoidance of daytime hypoglycaemia and keeping HbA1c in control may help maintain normoglycaemia also at night-time.

Higher blood glucose is associated with the severity of hemorrhagic transformation after endovascular therapy for stroke.

OBJECTIVES: Hyperglycemia is associated with poor outcome in large vessel occlusion (LVO) stroke, with mechanism for this effect unknown. MATERIALS AND METHODS: We used our prospective, multicenter, observational study, Blood Pressure After Endovascular Stroke Therapy (BEST), of anterior circulation LVO stroke undergoing endovascular therapy (EVT) from 11/2017-7/2018 to determine association between increasing blood glucose (BG) and intracerebral hemorrhage (ICH). Our primary outcome was degree of ICH, classified as none, asymptomatic ICH, or symptomatic ICH (≥4-point increase in National Institutes of Health Stroke Scale [NIHSS] at 24 h with any hemorrhage on imaging). Secondary outcomes included 24 h NIHSS, early neurologic recovery (ENR, NIHSS 0-1 or NIHSS reduction by ≥8 within 24 h), and 90-day modified Rankin Scale (mRS) using univariate and multivariable regression. RESULTS: Of 485 enrolled patients, increasing BG was associated with increasing severity of ICH (adjusted OR, aOR 1.06, 95 % CI 1.02-1.1, p < 0.001), higher 24 h NIHSS (aOR 1.22, 95 % CI 1.11-1.34, p < 0.001), ENR (aOR 0.90, 95 % CI 0.82-1.00, p < 0.002), and 90-day mRS (aOR 1.06, 95 % CI 1.03-1.09, p < 0.001) when adjusted for age, presenting NIHSS, ASPECTS, 24-hour peak systolic blood pressure, time from last known well, and successful recanalization. CONCLUSIONS: In the BEST study, increasing BG was associated with greater odds of increasing ICH severity. Further study is warranted to determine whether treatment of will decrease ICH severity following EVT.

Association of stress hyperglycemia ratio with left ventricular function and microvascular obstruction in patients with ST-segment elevation myocardial infarction: a 3.0 T cardiac magnetic resonance study.

BACKGROUND: Stress hyperglycemia, which is associated with poor prognosis in patients with acute myocardial infarction (AMI), can be determined using the stress hyperglycemia ratio (SHR). Impaired left ventricular function and microvascular obstruction (MVO) diagnosed using cardiac magnetic resonance (CMR) have also been proven to be linked to poor prognosis in patients with AMI and aid in risk stratification. However, there have been no studies on the correlation between fasting SHR and left ventricular function and MVO in patients with acute ST-segment elevation myocardial infarction (ASTEMI). Therefore, this study aimed to investigate the additive effect of fasting SHR on left ventricular function and global deformation in patients with ASTEMI and to explore the association between fasting SHR and MVO. METHODS: Consecutive patients who underwent CMR at index admission (3-7 days) after primary percutaneous coronary intervention (PPCI) were enrolled in this study. Basic clinical, biochemical, and CMR data were obtained and compared among all patients grouped by fasting SHR tertiles: SHR1: SHR < 0.85; SHR2: 0.85 ≤ SHR < 1.01; and SHR3: SHR ≥ 1.01. Spearman's rho (r) was used to assess the relationship between fasting SHR and left ventricular function, myocardial strain, and the extent of MVO. Multivariable linear regression analysis was performed to evaluate the determinants of left ventricular function and myocardial strain impairment in all patients with AMI. Univariable and multivariable regression analyses were performed to investigate the correlation between fasting SHR and the presence and extent of MVO in patients with AMI and those with AMI and diabetes mellitus (DM). RESULTS: A total of 357 patients with ASTEMI were enrolled in this study. Left ventricular ejection fraction (LVEF) and left ventricular global function index (LVGFI) were significantly lower in SHR2 and SHR3 than in SHR1. Compared with SHR1 and SHR2 groups, left ventricular strain was lower in SHR3, as evidenced by global radial (GRS), global circumferential (GCS), and global longitudinal (GLS) strains. Fasting SHR were negatively correlated with LVEF, LVGFI, and GRS (r = - 0.252; r = - 0.261; and r = - 0.245; all P<0.001) and positively correlated with GCS (r = 0.221) and GLS (r = 0.249; all P <0.001). Multivariable linear regression analysis showed that fasting SHR was an independent determinant of impaired LVEF, LVGFI, GRS, and GLS. Furthermore, multivariable regression analysis after adjusting for covariates signified that fasting SHR was associated with the presence and extent of MVO in patients with AMI and those with AMI and DM. CONCLUSION: Fasting SHR in patients with ASTEMI successfully treated using PPCI is independently associated with impaired cardiac function and MVO. In patients with AMI and DM, fasting SHR is an independent determinant of the presence and extent of MVO.

Contributions of elevated CRP, hyperglycaemia, and type 2 diabetes to cardiovascular risk in the general population: observational and Mendelian randomization studies.

OBJECTIVE: To investigate the contributions of low-grade inflammation measured by C-reactive protein (CRP), hyperglycaemia, and type 2 diabetes to risk of ischemic heart disease (IHD) and cardiovascular disease (CVD) death in the general population, and whether hyperglycaemia and high CRP are causally related. RESEARCH DESIGN AND METHODS: Observational and bidirectional, one-sample Mendelian randomization (MR) analyses in 112,815 individuals from the Copenhagen General Population Study and the Copenhagen City Heart Study, and bidirectional, two-sample MR with summary level data from two publicly available consortia, CHARGE and MAGIC. RESULTS: Observationally, higher plasma CRP was associated with stepwise higher risk of IHD and CVD death, with hazard ratios and 95% confidence intervals (95%CI) of 1.50 (1.38, 1.62) and 2.44 (1.93, 3.10) in individuals with the 20% highest CRP concentrations. The corresponding hazard ratios for elevated plasma glucose were 1.10 (1.02, 1.18) and 1.22 (1.01, 1.49), respectively. Cumulative incidences of IHD and CVD death were 365% and 592% higher, respectively, in individuals with both type 2 diabetes and plasma CRP ≥ 2 mg/L compared to individuals without either. Plasma CRP and glucose were observationally associated (ß-coefficient: 0.02 (0.02, 0.03), p = 3 × 10- 20); however, one- and two-sample MR did not support a causal effect of CRP on glucose (-0.04 (-0.12, 0.32) and - 0.03 (-0.13, 0.06)), nor of glucose on CRP (-0.01 (-0.08, 0.07) and - 0.00 (-0.14, 0.13)). CONCLUSIONS: Elevated concentrations of plasma CRP and glucose are predictors of IHD and CVD death in the general population. We found no genetic association between CRP and glucose, or vice versa, suggesting that lowering glucose pharmacologically does not have a direct effect on low-grade inflammation.

Association between the stress hyperglycemia ratio and 28-day all-cause mortality in critically ill patients with sepsis: a retrospective cohort study and predictive model establishment based on machine learning.

BACKGROUND: Sepsis is a severe form of systemic inflammatory response syndrome that is caused by infection. Sepsis is characterized by a marked state of stress, which manifests as nonspecific physiological and metabolic changes in response to the disease. Previous studies have indicated that the stress hyperglycemia ratio (SHR) can serve as a reliable predictor of adverse outcomes in various cardiovascular and cerebrovascular diseases. However, there is limited research on the relationship between the SHR and adverse outcomes in patients with infectious diseases, particularly in critically ill patients with sepsis. Therefore, this study aimed to explore the association between the SHR and adverse outcomes in critically ill patients with sepsis. METHODS: Clinical data from 2312 critically ill patients with sepsis were extracted from the MIMIC-IV (2.2) database. Based on the quartiles of the SHR, the study population was divided into four groups. The primary outcome was 28-day all-cause mortality, and the secondary outcome was in-hospital mortality. The relationship between the SHR and adverse outcomes was explored using restricted cubic splines, Cox proportional hazard regression, and Kaplan‒Meier curves. The predictive ability of the SHR was assessed using the Boruta algorithm, and a prediction model was established using machine learning algorithms. RESULTS: Data from 2312 patients who were diagnosed with sepsis were analyzed. Restricted cubic splines demonstrated a "U-shaped" association between the SHR and survival rate, indicating that an increase in the SHR is related to an increased risk of adverse events. A higher SHR was significantly associated with an increased risk of 28-day mortality and in-hospital mortality in patients with sepsis (HR > 1, P < 0.05) compared to a lower SHR. Boruta feature selection showed that SHR had a higher Z score, and the model built using the rsf algorithm showed the best performance (AUC = 0.8322). CONCLUSION: The SHR exhibited a U-shaped relationship with 28-day all-cause mortality and in-hospital mortality in critically ill patients with sepsis. A high SHR is significantly correlated with an increased risk of adverse events, thus indicating that is a potential predictor of adverse outcomes in patients with sepsis.

Correlation Between the Glycemia Risk Index and Longitudinal Hemoglobin A1c in Children and Young Adults With Type 1 Diabetes.

BACKGROUND: The glycemia risk index (GRI) is a composite metric developed and used to estimate quality of glycemia in adults with diabetes who use continuous glucose monitor (CGM) devices. In a cohort of youth with type 1 diabetes (T1D), we examined the utility of the GRI for evaluating quality of glycemia between clinic visits by analyzing correlations between the GRI and longitudinal glycated hemoglobin A1c (HbA1c) measures. METHOD: Using electronic health records and CGM data, we conducted a retrospective cohort study to analyze the relationship between the GRI and longitudinal HbA1c measures in youth (T1D duration ≥1 year; ≥50% CGM wear time) receiving care from a Midwest pediatric diabetes clinic network (March 2016 to May 2022). Furthermore, we analyzed correlations between HbA1c and the GRI high and low components, which reflect time spent with high/very high and low/very low glucose, respectively. RESULTS: In this cohort of 719 youth (aged = 2.5-18.0 years [median = 13.4; interquartile range [IQR] = 5.2]; 50.5% male; 83.7% non-Hispanic White; 68.0% commercial insurance), baseline GRI scores positively correlated with HbA1c measures at baseline and 3, 6, 9, and 12 months later (r = 0.68, 0.65, 0.60, 0.57, and 0.52, respectively). At all time points, strong positive correlations existed between HbA1c and time spent in hyperglycemia. Substantially weaker, negative correlations existed between HbA1c and time spent in hypoglycemia. CONCLUSIONS: In youth with T1D, the GRI may be useful for evaluating quality of glycemia between scheduled clinic visits. Additional CGM-derived metrics are needed to quantify risk for hypoglycemia in this population.