Medical Sciences

Background/Objectives: Prediabetes (PreDM) is a heterogeneous condition, impacting hundreds of millions worldwide, associated with a substantially high risk of Type 2 Diabetes Mellitus (T2DM) and cardiovascular complications. Early identification of subgroups within the PreDM population may support tailored prevention strategies. Methods: We conducted a cross-sectional study using data from annual health check-ups of 419 university staff (aged 27–69) in Kazakhstan. Latent Class Analysis (LCA) was applied to identify subgroups of individuals with PreDM based on cardiovascular risk factors. Differences in glucose metabolism markers (fasting glucose, OGTT, HOMA-IR, HOMA-β) were compared across identified classes. Results: PreDM prevalence was 43.4%. LCA revealed four distinct classes: Class 1: healthy, low-risk individuals; Class 2: overweight with moderate metabolic risk; Class 3: older, overweight individuals with high cardio-metabolic risk; and Class 4: obese, middle-aged to older individuals with very high cardio-metabolic risk. Significant differences were found in glucose metabolism profiles across the classes. IFG predominated in Class 1 (95%), while Classes 3 and 4 had higher rates of β-cell dysfunction and combined IFG/IGT patterns. HOMA-β differed significantly between classes (p  <  0.001), while HOMA-IR did not. Conclusions: PreDM is highly prevalent in this working-age Kazakh population and demonstrates marked heterogeneity. Based on easily obtainable cardiovascular risk factors, we have identified four subgroups with distinct glucose profiles that may inform personalized interventions. These distinct subgroups may require differentiated prevention strategies, moving beyond a one-size-fits-all approach. Full article

Background: Neoadjuvant chemotherapy (NAC) is a standard preoperative intervention for early-stage breast cancer (BC). Dynamic contrast-enhanced magnetic resonance imaging (CE-MRI) has emerged as a critical tool for evaluating treatment response and pathological complete response (pCR) following NAC. Computational modeling offers a robust framework to simulate tumor growth dynamics and therapy response, leveraging patient-specific data to enhance predictive accuracy. Despite this potential, integrating imaging data with computational models for personalized treatment prediction remains underexplored. This case study presents a proof-of-concept prognostic tool that bridges oncology, radiology, and computational modeling by simulating BC behavior and predicting individualized NAC outcomes. Methods: CE-MRI scans, clinical assessments, and blood samples from three retrospective NAC patients were analyzed. Tumor growth was modeled using a system of partial differential equations (PDEs) within a reaction–diffusion mass transfer framework, incorporating patient-specific CE-MRI data. Tumor volumes measured pre- and post-treatment were compared with model predictions. A 20% error margin was applied to assess computational accuracy. Results: All cases were classified as true positive (TP), demonstrating the model’s capacity to predict tumor volume changes within the defined threshold, achieving 100% precision and sensitivity. Absolute differences between predicted and observed tumor volumes ranged from 0.07 to 0.33 cm³. Virtual biomarkers were employed to quantify novel metrics: the biological conversion coefficient ranged from 4 × 10⁻⁷ to 6 × 10⁻⁶ s^-1, while the pharmacodynamic efficiency coefficient ranged from 1 × 10⁻⁷ to 4 × 10⁻⁴ s^-1, reflecting intrinsic tumor biology and treatment effects, respectively. Conclusions: This approach demonstrates the feasibility of integrating CE-MRI and computational modeling to generate patient-specific treatment predictions. Preliminary model training on retrospective cohorts with matched BC subtypes and therapy regimens enabled accurate prediction of NAC outcomes. Future work will focus on model refinement, cohort expansion, and enhanced statistical validation to support broader clinical translation. Full article

Background: Graves–Basedow disease (GBD) is an autoimmune thyroid disorder characterized by loss of tolerance to the thyrotropin receptor, with clinical manifestations such as a hyperadrenergic state, goiter, orbitopathy, and myxedema, inter alia. Selenium is a micronutrient, essential for the synthesis of selenoproteins. Selenium deficiency has been linked to an increased risk and exacerbation of GBD and GBD orbitopathy; therefore, it has been suggested that supplementation with this micronutrient could modify some outcomes associated with both conditions. Objectives: The objective of this scoping review was to synthesize and analyze the clinical trials that have evaluated the effectiveness of selenium on different outcomes in patients with GBD or GBD orbitopathy. Methods: The following databases were consulted: PubMed/Medline, Scopus, Biosis, ProQuest, Web of Science, and Google Scholar; and the search terms ‘Graves-Basedow disease’ or ‘Graves’ disease’ or ‘hyperthyroidism’ or ‘Graves’ hyperthyroidism’ or ‘selenium or selenium supplementation’ and ‘effectiveness’ were used. The search was limited to articles published in English between January 2000 and March 2025. To reduce selection bias, each article was reviewed independently by three authors using the Rayyan web tool and the JBI Critical Appraisal Checklist. Results: A total of 15 studies were identified (11 on patients with GBD and 4 on patients with GBD orbitopathy). In GBD, selenium supplementation was associated with significant improvements in TSH, FT4, FT3, TPOAb, TgAb, and TRAb levels; while in GBD orbitopathy, a positive effect of selenium supplementation was found on multiple clinical outcomes. Conclusions: Selenium supplementation in patients with GBD or GBD orbitopathy is associated with favorable biochemical and clinical outcomes. Full article

Background/Objectives: Cardiovascular disease is the leading cause of death in Mexico; this is due to the high prevalence of chronic non-communicable diseases (NCDs), including obesity, type 2 diabetes mellitus (T2DM), systemic arterial hypertension (SAH), cardiovascular disease, chronic kidney disease (CKD), and dyslipidemia. Primary care physicians require a classification tool that enables them to gain a broader understanding of their patients’ risks, thereby allowing them to make more informed clinical decisions. This study compared risk stratification for atherosclerotic cardiovascular disease (ASCVD) and Cardiovascular–Kidney–Metabolic (CKM) syndrome in a primary care setting in Mexico. Methods: An observational, descriptive, cross-sectional study analyzed 500 patients with T2DM, SAH, dyslipidemia, and/or CKD. Two ordinal logistic regression models were developed using a Chi-square test, Kruskal–Wallis test, and tetrachoric, polychoric, polyserial, and Pearson correlations. Results: Associations were found between ASCVD risk and factors like sex, age, and T2DM; for CKM syndrome, the associations were with age, T2DM, and dyslipidemia. Interestingly, 22% of advanced CKM patients had a low ASCVD risk. Alcohol consumption showed a strong positive relationship (42%) with CKM stages, while there was a negative relationship (33%) with the glomerular filtration rate. Conclusions: The ASCVD risk classification effectively identifies cardiac conditions, but the CKM syndrome score provides a broader assessment of comorbidities at earlier stages. Key factors like age, hypertension, T2DM, and smoking are crucial for cardiovascular risk but less so for CKM syndrome, highlighting the need for a broader stratification of risk. Full article

Background: Preeclampsia remains a leading cause of maternal and perinatal morbidity and mortality, yet its pathophysiology is not fully understood. Recent studies suggest that dysregulated maternal immune responses, particularly involving decidual Natural Killer (dNK) cells and immune checkpoint molecules such as B7-H3, may play a role in the pathogenesis of this heterogeneous syndrome, particularly in the development of early-onset preeclampsia (EOP). Objective: The aim of this study was to investigate the expression patterns of B7-H3 on extravillous trophoblasts (EVTs) and the abundance of dNK cells in preeclamptic versus normotensive pregnancies and to analyze the relationship between these two immune parameters. Methods: A cross-sectional study was conducted using 42 placental samples (21 preeclampsia, 21 controls). Immunohistochemistry (IHC) was performed to detect CD56 (dNK cells) and CD276 (B7-H3) expression. Expression was semi-quantitatively evaluated using the Remmele Immunoreactive Score (IRS). Statistical comparisons and correlation analyses were conducted. Results: Preeclamptic placentas exhibited significantly higher dNK cell expression (IRS 7.19 ± 2.16) and significantly lower B7-H3 expression (IRS 2.63 ± 0.90) compared to controls (p < 0.001 and p = 0.002, respectively). A positive correlation was found between B7-H3 and dNK cell expression in both groups, with a stronger correlation in normotensive pregnancies (r = 0.605; p = 0.004) and preeclampsia (r = 0.465; p = 0.034). Conclusions: The inverse expression pattern and reduction in B7-H3 expression compared to dNK cells in preeclampsia suggest a loss of immune tolerance at the maternal–fetal interface. These findings highlight the potential of B7-H3 as a biomarker and immunoregulatory target for early prediction and prevention of preeclampsia. Full article

Fuchs endothelial corneal dystrophy (FECD) is the leading cause of endothelial failure requiring keratoplasty in industrialised nations. Descemet membrane endothelial keratoplasty (DMEK) has become the gold-standard surgical therapy, yet it is constrained by limited donor tissue and a steep learning curve. This narrative review summarises current and emerging therapeutic strategies for FECD. We describe conventional endothelial keratoplasty and its outcomes, tissue-sparing procedures such as descemetorhexis without endothelial keratoplasty (DWEK) and quarter-DMEK, regenerative approaches including cultured endothelial cell injection and synthetic corneal substitutes, and adjunctive innovations ranging from Rho-associated kinase inhibitors to artificial intelligence-assisted diagnostics. Challenges surrounding donor shortages, variable clinical outcomes, regulatory hurdles and cost are critically appraised. We conclude by outlining future directions that are likely to combine advanced surgical techniques with cell-based and biomaterial solutions to deliver accessible, long-term restoration of vision for patients with FECD. Full article

Background/Objectives: Diabetic cardiomyopathy in type 2 diabetes mellitus (T2DM) often progresses silently, manifesting as diastolic dysfunction or subtle systolic impairment despite preserved ejection fraction (EF). Detecting these changes early is critical to prevent symptomatic heart failure. This study assessed the prevalence of left ventricular (LV) diastolic dysfunction and impaired global longitudinal strain (GLS) in T2DM patients with preserved EF and identified related risk factors. Methods: We performed a cross-sectional study of 232 adults with T2DM and EF > 50% at a tertiary hospital. Standard transthoracic and speckle-tracking echocardiography were used to evaluate LV diastolic function and GLS. Logistic regression identified predictors of myocardial dysfunction. Results: LV diastolic dysfunction was found in 53.9% of patients, while 13.4% showed impaired GLS (>–17.9%). Independent predictors of diastolic dysfunction were age ≥ 60 years (OR = 2.51, 95% CI: 1.25–5.07, p = 0.010) and diabetes duration of 5–10 years (OR = 3.06, 95% CI: 1.46–6.40, p = 0.003). Reduced GLS was independently associated with male sex (OR = 2.45, p = 0.040) and the presence of diastolic dysfunction (OR = 3.14, p = 0.010). Conclusions: Subclinical myocardial dysfunction is common in Vietnamese T2DM patients with preserved EF. Both diastolic dysfunction and reduced GLS may occur independently or together, influenced by age, sex, and diabetes duration. Incorporating GLS into echocardiographic evaluation may enhance early detection and support tailored cardiovascular risk management in this high-risk group. Full article

Background: Postoperative cognitive dysfunction (POCD) is a common postoperative condition after neurosurgery, and in patients of advancing age, with far-reaching implications for recovery and quality of life. Current evidence points to the gut–brain axis as the main mechanism for the regulation of perioperative neuroinflammation and cognition. Objective: The aim of this review is to consolidate the existing evidence for perioperative gut microbiome dysbiosis in POCD, specifically in neurosurgical patients. Methods: A review of preclinical and clinical evidence on the gut microbiome, surgical stress, and cognitive recovery was conducted. Both mechanistic and therapeutic evidence were examined. Results: Surgery and anesthesia enhance gut microbial diversity, intestinal permeability, and systemic inflammation, thereby compromising neuroplasticity and the integrity of blood–brain barriers. Preclinical models show that interventions to reestablish microbial homeostasis with probiotics, prebiotics, or fecal microbiota transplantation decrease postoperative cognition. Clinical studies offer evidence supporting the associations between decreased short-chain fatty acid-producing bacteria and POCD risk. Randomized controlled trials have demonstrated that perioperative probiotics lower the incidence and markers of POCD. Multi-omic approaches to integrating microbiome, metabolome, and neuroimaging signatures are being engineered to discern recovery phenotypes prior to surgery. Conclusions: Perioperative gut microbiota are a modifiable target for the optimization of cognitive recovery from neurosurgery. The inclusion of microbiome treatments and diagnostics into standard surgical care pathways is one potential pathway to POCD minimization, but large randomized trials will be necessary to establish this. Full article

Background/Objectives: Mycophenolic acid (MPA) is used as part of first-line combination immunosuppressive therapy for renal transplant recipients. Personalized dosing approaches are needed to balance efficacy and minimize toxicity due to the pharmacokinetic variability of the drug. In this study, population pharmacokinetic (PopPK) modeling and machine learning (ML) techniques are coupled to provide valuable insights into optimizing MPA therapy. Methods: Using data from 76 renal transplant patients, two PopPK models were developed to describe and predict MPA levels for two different formulations (enteric-coated mycophenolate sodium and mycophenolate mofetil). Covariate effects on drug clearance were assessed, and Monte Carlo simulations were used to evaluate exposure under normal and reduced clearance conditions. ML techniques, including principal component analysis (PCA) and ensemble tree models (bagging and boosting), were applied to identify predictive factors and explore associations between MPA plasma/saliva concentrations and the examined covariates. Results: Total daily dose and post-transplant time (PTP) were identified as key covariates affecting clearance. PCA highlighted MPA dose as the primary determinant of plasma levels, with urea and PTP also playing significant roles. Boosted tree analysis confirmed these findings, demonstrating strong predictive accuracy (R² > 0.91). Incorporating saliva MPA levels improved predictive performance, suggesting that saliva may be a complementary monitoring tool, although plasma monitoring remained superior. Simulations allowed exploring potential dosing adjustments for patients with reduced clearance. Conclusions: This study demonstrates the potential of integrating machine learning with population pharmacokinetic modeling to improve the understanding of MPA variability and support individualized dosing strategies in renal transplant recipients. The developed PopPK/ML models provide a methodological foundation for future research toward more personalized immunosuppressive therapy. Full article

Background: Saharan dust intrusions (SDIs) are associated with poor air quality and adverse respiratory outcomes. However, their impact on real-world inhaler utilization remains insufficiently characterized. We aimed to examine the association between SDI and the dispensing of short-acting beta-agonists (SABA) and inhaled corticosteroid–long-acting beta-agonist (ICS–LABA) combinations in the Canary Islands, Spain. Methods: Pharmaceutical sales data for SABA and ICS–LABA were collected from 60 pharmacies in Santa Cruz de Tenerife (TF) and Las Palmas de Gran Canaria (GC) between June 2017 and May 2022. SDI days were identified based on daily PM₁₀ concentrations > 40 µg/m³ from the regional air quality monitoring network. Linear regression models evaluated associations between drug dispensations and SDI presence, frequency, and intensity, adjusting for seasonality (winter vs. summer). Results: Over 60 months, SABA sales were 14.8% lower in TF compared with GC, while ICS–LABA sales were 10.9% higher. SDI presence was associated with significantly higher ICS–LABA dispensations in both provinces (+5.7% in TF, +10.2% in GC), whereas no association was found for SABA. ICS–LABA sales correlated weakly but significantly with both SDI frequency and PM₁₀ levels. Seasonal analysis revealed stronger effects in winter, with ICS–LABA dispensations increasing by 14.3% (TF) and 9.6% (GC) during SDI months. For SABA, seasonal differences were independent of SDI exposure. Conclusions: SDIs in the Canary Islands are independently associated with increased dispensing of ICS–LABA maintenance therapy, particularly during winter months. Dispensing data offer a valuable population-level indicator of respiratory impact from natural airborne pollution and support the integration of environmental alerts into preventive respiratory care strategies. Full article

Background: The incidence and prognosis of high-grade gliomas differ according to histopathological and molecular features. The WHO 2021 CNS classification emphasized IDH status, but historical cohorts often lacked systematic molecular profiling. Methods: We conducted a retrospective population-based study including adult patients diagnosed with IDH-wildtype glioblastoma or IDH-mutant astrocytoma in a Spanish tertiary center (2011–2021). Incidence trends and survival outcomes were analyzed according to treatment modality and sex. Results: A total of 1057 patients were included: 530 (50.1%) with IDH-wildtype glioblastoma and 137 (13%) with IDH-mutant astrocytoma. Incidence of both subtypes significantly increased during the study period (p < 0.01). Median overall survival (OS) was 12.3 months for IDH-wildtype glioblastoma and 38.4 months for IDH-mutant astrocytoma. Multimodal therapy (surgery, radiotherapy, chemotherapy) significantly improved OS and progression-free survival (PFS) in both subgroups (p < 0.001). Male sex was associated with longer OS in both tumor types (p < 0.05). Conclusions: IDH-wildtype glioblastoma shows persistently poor outcomes despite increasing incidence, while IDH-mutant astrocytoma demonstrates better survival, particularly in male patients and those receiving multimodal therapy. These findings reflect real-world practice and provide epidemiological and survival data from Southern Europe to guide future clinical and public health strategies. Full article

Background: The aim of this study was to evaluate the changes in platelet indices (PLT) provided by the ADVIA 2120 hematology analyzer (Siemens Hematology System) in the early stages of onset of infections and acute coronary syndromes (ACSs). Methods: Samples were selected from 40 patients admitted to the intensive care unit with suspected uncomplicated sepsis at presentation, from 40 patients with a biochemical diagnosis of ACS at presentation and from 40 apparently healthy subjects. These samples were tested for PLT and PLT indices [mean platelet volume (MPV); mean platelet mass (MPM); mean platelet component (MPC); immature platelets (RtcPlts)] obtained by automation with the ADVIA 2120 and specific biomarkers for sepsis [white blood cells (WBCs); neutrophil granulocytes (NGs); presepsin (PSP); procalcitonin (Pct); C-reactive protein (CRP)] and for SCA (hs cTnI). Results: Platelet indices (RtcPlts, MPV, MPM) were significantly altered (p > 0.005) in patients with suspected sepsis and patients with ACS compared to control subjects; however, no statistically significant difference was observed between the two groups of patients with disease. Cutoff values (ROC curves) were obtained for platelet indices that best discriminated healthy subjects from subjects with severe infection or ACS. Conclusions: Our data show that, in subjects with suspected sepsis and ACS at disease onset, a state of early platelet activation exists that is not disease-specific. Immature platelets (RtcPlts) and the platelet indices MPM and MPV, provided by the ADVIA 2120 hematology analyzer, showed high sensitivity in subjects with suspected sepsis or ACS at disease onset. Full article

Background/Objectives: Sentinel lymph node biopsy (SLNB) is currently the standard approach for axillary staging in breast cancer. Conventional techniques are radioisotope-based (Technetium-99m, Tc99m) and remain widely used, but novel tracers like Indocyanine Green (ICG) fluorescence provide potential advantages regarding feasibility and logistics. Methods: We conducted a prospective, observational study including 476 female patients diagnosed with primary invasive breast cancer who underwent SLNB at the Institute of Oncology “Prof. Dr. I. Chiricuță”, Cluj-Napoca, Romania, between January 2022 and May 2025. Clinical, surgical, and pathological variables were systematically extracted. SLNB was performed using either Tc99m or ICG, according to institutional protocols. Comparative analyses were performed to evaluate sentinel node characteristics, histopathological parameters, and positive surgical margins predictors. Results: The median age was 60 years (IQR: 52–69). Breast-conserving surgery (BCS) was performed in 77.9% of cases, while mastectomy was performed in 22.1%. Sentinel lymph node positivity was reported in 25.6% of cases, with no significant differences in the number of excised or metastatic nodes between Tc99m and ICG (mean nodes: 3.23 vs. 3.20, p = 0.860; mean positive nodes: 0.35 vs. 0.36, p = 0.897). Histologically, invasive carcinoma NST was predominant (90.1%), and surgical margins were negative in 96.8% of patients, with all margin-positive cases occurring following BCS. No pathological markers (grade, Ki67, TILs, DCIS extent) predicted margin status or nodal involvement. Notably, younger age correlated inversely with the extent of ductal carcinoma in situ (r = −0.21, p < 0.00001). Conclusions: Tc99m and ICG provided comparable diagnostic performance in performing SLNB, with equivalent rates of nodal detection and pathological yield. These findings support that ICG is a safe and effective alternative for routine axillary staging in breast cancer. Full article

Background: This narrative review examines the role of artificial intelligence (AI) in bowel sound analysis for the diagnosis and management of inflammatory bowel disease (IBD). Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, presents a significant clinical burden due to its unpredictable course, variable symptomatology, and reliance on invasive procedures for diagnosis and disease monitoring. Despite advances in imaging and biomarkers, tools such as colonoscopy and fecal calprotectin remain costly, uncomfortable, and impractical for frequent or real-time assessment. Meanwhile, bowel sounds—an overlooked physiologic signal—reflect underlying gastrointestinal motility and inflammation but have historically lacked objective quantification. With recent advances in artificial intelligence (AI) and acoustic signal processing, there is growing interest in leveraging bowel sound analysis as a novel, non-invasive biomarker for detecting IBD, monitoring disease activity, and predicting disease flares. This approach holds the promise of continuous, low-cost, and patient-friendly monitoring, which could transform IBD management. Objectives: This narrative review assesses the clinical utility, methodological rigor, and potential future integration of artificial intelligence (AI)-driven bowel sound analysis in inflammatory bowel disease (IBD), with a focus on its potential as a non-invasive biomarker for disease activity, flare prediction, and differential diagnosis. Methods: This manuscript reviews the potential of AI-powered bowel sound analysis as a non-invasive tool for diagnosing, monitoring, and managing inflammatory bowel disease (IBD), including Crohn’s disease and ulcerative colitis. Traditional diagnostic methods, such as colonoscopy and biomarkers, are often invasive, costly, and impractical for real-time monitoring. The manuscript explores bowel sounds, which reflect gastrointestinal motility and inflammation, as an alternative biomarker by utilizing AI techniques like convolutional neural networks (CNNs), transformers, and gradient boosting. We analyze data on acoustic signal acquisition (e.g., smart T-shirts, smartphones), signal processing methodologies (e.g., MFCCs, spectrograms, empirical mode decomposition), and validation metrics (e.g., accuracy, F1 scores, AUC). Studies were assessed for clinical relevance, methodological rigor, and translational potential. Results: Across studies enrolling 16–100 participants, AI models achieved diagnostic accuracies of 88–96%, with AUCs ≥ 0.83 and F1 scores ranging from 0.71 to 0.85 for differentiating IBD from healthy controls and IBS. Transformer-based approaches (e.g., HuBERT, Wav2Vec 2.0) consistently outperformed CNNs and tabular models, yielding F1 scores of 80–85%, while gradient boosting on wearable multi-microphone recordings demonstrated robustness to background noise. Distinct acoustic signatures were identified, including prolonged sound-to-sound intervals in Crohn’s disease (mean 1232 ms vs. 511 ms in IBS) and high-pitched tinkling in stricturing phenotypes. Despite promising performance, current models remain below established biomarkers such as fecal calprotectin (~90% sensitivity for active disease), and generalizability is limited by small, heterogeneous cohorts and the absence of prospective validation. Conclusions: AI-powered bowel sound analysis represents a promising, non-invasive tool for IBD monitoring. However, widespread clinical integration requires standardized data acquisition protocols, large multi-center datasets with clinical correlates, explainable AI frameworks, and ethical data governance. Future directions include wearable-enabled remote monitoring platforms and multi-modal decision support systems integrating bowel sounds with biomarker and symptom data. This manuscript emphasizes the need for large-scale, multi-center studies, the development of explainable AI frameworks, and the integration of these tools within clinical workflows. Future directions include remote monitoring using wearables and multi-modal systems that combine bowel sounds with biomarkers and patient symptoms, aiming to transform IBD care into a more personalized and proactive model. Full article

Background/Objectives: Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide. This study evaluates the predictive value of Carcinoembryonic Antigen (CEA) in identifying CRC recurrence following surgical resection. Methods: This retrospective study was realized in the Oncology Institute in Cluj-Napoca and included 88 patients diagnosed with CRC. Clinical, demographic, and tumor-specific data were collected, including TNM staging, tumor histology. CEA levels were recorded before surgery. Receiver Operating Characteristic (ROC) analysis was performed to determine the diagnostic accuracy of CEA in predicting tumor relapse, and the sensitivity and specificity of various CEA cut-off values were assessed. Results: Most patients presented with advanced-stage tumors (T3/T4, 80.6%). CEA levels were significantly higher in patients with lymphatic and perineural invasion and in those with metastases (mean CEA: 45.0 ng/mL for M1 vs. 13.2 ng/mL for M0, p = 0.032). ROC analysis revealed an area under the curve (AUC) of 0.877 (95% CI: 0.763–0.949). A CEA cut-off value of 11.73 ng/mL yielded 100% sensitivity and 74.5% specificity for detecting recurrence; Conclusions: CEA is a valuable non-invasive biomarker for predicting CRC relapse, with high sensitivity and acceptable specificity. Regular CEA monitoring post-surgery can facilitate early detection of recurrence, improving prognosis. Full article

Background: Night shift work has been classified as a probable carcinogen due to its disruption of circadian rhythms. However, whether night shift work can increase the risk of ovarian cancer remains unclear. Herein, we investigated this association using a systematic review and meta-analysis. Methods: We systematically searched several databases until June 2025 for relevant studies. Effect estimates were extracted and pooled using a random-effects model to calculate odds ratios (ORs) with 95% confidence intervals (CIs). Heterogeneity across studies was assessed using the I² statistic, and publication bias was assessed using Egger’s regression test and funnel plot asymmetry. Results: Seven studies (eight cohorts) involving >2.5 million women were included. Overall, night shift work was not significantly associated with ovarian cancer (OR = 1.13; 95% CI: 0.96, 1.32; I² = 49%). However, significant associations were observed in case–control studies (OR = 1.36; 95% CI: 1.12, 1.66; I² = 0.8%) and in high-quality studies (OR = 1.17; 95% CI: 1.00, 1.37; I² = 52%). Sensitivity analyses suggested that exposure misclassification in some cohort studies attenuated risk estimates. No publication bias was detected (z = −0.63, p = 0.53). Conclusions: While the overall findings did not demonstrate a statistically significant association, evidence from case–control studies that collected detailed information about night shift work suggests an increased ovarian cancer risk in night shift workers. Future large-scale prospective studies with detailed exposure assessments are warranted to confirm these findings. Full article

Background: Sarcopenia is linked with high rates of adverse surgical outcomes, and computed tomography angiography (CTA)-based psoas measurements are used as imaging sarcopenia surrogates. Their prognostic value in patients with chronic limb-threatening ischemia (CLTI) undergoing revascularization remains uncertain. Objectives: To evaluate whether CTA-derived psoas muscle indices predict complications and mortality after lower-limb revascularization for CLTI. Methods: We performed a retrospective cohort study of consecutive adults who underwent open, hybrid, or endovascular revascularization for CLTI at a single tertiary center (March 2018–December 2021). Psoas muscle area (PMA) and density (PMD) were measured preoperatively on CTA at the mid-L3 vertebral level. Psoas muscle index (PMI) was calculated as PMA/height². Patients were stratified by tertiles for each index (lowest tertile = “sarcopenic” vs. upper two tertiles). Outcomes included early in-hospital complications, late complications, overall complications, late mortality, and overall mortality. Group comparisons used χ²/Fisher tests with false discovery rate (FDR) adjustment; multivariable logistic regression with AIC-guided selection assessed independent predictors. Results: A total of 234 patients were included (median age 68 years; 65.4% men). Early complications occurred in 15.8%; late complications in 70.3%; overall mortality during follow-up was 26.6% (38/143 within follow-up data). In tertile analyses, none of the psoas-derived measures were significantly associated with early complications, late complications, overall complications, or mortality after FDR correction. Lower PMD showed consistent but non-significant trends toward higher late complications (84% vs. 64%), overall complications (87% vs. 72%), overall mortality (38% vs. 21%), and late mortality (37% vs. 20%) (all p < 0.05 unadjusted; all p_adj ≥ 0.139). In multivariable models, PMA, PMD, and PMI were not independent predictors of any outcome. Conclusions: In this retrospective cohort study, preoperative CTA-derived psoas indices were not independent predictors of early, late, or overall complications, nor of in-hospital or follow-up mortality after revascularization for chronic limb-threatening ischemia. Although lower psoas muscle density showed consistent trends toward higher risk, these associations did not reach statistical significance after adjustment. Taken together, our findings suggest that psoas-based measures have limited prognostic value in this setting and should be interpreted cautiously, while their potential role warrants confirmation in larger, prospective studies. Full article

Background: Monkeypox (Mpox) is a re-emerging zoonotic disease caused by the monkeypox virus (MPXV). Transmission occurs primarily through direct contact with lesions or contaminated materials, with sexual transmission playing a significant role in recent outbreaks. In 2022, Mpox triggered a major global outbreak and was declared a Public Health Emergency of International Concern (PHEIC) by the World Health Organization (WHO), prompting renewed interest in effective control strategies. Methods: This study developed a compartmental SEIR-based model to assess the epidemiological impact of key interventions, including vaccination and isolation, while incorporating critical epidemiological parameters. Sensitivity analyses were conducted to examine (1) disease dynamics in relation to the basic reproduction number, and (2) how different parameters influence the curve of symptomatic infections. Real-world continental-scale data were used to validate the model and identify the parameters that most significantly affect epidemic progression and potential control of Mpox. Results: Results showed that the basic reproduction number was most influenced by the recovery rate, vaccination rate, vaccine effectiveness, and transmission rates of symptomatic and asymptomatic individuals. In contrast, the progression of symptomatic cases was highly sensitive to the case fatality rate and incubation rate. Conclusions: These findings highlight the importance of integrated public health strategies combining vaccination, isolation, and early transmission control to mitigate future Mpox outbreaks. Full article

Background: Despite evidence discouraging contralateral prophylactic mastectomy (CPM) in average-risk patients, its use is increasing globally. While well-studied in Western settings, little is known about the factors influencing CPM decisions in the Middle East and North Africa (MENA) region. This study explores clinical, psychosocial, and communication-related factors associated with CPM choices among women with early-stage breast cancer. Methods: We conducted a retrospective study of 253 early-stage breast cancer patients who underwent mastectomy, with or without CPM, at the American University of Beirut Medical Center. Clinical and demographic data were extracted from medical records, and decision-making factors were assessed through tailored patient questionnaires. Associations were analyzed using chi-square tests and multivariable logistic regression. Results: Of the 253 women included in the study, 37 underwent CPM, while 216 had unilateral mastectomy (UM). Compared to the UM group, women who chose CPM were more likely to have a college education (96.9% vs. 57.6%, p < 0.001), be employed (69.7% vs. 41.3%, p = 0.002), and report a family history of breast cancer (55.6% vs. 30.2%, p = 0.003). Immediate reconstruction was significantly more common among CPM patients (67.6% vs. 16.4%, p < 0.001), and the 30-day rehospitalization rate was also higher (16.2% vs. 6.1%, p = 0.031). Women in the CPM group were more likely to prioritize extending life (84.6% vs. 56.7%, p = 0.007) and achieving peace of mind (80.8% vs. 49.3%, p = 0.003). Although all CPM patients cited risk reduction as a primary motivator, only 46.2% believed they had a lower recurrence risk than their peers (vs. 20% of UM patients, p < 0.001). Decisions to undergo UM were more frequently influenced by physicians’ recommendations (95.3% vs. 53.8%, p < 0.001), whereas CPM decisions appeared to be more patient-driven. Additionally, CPM patients reported more negative expectations and higher dissatisfaction with pain (57.7% vs. 32.0%, p = 0.012) and reconstructive outcomes (54.5% vs. 27.5%, p = 0.035). Conclusions: In this first study from the MENA region exploring CPM decision-making, choices were largely driven by personal preferences rather than clinical risk. These findings highlight the need for improved risk communication, shared decision-making, and broader integration of genetic counseling in surgical planning. Full article