Search Results (139)

Background: Pre-existing diabetes mellitus is prevalent among critically ill adults and can influence initial glycemic targets, therapeutic decisions, and early risk stratification in the intensive care unit (ICU). However, diabetes status may be distributed across heterogeneous electronic health record (EHR) sources and may be incomplete at the time of ICU admission, particularly for inter-facility transfers. Methods: Using the public WiDS Datathon 2021 tabular release derived from the Global Open-Source Severity of Illness Score (GOSSIS) initiative, we conducted a retrospective machine-learning benchmarking study for admission-time identification of documented diabetes status in ICU patients. Candidate predictors included demographics, admission characteristics, anthropometrics, day-1 physiologic and laboratory summaries, APACHE-related variables, comorbidity indicators, and site descriptors. We compared CatBoost, random forest, tuned XGBoost, tuned LightGBM, histogram-based gradient boosting, and a soft-voting ensemble combining XGBoost, LightGBM, and histogram-based gradient boosting. Because class imbalance was a central concern, the final workflow emphasized model-intrinsic class weighting and threshold-aware evaluation rather than synthetic oversampling. Results: In the primary leakage-mitigated random validation split, the voting ensemble achieved the highest overall balance, with AUROC 0.8539, precision 0.5671, recall 0.6690, and F1-score 0.6138. Tuned LightGBM was the most sensitivity-oriented individual model, achieving recall 0.7677 and AUROC 0.8537, although with lower precision and a less favorable Brier score. Ablation analyses clarified the source of this performance: removing leakage-prone and APACHE-related variables caused only modest decreases in discrimination, whereas the strict reduced model that also excluded glucose-like predictors produced a marked decline, with LightGBM AUROC falling to 0.7432 and the voting ensemble AUROC falling to 0.7448. These findings, together with SHAP analyses identifying day-1 glucose maximum, day-1 glucose minimum, BMI, age, hemoglobin, and related clinical variables as major contributors, indicate that glucose-related admission variables remained the dominant predictive signal. In grouped hospital validation, tuned LightGBM maintained recall of 0.7684 while AUROC decreased modestly to 0.8443, indicating preserved case detection under stricter site separation but reduced precision. Precision–recall analysis further showed that average precision decreased from 0.622 under random validation to 0.551 under grouped validation; at a high-sensitivity grouped-site operating point, a probability threshold of 0.4537 achieved recall of 0.8001 with precision of 0.4314. Calibration curves and Brier scores showed that predicted probabilities were imperfectly calibrated. Conclusions: Although the dominance of glucose-related predictors is clinically plausible for identifying documented diabetes status, early glycemic measurements in critically ill patients may also partly capture acute stress physiology, treatment-related effects, monitoring intensity, or other forms of acute dysglycemia rather than chronic diabetes status alone. Therefore, these findings support gradient-boosted and ensemble models as reproducible tools for ICU admission-time phenotyping of documented diabetes status, but the proposed system should be interpreted primarily as a screening-oriented phenotyping aid for chart review, cohort enrichment, or workflow support, not as a stand-alone diagnostic tool. Further external validation, recalibration, threshold selection matched to intended use, and clinical review are needed before deployment. Full article

Chronic low-grade inflammation is a key feature of obesity-associated dysglycemia, yet substantial heterogeneity exists in inflammatory responses among individuals with normoglycemia, prediabetes, and type 2 diabetes mellitus (T2DM). Whether circulating inflammatory protein profiles define distinct patient phenotypes beyond conventional glycemic classification remains incompletely understood. In this cross-sectional analysis of 142 individuals with severe obesity, plasma inflammatory proteins were quantified using Olink proximity extension assay technology. Subjects were stratified by glycemic status (noDM, normoglycemia; PreDM, prediabetes and T2DM) while maintaining comparable distributions of metabolic dysfunction-associated steatotic liver disease. Differential expression analyses were performed across glycemic groups, and unsupervised topological data analysis (TDA) was applied to identify inflammatory protein-based patient subgroups. Several inflammatory proteins were significantly upregulated in T2DM and PreDM compared with noDM, with interleukin-8 (IL-8), Fms-relatedlike tyrosine kinase 3 ligand (Flt3L), and CUB domain containing protein (CDCP1) showing the largest significant differences. NPX distributions of these proteins exhibited gradual increases across glycemic stages with substantial inter-individual variability. TDA identified seven clusters defined by distinct inflammatory protein signatures. One cluster was enriched for individuals with T2DM and characterized by coordinated upregulation of IL-8, Flt3L, CDCP1, and additional immune- and cytokine-related proteins, whereas other clusters displayed alternative inflammatory profiles that were not explained by glycemic status alone. Inflammatory proteomic profiling in severe obesity reveals both glycemia-associated protein changes and distinct inflammatory phenotypes that transcend conventional clinical classification. Integration of differential expression analysis with TDA highlights heterogeneity in inflammatory states, supporting a hypothesis-generating framework for future studies aimed at validating these proteomic patterns and clarifying their longitudinal relevance in obesity-related dysglycemia. Full article

Noninvasive blood glucose monitoring is crucial for detecting early dysglycemia, yet continuous glucose monitors remain invasive and costly. Electrocardiogram (ECG) and its derived heart rate variability (HRV) measure may offer a noninvasive indicator of autonomic and cardiac responses associated with acute changes in glucose. In this study, 30 adults underwent a 75 g oral glucose tolerance test with concurrent ECG Holter and interstitial glucose monitoring. From these recordings, HRV and ECG features were extracted. A deep learning classifier with HRV and ECG was then trained to detect hyperglycemia (glucose ≥ 180 mg/dL). Cross-correlation analysis confirmed a significant association between HRV and glucose (Pearson r ~0.65, p < 0.05) when aligning each participant’s data according to individual response delays. The model achieved high classification performance under rigorous temporal validation (accuracy ~89%, area under the receiver operating characteristic curve ~0.89). Saliency analyses revealed that the classifier’s decisions focus on distinct ECG waveform transitions and key HRV features linked to glucose-induced autonomic changes. Overall, acute hyperglycemia elicited discernible changes in HRV and cardiac conduction, supporting the feasibility of this physiologically grounded approach for detecting the acute hyperglycemic phase under controlled conditions. This method holds promise for real-time implementation in wearable devices, enabling early diabetes risk screening. Full article

Postprandial variability in glucose and protein levels is one of the elements of insulin resistance (IR) and prediabetes, which is an area precursor to type 2 diabetes mellitus (DM). The objective of the study was a comprehensive proteomic analysis according to glucose tolerance in the general population who did not self-report DM or other diseases. We used Olink^® Reveal, a novel, high-throughput platform by Olink Proteomics based on their Proximity Extension Assay (PEA), to identify levels of 1034 circulating proteins in small volumes (4 µL) of plasma samples. The study enrolled 508 participants (mean age 52 ± 10.5 years, 47.2% men) from the population-based study, Bialystok PLUS Polish Longitudinal University Study. The study population was categorized according to glucose metabolism in comparison to impaired fasting blood glucose (IFG), impaired glucose tolerance (IGT), and newly diagnosed DM. Analysis of variance (ANOVA) adjusted for age, weight, fat mass, lean mass, and body mass index (BMI), identified 19 proteins significantly associated with categories of glucose tolerance. Of the five markers with the greatest ability to distinguish newly diagnosed diabetes from non-diabetic participants, paralemmin 2 performed best (AUC = 0.81; 77% sensitivity, 75% specificity), whereas furin was the most accurate for detecting any abnormal glucose regulation (AUC = 0.69). A linear regression model adjusted for the same confounding factors showed statistically significant associations between Hb_A1c levels and 37 proteins. Our findings highlight multiple proteins with significantly different levels across categories of glucose tolerance, especially between the healthy controls and the group with newly diagnosed DM. The consistent patterns of protein level differences, independent of body composition, suggest potential involvement in the progression of glucose metabolism disturbances and provide unique insights into pathomechanisms. These findings identify PALM2, FURIN, PDZK1, ACAA1, and IL18R1 as potential biomarkers of early dysglycemia. Full article

Activating PIK3CA mutations occur in approximately 40% of hormone receptor-positive (HR+)/HER2-negative breast cancers and represent a major driver of endocrine resistance. The PI3Kα-selective inhibitor alpelisib, in combination with fulvestrant, significantly improves progression-free survival in patients with PIK3CA-mutant disease, as demonstrated in the SOLAR-1 trial. However, this therapeutic strategy is frequently complicated by treatment-induced hyperglycemia, a metabolic disturbance that promotes oxidative stress, mitochondrial dysfunction, and inflammatory signaling, thereby increasing cardiovascular vulnerability. Sodium–glucose cotransporter-2 (SGLT2) inhibitors have emerged as cardiometabolic modulators with benefits extending beyond glucose lowering. In this study, we used a human cardiomyocyte in vitro model designed to recapitulate the hyperglycemic metabolic milieu observed in breast cancer patients receiving PI3Kα-targeted therapy, to investigate whether the SGLT2 inhibitor dapagliflozin directly protects cardiomyocytes from alpelisib- and fulvestrant-induced injury. Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) were cultured under hyperglycemic conditions (25 mM glucose) to mimic the metabolic environment associated with PI3Kα inhibitor-induced dysglycemia. Cells were exposed to alpelisib (100 nM) and fulvestrant (100 nM), alone or in combination, in the absence or presence of dapagliflozin (1 μM). Cardiomyocyte viability was assessed using the MTS assay, mitochondrial function by TMRM-based mitochondrial membrane potential (ΔΨm) measurements, and apoptosis by caspase-3 quantification. Cardiomyocyte injury was evaluated by release of cardiac troponin I and heart-type fatty acid binding protein (H-FABP). Lipid peroxidation markers (MDA and 4-HNE) were measured to assess oxidative membrane damage. Intracellular inflammasome-related signaling (NLRP3 and MyD88) and secreted inflammatory mediators (IL-1β, IL-18, IL-6, TNF-α, and CCL2) were quantified by ELISA. Exposure to alpelisib, particularly in combination with fulvestrant, significantly reduced cardiomyocyte viability, induced mitochondrial depolarization, and increased caspase-3-mediated apoptotic signaling. These alterations were accompanied by elevated lipid peroxidation (MDA and 4-HNE) and increased release of cardiac injury biomarkers (troponin I and H-FABP). Alpelisib-based treatments also activated inflammasome-related signaling, as indicated by increased intracellular NLRP3 and MyD88 levels and enhanced secretion of pro-inflammatory mediators (IL-1β, IL-18, IL-6, TNF-α, and CCL2). Co-treatment with dapagliflozin significantly attenuated these alterations, preserving mitochondrial membrane potential, reducing apoptotic signaling, limiting oxidative membrane damage, and suppressing inflammatory cytokine release. This study provides evidence that alpelisib-based therapy under hyperglycemic conditions is associated with oxidative, mitochondrial, and inflammatory stress responses in human cardiomyocytes, recapitulating key features of cardiometabolic stress relevant to PI3Kα-targeted therapy. Importantly, dapagliflozin markedly attenuated these alterations, supporting a potential cardioprotective role that may extend beyond glycemic control. These findings provide a mechanistic rationale for further investigation of SGLT2 inhibition as a cardiometabolic protective strategy in patients receiving PI3Kα inhibitor-based cancer therapy. Full article

Background and Objective: The aim of this study is to describe the frequency of newly detected dysglycemia, including hyperglycemia and newly diagnosed diabetes mellitus, among hospitalized COVID-19 patients without previously known diabetes and to identify associated clinical and therapeutic factors, in an exploratory, descriptive manner. Materials and Methods: We conducted a retrospective study on 562 COVID-19 patients. Demographic and clinical data were collected at admission and during hospitalization. Newly diagnosed diabetes mellitus was defined based on plasma glucose values meeting international diagnostic criteria during hospitalization in patients without prior diabetes, while newly altered blood sugar referred to transient hyperglycemia or impaired fasting glucose not fulfilling diabetes criteria. Comparisons between groups were performed using appropriate statistical tests, with a p-value < 0.05 considered statistically significant. Results: Out of the total number of 562 COVID-19 patients, 14 (2.49%) were classified as having newly diagnosed diabetes, and 27 (4.8%) as having newly altered blood sugar levels. The median age of the participants was 67.5 years (interquartile range: 59.75; 71.75). Newly diagnosed diabetes was more frequently observed among patients presenting with gastrointestinal symptoms, elevated inflammatory markers, and those receiving specific in-hospital treatments. Newly altered blood sugar levels were more commonly associated with dyslipidemia, respiratory symptoms at admission, oxygen therapy, and selected COVID-19 treatments. COVID-19 vaccination status was descriptively stratified by admission period. Conclusions: New interdisciplinary approaches may support the identification and monitoring of glycemic alterations in hospitalized COVID-19 patients, with potential implications for clinical management and public health strategies. Full article

Background: Severe obesity is associated with chronic low-grade inflammation, dysglycemia, and higher periodontitis risk. Sleeve gastrectomy (SG) is now a dominant bariatric procedure and reliably improves weight and metabolic status yet reported oral and periodontal trajectories after surgery remain heterogeneous. Objective: To synthesize SG-centered evidence on periodontal outcomes, oral and gut microbiome remodeling, and mechanistic pathways that may link postoperative physiology to the gut–oral axis. Methods: We conducted a structured narrative review guided by SANRA principles using targeted searches of PubMed/MEDLINE, Web of Science, Scopus, and Embase, complemented by citation chaining of key reviews and mechanistic anchor papers; evidence was organized into clinical, oral microbiome, gut microbiome, and mechanistic gut–oral axis streams and interpreted with a pragmatic evidence hierarchy. Results: Small prospective SG cohorts suggest bleeding on probing (BOP), gingival indices, and sometimes probing depth (PD) may improve in some patients, particularly alongside weight loss, improved glycemic control, and lower systemic inflammatory burden, whereas clinical attachment level (CAL) and longer-term structural trajectories remain mixed; mixed-procedure syntheses also report early deterioration in some settings. Oral microbiome findings after bariatric surgery are site- and time-dependent, and salivary signals do not necessarily mirror subgingival plaque, whereas gut microbiome remodeling and bile acid signaling changes are more consistently reported and provide plausible but indirect mediator candidates. At the same time, reflux, vomiting, salivary changes, diet patterning, medications, and periodontal care can modify or counteract potential periodontal benefits and may increase competing risks such as caries or erosive tooth wear. Conclusions: The SG–gut–oral axis-periodontal pathway is a biologically plausible working hypothesis rather than a proven causal pathway in humans. The present evidence for any periodontal benefit relies mainly on small observational cohorts and is most credibly demonstrated for inflammatory, not structural, endpoints. Full article

Background/Objective: Women with a history of gestational diabetes mellitus (GDM) are at increased risk of type 2 diabetes mellitus (T2DM), dysglycemia, and dyslipidemia. However, the role of postpartum weight change in long-term metabolic outcomes remains unclear. Here, we determined the long-term incidence of dysglycemia and dyslipidemia after GDM and evaluated whether postpartum changes in body mass index (BMI) independently predicted these outcomes. Methods: This single-center prospective cohort study included 205 Japanese women diagnosed with GDM. All participants underwent a 75 g oral glucose tolerance test at 6–12 weeks postpartum. The incidence of impaired fasting glucose (IFG), impaired glucose tolerance (IGT), T2DM, and dyslipidemia was evaluated over a median follow-up of 3.6 years. Cumulative incidence was estimated using the Kaplan–Meier method, and Cox proportional hazards models identified independent risk factors, particularly postpartum BMI change. Results: During follow-up, 42.4%, 6.3%, and 35.6% of women developed IFG or IGT (prediabetes), T2DM, and dyslipidemia, respectively. The estimated cumulative incidence rates at 6 years postpartum were 57.1% and 50% for IFG/IGT and dyslipidemia, respectively, whereas the 5-year incidence of T2DM was 10.3%. Postpartum BMI increase was independently associated with new-onset dysglycemia. No independent predictor of T2DM progression was identified. Dyslipidemia was independently associated with higher pre-pregnancy BMI and multiparity, whereas postpartum BMI change was not independently associated after multivariable adjustment. Conclusions: Postpartum BMI change was independently associated with dysglycemia in women with a history of GDM. These findings suggest that postpartum weight change may help identify women at higher risk of subsequent metabolic abnormalities, particularly dysglycemia, in this high-risk population, although causal relationships cannot be inferred from this observational study. Full article

Background/Objectives: To investigate how β-cell glucose sensitivity, insulin clearance, and insulin sensitivity interact to determine glucose tolerance in a population without overt diabetes. Methods: We analyzed data from 54 individuals without diabetes (age: 44 years, IQR: 27–56; 63% females; BMI: 24.5 kg/m², IQR: 21.9–28.7; HbA1c 33.26 mmol/mol, IQR: 32.13–35.51) undergoing a 3-h OGTT. β-cell glucose sensitivity, insulin clearance, and insulin sensitivity were assessed via modeling of OGTT data. Their relationship with glucose tolerance was evaluated through linear regression models. Results: β-cell glucose sensitivity strongly predicted glucose tolerance during the OGTT (IQR increase effect: −87 mg/dL; 95% CI: −141, −32; p = 0.003) but not fasting glucose (p = 0.4). Patients with lower β-cell glucose sensitivity showed the widest range of glucose tolerance during the OGTT, some approaching diabetic levels whereas others tolerating glucose well; insulin sensitivity was the strongest determinant of this variance (IQR increase effect: −49 mg/dL; 95% CI: −68, −31; p < 0.001) significantly influencing the relationship between β-cell glucose sensitivity and glucose tolerance (interaction term p = 0.035). Conversely, insulin clearance did not show a statistically significant association with mean glucose levels during the OGTT (β: 4.2; 95% CI: −8.0, 16; p = 0.5). However, a non-linear relationship between insulin clearance and β-cell glucose sensitivity was identified, and three distinct metabolic subgroups were defined, highlighting the heterogeneity underlying the development of dysglycemia. Conclusions: β-cell glucose sensitivity is the primary determinant of glucose tolerance during an oral glucose challenge. While high β-cell glucose sensitivity often overcomes low insulin sensitivity, the latter becomes crucial when β-cell glucose sensitivity is low. The identification of distinct metabolic profiles, related to insulin secretion and clearance, highlights the heterogeneity of the transition from glucose tolerance to dysglycemia. Full article

Accurate perioperative glucose monitoring is essential in dogs undergoing general anesthesia, yet most validation studies of handheld glucometers have been performed under stable outpatient conditions. This prospective clinical validation study evaluated the analytical agreement, diagnostic performance, and ISO 15197 compliance of a human-calibrated (Accu-Chek) and a veterinary-specific (Centrivet GK) handheld glucometer compared with a laboratory spectrophotometric reference method in 34 anesthetized dogs (99 paired measurements per device). Linear mixed-effects modeling demonstrated significant method effects (p < 0.001), with the veterinary-specific device overestimating glucose concentrations relative to the reference method (β = 20.79 mg/dL; 95% CI: 8.08–33.50; p = 0.001), whereas the human-calibrated device did not differ significantly (β = 7.18 mg/dL; 95% CI: −5.53–19.89; p = 0.267). Bland–Altman analysis showed mean bias of 4.44 mg/dL (95% CI: 0.73–8.16) for the human-calibrated device and 22.72 mg/dL (95% CI: 18.22–27.21) for the veterinary-specific device. Passing–Bablok regression identified proportional bias only for the veterinary-specific device (slope 1.19; 95% CI: 1.01–1.34). ISO compliance was 69.7% and 39.4%, respectively. For hyperglycemia detection, AUC values were 0.9566 (95% CI: 0.8955–1.0000) and 0.9757 (95% CI: 0.9479–1.0000); for hypoglycemia, 0.8567 (95% CI: 0.7557–0.9578) and 0.7376 (95% CI: 0.6056–0.8697). In anesthetized dogs, the human-calibrated device demonstrated superior analytical robustness, whereas the veterinary-specific device showed greater bias and variability. Full article

Adiponectin and omentin are adipose tissue-derived adipokines implicated in insulin sensitivity and cardiometabolic regulation. Their behavior across different stages of dysglycemia, as well as in relation to visceral adiposity and cardiometabolic phenotypes, remains incompletely understood. In this cross-sectional study, circulating adiponectin and omentin levels were evaluated in individuals with prediabetes (PreDM, n = 100) and newly diagnosed type 2 diabetes mellitus (T2DM, n = 128). Associations with insulin resistance-related indices, including the triglyceride–glucose (TyG) index and TyG-derived composites, the visceral adiposity index (VAI), cardiometabolic phenotypes, and cardiovascular risk categories, were assessed using correlation and multivariable regression analyses. Discriminatory performance for metabolically unhealthy obesity was evaluated using receiver operating characteristic (ROC) curve analysis. Both adiponectin and omentin levels were lower in T2DM compared with PreDM (22.05 vs. 30.30 and 25.72 vs. 38.84, p < 0.0001 for both). In PreDMs, omentin showed a significant inverse correlation with the TyG index (weak correlation, ρ = −0.197, p = 0.050), whereas adiponectin demonstrated only weak trends. In multivariable models, VAI and male sex were independent predictors of circulating omentin levels, whereas fasting insulin was not. In contrast, adiponectin did not retain independent associations with metabolic or visceral adiposity indices. In T2DM, adipokine–metabolic associations were largely absent. Neither adipokine differed substantially across cardiometabolic phenotypes or cardiovascular risk categories. ROC analyses revealed modest overall discriminatory performance for metabolically obese phenotypes, with poor discrimination after stratification by glycemic status (area under the ROC curve (AUC) of 0.704 for adiponectin and 0.710 for omentin, and AUC of 0.431 for adiponectin and 0.461 for omentin, respectively). Circulating adipokines appear to exhibit stage-dependent relationships with metabolic dysfunction, being more informative in PreDM than in established T2DM. Omentin may reflect visceral adiposity-related metabolic alterations in early dysglycemia, whereas adiponectin shows limited independent associations. Overall, these findings suggest that adipokines have limited diagnostic or cardiovascular risk-stratification utility when considered in isolation and may be better interpreted within multimarker cardiometabolic assessment frameworks. Full article

Dysglycemia represents an early and progressive stage of cardiometabolic disease, characterized by IR, metabolic inflammation, and increased cardiovascular risk. Its high prevalence and largely asymptomatic course often lead to diagnostic and therapeutic inertia, resulting in missed opportunities for early intervention. Recognizing dysglycemia as a disease continuum rather than a transitional condition supports the need for anticipatory and integrated preventive strategies. Within this framework, nutraceuticals are emerging as valuable supportive tools in the management of dysglycemia, particularly in individuals with increased metabolic risk who are not yet candidates for pharmacological therapy. Nutraceutical compounds can target key pathophysiological mechanisms underlying dysglycemia, including impaired insulin sensitivity, oxidative stress, chronic low-grade inflammation, and altered postprandial glucose metabolism. Clinical evidence supports the use of selected micronutrients, polyphenols, and standardized plant extracts in improving fasting and postprandial glycemic control. Phytocomplexes derived from plants such as Mangifera indica, Momordica charantia, and Malus domestica exert complementary and multitarget actions, including modulation of carbohydrate absorption, activation of AMPK-related pathways, enhancement of peripheral glucose uptake, stimulation of incretin secretion, and improvement of endothelial function. When integrated with lifestyle and dietary interventions, nutraceuticals may reduce glycemic variability, improve metabolic resilience, and delay progression toward type 2 diabetes. Overall, nutraceuticals represent a rational bridge between lifestyle measures and pharmacological treatment in the personalized management of dysglycemia. Full article

Background: Skin and myocardial microvascular dysfunction in prediabetes remains underexplored, and limited studies have investigated the microcirculation in prediabetes in multiple vascular beds. This study aimed to examine microvascular alterations in patients with prediabetes, patients with type 2 diabetes mellitus (DM), and normoglycemic controls without established cardiovascular disease (CVD). Methods: In this cross-sectional study, the microcirculation was assessed using established and novel noninvasive techniques. The skin microvascular reactivity was evaluated using laser speckle contrast analysis (LASCA). The myocardial perfusion was assessed by the subendocardial viability ratio (SEVR). The retinal microvasculature was evaluated using digital nonmydriatic fundus photography, the renal microvascular damage through the urinary albumin-to-creatinine ratio (ACR), and the peripheral vasculopathy by the augmentation index (AIx). Results: Sixty-seven participants were included (22 controls, 24 with prediabetes, 21 with DM; aged: 55.9 ± 9.4 years). Patients with prediabetes and DM showed significantly reduced baseline-to-peak skin flux responses in LASCA compared with controls (p = 0.006), and lower SEVR values (p = 0.001). Moreover, no significant differences were identified in the retinal, renal, or peripheral microvascular indices. In multivariate analysis, systolic blood pressure and glucose were independently associated with skin microvascular dysfunction, while the heart rate and arteriovenous ratio were associated with the SEVR. Conclusions: In this cross-sectional study, impaired skin and myocardial microvascular function were observed in patients with prediabetes in the absence of overt CVD. These findings suggest that LASCA and the SEVR may serve as sensitive markers for the detection of early, subclinical microvascular dysfunction in prediabetes. Full article

Background: Mitral annular calcification (MAC) is associated with systemic atherosclerosis and cardiometabolic risk factors. Although hematologic inflammatory indices have been reported to be correlated with MAC, whether these associations persist after accounting for the cardiometabolic context in which MAC occurs remains unclear. Methods: In a prospective, cross-sectional study of consecutive adults, patients with mild MAC were compared to those without MAC. Individuals with major inflammatory conditions, advanced chronic kidney disease, cirrhosis, malignancy, autoimmune/acute inflammatory disorders, significant valvular disease, prosthetic valves/pacing devices, psychiatric disorders, or moderate-severe MAC were excluded. C-reactive protein (CRP) and hematological inflammatory indices, including neutrophil-to-lymphocyte ratio (NLR), Systemic Inflammatory Response Index (SIRI), and lymphocyte-to-leukocyte ratio (LLR), were analyzed in relation to MAC status. Results: Among 205 patients, 134 had mild MAC and 71 had no MAC. Patients with MAC were older and displayed higher cardiometabolic burden, including more frequent dysglycemia, higher blood pressure, and greater adiposity. In unadjusted comparisons, inflammatory markers differed according to MAC status: CRP (0.31 mg/dL vs. 0.18 mg/dL, p = 0.002), NLR (2.52 vs. 1.99, p = 0.032), SIRI (1.27 vs. 1.04, p = 0.039), and LLR (0.26 vs. 0.29, p = 0.032). In multivariable logistic regression models, none of the inflammatory markers remained independently associated with MAC. In contrast, age (ORs 1.056–1.063 per year increase, p ≤ 0.001), prediabetes (ORs 2.43–3.63, p ≤ 0.001), and type 2 diabetes (OR 5.91 and 6.19, p ≤ 0.001) demonstrated consistent independent associations with MAC across all models. Conclusions: In this cardiometabolic population with mild MAC, inflammatory indices showed unadjusted differences but no independent associations with MAC after comprehensive cardiometabolic adjustment. These findings are most compatible with inflammatory markers primarily reflecting the cardiometabolic milieu in which MAC occurs rather than representing MAC-specific processes. Age and glucose metabolism abnormalities emerged as the dominant independent factors associated with mild MAC, reinforcing the central role of metabolic dysfunction in MAC pathogenesis. Full article

Background: Obesity is associated with a broad range of complications that frequently develop before the onset of type 2 diabetes mellitus (T2DM). Identifying early metabolic markers associated with such complications is essential for improving risk stratification and supporting complication-driven therapeutic strategies. Plasma glucose measured at 1 h during the oral glucose tolerance test (OGTT) has emerged as a sensitive marker of early dysglycemia and adverse cardiometabolic outcomes, but its relationship with established obesity-related complications in individuals without diabetes remains incompletely characterized. We aimed to investigate the association between 1 h post-load plasma glucose levels during OGTT and obesity-related complications in adults living with obesity without T2DM. Methods: This observational cross-sectional study included 47 adults with obesity evaluated during their first visit to obesity clinics. Individuals with T2DM or prior use of anti-obesity pharmacotherapy were excluded. All participants underwent a standard 75-g OGTT with plasma glucose and insulin measurements at fasting, 1 h, and 2 h. Obesity-related complications were recorded retrospectively through structured questionnaires, clinical assessment, and medical record review. Between-group comparisons were performed using non-parametric tests, and repeated OGTT measurements were analyzed using non-parametric longitudinal models. Results: Higher 1 h post-load glucose levels were observed in participants with arterial hypertension (p < 0.001), dyslipidemia (p = 0.020), metabolic dysfunction-associated steatotic liver disease (p = 0.005), impaired glucose tolerance (p = 0.027), obesity hypoventilation syndrome (p = 0.039), urinary incontinence (p = 0.038), and chronic kidney disease (p = 0.048). In most comparisons, 1 h post-load glucose demonstrated stronger discriminatory capacity than fasting or 2 h glucose values. Insulin levels increased markedly after glucose loading in all participants, reflecting generalized insulin resistance, but showed limited ability to discriminate between complication phenotypes. Conclusions: In people living with obesity without T2DM, elevated 1 h post-load plasma glucose during OGTT is consistently associated with multisystem obesity-related complications. These findings support the clinical relevance of 1 h post-load glucose as an integrated marker of early metabolic and systemic burden that may inform complication-driven risk stratification in obesity. Due to the observational study design, causality cannot be inferred. Full article