Search Results (6,536)

Objective: This study seeks to investigate the association between nutritional, muscular, and functional status and moderate-to-severe postoperative complications (Clavien–Dindo ≥ grade II) in patients with lung cancer spinal metastases and to construct an individualized risk prediction nomogram. Methods: A total of 162 patients with histologically confirmed lung cancer spinal metastases who underwent surgery were retrospectively enrolled. Preoperative clinical data were collected. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for postoperative complications, with variable selection based on a combination of statistical significance and clinical judgment. A nomogram model was constructed and evaluated using receiver operating characteristic curve, calibration curve, and decision curve analysis. Internal validation was performed using the bootstrap method. For exploratory assessment of the model’s clinical stratification capability, patients were classified into low-, medium-, and high-risk groups based on tertiles of the predicted probability. Results: The incidence of Clavien–Dindo ≥ grade II complications during postoperative hospitalization or within 14 days was 57.4%. Multivariate analysis suggested that lower psoas muscle index (low PMI) (OR = 4.131, p = 0.034), lower body mass index (BMI) (continuous: OR = 0.539 per 1 kg/m² increase, p = 0.001, indicating that lower BMI was associated with higher risk), lower prognostic nutritional index (PNI) (OR = 0.456, p < 0.001), and lower Karnofsky Performance Status (KPS) score (OR = 0.890, p = 0.009) were identified as potential independent factors associated with postoperative complications. The nomogram achieved an Area Under the Curve of 0.907, showed acceptable calibration (Hosmer–Lemeshow test, p = 0.735), and demonstrated a favorable net clinical benefit in the decision curve analysis. In the exploratory risk stratification analysis, complication rates in the low-, medium-, and high-risk groups were 28.8%, 63.6%, and 78.2%, respectively (p < 0.001). Patients with complications had significantly longer hospital stays (median 20 vs. 13 days). Conclusions: In this cohort, low PMI, low BMI, low PNI, and low KPS were identified as potential independent factors associated with short-term moderate-to-severe postoperative complications. The nomogram may preliminarily predict the risk and might serve as a quantitative reference for individualized perioperative management, but its clinical utility requires further confirmation in external validation. The exploratory risk stratification suggests that the model has preliminary potential for clinical discrimination. Full article

Background: Obesity is increasing worldwide and remains a major contributor to cardiovascular morbidity and mortality. It is strongly associated with hypertension, dyslipidemia, diabetes mellitus, endothelial dysfunction, and chronic inflammation, all of which promote coronary artery disease and acute coronary syndrome (ACS). Despite this well-established risk profile, multiple studies have described an “obesity paradox,” suggesting that obese patients may experience better outcomes after percutaneous coronary intervention (PCI) for ACS than normal-weight individuals. Objective: This narrative review aims to discuss the pathophysiological basis of the obesity paradox and to synthesize contemporary evidence regarding the relationship between body mass index (BMI), major adverse cardiovascular events (MACE), and mortality after PCI in patients presenting with ACS. Results: Contemporary observational cohorts consistently suggest a non-linear relationship between BMI and MACE outcomes after PCI. Overweight and mildly obese patients often demonstrate lower crude mortality and fewer MACE, whereas underweight patients consistently show the poorest prognosis. However, after adjustment for age, left ventricular ejection fraction (LVEF), renal function, frailty, and nutritional status, obesity is less consistently associated with improved outcomes. Overweight status appears to be more reproducibly associated with better prognosis than obesity itself. Conclusions: The obesity paradox is likely driven less by a true protective effect of excess adiposity and more by younger age at presentation, preserved physiological reserve, lower frailty burden, and the limitations of BMI as a marker of cardiovascular risk. Underweight status emerges as the strongest predictor of adverse outcomes. Nutritional assessment and body composition should complement BMI in risk stratification after ACS. Full article

This study investigates the role of single nucleotide polymorphisms (SNPs) in the SNCA gene, encoding alpha-synuclein, in Alzheimer’s disease (AD). A case–control study was conducted including 95 AD patients and 97 healthy controls. Four SNCA polymorphisms (rs2583988, rs2619363, rs2619364, rs10005233) were analyzed using logistic regression, haplotype estimation, genotype combination analysis, and Random Forest modeling. Significant associations were identified for rs2583988, rs2619364, and rs2619363, while rs10005233 showed no association. The rs2583988 C allele and rs2619364 G allele were more frequent in patients, suggesting increased disease risk. Linkage disequilibrium analysis revealed weak correlations (low r²), indicating largely independent genetic effects. Multivariate logistic regression showed that clinical parameters, rather than genetic variants, were independently associated with AD. Multi-locus genotype analysis demonstrated that specific SNP combinations were linked to increased disease risk. Firth regression confirmed associations in low-frequency genotypes. The outcomes derived from the Random Forest methodology were classified as exploratory and not as proof of clinical predictive utility, attributed to the limited sample size, the absence of external validation, and the educational imbalance. Ordinal logistic regression indicated no association between SNCA variants and cognitive severity, while education had a protective effect. The selected SNCA variants showed exploratory associations with AD in this cohort; however, they failed to maintain their validity as independent predictors in multivariate logistic regression analysis. Before drawing any conclusions regarding screening or risk stratification, these findings require independent replication, correction for multiple testing and functional validation. Full article

Background: Ischemic cardiomyopathy (ICM) is characterized by heterogeneous structural remodeling that is not fully captured by conventional systolic metrics. How multidimensional structural echocardiographic information can improve pre-revascularization risk stratification remains unclear. Methods: In this retrospective study, 989 patients with ICM undergoing coronary angiography and revascularization were included in the derivation cohort, and 482 patients from an independent campus served as the validation cohort, with a median follow-up duration of 6.5 years. The primary endpoint was cardiovascular mortality. Eight routinely acquired pre-revascularization echocardiographic structural variables were analyzed. Unsupervised clustering identified structural clusters, and principal component analysis (PCA) was used to derive a structural risk score. Associations with cardiovascular mortality were assessed using the Cox proportional hazards model, and prognostic performance was evaluated by comparing individual echocardiographic predictors using Harrell’s C-index and time-dependent AUC analyses. Results: Three distinct structural clusters emerged, differing in chamber size, systolic function, pulmonary pressures, mitral regurgitation severity, and long-term cardiovascular mortality. The PCA-derived structural risk score, reflecting the dominant axis of remodeling and volume overload, showed association with cardiovascular mortality in the derivation cohort and remained independently predictive after multivariable adjustment. Compared with single echocardiographic parameters, both the structural clusters and the risk score demonstrated superior discriminative performance. In the validation cohort, the structural score again showed a consistent and independent association with cardiovascular mortality. Conclusions: Multidimensional structural echocardiographic assessment reveals clinically meaningful remodeling patterns and enables construction of a robust PCA-derived structural risk score. Both approaches provide prognostic information beyond individual echocardiographic measures and support more precise pre-revascularization risk stratification in patients with ICM. Full article

Background: Hungry bone syndrome (HBS) is a frequent and potentially severe complication following parathyroidectomy in patients with chronic kidney disease (CKD) and secondary (SHPT) or tertiary hyperparathyroidism (THPT). We aimed to identify preoperative risk factors associated with the development of HBS in this population. Methods: We conducted a retrospective cohort study including 99 adult patients with CKD-associated SHPT or THPT who underwent parathyroidectomy at Hospital San Vicente Fundación between 2018 and 2024. HBS was defined as corrected serum calcium <8.5 mg/dL requiring intravenous calcium supplementation for at least 72 h postoperatively. Clinical, biochemical, and histopathological variables were evaluated. Multivariable logistic regression analysis was performed to identify independent predictors of HBS, and model discrimination was assessed using the area under the receiver operating characteristic curve (AUC). Results: Overall, 40.4% of patients developed HBS after parathyroidectomy. Compared with patients without HBS, those with HBS more frequently had preoperative musculoskeletal symptoms (82.5% vs. 32.2%), higher preoperative intact parathyroid hormone levels (2135 vs. 1561 pg/mL), and parathyroid adenoma on histology (57.5% vs. 25.4%). In multivariable analysis, preoperative musculoskeletal symptoms (OR 10.92; 95% CI 2.32–51.43) and parathyroid adenoma (OR 6.16; 95% CI 1.38–27.54) were independently associated with increased risk of HBS. Conversely, higher preoperative calcium levels (OR 0.36; 95% CI 0.16–0.85) and the use of calcitriol or vitamin D receptor activators (OR 0.24; 95% CI 0.07–0.81) were protective factors. The final model demonstrated good discrimination (AUC = 0.86; 95% CI 0.77–0.93). Conclusions: HBS is a common complication after parathyroidectomy in patients with CKD-associated SHPT or THPT. Preoperative musculoskeletal symptoms and parathyroid adenoma were associated with increased risk, whereas higher calcium levels and calcitriol/vitamin D receptor activator use appeared protective. Early identification of high-risk patients may facilitate perioperative risk stratification and targeted management strategies. Full article

Background/Objectives: Precision nutrition is moving beyond population-based guidance and isolated gene–diet interactions toward integrative models of dietary response. However, current approaches remain fragmented across nutrigenomics, microbiome research, multi-omics profiling, digital health, and machine learning. This review proposes the Nutri-Exposome Intelligence Framework as a conceptual, data science-driven model for integrating cumulative dietary, environmental, microbial, molecular, clinical, and digital exposures for precision chronic disease prevention. Methods: This conceptual review synthesizes the literature on precision nutrition, nutrigenetics, nutrigenomics, exposomics, gut microbiome research, multi-omics integration, wearable and biomarker-based monitoring, and machine learning in nutrition studies. Evidence was organized into a framework linking exposure assessment, host susceptibility, microbiome-mediated biotransformation, molecular response profiling, computational modelling, personalized intervention, and longitudinal feedback. Results: The proposed framework consists of seven interconnected layers: diet, environment, and lifestyle exposures; host genome and microbiome; multi-omics molecular responses; machine learning-based integration; risk prediction and responder stratification; personalized dietary intervention; and wearable and biomarker-based feedback. It positions the nutri-exposome as a cumulative exposure–response system and highlights how machine learning can support data harmonization, feature engineering, predictive modelling, responder classification, explainable interpretation, and adaptive refinement of dietary recommendations. Key applications include obesity, type 2 diabetes, cardiovascular disease, metabolic dysfunction-associated steatotic liver disease, cardiovascular–kidney–metabolic syndrome, and broader cardiometabolic prevention. Conclusions: Nutri-exposome intelligence offers a structured pathway for transforming complex nutrition data into predictive, explainable, and adaptive precision nutrition strategies. Implementation will require longitudinal and multi-ethnic cohorts, standardized metadata, causal validation, interpretable machine learning, ethical governance, and equitable access to support responsible clinical and public health translation globally. Full article

Cardiorenal–metabolic (CKM) syndrome has emerged as a unifying condition describing the interplay between metabolic dysfunction, chronic kidney disease, and cardiovascular disease. To address this concept, the American Heart Association, in a 2023 Presidential Advisory, presented an official statement to capture the transition from metabolic risk and subtle cardiorenal dysfunction to overt cardiovascular and renal disease. Although this framework provides a structured representation of disease burden and facilitates risk stratification, emerging evidence suggests that it is primarily focused on the progressive nature, whereas high-risk patients may experience sudden cardiac or renal events. While staging systems provide important tools for risk stratification, they remain primarily descriptive and do not adequately reflect the dynamic and non-linear interactions underlying disease progression. Importantly, patients exhibit substantial heterogeneity in dominant pathophysiological drivers, related to various baseline risk factors and primitive cardio–kidney disorders, that is not fully captured by stage-based classifications. Notably, we propose a phenotype-oriented approach to CKM syndrome based on the recognition that its clinical expression reflects heterogeneous and evolving pathophysiological mechanisms rather than a uniform disease trajectory. According to this strategy, the paradigm of management shifts from an evolutive concept to a more appropriate use of disease modifying agents with cross-organ effects. Sodium–glucose cotransporter-2 inhibitors (SGLT2i), glucagon-like peptide-1 receptor agonists (GLP-1a), and non-steroidal mineralocorticoid receptor antagonists (MRA) have demonstrated the ability to modulate key biological pathways across the cardiovascular, renal, and metabolic axes. Therefore, personalized management that identifies a specific strategy according to CKM phenotypes must be assessed. Full article

Allostatic load (AL) is a multisystemic indicator of the cumulative “wear and tear” on the body caused by chronic stress. In oncology, high AL is associated with a poorer prognosis, a higher number of postoperative complications, and lower treatment tolerance. Patients with head and neck cancer (HNC)—due to frequent smoking, alcohol abuse, low socioeconomic status, and high psychological and functional burden—belong to a group particularly vulnerable to high AL; however, its role in this population remains poorly understood. This narrative review includes publications from 2015 to 2026 from the PubMed/MEDLINE, Embase, and Scopus databases. We analyzed original studies, systematic reviews, and narrative reviews concerning AL in oncology, prehabilitation, and HNC. Additionally, we employed the snowballing method and included studies from key research groups. The results reveal a clear research gap—the lack of direct studies evaluating AL in HNC patients. In other cancers (breast, colorectal, lung), high AL is an independent risk factor for complications, longer hospital stays, and poorer survival. Multimodal prehabilitation (exercise, nutritional, and psychological support) shows potential for reducing AL, but no prospective studies evaluating this effect have been conducted in the HNC population. Assessment of AL may serve as a valuable tool for preoperative risk stratification and monitoring the effects of prehabilitation in patients with head and neck cancer. Prospective cohort and randomized trials are needed to integrate AL into precision medicine for this patient group. Full article

Chronic hyperglycemia profoundly impairs skin integrity, with dermatological complications affecting up to half of patients with diabetes mellitus. The objective of this study was to describe the spectrum, frequency, and clinical characteristics of skin lesions in patients with diabetes mellitus and to evaluate whether specific cutaneous signs are associated with an increased risk of subsequently developing type 2 diabetes. This retrospective observational study evaluated 960 cases admitted to the Dermatology Clinic of “Sf. Spiridon” Emergency County Clinical Hospital, Iași, between 2017 and 2022, complemented by an 11-year longitudinal follow-up (2011–2016). Ulcerative lesions predominated (85.7%), followed by inflammatory manifestations (12.4%), while classical diabetes-specific dermatoses represented <2% of cases. Poor glycemic control (HbA1c > 7%) was documented in 94.2% of patients, with the most severe lesions occurring in those with HbA1c > 10%. In the longitudinal analysis, patients who later developed diabetes initially presented significantly higher rates of xerosis, pruritus, and callus compared with the controls. Multivariate logistic regression identified xerosis (OR 4.70) and pruritus (OR 3.41) as independent predictors of future diabetes. These findings suggest that certain dermatological signs may serve as early non-invasive markers of metabolic dysfunction and highlight the importance of routine skin examination in diabetes risk stratification. Full article

Necrotizing enterocolitis (NEC) remains one of the most serious gastrointestinal emergencies in preterm infants, and imaging plays a central role in diagnosis and clinical management. Historically, evaluation has relied primarily on abdominal radiography, which remains widely available and embedded in established diagnostic frameworks. However, the hallmark radiographic signs of NEC (i.e., pneumatosis intestinalis, portal venous gas, and free air) reflect relatively advanced manifestations of intestinal injury that indicate established mucosal disruption or transmural necrosis. Bowel ultrasound has increasingly complemented radiography by enabling real-time assessment of bowel wall integrity, perfusion, motility, and intra-abdominal fluid, providing physiologic information that may refine clinical interpretation and monitoring of disease progression. Expanding use of neonatologist-performed bowel ultrasound may further improve access to bedside intestinal imaging and facilitate more timely evaluation in neonatal intensive care settings. In parallel, emerging imaging technologies seek to extend the capabilities of conventional imaging by interrogating biologic processes that underlie intestinal injury. Modalities such as contrast-enhanced ultrasound, ultra-high-frequency ultrasound, and photoacoustic imaging offer the potential to characterize bowel microvascular perfusion, tissue oxygenation, and microstructural changes that may precede overt radiographic abnormalities. Complementary physiologic monitoring approaches are also being explored to identify infants at risk before clinical disease develops. Techniques including superior mesenteric artery Doppler, near-infrared spectroscopy, bowel acoustic monitoring, and electrogastrography aim to detect early alterations in intestinal perfusion, oxygenation, and motility. In addition, artificial intelligence applied to imaging and physiologic data may enhance pattern recognition, risk stratification, and clinical decision support. Together, these advances suggest that NEC evaluation is evolving from a paradigm focused on detecting late structural injury toward integrated approaches capable of identifying intestinal vulnerability earlier and monitoring disease more precisely. Full article

Dissolved oxygen (DO) is a critical indicator for assessing marine ecological health and hypoxia risk. Most existing DO prediction studies rely on time-series forecasting models, which require continuous temporal observations and are often unreliable in practical marine monitoring scenarios due to sparse sampling, missing records, and heterogeneous measurement conditions. To address this limitation, this paper investigates the problem of non-temporal DO prediction, aiming to learn a direct nonlinear mapping between environmental drivers and DO concentration. To explicitly model nonlinear pairwise interaction effects between environmental variables, we propose a Factor-Interaction Neural Network (FINN), which decomposes DO estimation into main effects and structured pairwise interaction effects. This interaction-driven design enhances both representation capacity and interpretability compared with conventional multilayer perceptrons. Furthermore, we develop a physics-informed extension, termed PI-FINN, by incorporating oceanographic-consistent regularization priors that reflect key DO formation mechanisms, including temperature-related solubility behavior, depth-wise smoothness associated with stratification, and chlorophyll-driven biological oxygen production tendencies. To evaluate the physical plausibility of model predictions beyond standard accuracy metrics, we introduce a physics-consistency assessment protocol based on Physics Consistency Violation Rate (PCVR) and its robust variant, and further analyze their convergence stability under different driver-weight configurations. Extensive experiments on a real-world marine dataset demonstrate that FINN achieves competitive predictive accuracy compared with strong machine learning baselines (e.g., SVR, Random Forest, and XGBoost), while the proposed physics-informed design mainly improves the physical consistency, robustness, and interpretability of DO estimation under heterogeneous environmental regimes, although it does not necessarily guarantee superior RMSE or MAE performance compared with purely data-driven models. Specifically, FINN achieves an RMSE of 0.3130, an $R^2$ of 0.9831, and a PCVR of 0.4826 on a dataset composed of key environmental variables, including depth, temperature, salinity, and chlorophyll-a, collected under sparse and irregular sampling conditions. Ablation studies confirm the effectiveness of both factor-interaction modeling and physics-guided regularization components. Overall, the proposed framework further provides a reliable tool for sustainable environmental monitoring by enabling physically consistent dissolved oxygen prediction under sparse observational conditions. Such capability is critical for supporting sustainable water resource management, hypoxia risk assessment, and long-term ecological protection. Full article

Therapy for chronic lymphocytic leukemia (CLL) has evolved dramatically with the introduction of targeted agents, particularly Bruton tyrosine kinase inhibitors (BTKis) and BCL2 inhibitors (BCL2is). This review summarizes contemporary frontline and relapsed/refractory treatment strategies, with an emphasis on molecular risk stratification, combination and triplet regimens, measurable residual disease (MRD)–guided therapy, and time-limited approaches. We further examine how genomic complexity, prior therapies, and sociodemographic factors influence disease progression, treatment resistance, and clinical outcomes. Full article

Background/Objectives: Acute-on-chronic liver failure (ACLF) is characterized by multiple organ failure and short-term mortality, and hepatic encephalopathy (HE) is its frequent complication. We investigated whether the severity of HE upon admission in patients with alcohol-related ACLF at the intensive care unit (ICU) was associated with short-term mortality. Methods: In total, 100 patients with alcohol-related ACLF and HE admitted in ICU were enrolled in the study. Laboratory biomarkers, total hospital length of stay (LOS), ICU length of stay, acute kidney injury (AKI), Acute Physiology and Chronic Health Evaluation II score, CLIF-C organ failure and Sequential Organ Failure Assessment score were tested in relation to the mortality risk. HE was assessed and divided into groups using the West Haven criteria. Results: Total hospital LOS, 7-day and 28-day mortality were significantly higher in the higher-grade HE group (p = 0.035, p = 0.031, p = 0.002, respectively). CLIF-C OF, SOFA, and APACHE II scores were significantly higher in the higher-grade HE group (p < 0.001). Kaplan–Meier survival analysis demonstrated reduced survival in patients with higher-grade HE (log-rank p < 0.001). In Cox regression analyses, AKI was associated with short-term mortality in both HE groups. Total hospital LOS and ICU length of stay were also associated with mortality, but were interpreted as post-baseline markers of clinical trajectory rather than baseline prognostic predictors. Conclusions: In patients with alcohol-related ACLF and HE, higher-grade HE was associated with poorer short-term survival. AKI and higher CLIF-C OF, SOFA and APACHE II scores were associated with poor outcomes, supporting their clinical relevance for mortality risk stratification in this population. LOS-related findings should be interpreted as markers of clinical trajectory rather than baseline prognostic predictors. Full article

Coronary artery calcification (CAC) represents a clear sign of advanced atherosclerosis and a strong indicator of coronary artery disease burden and cardiovascular risk. Beyond its established prognostic value, CAC significantly influences plaque biology, lesion morphology, and the technical complexity of percutaneous coronary intervention (PCI). This review summarizes current knowledge on the mechanisms of vascular calcification, its clinical determinants, diagnostic assessment, and therapeutic implications. Vascular calcification is now understood as an active, regulated process involving osteogenic transdifferentiation of vascular smooth muscle cells, inflammatory signaling pathways, extracellular vesicle release, and disturbances in mineral metabolism. Distinct calcification phenotypes exert different effects on plaque stability: micro- and spotty calcifications are frequently linked to plaque vulnerability, whereas dense, sheet-like calcification is more typical of stable fibrocalcific lesions. The prevalence of CAC increases with age and differs between sexes, while cardiometabolic risk factors, chronic kidney disease, systemic inflammation, and genetic predisposition further contribute to its development. Noninvasive computed tomography remains the cornerstone for CAC detection and quantification, enabling reliable cardiovascular risk stratification. Intravascular imaging techniques, particularly intravascular ultrasound and optical coherence tomography, provide detailed characterization of calcified plaque morphology and support optimal procedural planning. In patients with heavily calcified lesions, intravascular imaging-guided lesion preparation and stent optimization represent the most effective strategy for improving PCI outcomes. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly termed non-alcoholic fatty liver disease (NAFLD), is the most prevalent chronic liver condition globally, affecting one-quarter of the adult population. Non-invasive metabolic indices offer a pragmatic alternative to liver biopsy for population-level steatosis screening. We aimed to systematically compare the diagnostic performance of four widely used metabolic indices—TyG, LAP, FLI, and VAI—and to derive a novel composite score that demonstrably surpasses each constituent index. Methods: Retrospective cross-sectional study; 1204 consecutive adults undergoing abdominal ultrasonography at a single tertiary centre (study period: 2024–2025; data collection period: January–April 2026); steatosis graded 0–3 by certified radiologists; four metabolic indices retrieved from pre-calculated columns; novel composite score derived by binary logistic regression with 10-fold stratified cross-validation (stratified by binary outcome); AUROC with 1000-iteration bootstrap 95% CI; and pairwise comparisons by the DeLong method. Results: Of 1204 patients (mean age 42.3 ± 12.5 years; 73.3% male; 13.4% with diabetes), steatosis grades were: Grade 0, 185 (15.4%); Grade 1, 539 (44.8%); Grade 2, 311 (25.8%); and Grade 3, 169 (14.0%). For significant steatosis (Grade ≥ 2), TyG achieved AUROC 0.884 [0.863–0.904] and LAP 0.883 [0.862–0.901], while FLI showed only moderate performance. The novel composite score achieved AUROC 0.896 [0.870–0.920] for any steatosis and 0.922 [0.906–0.938] for significant steatosis, significantly outperforming all four individual indices (DeLong p = 0.004 vs. TyG; p = 0.002 vs. LAP; p < 0.001 vs. FLI; p < 0.001 vs. VAI). Youden-optimal performance: sensitivity 87.1%, specificity 86.0%, and Youden index 0.731. Conclusions: A 10-fold cross-validated logistic composite of four metabolic indices significantly outperforms each constituent index for ultrasonographic hepatic steatosis detection. The composite score may serve as a practical, non-invasive tool for steatosis risk stratification pending external validation. Full article