Background/Objectives: Sepsis is a severe medical condition characterized by a dysregulated host response to infection, with potentially fatal outcomes, requiring early diagnosis and rapid intervention. The limitations of traditional sepsis identification methods, as well as the complexity of clinical data generated in intensive care, have driven increased interest in applying artificial intelligence in this field. The aim of this narrative review article is to analyze how artificial intelligence is being used in the diagnosis and prognosis of sepsis, to present the most relevant current models and algorithms, and to discuss the challenges and opportunities related to integrating these technologies into clinical practice. Methods: We conducted a structured literature search for this narrative review, covering studies published between 2016 and 2024 in databases such as PubMed/Medline, Scopus, Web of Science, IEEE Xplore, and Google Scholar. The review covered models based on machine learning (ML), deep neural networks (DNNs), Recurrent Neural Networks (RNNs), and clinical alert systems implemented in hospitals. The clinical data sources used, algorithms applied, system architectures, and performance outcomes are presented. Results: Numerous artificial intelligence models demonstrated superior performance compared to conventional clinical scores (qSOFA, SIRS), achieving AUC values above 0.90 in predicting sepsis and mortality. Systems such as Targeted Real-Time Early Warning System (TREWS) and InSight have been clinically validated and have significantly reduced the time to treatment initiation. However, challenges remain, such as a lack of model transparency, algorithmic bias, difficulties integrating into clinical workflows, and the absence of external validation in multicenter settings. Conclusions: Artificial intelligence has the potential to transform sepsis management through early diagnosis, risk stratification, and personalized treatment. A responsible, multidisciplinary approach is necessary, including rigorous clinical validation, enhanced interpretability, and training of healthcare personnel to effectively integrate these technologies into everyday practice.

Background: Given the increasing rate of infections following hip arthroplasty, one of the current options is the application of a biocomposite at the site of the infection. One of the products used is Stimulan, a completely resorbable calcium sulfate, designed to treat acute and chronic infections. This biocomposite has a controlled purity, is easy to mix with liquid, powder, and antibiotics, and can be applied directly to the site of infection, or it can be injected. Methods: We analyzed data from 76 patients, who were admitted to the County Clinical Hospital of Emergency “St. Apostol Andrei” in Galati during January 2017–September 2023, with a diagnosis of infection associated with hip arthroplasty. Results: In 69.73% of cases (52 patients), we decided to keep the implant in place. In this subgroup, Stimulan was applied in 26 cases (57.78%). Of these, 100% were cured—compared to the subgroup in which Stimulan was not applied, where this percentage was lower. All patients underwent chemical and mechanical toileting, and for 24 patients (20.27%), it was necessary to ablate the implant with or without the application of Stimulan, then reimplantation of the prosthesis. Conclusions: The patients with Stimulan had a longer average length of hospitalization, almost half of them required intervention in two periods, and a quarter required the implantation of spacers. However, the cure rate was higher, only in three people could we not control the infection, and there was no death. This study confirms the effectiveness of the treatment when using a biocomposite in addition to the classical treatment for both acute and chronic cases.

The incidence of right colon cancer presenting in a stage with complications is significant. There are major differences in therapeutic approach between elective colon cancer surgery and emergency surgery. Complications such as hemorrhage, obstruction, and perforation require careful evaluation of prognostic factors, with morbidity and mortality rates being much higher compared to elective colon surgery. We retrospectively analyzed a group of 95 patients admitted in an emergency to the County Emergency Hospital St. Apostol Apostol Andrei Galati with complicated tumors of the right colon—occlusive, perforated, or hemorrhagic. A series of clinical and biological parameters were followed in order to identify the prognostic factors in the occurrence of death. We analyzed the specialized literature, comparing our study with other similar research from the most important databases. The postoperative death rate in patients with complicated right colon cancer was high. Most complications were occlusive, followed by hemorrhagic and perforative.

Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental disorder in which dopaminergic dysfunction plays a central role. Beyond its neurotransmitter function, dopamine is a redox-active molecule capable of generating reactive oxygen species and toxic intermediates, particularly when cytosolic dopamine accumulates because of altered vesicular storage or transporter imbalance. This review examines whether dopamine-derived oxidative stress may represent a biologically plausible and testable framework for ADHD by integrating current evidence on dopamine metabolism, oxidative stress, and neuronal dysfunction, while distinguishing direct evidence from indirect and translational findings. A structured literature search was conducted in PubMed, Scopus, and Web of Science for relevant English-language studies published between January 2000 and March 2026. The available evidence suggests that dopamine-derived oxidative stress may help link disturbed dopamine handling to protein modification, lipid peroxidation, mitochondrial dysfunction, synaptic inefficiency, and circuit-level abnormalities in ADHD. Although direct in vivo evidence remains limited, this framework may help distinguish dopamine-derived oxidative stress from more general oxidative imbalance in ADHD and may guide future biomarker-based, experimental, and translational research.

Cardiac telerehabilitation has become a promising alternative to traditional programmes for preventing acute coronary syndrome (ACS) in the secondary phase. However, current implementations are still reactive and standardised, lacking personalisation and flexibility in clinical settings. By integrating artificial intelligence (AI), it may be possible to overcome these limitations and provide intelligent, scalable, and patient-centred care. Methods: We conducted a structured literature review across PubMed, Scopus, the Cochrane Library, and Web of Science, targeting English-language studies published from January 2015 to May 2025. Inclusion criteria included adult populations with a history of ACS or high cardiovascular risk, assessing interventions based on AI, telerehabilitation, or their combination. Studies are needed to report clinical, functional, behavioural, or technological outcomes. A thematic narrative synthesis was utilised. Results: AI-enhanced telerehabilitation demonstrates potential advantages over conventional digital care in selected domains, including adaptive risk prediction, personalised exercise modulation, and adherence support. Several systems report real-time adjustment of exercise protocols, early dropout detection, and predictive analytics for rehospitalisation. AI integration may also contribute to personalised behavioural feedback and psychosocial monitoring. Nevertheless, the overall level of evidence remains preliminary and heterogeneous, with most AI-based interventions evaluated in pilot, feasibility, or modelling studies rather than large-scale randomized trials. Conclusions: The integration of AI into telerehabilitation represents a promising evolution in post-ACS care, shifting from predominantly reactive monitoring toward more adaptive and data-driven support models. While early-phase studies suggest feasibility and potential clinical benefit, robust multicentre randomized controlled trials and cost-effectiveness analyses are required before definitive conclusions regarding superiority or widespread implementation can be drawn.

Background and Objectives: Retinopathy of prematurity (ROP) remains a leading cause of preventable childhood blindness, with its severity influenced by a complex interaction between nutritional status, metabolic maturation, and systemic vulnerability. This study aimed to evaluate whether early nutritional patterns and serum metabolic parameters, including hepatic and renal biomarkers, are associated with ROP severity and whether they may serve as potential predictors of disease progression. Materials and Methods: We conducted a retrospective study on 140 preterm infants, totaling 280 eyes, admitted between 2021 and 2024 in two neonatal intensive care units (NICU). Each eye was analyzed independently according to International Classification of Retinopathy of Prematurity (ICROP) criteria. Data on the timing of enteral feeding, duration and type of nutrition, and serum levels of alanine aminotransferase (ALT), aspartate aminotransferase (AST), total protein, blood glucose, urea and creatinine were collected throughout the first 28 days of life. Statistical analysis included Kruskal–Wallis and Chi-square tests, with a significance threshold of p < 0.05. Results: ROP was identified in 53.57% of cases. Enteral feeding began earlier in infants without ROP, whereas delayed initiation and prolonged parenteral nutrition were associated with more advanced stages. Natural feeding decreased with increasing severity and was absent in aggressive retinopathy of prematurity (A-ROP). Severe disease stages showed higher AST, ALT, urea and creatinine levels, along with lower early total protein values. Glycemic instability was observed more frequently in stage 2 and stage 3. Conclusions: Early nutritional support, especially early enteral feeding and natural feeding, appears protective against ROP progression. Hepatic, renal and glycemic metabolic changes are closely correlated with disease severity, indicating that metabolic balance reflects overall vulnerability in preterm infants. Incorporating nutritional and metabolic assessment into routine screening may enhance early risk identification and optimize clinical monitoring.