Neonatal outcomes according to different glucose threshold values in gestational diabetes: a register-based study.

BACKGROUND: Mild hyperglycaemia is associated with increased birth weight but association with other neonatal outcomes is controversial. We aimed to study neonatal outcomes in untreated mild hyperglycaemia using different oral glucose tolerance test (OGTT) thresholds. METHODS: This register-based study included all (n = 4,939) singleton pregnant women participating a 75 g 2-h OGTT in six delivery hospitals in Finland in 2009. Finnish diagnostic cut-offs for GDM were fasting ≥ 5.3, 1 h ≥ 10.0 or 2-h glucose ≥ 8.6 mmol/L. Women who did not meet these criteria but met the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) criteria (fasting 5.1-5.2 mmol/L and/or 2-h glucose 8.5 mmol/L, n = 509) or the National Institute for Health and Clinical Excellence (NICE) criteria (2-h glucose 7.8-8.5 mmol/L, n = 166) were considered as mild untreated hyperglycaemia. Women who met both the Finnish criteria and the IADPSG or the NICE criteria were considered as treated GDM groups (n = 1292 and n = 612, respectively). Controls were normoglycaemic according to all criteria (fasting glucose < 5.1 mmol/L, 1-h glucose < 10.0 mmol/L and 2-h glucose < 8.5 mmol/L, n = 3031). Untreated mild hyperglycemia groups were compared to controls and treated GDM groups. The primary outcome - a composite of adverse neonatal outcomes, including neonatal hypoglycaemia, hyperbilirubinaemia, birth trauma or perinatal mortality - was analysed using multivariate logistic regression. RESULTS: The risk for the adverse neonatal outcome in untreated mild hyperglycemia was not increased compared to controls (adjusted odds ratio [aOR]: 1.01, 95% confidence interval [CI]: 0.71-1.44, using the IADPSG criteria; aOR: 1.05, 95% CI: 0.60-1.85, using the NICE criteria). The risk was lower compared to the treated IADPSG (aOR 0.38, 95% CI 0.27-0.53) or the treated NICE group (aOR 0.32, 95% CI 0.18-0.57). DISCUSSION: The risk of adverse neonatal outcomes was not increased in mild untreated hyperglycaemia compared to normoglycaemic controls and was lower than in the treated GDM groups. The OGTT cut-offs of 5.3 mmol/L at fasting and 8.6 mmol/L at 2 h seem to sufficiently identify clinically relevant GDM, without excluding neonates with a risk of adverse outcomes.

A risk analysis of alpelisib-induced hyperglycemia in patients with advanced solid tumors and breast cancer.

BACKGROUND: Hyperglycemia is an on-target effect of PI3Kα inhibitors. Early identification and intervention of treatment-induced hyperglycemia is important for improving management of patients receiving a PI3Kα inhibitor like alpelisib. Here, we characterize incidence of grade 3/4 alpelisib-related hyperglycemia, along with time to event, management, and outcomes using a machine learning model. METHODS: Data for the risk model were pooled from patients receiving alpelisib ± fulvestrant in the open-label, phase 1 X2101 trial and the randomized, double-blind, phase 3 SOLAR-1 trial. The pooled population (n = 505) included patients with advanced solid tumors (X2101, n = 221) or HR+/HER2- advanced breast cancer (SOLAR-1, n = 284). External validation was performed using BYLieve trial patient data (n = 340). Hyperglycemia incidence and management were analyzed for SOLAR-1. RESULTS: A random forest model identified 5 baseline characteristics most associated with risk of developing grade 3/4 hyperglycemia (fasting plasma glucose, body mass index, HbA1c, monocytes, age). This model was used to derive a score to classify patients as high or low risk for developing grade 3/4 hyperglycemia. Applying the model to patients treated with alpelisib and fulvestrant in SOLAR-1 showed higher incidence of hyperglycemia (all grade and grade 3/4), increased use of antihyperglycemic medications, and more discontinuations due to hyperglycemia (16.7% vs. 2.6% of discontinuations) in the high- versus low-risk group. Among patients in SOLAR-1 (alpelisib + fulvestrant arm) with PIK3CA mutations, median progression-free survival was similar between the high- and low-risk groups (11.0 vs. 10.9 months). For external validation, the model was applied to the BYLieve trial, for which successful classification into high- and low-risk groups with shorter time to grade 3/4 hyperglycemia in the high-risk group was observed. CONCLUSIONS: A risk model using 5 clinically relevant baseline characteristics was able to identify patients at higher or lower probability for developing alpelisib-induced hyperglycemia. Early identification of patients who may be at higher risk for hyperglycemia may improve management (including monitoring and early intervention) and potentially lead to improved outcomes. REGISTRATION: ClinicalTrials.gov: NCT01219699 (registration date: October 13, 2010; retrospectively registered), ClinicalTrials.gov: NCT02437318 (registration date: May 7, 2015); ClinicalTrials.gov: NCT03056755 (registration date: February 17, 2017).

The correlation between admission hyperglycemia and 30-day readmission after hip fracture surgery in geriatric patients: a propensity score-matched study.

Purpose: This study aimed to investigate the association between admission hyperglycemia and 30-day readmission after hip fracture surgery in geriatric patients. Methods: This retrospective study included 1253 geriatric hip fracture patients. Patients were categorized into normoglycemia(<6.10 mmol/L) and hyperglycemia groups(≥6.10 mmol/L) based on admission blood glucose. We performed multivariable logistic regression analyses and propensity score matching (PSM) to estimate adjusted odds ratios and 95% confidence intervals for 30-day readmission, controlling for potential confounding factors. An analysis of the dose-dependent association between admission blood glucose and the probability of 30-day readmission was performed. Additional subgroup analysis was conducted to examine the impact of other factors on the relationship between admission blood glucose and 30-day readmission. Results: Patients with hyperglycemia had higher 30-day readmission rates than normoglycemic patients before (19.1% vs 9.7%, p<0.001) and after PSM (18.1% vs 12.3%, p=0.035). Admission hyperglycemia was an independent predictor of increased 30-day readmission risk, with an adjusted odds ratio of 1.57 (95% CI 1.08-2.29, p=0.019) after multivariable regression and 1.57 (95% CI 1.03-2.39, p=0.036) after PSM. A dose-response relationship was observed between higher glucose levels and increased readmission risk. Conclusion: Admission hyperglycemia is an independent risk factor for 30-day readmission after hip fracture surgery in the elderly. Routine glucose testing upon admission and perioperative glycemic control may help reduce short-term readmissions in this vulnerable population.

Does the duration of diabetes increase the risk of cancer? A nationwide population-based cohort of patients with new-onset diabetes and a matched reference cohort.

Diabetes mellitus and cancer are both common health issues, but the correlation between these two diseases remains unclear. We investigated the association of cumulative exposure of diabetes mellitus as an indication of hyperglycemia in terms of disease duration on multiple cancer types. We hypothesized that the risk of cancer would increase over time after the onset of diabetes. The study population consisted of a population-based cohort of 398,708 people and it was constructed from the Finnish CARING project. The Diabetes group consisted of 185,258 individuals, and the non-diabetic reference group comprised 187,921 individuals. Over 4.1 million person-years were accumulated, and the median follow-up time was 10.55 years. In the diabetes group, 25,899 cancer cases were observed compared with 23,900 cancers in the non-diabetic group. We did not find a clear relationship between the duration of diabetes mellitus and most cancer types examined. However, for cancers of the pancreas, prostate gland, bronchus, and lungs, a temporal relationship was found. Furthermore, even within the cancer types where the relationship was detected, it did not change over time. These findings indicate that diabetes does not independently increase the risk of cancer. Instead, the development of diabetes may be attributed to shared risk factors with cancer, such as obesity and/or insulin resistance accompanied by hyperinsulinemia. Thus, it is likely that the clock for increased cancer risk starts ticking already before onset of diabetes and hyperglycemia.

The association between patterns of weight change, diabetes status and glycaemia among adults with overweight and obesity.

AIMS: To investigate the associations between weight change patterns and 5-year incident non-diabetic hyperglycaemia (NDH), and glycated haemoglobin (HbA1c) levels among individuals who had overweight or obesity. METHODS: This longitudinal cohort study (N = 435) pooled data from a weight management trial. Participants were adults with a body mass index of ≥28 kg/m2. They were categorised as "no weight loss", "maintainers", and "regainers" based on their weight at 3 months and 12 months after baseline. Multivariable logistic regression models and linear regressions were conducted to examine the associations. RESULTS: Between 1-year and 5-year follow-ups, 77 participants developed NDH. We found no statistically significant association between weight change patterns and incident NDH at 5 years. Among weight loss maintainers, mean HbA1c was -0.15% (95% confidence intervals (CI): -0.22, -0.10) lower after 1 year and -0.15% (95% CI: -0.23, -0.06) lower after 5 years compared to the no weight loss group. There was no difference between weight loss regainers and no weight loss group in HbA1c levels. CONCLUSIONS: Compared to those who did not lose weight, participants who maintained their weight loss had lower HbA1c levels after 1 year and 5 years, which highlights the importance of providing long-term support to prevent weight regain.

Insulin resistance prior to term age in very low birthweight infants: a prospective study.

OBJECTIVE: To explore the glucose-related hormone profile of very low birthweight (VLBW) infants and assess the association between neonatal hyperglycaemia and insulin resistance during the admission period. DESIGN: A prospective observational study-the Very Low Birth Weight Infants, Glucose and Hormonal Profiles over Time study. SETTING: A tertiary neonatal intensive care unit and four neonatal units in county hospitals in Sweden. PATIENTS: 48 infants born <1500 g (VLBW) during 2016-2019. OUTCOME MEASURES: Plasma concentrations of glucose-related hormones and proteins (C-peptide, insulin, ghrelin, glucagon-like peptide 1 (GLP-1), glucagon, leptin, resistin and proinsulin), insulin:C-peptide and proinsulin:insulin ratios, Homoeostatic Model Assessment 2 (HOMA2) and Quantitative Insulin Sensitivity Check (QUICKI) indices, measured on day of life (DOL) 7 and at postmenstrual age 36 weeks. RESULTS: Lower gestational age was significantly associated with higher glucose, C-peptide, insulin, proinsulin, leptin, ghrelin, resistin and GLP-1 concentrations, increased HOMA2 index, and decreased QUICKI index and proinsulin:insulin ratio. Hyperglycaemic infants had significantly higher glucose, C-peptide, insulin, leptin and proinsulin concentrations, and lower QUICKI index, than normoglycaemic infants. Higher glucose and proinsulin concentrations and insulin:C-peptide ratio, and lower QUICKI index on DOL 7 were significantly associated with longer duration of hyperglycaemia during the admission period. CONCLUSIONS: VLBW infants seem to have a hormone profile consistent with insulin resistance. Lower gestational age and hyperglycaemia are associated with higher concentrations of insulin resistance markers.

The effect of frailty on post-discharge management and outcomes of acute glycaemic crises: Analysis of admissions for hypoglycaemia and hyperglycaemia in Australia.

OBJECTIVE: To describe changes in glucose-lowering drug (GLD) dispensing by frailty status for people with diabetes following admission for hypoglycaemia or hyperglycaemia. METHODS: This study included all people with probable type 2 diabetes in the state of Victoria, Australia, admitted to hospital for hypoglycaemia (n = 2,506 admissions) or hyperglycaemia (n = 1,693) between 1 July 2013 and 29 June 2017. Frailty was defined via the Hospital Frailty Risk Score (HFRS). We examined differences in dispensing of GLDs in the year before and after admission using linear regression models adjusted for age, sex, comorbidities, and socioeconomic status. RESULTS: Dispensing of GLDs decreased following hypoglycaemia admission. Decreased dispensing was strongly associated with frailty status, with a change in mean annual GLD dispensing count of -4.11 (-5.05, -3.17) for an HFRS of 15 vs. -0.99 (-1.47, -0.50) for an HFRS of 0. Changes were greatest for metformin and sulfonylureas. Following hyperglycaemia admission, the mean number of annual GLD dispensings increased, with a smaller increase with increasing frailty: 2.44 (1.32, 3.56) for an HFRS of 0 vs. 1.16 (0.18, 2.14) for an HFRS of 15. CONCLUSIONS: Frailty was associated with more conservative diabetes medication management following hypoglycaemia and hyperglycaemia admissions.

Relationship between stress hyperglycaemic ratio and incidence of in-hospital cardiac arrest in patients with acute coronary syndrome: a retrospective cohort study.

BACKGROUND: The stress hyperglycaemic ratio (SHR), a new marker that reflects the true hyperglycaemic state of patients with acute coronary syndrome (ACS), is strongly associated with adverse clinical outcomes in these patients. Studies on the relationship between the SHR and in-hospital cardiac arrest (IHCA) incidence are limited. This study elucidated the relationship between the SHR and incidence of IHCA in patients with ACS. METHODS: In total, 1,939 patients with ACS who underwent percutaneous coronary intervention (PCI) at the Affiliated Hospital of Zunyi Medical University were included. They were divided into three groups according to the SHR: group T1 (SHR ≤ 0.838, N = 646), group T2 (0.838< SHR ≤ 1.140, N = 646), and group T3 (SHR3 > 1.140, N = 647). The primary endpoint was IHCA incidence. RESULTS: The overall IHCA incidence was 4.1% (N = 80). After adjusting for covariates, SHR was significantly associated with IHCA incidence in patients with ACS who underwent PCI (odds ratio [OR] = 2.6800; 95% confidence interval [CI] = 1.6200-4.4300; p<0.001), and compared with the T1 group, the T3 group had an increased IHCA risk (OR = 2.1800; 95% CI = 1.2100-3.9300; p = 0.0090). In subgroup analyses, after adjusting for covariates, patients with ST-segment elevation myocardial infarction (STEMI) (OR = 3.0700; 95% CI = 1.4100-6.6600; p = 0.0050) and non-STEMI (NSTEMI) (OR = 2.9900; 95% CI = 1.1000-8.1100; p = 0.0310) were at an increased IHCA risk. After adjusting for covariates, IHCA risk was higher in patients with diabetes mellitus (DM) (OR = 2.5900; 95% CI = 1.4200-4.7300; p = 0.0020) and those without DM (non-DM) (OR = 3.3000; 95% CI = 1.2700-8.5800; p = 0.0140); patients with DM in the T3 group had an increased IHCA risk compared with those in the T1 group (OR = 2.4200; 95% CI = 1.0800-5.4300; p = 0.0320). The restriction cubic spline (RCS) analyses revealed a dose-response relationship between IHCA incidence and SHR, with an increased IHCA risk when SHR was higher than 1.773. Adding SHR to the baseline risk model improved the predictive value of IHCA in patients with ACS treated with PCI (net reclassification improvement [NRI]: 0.0734 [0.0058-0.1409], p = 0.0332; integrated discrimination improvement [IDI]: 0.0218 [0.0063-0.0374], p = 0.0060). CONCLUSIONS: In patients with ACS treated with PCI, the SHR was significantly associated with the incidence of IHCA. The SHR may be a useful predictor of the incidence of IHCA in patients with ACS. The addition of the SHR to the baseline risk model had an incremental effect on the predictive value of IHCA in patients with ACS treated with PCI.

Frequency and correlates of poor glycemic control in patients with type 2 diabetes at Jimma Medical Centre, Ethiopia: a cross-sectional study.

Introduction: the majority of studies in Ethiopia determine the prevalence of glycemic control employed by fasting blood sugar (FBS), which is impacted by a variety of factors. Hence, the purpose of this study was to assess the status of glycemic control using HbA1c and its correlates in patients with type 2 diabetes in Southwest Ethiopia. Methods: a cross-sectional study was employed among 124 T2 diabetes mellitus (DM) patients at Jimma Medical Center (JMC), Southwest Ethiopia. HbA1c and FBS were estimated using the Cobas 6000 analyzer. The body mass index (BMI) and waist-to-hip ratio were calculated as the standard formula. Data were analyzed by SPSS version 25. Logistic regression analysis was employed to identify independent risk factors associated with poor glycemic control of DM patients. Results: males comprised 63.7% (n=79) of the total respondents. The mean age of aOR: 2.21, 95% CI 1.13, 4.34; p = 0.01f participants was 51.84 ± 11.6 years; 60.5% (n=75) of T2 DM patients were in poor glycemic control (HbA1c ≥ 7%). In multivariate logistic regression analysis, BMI of ≥ 30, (aOR: 2.21, 95% CI 1.13, 4.34) increased waist-to-hip ratio (aOR: 1.63, 95% CI 0.82, 2.18), high systolic blood pressure (aOR: 1.52, 95% CI 1.11, 6.23), high FBS (aOR: 1.61, 95% CI 1.00, 4.12), and longer duration of DM (aOR: 1.23, 95% CI 0.87, 1.88) were associated with poor glycemic control. Conclusion: the level of poor glycemic control in the study population is high. Obesity and/or overweight, central obesity, systolic hypertension, and fasting blood sugar levels were all associated with poor glycemic control in T2 DM patients.

Association of preoperative blood glucose level with delirium after non-cardiac surgery in diabetic patients.

BACKGROUND: Hyperglycemia has shown a negative association with cognitive dysfunction. We analyzed patients with high preoperative blood glucose level and hemoglobin A1c (HbA1c) level to determine the prevalence of postoperative delirium. METHODS: We reviewed a database of 23,532 patients with diabetes who underwent non-cardiac surgery. Acute hyperglycemia was defined as fasting blood glucose > 140 mg/dl or random glucose > 180 mg/dl within 24 h before surgery. Chronic hyperglycemia was defined as HbA1c level above 6.5% within three months before surgery. The incidence of delirium was compared according to the presence of acute and chronic hyperglycemia. RESULTS: Of the 23,532 diabetic patients, 21,585 had available preoperative blood glucose level within 24 h before surgery, and 18,452 patients reported levels indicating acute hyperglycemia. Of the 8,927 patients with available HbA1c level within three months before surgery, 5,522 had levels indicating chronic hyperglycemia. After adjustment with inverse probability weighting, acute hyperglycemia was related to higher incidence of delirium (hazard ratio: 1.33, 95% CI [1.10,1.62], P = 0.004 for delirium) compared with controls without acute hyperglycemia. On the other hand, chronic hyperglycemia did not correlate with postoperative delirium. CONCLUSIONS: Preoperative acute hyperglycemia was associated with postoperative delirium, whereas chronic hyperglycemia was not significantly associated with postoperative delirium. Irrespective of chronic hyperglycemia, acute glycemic control in surgical patients could be crucial for preventing postoperative delirium.

Hyperglycaemia is a causal risk factor for upper limb pathologies.

BACKGROUND: Diabetes (regardless of type) and obesity are associated with a range of musculoskeletal disorders. The causal mechanisms driving these associations are unknown for many upper limb pathologies. We used genetic techniques to test the causal link between glycemia, obesity and musculoskeletal conditions. METHODS: In the UK Biobank's unrelated European cohort (N = 379 708) we performed mendelian randomisation (MR) analyses to test for a causal effect of long-term high glycaemia and adiposity on four musculoskeletal pathologies: frozen shoulder, Dupuytren's disease, carpal tunnel syndrome and trigger finger. We also performed single-gene MR using rare variants in the GCK gene. RESULTS: Using MR, we found evidence that long-term high glycaemia has a causal role in the aetiology of upper limb conditions. A 10-mmol/mol increase in genetically predicted haemoglobin A1C (HbA1c) was associated with frozen shoulder: odds ratio (OR) = 1.50 [95% confidence interval (CI), 1.20-1.88], Dupuytren's disease: OR = 1.17 (95% CI, 1.01-1.35), trigger finger: OR = 1.30 (95% CI, 1.09-1.55) and carpal tunnel syndrome: OR = 1.20 (95% CI, 1.09-1.33). Carriers of GCK mutations have increased odds of frozen shoulder: OR = 7.16 (95% CI, 2.93-17.51) and carpal tunnel syndrome: OR = 2.86 (95% CI, 1.50-5.44) but not Dupuytren's disease or trigger finger. We found evidence that an increase in genetically predicted body mass index (BMI) of 5 kg/m2 was associated with carpal tunnel syndrome: OR = 1.13 (95% CI, 1.10-1.16) and associated negatively with Dupuytren's disease: OR = 0.94 (95% CI, 0.90-0.98), but no evidence of association with frozen shoulder or trigger finger. Trigger finger (OR 1.96 (95% CI, 1.42-2.69) P = 3.6e-05) and carpal tunnel syndrome [OR 1.63 (95% CI, 1.36-1.95) P = 8.5e-08] are associated with genetically predicted unfavourable adiposity increase of one standard deviation of body fat. CONCLUSIONS: Our study consistently demonstrates a causal role of long-term high glycaemia in the aetiology of upper limb musculoskeletal conditions. Clinicians treating diabetes patients should be aware of these complications in clinic, specifically those managing the care of GCK mutation carriers. Upper limb musculoskeletal conditions should be considered diabetes complications.

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.

Maternal and neonatal outcomes according to the timing of diagnosis of hyperglycaemia in pregnancy: a nationwide cross-sectional study of 695,912 deliveries in France in 2018.

AIMS/HYPOTHESIS: We aimed to assess maternal-fetal outcomes according to various subtypes of hyperglycaemia in pregnancy. METHODS: We used data from the French National Health Data System (Système National des Données de Santé), which links individual data from the hospital discharge database and the French National Health Insurance information system. We included all deliveries after 22 gestational weeks (GW) in women without pre-existing diabetes recorded in 2018. Women with hyperglycaemia were classified as having overt diabetes in pregnancy or gestational diabetes mellitus (GDM), then categorised into three subgroups according to their gestational age at the time of GDM diagnosis: before 22 GW (GDM<22); between 22 and 30 GW (GDM22-30); and after 30 GW (GDM>30). Adjusted prevalence ratios (95% CI) for the outcomes were estimated after adjusting for maternal age, gestational age and socioeconomic status. Due to the multiple tests, we considered an association to be statistically significant according to the Holm-Bonferroni procedure. To take into account the potential immortal time bias, we performed analyses on deliveries at ≥31 GW and deliveries at ≥37 GW. RESULTS: The study population of 695,912 women who gave birth in 2018 included 84,705 women (12.2%) with hyperglycaemia in pregnancy: overt diabetes in pregnancy, 0.4%; GDM<22, 36.8%; GDM22-30, 52.4%; and GDM>30, 10.4%. The following outcomes were statistically significant after Holm-Bonferroni adjustment for deliveries at ≥31 GW using GDM22-30 as the reference. Caesarean sections (1.54 [1.39, 1.72]), large-for-gestational-age (LGA) infants (2.00 [1.72, 2.32]), Erb's palsy or clavicle fracture (6.38 [2.42, 16.8]), preterm birth (1.84 [1.41, 2.40]) and neonatal hypoglycaemia (1.98 [1.39, 2.83]) were more frequent in women with overt diabetes. Similarly, LGA infants (1.10 [1.06, 1.14]) and Erb's palsy or clavicle fracture (1.55 [1.22, 1.99]) were more frequent in GDM<22. LGA infants (1.44 [1.37, 1.52]) were more frequent in GDM>30. Finally, women without hyperglycaemia in pregnancy were less likely to have preeclampsia or eclampsia (0.74 [0.69, 0.79]), Caesarean section (0.80 [0.79, 0.82]), pregnancy and postpartum haemorrhage (0.93 [0.89, 0.96]), LGA neonate (0.67 [0.65, 0.69]), premature neonate (0.80 [0.77, 0.83]) and neonate with neonatal hypoglycaemia (0.73 [0.66, 0.82]). Overall, the results were similar for deliveries at ≥37 GW. Although the estimation of the adjusted prevalence ratio of perinatal death was five times higher (5.06 [1.87, 13.7]) for women with overt diabetes, this result was non-significant after Holm-Bonferroni adjustment. CONCLUSIONS/INTERPRETATION: Compared with GDM22-30, overt diabetes, GDM<22 and, to a lesser extent, GDM>30 were associated with poorer maternal-fetal outcomes.

Relationship between stress hyperglycemia ratio and acute kidney injury in patients with congestive heart failure.

BACKGROUND: The stress hyperglycemia ratio (SHR) has been demonstrated as an independent risk factor for acute kidney injury (AKI) in certain populations. However, this relationship in patients with congestive heart failure (CHF) remains unclear. Our study sought to elucidate the relationship between SHR and AKI in patients with CHF. METHODS: A total of 8268 patients with CHF were included in this study. We categorized SHR into distinct groups and evaluated its association with mortality through logistic or Cox regression analyses. Additionally, we applied the restricted cubic spline (RCS) analysis to explore the relationship between SHR as a continuous variable and the occurrence of AKI. The primary outcome of interest in this investigation was the incidence of AKI during hospitalization. RESULTS: Within this patient cohort, a total of 5,221 (63.1%) patients experienced AKI during their hospital stay. Upon adjusting for potential confounding variables, we identified a U-shaped correlation between SHR and the occurrence of AKI, with an inflection point at 0.98. When the SHR exceeded 0.98, for each standard deviation (SD) increase, the risk of AKI was augmented by 1.32-fold (odds ratio [OR]: 1.32, 95% CI: 1.22 to 1.46). Conversely, when SHR was below 0.98, each SD decrease was associated with a pronounced increase in the risk of AKI. CONCLUSION: Our study reveals a U-shaped relationship between SHR and AKI in patients with CHF. Notably, we identified an inflection point at an SHR value of 0.98, signifying a critical threshold for evaluating AKI in this population.

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.

Supporting Type 1 and Type 2 Diabetes Care in the Hemodialysis Unit: A Quality-improvement Initiative Throughout the COVID-19 Pandemic.

OBJECTIVE: People living with diabetes mellitus (DM) and chronic kidney disease can have difficulty attending multiple appointments to receive DM care. We developed and studied the utility of a DM outreach program to offer in the hemodialysis (HD) unit. METHODS: We conducted a quality improvement project in a satellite HD unit in London, Ontario, Canada, between August 1, 2019, and July 31, 2022. We assessed for baseline gaps in DM care among those with DM, performed root-cause analysis with key stakeholders to identify critical drivers of gaps, and conceptualized a certified diabetes educator-led outreach program to offer in the HD unit. We aimed to improve DM self-monitoring, hypo- and hyperglycemia, and DM-related screening. We used run and control charts to track outcome measures over time and modified our outreach program iteratively. RESULTS: Fifty-eight persons with DM receiving HD participated in our program. Support spanned multiple waves of the COVID-19 pandemic. With 4 tests of change, we observed improvement in DM self-monitoring with a modest decline in self-reported hyperglycemia. There were no adverse consequences, and satisfaction with our program was high. CONCLUSIONS: Although we did not meet all measures of success during the pandemic, outreach DM support in the HD unit appeared to improve self-monitoring and self-reported hyperglycemia. Similar programs could be modified and implemented in other centres.

Associations Between Incarceration History and Risk of Hypertension and Hyperglycemia: Consideration of Differences among Black, Hispanic, Asian and White Subgroups.

BACKGROUND: Studies have shown that adults with a history of incarceration have elevated cardiovascular (CVD) risk. Research on racial/ethnic group differences in the association between incarceration and CVD risk factors of hypertension and hyperglycemia is limited. OBJECTIVE: To assess racial/ethnic group differences in the association between incarceration and hypertension and hyperglycemia. DESIGN: We performed a secondary data analysis using the National Longitudinal Survey of Adolescent to Adult Health (Add Health). Using modified Poisson regression, we estimated the associations between lifetime history of incarceration reported during early adulthood with hypertension and hyperglycemia outcomes measured in mid-adulthood, including incident diagnosis. We evaluated whether associations varied by self-reported race/ethnicity (non-Hispanic White, non-Hispanic Black, Hispanic, and Asian). PARTICIPANTS: The analytic sample included 4,015 Add Health respondents who self-identified as non-Hispanic White, Non-Hispanic Black, Hispanic, and Asian, and provided incarceration history and outcome data. MAIN MEASURES: Outcome measures included (1) hypertension (2) systolic blood pressure ≥ 130 mmHg, and (3) hyperglycemia. KEY RESULTS: In non-Hispanic Black and non-Hispanic White participants, there was not evidence of an association between incarceration and measured health outcomes. Among Hispanic participants, incarceration was associated with hyperglycemia (Adjusted Risk Ratio (ARR): 2.1, 95% Confidence Interval (CI): 1.1-3.7), but not with hypertension risk. Incarceration was associated with elevated systolic blood pressure (ARR: 3.1, CI: 1.2-8.5) and hypertension (ARR: 1.7, CI: 1.0-2.8, p = 0.03) among Asian participants, but not with hyperglycemia risk. Incarceration was associated with incident hypertension (ARR 2.5, CI 1.2-5.3) among Asian subgroups. CONCLUSIONS: Our findings add to a growing body of evidence suggesting that incarceration may be linked to chronic disease outcomes. Race/ethnic-specific results, while limited by small sample size, highlight the need for long-term studies on incarceration's influence among distinct US groups.

Leptin and adiposity measures from birth to later childhood: Findings from the Hyperglycemia and Adverse Pregnancy Outcomes Follow-Up Study.

BACKGROUND: Cord blood (CB) leptin is positively associated with adiposity at birth, but the association with child adiposity is unclear. OBJECTIVES: We hypothesized that CB leptin is positively associated with adiposity in peripubertal children and with childhood leptin. METHODS: Leptin was measured in 986 CB and 931 childhood stored samples from a prospective birth cohort. Adiposity measures were collected at birth and mean age 11.5 years. Linear and logistic regression analyses were used to evaluate associations between log-transformed CB leptin and neonatal and childhood adiposity measures as continuous and categorical variables, respectively. RESULTS: CB leptin was positively associated with neonatal and childhood adiposity. Childhood associations were attenuated when adjusted for maternal body mass index (BMI) and glucose, but remained statistically significant for childhood body fat percentage (ß = 1.15%, confidence interval [CI] = 0.46-1.84), body fat mass (ß = 0.69 kg, 95% CI = 0.16-1.23), sum of skin-folds (ß = 1.77 mm, 95% CI = 0.31-3.24), log-transformed child serum leptin (ß = 0.13, 95% CI = 0.06-0.20), overweight/obesity (OR = 1.21, 95% CI = 1.03-1.42), obesity (OR = 1.31, 95% CI = 1.04-1.66) and body fat percentage >85th percentile (OR = 1.38, 95% CI = 1.12-1.73). Positive associations between newborn adiposity measures and CB leptin confirmed previous reports. CONCLUSION: CB leptin is positively associated with neonatal and childhood adiposity and child leptin levels, independent of maternal BMI and maternal hyperglycemia. CB leptin may be a biomarker of future adiposity risk.

Predictors of Poor Glycemic Control and Increased Glucose Variability Among Admitted Moderate to Critical COVID-19 Patients with Type 2 Diabetes Mellitus: A Single Center Cross-sectional Study.

Objectives: COVID-19 exacerbates the long-standing, low-grade chronic inflammation observed in diabetes leading to heightened insulin resistance and hyperglycemia. Mortality increases with hyperglycemia and poor glycemic variability, hence, this study aims to identify the predictors associated with poor glycemic control and increased glucose variability among patients with COVID-19 and Type 2 Diabetes Mellitus (T2DM). Methodology: A retrospective chart review of 109 patients with moderate to severe COVID-19 and T2DM admitted from March 2020 to June 2021 was done. Logistic regression was done to determine predictors for hyperglycemia and poor variability. Results: Of the 109 patients, 78% had hyperglycemia and poor variability and 22% had no poor outcomes. Chronic kidney disease (eOR 2.83, CI [1.07-7.46], p = 0.035) was associated with increased glycemic variability. In contrast, increasing eGFR level (eOR 0.97, CI [0.96-0.99], p = 0.004) was associated with less likelihood of increased variability. Hs-CRP (eOR 1.01, CI [1.00-1.01], p = 0.011), HbA1c (eOR 1.86, CI [1.23-2.82], p = 0.003), severe COVID-19 (eOR 8.91, CI [1.77-44.94], p = 0.008) and critical COVID-19 (eOR 4.42, CI [1.65-11.75], p = 0.003) were associated with hyperglycemia. Steroid use (eOR 71.17, CI [8.53-593.54], p<0.001) showed the strongest association with hyperglycemia. Conclusion: Potential clinical, laboratory and inflammatory profiles were identified as predictors for poor glycemic control and variability outcomes. HbA1c, hs-CRP, and COVID-19 severity are predictors of hyperglycemia. Likewise, chronic kidney disease is a predictor of increased glycemic variability.

Patterns of metabolic syndrome and associated factors in women from the ELSA-Brasil: a latent class analysis approach.

This study aimed to identify patterns of metabolic syndrome among women and estimate their prevalence and relationship with sociodemographic and biological characteristics. In total, 5,836 women were evaluated using baseline data from the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil). Patterns of metabolic syndrome were defined via latent class analysis, using the following metabolic abnormalities as indicators: abdominal obesity, hyperglycemia, hypertension, hypertriglyceridemia, and reduced HDL cholesterol. The relationship between these patterns and individual characteristics was assessed using latent class analysis with covariates. Three patterns of metabolic syndrome were identified: high metabolic expression, moderate metabolic expression, and low metabolic expression. The first two patterns represented most women (53.8%) in the study. Women with complete primary or secondary education and belonging to lower social classes were more likely to have higher metabolic expression. Black and mixed-race women were more likely to have moderate metabolic expression. Menopausal women aged 50 years and older were more often classified into patterns of greater health risk. This study addressed the heterogeneous nature of metabolic syndrome, identifying three distinct profiles for the syndrome among women. The combination of abdominal obesity, hyperglycemia, and hypertension represents the main metabolic profile found among ELSA-Brasil participants. Sociodemographic and biological factors were important predictors of patterns of metabolic syndrome.