Background. Sepsis presents significant diagnostic and prognostic challenges, and traditional scoring systems, such as SOFA and APACHE, show limitations in predictive accuracy. Machine learning (ML)-based predictive survival models can support risk assessment and treatment decision-making in the intensive care unit (ICU) by accounting for the numerous and complex factors that influence the outcome in the septic patient. Methods. A systematic literature review of studies published from 2014 to 2024 was conducted using the PubMed database. Eligible studies investigated the development of ML models incorporating commonly available laboratory and clinical data for predicting survival outcomes in adult ICU patients with sepsis. Study selection followed the PRISMA guidelines and relied on predefined inclusion criteria. All records were independently assessed by two reviewers, with conflicts resolved by a third senior reviewer. Data related to study design, methodology, results, and interpretation of the results were extracted in a predefined grid. Results. Overall, 19 studies were identified, encompassing primarily logistic regression, random forests, and neural networks. Most used datasets were US-based (MIMIC-III, MIMIC-IV, and eICU-CRD). The most common variables used in model development were age, albumin levels, lactate levels, and ventilator. ML models demonstrated superior performance metrics compared to conventional methods and traditional scoring systems. The best-performing model was a gradient boosting decision tree, with an area under curve of 0.992, an accuracy of 0.954, and a sensitivity of 0.917. However, several critical limitations should be carefully considered when interpreting the results, such as population selection bias (i.e., single center studies), small sample sizes, limited external validation, and model interpretability. Conclusions. Through real-time integration of routine laboratory and clinical data, ML-based tools can assist clinical decision-making and enhance the consistency and quality of sepsis management across various healthcare contexts, including ICUs with limited resources.

Colorectal cancer (CRC) represents a significant global health burden, ranking as the third most frequently diagnosed malignancy worldwide. Emerging evidence has established a compelling association between gut microbiota dysbiosis and CRC pathogenesis, revealing complex mechanisms through which specific bacterial communities modulate carcinogenesis. This comprehensive review synthesizes current knowledge on the mechanistic contributions of gut microbiota to CRC development, with particular emphasis on key pathogenic bacteria including Fusobacterium nucleatum, Bacteroides fragilis, and Escherichia coli. We examine the molecular pathways through which these microorganisms promote tumorigenesis, including chronic inflammation induction, immune response modulation, metabolic reprogramming, and direct genotoxic effects. Furthermore, we discuss the therapeutic implications of microbiota-targeted interventions and the potential utility of microbial biomarkers for early CRC detection. Understanding the intricate host–microbiota interactions in CRC pathogenesis may facilitate the development of novel preventive strategies and therapeutic approaches for this devastating disease.

Postoperative adhesions are a frequent complication encountered after surgical procedures, mainly after intraperitoneal interventions. To this day, the pathophysiological mechanism behind the process of adhesions formation is not completely known. There are many strategies proposed as prophylaxis methods, involving surgical techniques, drugs or materials that prevent adhesions and even state of the art technologies such as nanoparticles or gene therapy. The aim of our review is to present these innovative approaches and techniques for postoperative adhesions prevention. After a thorough scientific database query, we selected 84 articles published in the past 15 years that were relevant to our topic. Despite all the recent groundbreaking discoveries, we are at an early stage of understanding the complexity of the adhesion formation mechanism. Further investigations should be made in order to create an ideal product for safe clinical use for prevention.

Background: The potential impact of maternal SARS-CoV-2 infection during pregnancy on the neurodevelopment of offspring has raised considerable concern. Emerging studies have evaluated various developmental domains in exposed infants, yet findings remain inconsistent. Objective: To synthesize current evidence regarding neurodevelopmental outcomes in infants born to mothers with confirmed SARS-CoV-2 infection during pregnancy. Methods: We conducted a narrative review following PRISMA guidelines. A literature search was performed in PubMed, Cochrane, and ScienceDirect using keywords including “COVID-19”, “pregnancy”, “neurodevelopment”, and “SARS-CoV-2”. Nineteen studies were included. Data were extracted regarding study design, sample size, timing of exposure, age at assessment, developmental tools used, and key findings. Study quality was assessed using the Newcastle–Ottawa Scale. Results: Among 19 included studies, 12 reported at least some neurodevelopmental delays, particularly in motor and language domains. However, these delays were generally mild, domain-specific, and often not statistically significant. Seven studies, most of which were high-quality and low-risk, reported no significant differences between exposed and unexposed groups. Assessment tools and follow-up durations varied widely, limiting comparability. Conclusions: Current evidence does not support a consistent association between in utero SARS-CoV-2 exposure and an unfavorable neurodevelopmental outcome up to 24 months. However, heterogeneity in methods and short-term follow-up warrant further high-quality longitudinal research.

Background and Objectives: Sepsis is a leading cause of morbidity and mortality worldwide, yet data from Central and Eastern Europe remain scarce. Our study aims to address the scarcity of information regarding the characteristics and mortality rates of patients with sepsis by reporting recent data from one of the largest emergency centers in Romania over an 18-year period (2007–2024). Materials and Methods: A retrospective analysis was conducted on 12,089 adult patients diagnosed with sepsis at the University Emergency Hospital of Bucharest. Patients were identified using International Classification of Diseases (ICD-10) codes and free-text diagnosis. Demographic and clinical data were extracted, including comorbidities, interventions, and mortality outcomes. Associations between comorbidities and in-hospital mortality were assessed using odds ratios (ORs) and 95% confidence intervals (CIs). Results: The study population had a mean age of 68.7 years, with a slight predominance of males (50.9%). In-hospital mortality was 53.9%, and 30-day mortality reached 85.1%. The most common comorbidities were diabetes (27.2%), chronic kidney disease (14.0%), and cancer (12.9%). Pneumonia (OR = 2.08, 95% CI: 1.89–2.28), cirrhosis (OR = 1.69, 95% CI: 1.40–2.03), and chronic obstructive pulmonary disease (OR = 1.50, 95% CI: 1.27–1.77) were strong predictors of mortality, while diabetes was associated with a slightly lower risk (OR = 0.90, 95% CI: 0.83–0.97). Conclusions: Sepsis-related mortality in Romania is higher than reported in Western Europe and North America, resembling trends in resource-limited settings. Targeted early recognition, antimicrobial stewardship, and improved intensive care units (ICU) resource allocation are crucial for reducing mortality. Multicenter studies and microbiological analyses are needed to further understand sepsis outcomes in this region.

Background: Abdominal wall hernias represent a significant global surgical burden, with over 20 million repairs performed annually. The convergence of rising obesity and diabetes rates with complex hernia management has necessitated innovative preoperative optimization strategies that address both metabolic dysfunction and mechanical challenges. Objectives: This comprehensive review synthesizes current evidence on emerging pharmacologic and procedural optimization strategies for patients undergoing abdominal wall hernia repair, with particular emphasis on glucagon-like peptide-1 (GLP-1) receptor agonists, botulinum toxin A (BTA) injections, progressive preoperative pneumoperitoneum (PPP) and biomechanical calculated repair. Methods: We conducted an extensive literature review incorporating recent clinical trials, observational studies, and meta-analyses, focusing on metabolic optimization with GLP-1 receptor agonists, mechanical preparation techniques, and their comparative effectiveness in reducing perioperative complications and hernia recurrence. Results: GLP-1 and GLP-1/GIP agonists demonstrate substantial metabolic benefits including weight reduction (10–20%), improved glycemic control, reduced systemic inflammation, and decreased postoperative complications in surgical populations. Recent evidence suggests reduced surgical site infection, thromboembolic events, and wound dehiscence in GLP-1 receptor agonists users. However, concerns regarding delayed gastric emptying and aspiration risk require careful perioperative management. BTA and PPP remain valuable techniques for mechanical optimization in loss-of-domain hernias, though modern biomechanically calculated repair (BCR) approaches using cyclic load analysis may reduce their necessity in many cases. The GRIP/CRIP concept demonstrates superior outcomes with 5–7% five-year recurrence rates compared to 15% with conventional approaches. Emerging evidence highlights collagen metabolism dysfunction as a fundamental determinant of hernia recurrence, prompting development of collagen-focused prehabilitation programs incorporating nutritional supplementation, aquatic exercise, and targeted physical conditioning. Conclusions: A paradigm shift toward integrated, personalized preoperative optimization is emerging, combining metabolic conditioning with mechanical preparation based on individual patient phenotypes and hernia complexity. Future research should focus on comparative effectiveness trials, optimal timing protocols, and multimodal strategies to maximize surgical outcomes while minimizing complications.