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.

Effects of the stress hyperglycemia ratio on long-term mortality in patients with triple-vessel disease and acute coronary syndrome.

AIMS: Risk assessment for triple-vessel disease (TVD) remain challenging. Stress hyperglycemia represents the regulation of glucose metabolism in response to stress, and stress hyperglycemia ratio (SHR) is recently found to reflect true acute hyperglycemic status. This study aimed to evaluate the prognostic value of SHR and its role in risk stratification in TVD patients with acute coronary syndrome (ACS). METHODS: A total of 3812 TVD patients with ACS with available baseline SHR measurement were enrolled from two independent centers. The endpoint was cardiovascular mortality. Cox regression was used to evaluate the association between SHR and cardiovascular mortality. The SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) II (SSII) was used as the reference model in the model improvement analysis. RESULTS: During a median follow-up of 5.1 years, 219 (5.8%) TVD patients with ACS suffered cardiovascular mortality. TVD patients with ACS with high SHR had an increased risk of cardiovascular mortality after robust adjustment for confounding (high vs. median SHR: adjusted hazard ratio 1.809, 95% confidence interval 1.160-2.822, P = 0.009), which was fitted as a J-shaped pattern. The prognostic value of the SHR was found exclusively among patients with diabetes instead of those without diabetes. Moreover, addition of SHR improved the reclassification abilities of the SSII model for predicting cardiovascular mortality in TVD patients with ACS. CONCLUSIONS: The high level of SHR is associated with the long-term risk of cardiovascular mortality in TVD patients with ACS, and is confirmed to have incremental prediction value beyond standard SSII. Assessment of SHR may help to improve the risk stratification strategy in TVD patients who are under acute stress.

International Diabetes Federation Position Statement on the 1-hour post-load plasma glucose for the diagnosis of intermediate hyperglycaemia and type 2 diabetes.

Many individuals with intermediate hyperglycaemia (IH), including impaired fasting glycaemia (IFG) and impaired glucose tolerance (IGT), as presently defined, will progress to type 2 diabetes (T2D). There is confirmatory evidence that T2D can be prevented by lifestyle modification and/or medications, in people with IGT diagnosed by 2-h plasma glucose (PG) during a 75-gram oral glucose tolerance test (OGTT). Over the last 40 years, a wealth of epidemiological data has confirmed the superior value of 1-h plasma glucose (PG) over fasting PG (FPG), glycated haemoglobin (HbA1c) and 2-h PG in populations of different ethnicity, sex and age in predicting diabetes and associated complications including death. Given the relentlessly rising prevalence of diabetes, a more sensitive, practical method is needed to detect people with IH and T2D for early prevention or treatment in the often lengthy trajectory to T2D and its complications. The International Diabetes Federation (IDF) Position Statement reviews findings that the 1-h post-load PG ≥ 155 mg/dL (8.6 mmol/L) in people with normal glucose tolerance (NGT) during an OGTT is highly predictive for detecting progression to T2D, micro- and macrovascular complications, obstructive sleep apnoea, cystic fibrosis-related diabetes mellitus, metabolic dysfunction-associated steatotic liver disease, and mortality in individuals with risk factors. The 1-h PG of 209 mg/dL (11.6 mmol/L) is also diagnostic of T2D. Importantly, the 1-h PG cut points for diagnosing IH and T2D can be detected earlier than the recommended 2-h PG thresholds. Taken together, the 1-h PG provides an opportunity to avoid misclassification of glycaemic status if FPG or HbA1c alone are used. The 1-h PG also allows early detection of high-risk people for intervention to prevent progression to T2D which will benefit the sizeable and growing population of individuals at increased risk of T2D. Using a 1-h OGTT, subsequent to screening with a non-laboratory diabetes risk tool, and intervening early will favourably impact the global diabetes epidemic. Health services should consider developing a policy for screening for IH based on local human and technical resources. People with a 1-h PG ≥ 155 mg/dL (8.6 mmol/L) are considered to have IH and should be prescribed lifestyle intervention and referred to a diabetes prevention program. People with a 1-h PG ≥ 209 mg/dL (11.6 mmol/L) are considered to have T2D and should have a repeat test to confirm the diagnosis of T2D and then referred for further evaluation and treatment. The substantive data presented in the Position Statement provides strong evidence for redefining current diagnostic criteria for IH and T2D by adding the 1-h PG.

The prognostic value of the stress hyperglycemia ratio for all-cause and cardiovascular mortality in patients with diabetes or prediabetes: insights from NHANES 2005-2018.

BACKGROUND: The Stress hyperglycemia ratio (SHR) is a novel marker reflecting the true acute hyperglycemia status and is associated with clinical adverse events. The relationship between SHR and mortality in patients with diabetes or prediabetes is still unclear. This study aimed to investigate the predictive value of the SHR for all-cause and cardiovascular mortality in patients with diabetes or prediabetes. METHODS: This study included 11,160 patients diagnosed with diabetes or prediabetes from the National Health and Nutrition Examination Survey (2005-2018). The study endpoints were all-cause and cardiovascular mortality, and morality data were extracted from the National Death Index (NDI) up to December 31, 2019. Patients were divided into SHR quartiles. Cox proportion hazards regression was applied to determine the prognostic value of SHR. Model 1 was not adjusted for any covariates. Model 2 was adjusted for age, sex, and race. Model 3 was adjusted for age, sex, race, BMI, smoking status, alcohol use, hypertension, CHD, CKD, anemia, and TG. RESULTS: During a mean follow-up of 84.9 months, a total of 1538 all-cause deaths and 410 cardiovascular deaths were recorded. Kaplan-Meier survival analysis showed the lowest all-cause mortality incidence was in quartile 3 (P < 0.001). Multivariate Cox regression analyses indicated that, compared to the 1st quartile, the 4th quartile was associated with higher all-cause mortality (model 1: HR = 0.89, 95% CI 0.74-10.7, P = 0.226; model 2: HR = 1.24, 95% CI 1.03-1.49, P = 0.026; model 3: HR = 1.30, 95% CI 1.08-1.57, P = 0.006). The 3rd quartile was associated with lower cardiovascular mortality than quartile 1 (model 1: HR = 0.47, 95% CI 0.32-0.69, P < 0.001; model 2: HR = 0.66, 95% CI 0.45-0.96, P = 0.032; model 3: HR = 0.68, 95% CI 0.46-0.99, P = 0.049). There was a U-shaped association between SHR and all-cause mortality and an L-shaped association between SHR and cardiovascular mortality, with inflection points of SHR for poor prognosis of 0.87 and 0.93, respectively. CONCLUSION: SHR is related to all-cause and cardiovascular mortality in patients with diabetes or prediabetes. SHR may have predictive value in those patients.

Detection and Management of Perioperative Hyperglycemia at a Tertiary Cancer Center.

INTRODUCTION: To improve the detection and management of perioperative hyperglycemia at our tertiary cancer center, we implemented a glycemic control quality improvement initiative. The primary goal was to decrease the percentage of diabetic patients with median postoperative glucose levels > 180 mg/dL during hospitalization by 15% within 2 years. METHODS: A multidisciplinary team standardized preoperative screening, preoperative, intraoperative, and postoperative hyperglycemia management. We included all patients undergoing nonemergent inpatient and outpatient operations. We used a t test, rank sum, chi-square, or Fisher's exact test to assess differences in outcomes between patients at baseline (BL) (10/2018-4/2019), during the first phase (P1) (10/2019-4/2020), second phase (P2) (5/2020-12/2020), and maintenance phase (M) (1/2021-10/2022). RESULTS: The analysis included 9891 BL surgical patients (1470 with diabetes), 8815 P1 patients (1233 with diabetes), 10,401 P2 patients (1531 with diabetes) and 30,410 M patients (4265 with diabetes). The percentage of diabetic patients with median glucose levels >180 mg/dL during hospitalization decreased 32% during the initiative (BL, 20.1%; P1, 16.9%; P2, 12.1%; M, 13.7% [P < .001]). We also saw reductions in the percentages of diabetic patients with median glucose levels >180 mg/dL intraoperatively (BL, 34.0%; P1, 26.6%; P2, 23.9%; M, 20.3% [P < .001]) and in the postanesthesia care unit (BL, 36.0%; P1, 30.4%; P2, 28.5%; M, 25.8% [P < .001]). The percentage of patients screened for diabetes by hemoglobin A1C increased during the initiative (BL, 17.5%; P1, 52.5%; P2, 66.8%; M 74.5% [P < .001]). CONCLUSIONS: Our successful initiative can be replicated in other hospitals to standardize and improve glycemic control among diabetic surgical patients.

Cross-sectional study examining factors impacting on uptake of postpartum type 2 diabetes screening among women diagnosed with hyperglycaemia in pregnancy.

AIMS: Early postpartum glucose screening of women with hyperglycaemia in pregnancy (HIP) can identify women who have the highest risk of developing impaired glucose tolerance and T2DM. This study examines the association between demographics, events during pregnancy, socioeconomic status and postpartum T2DM screening. METHODS: Using the French National Health Data System, this cross-sectional study included all deliveries where the mother had HIP in France in 2015, (n = 76,862). The odds ratio (OR) for attending postpartum screening was calculated via multi-level logistic regression. RESULTS: T2DM screening uptake at six months postpartum was 42·9% [95 % Confidence Interval: 42·6-43·3]. Several characteristics were associated with lower uptake: living in the most deprived area(OR = 0·78[0·74-0·83]); being < 25 years-old (reference age group 25-29;≤17: 0.53 [0·31-0·90];18-24: 0.73[0·69-0·78]); smoking (0·65[0·62-0·68]); obesity (0·93[0·89-0·97]); caesarean delivery (0·95[0·92-0·99]). Factors associated with higher uptake included primiparity (1·30[1·26-1·34]); having followed the French recommendations for HIP screening (1·24[1·20-1·28]); insulin prescription (1·75[1·69-1·81]) and pre-eclampsia (1·30[1·19-1·42]). p < 0.01 is justified due to sample size. CONCLUSION: Improving identification of factors affecting postpartum T2DM screening uptake, such as demographics, socioeconomic context and events during pregnancy, may lead to development of target interventions to aide adherence to screening regime and thereby diagnosis of women with prediabetes or diabetes, for whom secondary and tertiary prevention is crucial.

Intensive Care Unit Hyperglycemia After Cardiac Surgery: Risk Factors and Clinical Outcomes.

OBJECTIVES: Patients with hyperglycemia after cardiac surgery face increased morbidity and mortality due to postoperative complications. The main purpose of this study was to evaluate the incidence of postoperative hyperglycemia, the hyperglycemia risk factors, and its association with clinical outcomes in patients admitted to the cardiac surgery intensive care unit after cardiac surgery. DESIGN: Prospective, observational study. SETTING: Single-center hospital. PARTICIPANTS: Two hundred ten consecutive postoperative cardiac surgery patients admitted to the cardiac surgery intensive care unit. INTERVENTIONS: Patients' blood glucose levels were evaluated immediately after cardiac surgery and every 3 hours daily for 7 days or earlier upon discharge. Intravenous insulin was administered as per the institution's protocol. Perioperative predisposing risk factors for hyperglycemia and clinical outcomes were assessed. MEASUREMENTS AND MAIN RESULTS: Postoperative hyperglycemia, defined as glucose level ≥180 mg/dL, occurred in 30% of cardiac surgery patients. Diabetes mellitus (odds ratio [OR] 6.73; 95% CI [3.2-14.3]; p < 0.001), white blood cell count (OR 1.28; 95% CI [1.1-1.4]; p < 0.001), and EuroSCORE II (OR 1.20; 95% CI [1.1-1.4]; p = 0.004) emerged as independent prognostic factors for hyperglycemia. Moreover, patients with glucose ≥180 mg/dL had higher rates of acute kidney injury (34.9% v 18.9%, p = 0.013), longer duration of mechanical ventilation (959 v 720 min, p = 0.019), and sedation (711 v 574 min, p = 0.034), and higher levels of intensive care unit (ICU)-acquired weakness (14% v 5.5%, p = 0.027) and rate of multiorgan failure (6.3% v 0.7%, p = 0.02) compared with patients with glucose levels <180 mg/dL. CONCLUSIONS: In the intensive care unit, hyperglycemia occurs frequently in patients immediately after cardiac surgery. Diabetes, high EuroSCORE II, and preoperative leukocytosis are independent risk factors for postoperative hyperglycemia. Hyperglycemia is associated with worse clinical outcomes, including a higher rate of acute kidney injury and ICU-acquired weakness, greater duration of mechanical ventilation, and a higher rate of multiorgan failure.

Analysis of the detection rate and related factors of fatty liver disease in physical examination of healthy population in Chengdu district.

BACKGROUND: In the present study, we analyzed the detection rate and related influencing factors of fatty liver in the health examination population in Chengdu area. METHODS: The case-control study was performed to compare the gender, age (years), body mass index (BMI), smoking, drinking, abnormal lipid metabolism, hypertension, hyperglycemia, hyperuricemia Is there any statistically significant difference in the detection rate of diseases such as metabolic syndrome, and logistic regression analysis is conducted to analyze the comprehensive impact of each influencing factor on the prevention of fatty liver disease. RESULTS: Among 14,426 survey subjects, a total of 6717 patients with fatty liver were detected, with a detection rate of 47.22%. There are significant differences in the incidence of fatty liver disease among different gender groups, with the incidence rate in males being significantly higher than that in females (P < .05); The incidence of fatty liver in elderly subjects was significantly higher than that in middle-aged and young subjects (P < .05); The prevalence rate of individuals with a BMI > 24 was significantly higher than that of individuals with a BMI < 24 (P < .05). The prevalence of fatty liver in the population with abnormal lipid metabolism, hypertension, hyperglycemia, hyperuricemia, metabolic syndrome and other diseases was significantly higher (P < .05); After stratified analysis by gender and age, the incidence of fatty liver in males was significantly higher than that in females in the 3 age groups < 60 years old (P < .05); In the age group ≥ 60 years old, the difference in the incidence of fatty liver disease between males and females was significantly reduced, and the difference was not statistically significant (P > .05). CONCLUSION: The health screening of patients with fatty liver should be carried out regularly, and attention should be paid to the intervention and prevention of overweight people and people with basal metabolism diseases such as hyperglycemia and hypertension, so as to reduce the incidence of fatty liver.

Glycemic status during pregnancy according to fasting and post-load glucose values: The association with adverse pregnancy outcomes. An observational study.

AIM: Prognosis of treated hyperglycemia in pregnancy (HIP) may differ according to whether diagnosis following an oral glucose tolerance test (OGTT) is based on high fasting and/or high post-load glucose values. METHODS: From a multiethnic prospective study, we included 8,339 women screened for HIP after 22 weeks of gestation. We evaluated the risk of large-for-gestational-age (LGA) infant (primary endpoint) and other adverse pregnancy outcomes according to HIP status in four groups defined as follows: no HIP (n = 6,832, reference); isolated fasting HIP (n = 465), isolated post-load HIP (n = 646), and fasting and post-load HIP (n = 396). RESULTS: After adjusting for age, body mass index, ethnicity, smoking during pregnancy and parity, compared with no HIP, the adjusted odds ratios [95% confidence interval] for LGA infant were higher in the isolated fasting HIP (1.47 [1.11-1.96]) and fasting and post-load HIP (1.65 [1.23-2.21]) groups, but not in the isolated post-load HIP (1.13 [0.86-1.48]) group. The adjusted odds ratios for preterm delivery and neonatal intensive care unit were higher in the post-load HIP group (1.44 [1.03-2.03] and 1.28 [1.04-1.57], respectively), the fasting and post-load HIP group (1.81 [1.23-2.68] and 1.42 [1.10-1.81], respectively) but not in the isolated fasting HIP group (1.34 [0.90-2.00] and 1.20 [0.94-1.52], respectively). CONCLUSION: Despite glucose-lowering care and adjustment for confounders, compared with no HIP, fasting HIP was associated with a higher rate of LGA infant, whereas post-load HIP was associated with higher preterm delivery and neonatal intensive care unit admission rates.

Role of hyperglycemia in cystic fibrosis pulmonary exacerbations.

BACKGROUND: Hyperglycemia could affect treatment response during cystic fibrosis (CF) exacerbations. We aimed to evaluate the prevalence and associations of hyperglycemia with exacerbation outcomes. We also evaluated feasibility of continuous glucose monitoring (CGM) during exacerbations. METHODS: The STOP2 study assessed efficacy and safety of different durations of intravenous antibiotics for CF exacerbations. We conducted a secondary data analysis of random glucose levels measured as part of clinical care during exacerbations. A small subset of participants also underwent CGM per research protocol. The associations between hyperglycemia, defined as random glucose ≥140 mg/dL, and changes in weight and lung function with exacerbation treatment were evaluated with linear regression after adjustment for confounding variables. RESULTS: Glucose levels were available for 182 STOP2 participants of mean (SD) age 31.6 (10.8) years, baseline percent predicted (pp) FEV1 53.6 (22.5); 37% had CF related diabetes and 27% were on insulin. Hyperglycemia was detected in 44% of participants. Adjusted mean difference (95% CI) was 1.34% (-1.39, 4.08) (p = 0.336) for change in ppFEV1 and 0.33 kg (-0.11, 0.78) (p = 0.145) for change in weight between hyperglycemic and non-hyperglycemic groups. Ten participants not on antidiabetic agents in the 4 weeks prior to enrollment underwent CGM; mean (SD) time spent >140 mg/dL was 24.6% (12.5) with 9/10 participants spending >4.5% time >140 mg/dL. CONCLUSIONS: Hyperglycemia identified with random glucose is prevalent during CF exacerbations but not associated with changes in lung function or weight with exacerbation treatment. CGM is feasible and may provide a useful tool for hyperglycemia monitoring during exacerbations.

Diagnosis and treatment of allograft rejection in islet transplantation.

Islet transplantation stabilizes glycemic control in patients with complicated diabetes mellitus. Rapid functional decline could be due to islet allograft rejection. However, there is no reliable method to assess rejection, and treatment protocols are absent. We aimed to characterize diagnostic features of islet allograft rejection and assess effectiveness of high-dose methylprednisolone treatment. Over a median follow-up of 61.8 months, 22% (9 of 41) of islet transplant recipients experienced 10 suspected rejection episodes (SREs). All first SREs occurred within 18 months after transplantation. Important features were unexplained hyperglycemia (all cases), unexplained C-peptide decrease (ΔC-peptide, 77.1% [-59.1% to -91.6%]; ΔC-peptide:glucose, -76.3% [-49.2% to -90.4%]), predisposing event (5 of 10 cases), and increased immunologic risk (5 of 10 cases). At 6 months post-SRE, patients who received protocolized methylprednisolone (n = 4) had significantly better islet function than untreated patients (n = 4), according to C-peptide (1.39 ± 0.59 vs 0.14 ± 0.19 nmol/L; P = .007), Igls score (good [4 of 4 cases] vs failure [3 of 4 cases] or marginal [1 of 4 cases]; P = .018) and ß score (6.0 [6.0-6.0] vs 1.0 [0.0-3.5]; P = .013). SREs are prevalent among islet transplant recipients and are associated with loss of islet graft function. Timely treatment with high-dose methylprednisolone mitigates this loss. Unexplained hyperglycemia, unexpected C-peptide decrease, a predisposing event, and elevated immunologic risk are diagnostic indicators for SRE.

Risk Factors of Hyperglycemia After Treatment With the AKT Inhibitor Ipatasertib in the Prostate Cancer Setting: A Machine Learning-Based Investigation.

PURPOSE: Hyperglycemia is a major adverse event of phosphatidylinositol 3-kinase/AKT inhibitor class of cancer therapeutics. Machine learning (ML) methodologies can identify and highlight how explanatory variables affect hyperglycemia risk. METHODS: Using data from clinical trials of the AKT inhibitor ipatasertib (IPAT) in the metastatic castrate-resistant prostate cancer setting, we trained an XGBoost ML model to predict the incidence of grade ≥2 hyperglycemia (HGLY ≥ 2). Of the 1,364 patients included in our analysis, 19.4% (n = 265) of patients had HGLY ≥2 events with a median time of first onset of 28 days (range, 0-753 days), and 30.0% (n = 221) of patients on an IPAT regimen had at least one HGLY ≥2 event compared with 7.0% (n = 44) of patients on placebo. RESULTS: An 11-variable XGBoost model predicted HGLY ≥2 events well with an AUROC of 0.83 ± 0.02 (mean ± standard deviation). Using SHapley Additive exPlanations analysis, we found IPAT exposure and baseline HbA1c levels to be the strongest predictors of HGLY ≥2, with additional predictivity of baseline measurements of fasting glucose, magnesium, and high-density lipoproteins. CONCLUSION: The findings support using patients' prediabetic status as a key factor for hyperglycemia monitoring and/or trial exclusion criteria. Additionally, the model and relationships between explanatory variables and HGLY ≥2 described herein can help identify patients at high risk for hyperglycemia and develop rational risk mitigation strategies.

Investigating glycemic control in patients undergoing lower extremity bypass within an enhanced recovery pathway at a single institution.

BACKGROUND: Enhanced recovery pathways (ERPs) aim to lower perioperative stress to facilitate recovery. Limited fasting combined with carbohydrate loading is a common ERP element. The effect of limited fasting has not been elucidated in patients with diabetes. Given the known deleterious effects of poor glycemic control in the perioperative period, such as increased rates of surgical site infection, the associations of preoperative limited fasting with perioperative glycemic control and early outcomes after lower extremity bypass (LEB) were investigated. METHODS: A single institutional retrospective review of patients who underwent infrainguinal LEB from 2016 to 2022 was performed. The ERP was initiated in May 2018. Patients were stratified by diabetes diagnosis and preoperative hemoglobin A1C (HbA1C) levels. Perioperative glycemic control was compared between the limited fasting and traditional fasting patients (nil per os at midnight). Limited fasting was defined as a clear liquid diet until 2 hours before surgery with recommended carbohydrate loading consisting of 400 cc of a clear sports drink (approximately 30 g of carbohydrates). All limited fasting patients were within the ERP. Early perioperative hyperglycemia (EPH) was defined as blood glucose of >180 mg/dL within the first 24 hours of surgery. Perioperative outcomes such as surgical site infection, readmission, reinterventions, and complications were also compared. RESULTS: A total of 393 patients were included (limited fasting patients N = 135; traditional fasting patients N = 258). A trend toward EPH was seen in all limited fasting groups. Evaluating limited fasting within diabetic patients revealed that 74.5% of limited fasting-diabetic patients had EPH compared with 49.6% of traditional fasting-diabetic patients (P = .001). When stratified by the HbA1C level, a significantly higher rate of EPH was seen in the HbA1c >8.0% groups, with 90.5% in the limited fasting patients compared with 67.9% in traditional fasting patients (P = .05). Limited fasting-diabetic patients experience a longer postoperative length of stay at 5.0 days (interquartile range: 3, 9) vs 4.0 days (2, 6) in nondiabetic patients (P = .016). CONCLUSIONS: ERP limited fasting was associated with early perioperative hyperglycemia after LEB, particularly in patients with HbA1C >8.0%. Due to the high prevalence of diabetic patients undergoing LEB under ERP, the role of limited fasting and common glycemic elements of ERP may need to be re-evaluated in this subpopulation.

Association of stress hyperglycemia with clinical outcomes in patients with ST-elevation myocardial infarction undergoing percutaneous coronary intervention: a cohort study.

BACKGROUND: In recent years, several studies have demonstrated that stress hyperglycemia is significantly associated with poor prognosis in patients diagnosed with acute coronary syndrome (ACS). In the present study, we aimed to investigate the potential associations between various markers of stress hyperglycemia, such as admission blood glucose (ABG), fasting blood sugar (FBS), and stress hyperglycemia ratio (SHR) with different definitions, and the occurrence of adverse cardiovascular events in patients diagnosed with ST-elevation myocardial infarction (STEMI) who have undergone percutaneous coronary intervention (PCI). METHODS: Our study enrolled a total of 1099 patients diagnosed with STEMI who underwent PCI from 2016 to 2021. The primary outcomes of this study were in-hospital death and all-cause mortality. RESULTS: Stress hyperglycemia was associated with a higher incidence of in-hospital death (ABG OR: 1.27 95% CI 1.19-1.36; FBS OR: 1.25 95% CI 1.16-1.35; SHR1 OR: 1.61 95% CI 1.21-2.14; SHR2 OR: 1.57, 95%CI 1.22-2.01; SHR3 OR: 1.59, 95%CI 1.24-2.05) and all-cause mortality (ABG HR: 1.10, 95% CI 1.07-1.14; FBS HR: 1.12, 95 CI 1.07-1.17; SHR1 HR: 1.19 95% CI 1.03-1.39; SHR2 HR: 1.28, 95%CI 1.14-1.44; SHR3 HR: 1.29, 95%CI 1.14-1.45) after adjusting for ischemic time, age, gender, BMI, hypertension, hyperlipidemia, diabetes mellitus (DM), current smoking history, chronic kidney disease (CKD), previous history of coronary artery disease (CAD), atrial fibrillation (AF), heart failure (HF), stroke, cancer, culprit vessel, multi-vessel disease. These associations exhibited a non-linear, J-shaped pattern, wherein the risk significantly increased when the ABG and FBS levels exceeded 5mmol/L. Moreover, the inflection point for SHR was estimated to be 1.2. CONCLUSIONS: Stress hyperglycemia was significantly associated with an increased risk of in-hospital death and all-cause mortality in STEMI patients treated with PCI. Stress hyperglycemia should be considered a high-risk prognostic marker in all STEMI patients, regardless of with or without diabetes.

Perioperative Glycemic Surveillance and Control-Current Practices, Efficacy and Impact on Postoperative Outcomes following Infrainguinal Vascular Intervention.

BACKGROUND: Perioperative glycemic control plays a pivotal role in improving postsurgical outcomes. Hyperglycemia occurs frequently in surgical patients and has been associated with higher rates of mortality and postoperative complications. However, no current guidelines exist regarding intraoperative glycemic monitoring of patients undergoing peripheral vascular procedures and postoperative surveillance is often restricted to diabetic patients. We sought to characterize the current practices around glycemic monitoring and efficacy of perioperative glycemic control at our institution. We also examined the impact of hyperglycemia in our surgical population. METHODS: This was a retrospective cohort study performed at the McGill University Health Centre and Jewish General Hospital in Montreal, Canada. Patients undergoing elective open lower extremity revascularization or major amputation between 2019 and 2022 were included. Data collected from the electronic medical record included standard demographics, clinical, and surgical characteristics. Glycemic measurements and perioperative insulin use were recorded. Outcomes included 30-day mortality and postoperative complications. RESULTS: A total of 303 patients were included in the study. Overall, 38.9% of patients experienced perioperative hyperglycemia defined as glucose ≥180 mg/dL (10 mmol/L) during their hospital admission. Only 12 (3.9%) patients within the cohort underwent any intraoperative glycemic surveillance, while 141 patients (46.5%) had an insulin sliding scale prescribed postoperatively. Despite these efforts, 51 (16.8%) patients remained hyperglycemic for at least 40% of their measurements during their hospitalization. Hyperglycemia in our cohort was significantly associated with an increased risk of 30-day acute kidney injury (11.9% vs. 5.4%, P = 0.042), major adverse cardiac events (16.1% vs. 8.6%, P = 0.048), major adverse limb events (13.6% vs. 6.5%, P = 0.038), any infection (30.5% vs. 20.5%, P = 0.049), intensive care unit admission (11% vs. 3.2%, P = 0.006) and reintervention (22.9% vs. 12.4%, P = 0.017) on univariate analysis. Furthermore, multivariable logistic regression including the covariates of age, sex, hypertension, smoking status, diabetic status, presence of chronic kidney disease, dialysis, Rutherford stage, coronary artery disease and perioperative hyperglycemia demonstrated a significant relationship between perioperative hyperglycemia and 30-day mortality (odds ratio [OR]: 25.00, 95% confidence interval [CI]: 2.469-250.00, P = 0.006), major adverse cardiac events (OR: 2.08, 95% CI: 1.008-4.292, P = 0.048), major adverse limb events (OR: 2.24, 95% CI: 1.020-4.950, P = 0.045), acute kidney injury (OR: 7.58, 95% CI: 3.021-19.231, P < 0.001), reintervention (OR: 2.06, 95% CI: 1.117-3.802, P = 0.021), and intensive care unit admission (OR: 3.38, 95% CI: 1.225-9.345, P = 0.019). CONCLUSIONS: Perioperative hyperglycemia was associated with 30-day mortality and complications in our study. Despite this, intraoperative glycemic surveillance occurred rarely in our cohort and current postoperative glycemic control protocols and management failed to achieve optimal control in a significant percentage of patients. Standardized glycemic monitoring and stricter control in the intraoperative and postoperative period therefore represent an area of opportunity for reducing patient mortality and complications following lower extremity vascular surgery.

[Gestational diabetes mellitus (Update 2023)]. / Gestationsdiabetes (GDM) (Update 2023).

Gestational diabetes (GDM) is defined as any degree of glucose intolerance with onset during pregnancy and is associated with increased feto-maternal morbidity as well as long-term complications in mothers and the offspring. Women detected to have diabetes early in pregnancy receive the diagnosis of overt, non-gestational, diabetes (glucose: fasting ≥ 126 mg/dl, spontaneous ≥ 200 mg/dl or HbA1c ≥ 6.5% before 20 weeks of gestation). GDM is diagnosed by an oral glucose tolerance test (oGTT) or increased fasting glucose (≥ 92 mg/dl). Screening for undiagnosed type 2 diabetes at the first prenatal visit is recommended in women at increased risk (history of GDM/pre-diabetes; malformation, stillbirth, successive abortions or birth weight > 4500 g previously; obesity, metabolic syndrome, age > 35 years, vascular disease; clinical symptoms of diabetes (e.g. glucosuria) or ethnic origin with increased risk for GDM/T2DM (Arab, South- and Southeast Asian, Latin American)) using standard diagnostic criteria. Performance of the oGTT (120 min; 75 g glucose) may already be indicated in the first trimester in high-risk women but is mandatory between gestational week 24-28 in all pregnant women with previous non-pathological glucose metabolism. Following WHO recommendations, which are based on the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study, GDM is defined, if fasting venous plasma glucose is ≥ 92 mg/dl or 1 h ≥ 180 mg/dl or 2 h ≥ 153 mg/dl after glucose loading (international consensus criteria). In case of one pathological value a strict metabolic control is mandatory. After bariatric surgery we do not recommend to perform an oGTT due to risk of postprandial hypoglycemia. All women with GDM should receive nutritional counseling, be instructed in blood glucose self-monitoring and motivated to increase physical activity to moderate intensity levels-if not contraindicated (Evidence level A). If blood glucose levels cannot be maintained in the therapeutic range (fasting < 95 mg/dl and 1 h after meals < 140 mg/dl, Evidence level B) insulin therapy should be initiated as first choice (Evidence level A). Maternal and fetal monitoring is required in order to minimize maternal and fetal/neonatal morbidity and perinatal mortality. Regular obstetric examinations including ultrasound examinations are recommended (Evidence level A). Neonatal care of GDM offspring at high risk for hypoglycaemia includes blood glucose measurements after birth and if necessary appropriate intervention. Monitoring the development of the children and recommendation of healthy lifestyle are important issues to be tackled for the whole family. After delivery all women with GDM have to be reevaluated as to their glucose tolerance by a 75 g oGTT (WHO criteria) 4-12 weeks postpartum. Assessment of glucose parameters (fasting glucose, random glucose, HbA1c or optimally oGTT) are recommended every 2-3 years in case of normal glucose tolerance. All women have to be instructed about their increased risk of type 2 diabetes and cardiovascular disease at follow-up. Possible preventive meassures, in particular lifestyle changes as weight management and maintenance/increase of physical activity should be discussed (evidence level A).

Proactive Glucose Screening Tool Effective for Time-sensitive Identification of Hyperglycemia in Childhood Cancer Patients.

Approximately 4% to 35% of pediatric patients undergoing treatment for acute lymphoblastic leukemia (ALL) and lymphoblastic lymphoma (LLy) develop drug-induced hyperglycemia. Though hyperglycemia is associated with poor outcomes, no guidelines for identifying drug-induced hyperglycemia currently exist, and the time course for developing hyperglycemia remains relatively uncharacterized after induction therapy. The present study evaluated a hyperglycemia screening protocol that was implemented to identify hyperglycemia more promptly, examined predictors of hyperglycemia during ALL and LLy therapy, and described the timeline for developing hyperglycemia. A retrospective review of 154 patients diagnosed with ALL or LLy at Cook Children's Medical Center between March 2018 and April 2022 was performed. Predictors of hyperglycemia were examined with Cox regression. The hyperglycemia screening protocol was ordered for 88 (57%) patients. Fifty-four (35%) patients developed hyperglycemia. In multivariate analyses, age 10 years or older (hazard ratio = 2.50, P = 0.007) and weight loss (vs gain) during induction (hazard ratio = 3.39, P < 0.05) were associated with hyperglycemia. The present study identified a population of patients at risk of developing hyperglycemia and identifies strategies for hyperglycemia screening. In addition, the present study showed that some patients developed hyperglycemia after induction therapy, which highlights the importance of continued blood glucose monitoring in at-risk patients. Implications and suggestions for further research are discussed.

Characterization of perioperative glycemic status and dexamethasone use with associated postoperative complications in glioblastoma patients.

PURPOSE: Postoperative morbidity in glioblastoma (GBM) patients can be due to the disease course but can also come from postoperative complications. Our objective was to study the association of dexamethasone use and perioperative hyperglycemia with postoperative complications in GBM patients. METHODS: A single-center, retrospective cohort study was conducted in patients who underwent surgery for primary GBM from 2014-2018. Patients with perioperative fasting blood glucose (FBG) measurements and adequate follow-up to assess for complications were included. RESULTS: A total of 199 patients were included. More than half (53%) had poor perioperative glycemic control (FBG ≥ 7 mM for ≥ 20% perioperative days). Higher dexamethasone dose (≥ 8 mg) was associated with higher FBG on postoperative days 2-4 and 5 (p = 0.02,0.05,0.004,0.02, respectively). Poor glycemic control was associated with increased odds of 30-day any complication and 30-day infection on univariate analysis (UVA), and 30-day any complication and increased length of stay (LOS) on multivariate analysis (MVA). Higher average perioperative daily dexamethasone dose was associated with increased odds of 30-day any complication and 30-day infection on MVA. Elevated hemoglobin A1c (HgbA1c, ≥ 6.5%) was associated with increased odds of 30-day any complication, 30-day infection, and LOS on UVA. In a multivariate linear regression model, only the diagnosis of diabetes mellitus predicted perioperative hyperglycemia. CONCLUSIONS: Perioperative hyperglycemia, higher average dexamethasone use and elevated preoperative HgbA1c are associated with increased risk of postoperative complications in GBM patients. Avoiding hyperglycemia and limiting dexamethasone use in postoperative period may decrease the risk of complications. Select HgbA1c screening may allow the identification of a group of patients at higher risk of complications.

Feasibility of intraoperative continuous glucose monitoring: An observational study in general surgery patients.

BACKGROUND: Perioperative hyperglycemia is associated with adverse outcomes in surgical patients, and major societies recommend intraoperative monitoring and treatment targeting glucose <180-200 mg/dL. However, compliance with these recommendations is poor, in part due to fear of unrecognized hypoglycemia. Continuous Glucose Monitors (CGMs) measure interstitial glucose with a subcutaneous electrode and can display the results on a receiver or smartphone. Historically CGMs have not been utilized for surgical patients. We investigated the use of CGM in the perioperative setting compared to current standard practices. METHOD: This study evaluated the use of Abbott Freestyle Libre 2.0 and/or Dexcom G6 CGMs in a prospective cohort of 94 participants with diabetes mellitus undergoing surgery of ≥3 h duration. CGMs were placed preoperatively and compared to point of care (POC) BG checks obtained by capillary samples analyzed with a NOVA glucometer. Frequency of intraoperative blood glucose measurement was at the discretion of the anesthesia care team, with a recommendation of once per hour targeting BG of 140-180 mg/dL. Of those consented, 18 were excluded due to lost sensor data, surgery cancellation, or rescheduling to a satellite campus resulting in 76 enrolled subjects. There were zero occurrences of failure with sensor application. Paired POC BG and contemporaneous CGM readings were compared with Pearson product-moment correlation coefficients, and Bland-Altman plots. RESULTS: Data for use of CGM in perioperative period was analyzed for 50 participants with Freestyle Libre 2.0, 20 participants with Dexcom G6, and 6 participants with both devices worn simultaneously. Lost sensor data occurred in 3 participants (15%) wearing Dexcom G6, 10 participants wearing Freestyle Libre 2.0 (20%) and 2 of the participants wearing both devices simultaneously. The overall agreement of the two CGM's utilized had a Pearson correlation coefficient of 0.731 in combined groups with 0.573 in Dexcom arm evaluating 84 matched pairs and 0.771 in Libre arm with 239 matched pairs. Modified Bland-Altman plot of the difference of CGM and POC BG indicated for the overall dataset a bias of -18.27 (SD 32.10). CONCLUSIONS: Both Dexcom G6 and Freestyle Libre 2.0 CGMs were able to be utilized and functioned well if no sensor error occurred at time of initial warmup. CGM provided more glycemic data and further characterized glycemic trends more than individual BG readings. Required time of CGM warm up was a barrier for intraoperative use as well as unexplained sensor failure. CGMs had a fixed warm of time, 1 h for Libre 2.0 and 2 h for Dexcom G6 CGM, before glycemic data obtainable. Sensor application issues did not occur. It is anticipated that this technology could be used to improve glycemic control in the perioperative setting. Additional studies are needed to evaluate use intraoperatively and assess further if any interference from electrocautery or grounding devices may contribute to initial sensor failure. It may be beneficial in future studies to place CGM during preoperative clinic evaluation the week prior to surgery. Use of CGMs in these settings is feasible and warrants further evaluation of this technology on perioperative glycemic management.

Referral to the NHS Diabetes Prevention Programme and conversion from nondiabetic hyperglycaemia to type 2 diabetes mellitus in England: A matched cohort analysis.

BACKGROUND: The NHS Diabetes Prevention Programme (NDPP) is a behaviour change programme for adults who are at risk of developing type 2 diabetes mellitus (T2DM): people with raised blood glucose levels, but not in the diabetic range, diagnosed with nondiabetic hyperglycaemia (NDH). We examined the association between referral to the programme and reducing conversion of NDH to T2DM. METHODS AND FINDINGS: Cohort study of patients attending primary care in England using clinical Practice Research Datalink data from 1 April 2016 (NDPP introduction) to 31 March 2020 was used. To minimise confounding, we matched patients referred to the programme in referring practices to patients in nonreferring practices. Patients were matched based on age (≥3 years), sex, and ≥365 days of NDH diagnosis. Random-effects parametric survival models evaluated the intervention, controlling for numerous covariates. Our primary analysis was selected a priori: complete case analysis, 1-to-1 practice matching, up to 5 controls sampled with replacement. Various sensitivity analyses were conducted, including multiple imputation approaches. Analysis was adjusted for age (at index date), sex, time from NDH diagnosis to index date, BMI, HbA1c, total serum cholesterol, systolic blood pressure, diastolic blood pressure, prescription of metformin, smoking status, socioeconomic status, a diagnosis of depression, and comorbidities. A total of 18,470 patients referred to NDPP were matched to 51,331 patients not referred to NDPP in the main analysis. Mean follow-up from referral was 482.0 (SD = 317.3) and 472.4 (SD = 309.1) days, for referred to NDPP and not referred to NDPP, respectively. Baseline characteristics in the 2 groups were similar, except referred to NDPP were more likely to have higher BMI and be ever-smokers. The adjusted HR for referred to NDPP, compared to not referred to NDPP, was 0.80 (95% CI: 0.73 to 0.87) (p < 0.001). The probability of not converting to T2DM at 36 months since referral was 87.3% (95% CI: 86.5% to 88.2%) for referred to NDPP and 84.6% (95% CI: 83.9% to 85.4%) for not referred to NDPP. Associations were broadly consistent in the sensitivity analyses, but often smaller in magnitude. As this is an observational study, we cannot conclusively address causality. Other limitations include the inclusion of controls from the other 3 UK countries, data not allowing the evaluation of the association between attendance (rather than referral) and conversion. CONCLUSIONS: The NDPP was associated with reduced conversion rates from NDH to T2DM. Although we observed smaller associations with risk reduction, compared to what has been observed in RCTs, this is unsurprising since we examined the impact of referral, rather than attendance or completion of the intervention.