Search Results (5,952)

Introduction: Multiple sclerosis (MS) is a chronic inflammatory and neurodegenerative disease of the central nervous system, frequently associated with visual and oculomotor disturbances. Quantitative analysis of eye movements represents a non-invasive method for assessing central nervous system dysfunction beyond conventional imaging; however, the diagnostic and predictive value of oculomotor metrics remains insufficiently defined. Objectives: The aims of this study were to compare smooth pursuit gain and reflexive saccade parameters (latency, velocity, and precision) between individuals with MS and healthy controls, and to evaluate their ability to discriminate disease status. Methods: This cross-sectional study included 46 clinically stable patients with MS (EDSS ≤ 6.5) and 46 age- and sex-matched healthy controls. Oculomotor function was assessed using videonystagmography under standardized conditions. Group differences across horizontal and vertical gaze directions were analyzed using linear mixed-effects models. Random forest models were applied to assess the discriminative performance of oculomotor parameters, with permutation-based feature importance and receiver operating characteristic (ROC) curve analysis. Results: Patients with MS showed significantly reduced smooth pursuit gain across most horizontal and vertical directions compared with controls. Saccadic latency was significantly prolonged in all tested movement directions. Saccadic velocity exhibited selective directional impairment consistent with subtle medial longitudinal fasciculus involvement, whereas saccadic precision did not differ significantly between groups. A random forest model combining pursuit and saccadic parameters demonstrated only moderate discriminative performance between MS patients and controls (AUC = 0.694), with saccadic latency contributing most strongly to classification. Conclusions: Quantitative eye-movement assessment revealed widespread oculomotor abnormalities in MS, particularly reduced smooth pursuit gain and prolonged saccadic latency. Although the overall discriminative accuracy of oculomotor parameters was limited, these findings support their potential role as complementary markers of central nervous system dysfunction. Further longitudinal and multimodal studies are required to clarify their clinical relevance and prognostic value. Full article

The traditional Chinese medicinal herb Gynura segetum is increasingly recognized for its hepatotoxic potential, primarily attributed to its pyrrolizidine alkaloid (PA) content. PAs are a leading cause of herb-induced liver injury (HILI) in China and are strongly linked to hepatic sinusoidal obstruction syndrome (HSOS). This review systematically summarizes the pathogenesis, diagnostic advancements, and therapeutic strategies for PA-induced HSOS. Molecular mechanisms of PA metabolism are detailed, encompassing cytochrome P450-mediated bioactivation and the subsequent formation of pyrrole–protein adducts, which trigger sinusoidal endothelial cell injury and hepatocyte apoptosis. Advances in diagnostic criteria, including the Nanjing Criteria and the Roussel Uclaf Causality Assessment Method (RUCAM)-integrated Drum Tower Severity Scoring System, are discussed. Furthermore, emerging biomarkers, such as circulating microRNAs and pyrrole–protein adducts, are examined. Imaging modalities, such as contrast-enhanced computed tomography (CT) and gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) magnetic resonance imaging (MRI), have evolved from descriptive tools into quantitative and prognostic instruments. Therapeutic approaches have evolved from supportive care to precision interventions, including anticoagulation, transjugular intrahepatic portosystemic shunt (TIPS), and autophagy-modulating agents. A comprehensive literature review, utilizing databases such as PubMed and Web of Science, was conducted to summarize progress since the introduction of the “Nanjing Guidelines”. Ultimately, this review underscores the critical need for integrated diagnostic and therapeutic frameworks, alongside enhanced public awareness and regulatory oversight, to effectively mitigate PA-related liver injury. Full article

Ocular melanomas, comprising uveal melanoma (UM) and conjunctival melanoma (CoM), represent the most common primary intraocular and ocular surface malignancies in adults. Although rare compared with cutaneous melanoma, they exhibit unique molecular landscapes that provide critical opportunities for biomarker-driven precision medicine. In UM, recurrent mutations in GNAQ and GNA11, together with alterations in BAP1, SF3B1, and EIF1AX, have emerged as key prognostic biomarkers that stratify metastatic risk and guide surveillance strategies. Conversely, in CoM, the mutational spectrum overlaps with cutaneous melanoma, with frequent alterations in BRAF, NRAS, NF1, and KIT, offering actionable targets for personalised treatment. Beyond genomics, epigenetic signatures, microRNAs, and protein-based markers provide further insights into tumour progression, microenvironmental remodelling, and immune evasion. In parallel, liquid biopsy has emerged as a minimally invasive approach for real-time disease monitoring. Analyses of circulating tumour DNA (ctDNA), circulating tumour cells (CTCs), and exosome-derived microRNAs demonstrate increasing potential for early detection of minimal residual disease, prognostic assessment, and evaluation of treatment response. However, the clinical integration of these biomarkers remains limited by tumour heterogeneity, technical variability, and the lack of unified translational frameworks. This review synthesises current knowledge of molecular and liquid biopsy biomarkers in ocular melanoma, highlighting their relevance for diagnosis, prognosis, and treatment personalisation. The integration of established tissue-based molecular markers with novel liquid biopsy technologies will enable a unique framework for biomarker-guided precision oncology and risk-adapted surveillance in uveal and conjunctival melanoma, offering insight into strategies for early detection, therapeutic monitoring, and personalised clinical management. Full article

Background: Altered lipid metabolism has been reported in several malignancies, but its clinical relevance in non-small cell lung cancer (NSCLC) remains uncertain. This study aimed to compare serum lipid parameters between NSCLC patients and healthy controls and to explore their association with histological subtype and selected driver mutations. Methods: We retrospectively analyzed serum total cholesterol (TC), low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglycerides (TG) in patients diagnosed with adenocarcinoma or squamous cell carcinoma from 2021 to 2024, alongside a control group of 100 healthy individuals. Statistical comparisons were performed using appropriate parametric or nonparametric tests after normality assessment (Shapiro–Wilk), and p-values were adjusted using the Benjamini–Hochberg false discovery rate (FDR). Results: A total of 160 NSCLC patients were included. Most were male (75.5%) and current or former smokers (96.1%), with a mean age of 70.4 ± 10.3 years. Squamous cell carcinoma was the predominant subtype (64.4%). Hypocholesterolemia was observed in 59.9% of patients, while hypercholesterolemia was less frequent (40.1%). Compared with controls, patients had significantly lower HDL levels (p = 0.007, FDR-adjusted p = 0.024), while other lipid markers showed no statistically significant differences after correction for multiple testing. Differences between adenocarcinoma and squamous cell carcinoma were not statistically significant. Squamous cell carcinoma patients had higher TG but lower TC, LDL, and HDL levels compared with adenocarcinoma. A negative correlation between TG and ROS1 expression remained significant (r = −0.223, FDR-adjusted p = 0.004). Conclusions: In this retrospective, real-world cohort, only HDL levels demonstrated a robust difference between NSCLC patients and controls. Observed associations should be interpreted cautiously due to potential confounding factors and incomplete clinical data inherent to retrospective analyses. Prospective studies are needed to clarify whether lipid alterations play a biological or prognostic role in NSCLC. Full article

Background and Objectives: Acute pancreatitis (AP) is an acute inflammatory disease ranging from mild, self-limiting forms to severe presentations associated with high morbidity and mortality. Early prognostic assessment is crucial for guiding clinical management. This study aimed to evaluate the prognostic value of the red cell distribution width-to-albumin ratio (RDW/Alb, RAR) in relation to clinically relevant outcomes, including intensive care unit (ICU) admission and in-hospital mortality, in patients with AP. Materials and Methods: This retrospective study included 282 patients diagnosed with AP who were hospitalized at Mersin University Hospital between January 2019 and February 2024. Clinical, laboratory, and radiological data were retrospectively analyzed. The predictive performance of RAR was evaluated and compared with established clinical scoring systems, including bedside index for severity in acute pancreatitis (BISAP), systemic inflammatory response syndrome (SIRS), harmless acute pancreatitis score (HAPS), and pancreatitis activity scoring system (PASS). Results: The median RDW-to-albumin ratio (RAR) was 3.9 (range: 2.6–36.7). Receiver operating characteristic (ROC) curve analysis demonstrated that RAR showed good predictive performance for ICU admission (Area Under the Curve (AUC): 0.781; p < 0.001; optimal cut-off: 4.15) and high predictive performance for in-hospital mortality (AUC: 0.927; p < 0.001; optimal cut-off: 5.26). RAR exhibited limited but statistically significant discriminatory performance when compared with the BISAP score (AUC: 0.591; p = 0.017), whereas no significant predictive performance was observed in relation to PASS, HAPS, or SIRS scores. Conclusions: Within the context of this retrospective cohort, RAR is a simple, inexpensive, and readily available biomarker that may be associated with ICU admission and in-hospital mortality in patients with AP. Given the absence of standard severity endpoints such as persistent organ failure or pancreatic necrosis, these findings should not be interpreted as evidence of conventional disease severity prediction but rather as hypothesis-generating observations that warrant validation in larger prospective studies. Full article

Background: Pulmonary infarction (PI) is the result of the occlusion of distal pulmonary arteries resulting in damage to downstream lung areas that become ischemic, hemorrhagic, or necrotic, and it is often a complication of an underlying condition such as pulmonary embolism (PE). Since in most of cases it is located peripherally, lung ultrasound (LUS) can be a good evaluation tool. The typical radiological features of PI are well-known; however, there are limited data on its sonographic characteristics and its evolution. Methods: The aim of this study is to evaluate, using LUS, a convenience sample of patients with acute PE with computed tomography (CT) consolidation findings consistent with PI. Patients’ clinical characteristics were collected and LUS findings at baseline and their short-term progression was assessed. LUS was performed within 72 h of PE diagnosis (T0) and repeated after one (T1) and four weeks (T2). Each procedure started with a focused examination of the areas of lesions based on CT findings, followed by an exploration of the other posterior and lateral lung fields. The convex probe was used for initial evaluation integrating LUS evaluation with the linear one was employed for smaller and more superficial lesions and when appropriate. Color Doppler mode was added to study vascularization. Results: From June to October 2023, 14 consecutive patients were enrolled at the Respiratory Unit of the University Hospital of Pisa. The main population characteristics included the absence of respiratory failure and prognostic high-risk PE (100%), the absence of significant comorbidities (79%), and the presence of typical symptoms, such as chest pain (57%) and dyspnea (50%). The average number of consolidations per patient was 1.4 ± 0.6. Follow-up LUS showed the disappearance of some consolidations and some morphological changes in the remaining lesions: the presence of hypoechoic consolidation with a central hyperechoic area (“bubbly consolidation”) was more typical at T1 while the presence of a small pleural effusion often persisted both at T1 and T2. A decrease in wedge/triangular-shaped consolidations was observed (82% at T0, 67% at T1, 24% at T2), as was an increase in elongated shapes, representing a residual pleural thickening over time (9% at T0, 13% at T1, 44% at T2). A reduction in size was also observed by comparing the mean diameter, long axis, and short axis measurements of each consolidation at the three different studied time points: the average of the short axes and the median of the mean diameters showed a statistically significant reduction after four weeks. Additionally, a correlation between lesion size and pleuritic pain was described, although it did not achieve statistical significance. Conclusions: Patients’ clinical characteristics and ultrasound features are consistent with previous studies studying PI at PE diagnosis. Most consolidations detected by LUS change over time regarding size and form, but a minority of them do not differ. LUS is a safe and non-invasive exam that could help to improve patients’ clinical approach in emergency rooms as well as medical and pulmonology settings, clinically contextualized for cases of chest pain and dyspnea. Future studies could expand the morphological study of PI. Full article

Background/Objectives: Malnutrition is highly prevalent in patients with acute leukemia and is frequently underrecognized at diagnosis. Traditional screening tools based on anthropometry often fail to identify early nutritional deterioration. This study aimed to evaluate the prognostic utility of a comprehensive morphofunctional assessment—including bioelectrical impedance vector analysis (BIVA), handgrip strength (HGS), and muscle ultrasound—conducted at diagnosis and after induction therapy, to evaluate the prognostic association with 12-month mortality. Methods: In this prospective cohort study, 52 adult patients with newly diagnosed acute leukemia were enrolled between November 2022 and November 2024 at two tertiary hospitals in Málaga, Spain. Nutritional status was determined using GLIM criteria. Morphofunctional assessment included BIVA-derived phase angle (PhA), HGS via dynamometry, and rectus femoris ultrasound. A second evaluation was performed prior to haematopoietic stem cell transplantation. Mortality at 12 months was the primary outcome. Logistic regression and ROC analysis were used to assess prognostic associations. Results: At baseline, 65.4% of patients were classified as malnourished. After three months, patients showed significant declines in PhA (−0.55°, p < 0.001), body cell mass (−3.15 kg, p < 0.01), skeletal muscle mass (−1.66 kg, p < 0.01), and rectus femoris cross-sectional area (−0.36 cm², p = 0.011). Baseline malnutrition (OR = 6.88; 95% CI: 1.17–40.38; p = 0.033) and PhA decline ≥ 0.90° were both independently associated with higher 12-month mortality. Conclusions: Early morphofunctional assessment using GLIM criteria, BIVA, and muscle ultrasound identifies patients at nutritional and functional risk. PhA decline during treatment was associated with higher 12-month mortality, supporting the need for early, personalized nutritional intervention in leukemia care. Full article

Background: People with Parkinson’s disease suffer from gait impairments. Clinical scales provide a limited and rater-dependent assessment of gait. Wearable sensors allow an objective characterization by capturing rhythm, pace, and signature patterns. This study investigated if sensor-derived gait parameters have prognostic value for short-term progression of gait impairments. Methods: A total of 111 longitudinal visit pairs were analyzed, where participants underwent clinical evaluation and a 4 × 10 m walking test instrumented with wearable sensors. Changes in the UPDRSIII gait score between baseline and follow-up were used to classify participants as Improvers, Stables, or Deteriorators. Baseline group differences were assessed statistically. Machine-learning classifiers were trained to predict group membership using clinical variables alone, sensor-derived gait features alone, or a combination of both. Results: Significant between-group differences emerged. In participants with UPDRSIII gait score = 1, Improvers showed higher median gait velocity ($0.81 \mathrm{m}/\mathrm{s}$) and stride length ($0.80 \mathrm{m}$) than Stables ($0.68 \mathrm{m}/\mathrm{s}$; $0.70 \mathrm{m}$) and Deteriorators ($0.59 \mathrm{m}/\mathrm{s}$; $0.68 \mathrm{m}$), along with lower stance time variability (3.10% vs. 4.49% and 3.75%; all $p<0.05$). The combined sensor-based and clinical model showed the best performance (AUC $0.82$). Conclusions: Integrating sensor-derived gait parameters with clinical score can support the identification of patients at risk of gait deterioration in the near future. Full article

Background: Artificial intelligence (AI) and machine learning (ML) are increasingly used in the diagnosis and management of bone metastases, spanning lesion detection, segmentation, prognostic modeling, fracture risk assessment, and surgical decision support. However, the literature is heterogeneous and rapidly evolving, making it difficult for clinicians to contextualize these developments. Methods: We performed a narrative review of the literature on AI/ML applications in bone metastasis management, focusing on studies that address clinically relevant problems such as detection and segmentation of metastatic lesions, prediction of skeletal-related events and survival, and support for reconstructive decision-making. We prioritized recent, peer-reviewed work that reports model performance and highlights opportunities for clinical translation. Results: Most published studies center on imaging-based diagnosis and lesion segmentation using radiomics and deep learning, with generally high internal performance but limited external validation. Emerging work explores prognostic models and biomechanically informed fracture risk estimation, yet these remain at an early proof-of-concept stage. Very few frameworks are integrated into routine workflows, and explainability, bias mitigation, and health-economic impacts are rarely evaluated. Conclusions: AI and ML tools have substantial potential to standardize imaging assessment, refine risk stratification, and ultimately support personalized management of bone metastases. Future research should focus on externally validated, multimodal models; development of AI-augmented alternatives to the Mirels score; federated multicenter collaboration; and routine incorporation of explainability and cost-effectiveness analyses. Full article

In addition to standardized lateral cephalometric radiographs, comprehensive assessment using dental cone-beam computed tomography (CBCT) and CT has become commonplace in the diagnosis and treatment of jaw deformities. Simulation based on cephalometric and CT data is particularly useful in the management of jaw deformities, both for evaluation and prognostic prediction. As such imaging examinations cover a wide anatomical region, it is not uncommon for various incidental pathologies to be discovered. This review emphasizes the necessity of evaluating the entire imaged area in addition to the chief complaint. Furthermore, it outlines the essential anatomical structures that should be assessed during diagnostic imaging performed prior to representative surgical procedures for jaw deformities (e.g., sagittal split ramus osteotomy and Le Fort I osteotomy). This review paper is descriptive in nature, incorporating our facility’s empirical aspects, and presents representative cases in a narrative format; it is not a systematic review. In other word, as the evidence-based literature does not cover all aspects of pretreatment evaluation, these criteria are based on the past experience of the authors. Full article

Glioblastoma (GBM) shows extensive epigenetic heterogeneity. In IDH-wildtype (IDH-WT) GBM, promoter DNA methylation may regulate lineage programs influencing tumor evolution and prognosis; here, we systematically profiled promoter-level methylation dynamics across longitudinal tumors. Genome-wide DNA methylation data were obtained from the publicly available Gene Expression Omnibus (GEO; GSE279073) dataset, comprising a longitudinal cohort of 226 IDH-wildtype glioblastomas profiled on the Illumina Infinium EPIC 850K array across primary and recurrent stages at the University of California, San Francisco. From 333 Gene Ontology gliogenesis-annotated genes (GO:0042063), a 48-gene promoter panel was derived, with ≥2 probes per gene. Promoter methylation was summarized as the median β-value and tested using one-sample Wilcoxon with FDR correction. Functional enrichment, longitudinal variation, and patient-level methylation burden were assessed. Validation analyses were performed using independent IDH-wildtype GBM datasets from The Cancer Genome Atlas (RNA-seq and 450K methylation; n = 347). Promoter hypomethylation predominated across all stages, with 25 genes consistently hypomethylated and 7 hypermethylated. Functional enrichment highlighted gliogenesis, glial cell differentiation, neurogenesis, and Notch-related signaling. In TCGA, promoter methylation inversely correlated with expression for 11 of 33 genes (FDR < 0.05). An Expression Score contrasting hypomethylated and hypermethylated genes was positively associated with improved overall survival, where higher scores predicted better outcome (HR = 0.87, p = 0.016; Q4 vs. Q1 HR = 0.68, p = 0.025), and a complementary Methylation Score showed that higher promoter hypermethylation predicted poorer outcome (HR = 1.73, p < 0.001). CNTN2 and TSPAN2 were adverse prognostic genes (FDR < 0.05). The Expression Score was highest in Proneural tumors and lowest in Mesenchymal tumors (p < 0.001), reflecting a proneural-like state associated with better prognosis. Promoter methylation within gliogenesis genes defines a stable yet prognostically informative epigenetic signature in IDH-WT GBM. Hypomethylation promotes transcriptional activation and a favorable outcome, whereas hypermethylation represses lineage programs and predicts poorer survival. Full article

Battery management systems (BMSs) are integral components of electric vehicles (EVs), as they ensure the safe and efficient operation of lithium-ion batteries. State of health (SoH) estimation is one of the core functions of BMSs, providing an assessment of the current condition of a battery, while prognostics aim to predict remaining useful life (RUL) as a function of the battery’s condition. An accurate SoH estimation allows proactive maintenance to prolong battery lifespan. Traditional SoH estimation methods can be broadly divided into experiment-based and model-based approaches. Experiment-based approaches rely on direct physical measurements, while model-driven approaches use physics-based or data-driven models. Although experiment-based methods can offer high accuracy, they are often impractical and costly for real-time applications. With recent advances in artificial intelligence (AI), deep learning models have emerged as powerful alternatives for SoH prediction. This paper offers an in-depth examination of AI-driven SoH prediction technologies, including their historical development, recent advancements, and practical applications, with particular emphasis on the implementation of widely used AI algorithms for SoH prediction. Key technical challenges associated with SoH prediction, such as computational complexity, data availability constraints, interpretability issues, and real-world deployment constraints, are discussed, along with possible solution strategies. Full article

Despite the introduction of novel therapeutic options, the prognosis of advanced endometrial cancer remains poor. In recent years, increasing attention has been directed toward the molecular characterization of endometrial cancer. However, data specifically focusing on advanced-stage disease are still limited. In our single-center, retrospective, exploratory study with a limited sample size, we analyzed 32 patients with advanced or recurrent endometrial cancer treated at the Modena Cancer Center. Comprehensive molecular profiling was performed to assess DNA mutations, copy number variations, and RNA expression. We characterized the molecular landscape of this cohort, evaluated selected genomic alterations across predefined clinical subgroups, and explored their association with overall survival. Consistent with previous reports, a high prevalence of PTEN and PIK3CA mutations were observed. Patients experiencing relapse more than six months after diagnosis were more likely to harbor CTNNB1 mutations. KRAS mutations were more frequently detected in younger patients and in those with endometrioid histology, whereas PPP2R1A and TP53 mutations were enriched in tumors with non-endometrioid histology. Notably, CTNNB1 mutations were associated with a favorable prognostic impact, while KRAS mutations correlated with poorer overall survival. Our findings underscore the need for further investigation into the molecular landscape of advanced endometrial cancer, particularly in the context of therapeutic implications. Combinatorial treatment strategies targeting specific molecular alterations, such as KRAS, in combination with other targeted agents or therapeutic approaches, warrant further exploration. Full article

Background: Early recognition of renal allograft dysfunction requires biochemical markers capable of detecting molecular injury before functional decline becomes apparent. Serum creatinine, a late and nonspecific indicator of renal function, has limited value for early diagnosis. Protein biomarkers implicated in tubular injury, inflammation, and immune activation—including neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), β2-microglobulin, interleukin-1β (IL-1β), and tumor necrosis factor-α (TNF-α)—have emerged as promising alternatives. This study evaluated early post-transplant serum profiles of these biomarkers and their prognostic relevance for long-term graft outcomes. Methods: Nineteen adult recipients undergoing primary kidney transplantation were prospectively enrolled. Serum creatinine and protein biomarkers were measured 24 h post-transplant using validated immunochemical assays. Biomarker concentrations were compared with values from healthy controls, and correlations with renal function at 12 months were assessed. Receiver operating characteristic (ROC) analysis was used to evaluate predictive performance. Results: Significant biochemical alterations were observed at 24 h post-transplant. KIM-1 levels were markedly elevated compared with controls (74.50 ± 98.45 vs. 10.54 ± 17.19 ng/mL; p = 0.01), consistent with early tubular injury. IL-1β and NGAL showed upward trends without reaching statistical significance. β2-microglobulin and TNF-α levels did not differ substantially from control values. Serum KIM-1 correlated with serum creatinine both at 24 h (r = 0.35) and at 12 months (r = 0.40). ROC analysis identified a KIM-1 threshold of 24.5 ng/mL (AUC = 0.68) as a potential indicator of future graft dysfunction, outperforming serum creatinine (AUC = 0.64). Six patients experienced graft dysfunction at 12 months post-transplant, five of whom had serum creatinine values > 5 mg/dL at 24 h. Based on early creatinine levels, patients were stratified into low-risk (creatinine < 5 mg/dL; n = 10) and high-risk groups (creatinine > 5 mg/dL; n = 9). Mean KIM-1 concentrations were significantly higher in the high-risk group (110.68 ± 115.29 vs. 26.67 ± 18.05 ng/mL; p = 0.05), consistent with more severe early tubular injury. Conclusions: Among the evaluated biomarkers, KIM-1 demonstrated the strongest potential as an early biochemical indicator of renal allograft dysfunction. Its rapid post-transplant elevation underscores its sensitivity to early tubular injury. Further prospective validation in larger, multicenter cohorts is warranted. Full article

Background and Objectives: Early recognition of life-threatening organ dysfunction is central to modern sepsis frameworks. We systematically reviewed the prognostic performance and clinical utility of the Neonatal Sequential Organ Failure Assessment (nSOFA) for mortality and major morbidity in NICU populations. The search identified 939 records across databases; after screening and full-text assessment, 16 studies met the inclusion criteria. Methods: Following PRISMA guidance, we searched major databases (2019–2025) for observational or interventional studies reporting discrimination or risk stratification using nSOFA in neonates. Populations included suspected/proven infection and condition-specific cohorts. Heterogeneity in timing, thresholds, and outcomes precluded meta-analysis. Results: A cumulative sample exceeding 25,000 neonates was identified across late- and early-onset infection, all-NICU admissions, necrotizing enterocolitis, respiratory distress, and very preterm screening cohorts. Across settings and timepoints, nSOFA demonstrated consistent, good-to-excellent mortality discrimination, with reported AUROCs ≥ 0.80 and upper ranges near 0.90–0.92; serial scoring within the first 6–12 h generally improved risk classification. Disease-specific applications (NEC, early-onset infection) showed similar discrimination for death or composite adverse outcomes. Conclusions: Evidence from diverse NICU contexts indicates that nSOFA is a pragmatic, EHR-ready organ dysfunction score with robust discrimination for mortality and serious morbidity, supporting routine, serial use for risk stratification and standardized endpoints in neonatal sepsis pathways, aligned with contemporary organ dysfunction–based pediatric criteria. Full article