Objectives: Acute coronary syndrome (ACS), pulmonary embolism (PE), and aortic dissection (AD) present with overlapping symptoms but require markedly different treatments. We investigated whether cardiac quantitative parameters obtained by automated segmentation of non-contrast and contrast-enhanced chest CT can support machine learning-based multiclass differentiation of these conditions. Materials and Methods: This single-center retrospective study included 628 patients who underwent triple rule-out CT angiography (147 negative controls, 193 ACS, 147 PE, and 141 AD). Twenty-six features were extracted separately from automated cardiac segmentation of non-contrast and contrast-enhanced images. Five classifiers—multivariable logistic regression, random forest, XGBoost, LightGBM, and support vector machine—were developed with a 7:3 stratified train–test split and five-fold cross-validation. Performance was evaluated by accuracy, macro-averaged F1 score, and macro-averaged area under the receiver operating characteristic curve (AUC), and feature importance was assessed with SHapley Additive exPlanations (SHAP). Results: Multivariable logistic regression showed the most balanced performance for both modalities. The non-contrast model achieved an accuracy of 0.635, a macro-averaged F1 score of 0.637, and a macro-averaged AUC of 0.840, with class-specific AUCs of 0.814 for ACS, 0.878 for PE, and 0.887 for AD. The contrast-enhanced model achieved 0.683, 0.673, and 0.861, with AUCs of 0.881, 0.876, and 0.919. Recall for ACS increased from 58.6% to 70.7% and for AD from 74.4% to 83.7%, while AD cases misclassified as negative decreased from 11.6% to 2.3%. Left ventricular mass index and right-heart parameters ranked among the most contributory features in both models. Conclusion: Machine learning models built on automatically segmented cardiac parameters showed moderate discriminatory potential for differentiating ACS, PE, and AD. The contrast-enhanced model outperformed the non-contrast model, whereas non-contrast CT still carried complementary structural information that may support risk stratification before contrast administration.
Background and Objectives: Adropin is a peptide involved in metabolic regulation and vascular function, but its role in exercise adaptation remains uncertain. This narrative review synthesizes evidence on adropin responses to exercise, factors that may influence these responses, and their relationships with metabolic and vascular adaptation. Materials and Methods: A structured literature search was conducted in PubMed, Embase, and Cochrane Library from database inception to August 2026, supplemented by reference-list screening. Two reviewers independently assessed full texts and selected relevant articles. Disagreements were resolved through discussion with a third reviewer. Human exercise studies, observational studies of physiological factors, and experimental studies of metabolic and vascular mechanisms were synthesized narratively. Results: Human studies generally reported increased circulating adropin after aerobics, interval, resistance, and combined training. These increases were associated with improvements in cardiorespiratory fitness, glucose regulation, endothelial function, or arterial stiffness. However, acute responses were not consistently observed, and differences in populations, exercise protocols, and sampling conditions limited comparisons. Age, adiposity, metabolic status, hormonal factors, and nutrition were associated with baseline adropin concentrations, but direct evidence that these factors modify training responses remained limited. Experimental studies support effects on skeletal muscle substrate utilization, insulin signaling, and endothelial nitric oxide production. These findings provide biological plausibility but do not establish that exercise-induced changes in circulating adropin mediate human adaptations. One small, randomized trial reported an exploratory indirect effect on arterial stiffness through adropin. Small samples, uncontrolled comparisons, measurement differences, and reliance on observational and preclinical evidence limit interpretation. Conclusions: Adropin is an exercise-responsive biomarker candidate and a potential biological mediator whose causal role remains unresolved. Current evidence does not establish an optimal exercise modality or dose for increasing adropin. Standardized measurements and studies that establish temporal relationships and test mediation are needed to determine whether adropin provides information beyond established metabolic and vascular outcomes.
Background and Objectives: Sodium-glucose cotransporter type 2 (SGLT-2) inhibitors provide substantial cardiovascular and renal benefits, but concerns regarding urinary tract infections (UTIs) may limit their use. This study aimed to evaluate the incidence and management of lower UTIs among patients receiving SGLT-2 inhibitors compared to other patients and to identify associated risk factors in primary care. Materials and Methods: This retrospective observational study included 5764 adults from four family medicine practices from November 2024 to October 2025. Patients were categorized according to lower UTI occurrence, complexity, and SGLT-2 inhibitor use. Demographic characteristics, comorbidities, laboratory parameters, treatment duration, urine cultures, and antibiotic therapy were analyzed. Results: Lower UTIs occurred in 567 patients (9.8%), of whom 30 (16.3%) were taking SGLT-2 inhibitors, and were more frequent among women and patients with diabetes, chronic kidney disease (CKD), benign prostatic hyperplasia (BPH), urolithiasis, and permanent urinary catheters. Except for urolithiasis, all these factors were also independent predictors of lower UTI development in the logistic regression model. In contrast, patients taking an SGLT-2 inhibitor had 43.8% lower odds of developing a UTI, though this may reflect temporal relationship bias. SGLT-2 inhibitors were prescribed to 24.2% of patients with type 2 diabetes, while their use for CKD and heart failure was limited. Family physicians managed 90% of uncomplicated and 64% of complicated lower UTIs. Urine cultures were performed in less than one-third of these patients. Nitrofurantoin was prescribed as the first-choice antibiotic regardless of UTI complexity, predominantly by family physicians. Hospital specialists more often choose fluoroquinolones, followed by cephalosporins. Conclusions: Despite increased lower UTI incidence among patients receiving SGLT-2 inhibitors, their use was not associated with lower UTI development. Urine cultures were insufficiently utilized in patients with UTIs, and they were predominantly not treated according to the latest guidelines. SGLT-2 inhibitors were also underused, particularly for CKD and heart failure, suggesting a potential gap between recommendations and clinical practice.
Background and Objectives: We compared the prognostic value of the preoperative hemoglobin–albumin–lymphocyte–platelet (HALP) index and Cancer Inflammation Prognostic Index (CIPI) after colorectal cancer surgery. Materials and Methods: This single-center retrospective study included 264 patients who underwent colorectal adenocarcinoma resection between 2014 and 2019. The primary Cox model entered both log2-transformed indices simultaneously and adjusted for age, sex, ASA class, neoadjuvant treatment, and recorded pathological stage. Discrimination was assessed using 3- and 5-year time-dependent ROC analysis and Harrell’s C-index. Cut-off-based analyses were exploratory. Results: Over a median follow-up of 86.9 months, 120 patients (45.5%) died. In the primary model, the adjusted hazard ratio per doubling was 0.822 for HALP (95% CI 0.661–1.023) and 1.058 for CIPI (95% CI 0.978–1.145). The 3-year AUCs were 0.649 for HALP and 0.699 for CIPI (p = 0.261). The 5-year AUCs were 0.631 and 0.636, respectively (p = 0.887). In exploratory analyses, the cohort-derived high-CIPI group had poorer adjusted survival (aHR 1.703, 95% CI 1.138–2.548). Both continuous indices were associated with survival in stage I–III disease, whereas neither was statistically significant in patients without neoadjuvant treatment. Conclusions: Both indices showed modest discrimination. The adjusted associations varied by model and subgroup. Incremental clinical value was not established.
Clinical research in orthopedics and trauma surgery has evolved considerably, driven by advances in surgical techniques, imaging technologies, implant design, rehabilitation, and digital medicine [...]
