Search Results (328)

This review synthesizes current knowledge on the biology and ecology of the small cyclopoid copepod Oithona similis, a prevalent planktonic species in the Barents Sea, during the period of Arctic warming since the early 2000s. The region serves as an effective model system for examining the influence of different water masses on Arctic zooplankton dynamics. The highest abundances and biomass of Oithona similis are observed in Murmansk Coastal Waters (MCW) and Arctic Waters (ArW). Although its contribution to total zooplankton biomass is generally lower than that of higher copepod taxa, it can account for up to 27–35% seasonally and regionally. Ovigerous females are most abundant in Novaya Zemlya Waters (NZW) and ArW. Egg production rates exhibit a decreasing trend from south to north across the sea. Morphometric analyses reveal an increase in prosome length for both sexes, while relative antenna size diminishes from the south (MCW) to the north (ArW). The highest mortality rates occur during summer, coinciding with peak abundances of Oithona similis, its predators, and parasites, as well as increased interspecific competition. Based on morphological and reproductive parameters, three distinct populations are delineated within the Barents Sea: southern (MCW), central (Atlantic Water/Barents Sea Water), and northern/eastern (ArW/NZW), with respective life cycle durations of 11–12, 9–10, and 11 months, and typically one to two generations per year. The primary environmental drivers influencing population abundance, biomass, size, and reproduction are temperature and salinity, while chlorophyll a concentration predominantly affects mortality rates. Full article

Background: Chromobacterium violaceum is an emerging multidrug-resistant (MDR) Gram-negative bacterium associated with severe septicemia, abscess formation, and high mortality, particularly in immunocompromised individuals. Increasing antimicrobial resistance and the absence of approved vaccines underscore the urgent need for alternative preventive strategies. Traditional vaccine approaches are often inadequate against genetically diverse MDR pathogens, prompting the use of computational immunology and reverse vaccinology for vaccine design. Objectives: This study aimed to design and characterize a novel multi-epitope subunit vaccine (MEV) candidate against C. violaceum using a comprehensive pangenome-guided subtractive proteomics and immunoinformatics pipeline to identify conserved antigenic targets capable of eliciting strong immune responses. Methods: Comparative genomic analysis across eight C. violaceum strains identified 3144 core genes. Subtractive proteomics filtering yielded two essential, non-homologous, surface-accessible, and antigenic proteins—penicillin-binding protein 1A (Pbp1A) and organic solvent tolerance protein (LptD)—as vaccine targets. Cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes were predicted and integrated into a 272-amino-acid MEV construct adjuvanted with human β-defensin-4A using optimal linkers. The construct was evaluated through structural modeling, molecular docking with TLR4, molecular dynamics simulation, immune simulation, and in silico cloning into the pET-28a(+) vector. Results: The MEV construct exhibited strong antigenicity, non-allergenicity, and non-toxicity, with stable tertiary structure and favorable physicochemical properties. Docking and dynamics simulations demonstrated high binding affinity and stability with TLR4 (ΔG = −16.2 kcal/mol), while immune simulations predicted durable humoral and cellular immune responses with broad population coverage (≈89%). Codon optimization confirmed high expression potential in E. coli K12. Conclusions: The pangenome-guided immunoinformatics approach enabled the identification of conserved antigenic proteins and rational design of a promising multi-epitope vaccine candidate against MDR C. violaceum. The construct exhibits favorable immunogenic and structural features, supporting its potential for experimental validation and future development as a preventive immunotherapeutic against emerging MDR pathogens. Full article

Objective: This study aimed to investigate annual and seasonal trends, as well as regional differences, in female breast cancer mortality in Hungary between 2004 and 2023. Methods: Data on cancer mortality were obtained from the publicly available nationwide population register. Poisson and quasi-Poisson regression models were applied to investigate the annual trend in breast cancer mortality rates. Cyclic trends in mortality were analysed using the Walter–Elwood method, and regional differences in age-standardised mortality rates (ASMRs) were evaluated across Hungarian regions. Results: Over the two decades studied, a total of 42,779 deaths from breast cancer were recorded. A significant declining trend in annual ASMRs for female breast cancer was observed during the study period (IRR = 0.996; 95% CI [0.993–0.998]; p = 0.002). Seasonal analysis revealed a significant cyclic pattern, with the highest number of deaths occurring during the winter months, peaking in December. The highest age-standardised breast cancer mortality rate (43.9 ± 0.2 per 100,000 female persons per year) was observed in the Capital region (Budapest), while the lowest ASMR (36.2 ± 0.25 per 100,000 female persons per year) was found in the Northern Great Plain region (p = 0.028). Conclusions: Although Hungary has implemented a free national breast cancer screening programme, this study demonstrates that breast cancer mortality remains high in the country. Additionally, breast cancer mortality exhibits significant regional and seasonal variation. These findings underscore the need for targeted public health interventions and optimised resource allocation to improve outcomes. Full article

Background/Objectives: Acute respiratory distress syndrome (ARDS) represents a critical complication in polytrauma patients, characterized by diffuse lung inflammation and bilateral pulmonary infiltrates with mortality rates reaching 45% in intensive care units (ICU). The heterogeneous nature of ARDS and complex clinical presentation in severely injured patients poses substantial diagnostic challenges, necessitating early prediction tools to guide timely interventions. Machine learning (ML) algorithms have emerged as promising approaches for clinical decision support, demonstrating superior performance compared to traditional scoring systems in capturing complex patterns within high-dimensional medical data. Based on the identified research gaps in early ARDS prediction for polytrauma populations, our study aimed to: (i) develop a balanced random forest (BRF) ML model for early ARDS prediction in critically ill polytrauma patients, (ii) identify the most predictive clinical features using ANOVA-based feature selection, and (iii) evaluate model performance using comprehensive metrics addressing class imbalance challenges. Methods: This retrospective cohort study analyzed 407 polytrauma patients admitted to the ICU of the Center of Traumatology and Major Burns of Ben Arous, Tunisia, between 2017 and 2021. We implemented a comprehensive ML pipeline that incorporates Tomek Links undersampling, ANOVA F-test feature selection for the top 10 predictive variables, and SMOTE oversampling with a conservative sampling rate of 0.3. The BRF classifier was trained with class weighting and evaluated using stratified 5-fold cross-validation. Performance metrics included AUROC, PR-AUC, sensitivity, specificity, F1-score, and Matthews correlation coefficient. Results: Among 407 patients, 43 developed ARDS according to the Berlin definition, representing a 10.57% incidence. The BRF model demonstrated exceptional predictive performance with an AUROC of 0.98, a sensitivity of 0.91, a specificity of 0.80, an F1-score of 0.84, and an MCC of 0.70. Precision–recall AUC reached 0.86, demonstrating robust performance despite class imbalance. During stratified cross-validation, AUROC values ranged from 0.93 to 0.99 across folds, indicating consistent model stability. The top 10 selected features included procalcitonin, PaO₂ at ICU admission, 24-h pH, massive transfusion, total fluid resuscitation, presence of pneumothorax, alveolar hemorrhage, pulmonary contusion, hemothorax, and flail chest injury. Conclusions: Our BRF model provides a robust, clinically applicable tool for early prediction of ARDS in polytrauma patients using readily available clinical parameters. The comprehensive two-step resampling approach, combined with ANOVA-based feature selection, successfully addressed class imbalance while maintaining high predictive accuracy. These findings support integrating ML approaches into critical care decision-making to improve patient outcomes and resource allocation. External validation in diverse populations remains essential for confirming generalizability and clinical implementation. Full article

Background: Prostate cancer is a major public health concern in Ghana, where most cases present late and mortality remains high. Community education is essential for improving awareness and early detection. Traditional health talks are widely used, but interactive approaches such as board games have received little evaluation. Aim: To compare the effectiveness of a Social Cognitive Theory–Socioecological Model-based literacy board game (S-S-LIBOG) with a traditional health talk in improving prostate cancer knowledge, attitudes, and perceptions. Methods: A quasi-experimental, two-arm interventional study was conducted in a semi-urban Ghanaian cohort. Participants (n = 197) were allocated to either the board game arm (n = 80) or the health talk arm (n = 61) after accounting for attrition. A structured questionnaire measured knowledge, attitudes, and perceptions (KAP) before and after intervention. Statistical analyses at 5% alpha level included chi-square tests, two-proportion Z-tests, Wilcoxon signed-rank tests, and multivariate logistic regression. Results: Among participants, 29.4% were female, 64.5% male, and 6.1% other genders. Tertiary education was reported by 81.7%, secondary 9.6%, postgraduate 5.6%, and primary 3.0%. Ethnicities: Ewe 41.6%, Akan 26.9%, Northern 13.7%, Ga 6.6%, Guan 1.5%, others 9.6%. Rural dwellers: 29.9%. LIBOG improved ‘good knowledge level’ from 35.0% at baseline to 60.0% post-intervention, compared to 35.0% to 62.3% by the Health Talk (HT). S-S-LIBOG also narrowed gender, education, and lifestyle disparities in KAP, with males showing higher odds of positive attitude (OR = 4.16, p = 0.004) and perception (OR = 2.79, p = 0.047), and rural residents having increased odds of good knowledge (OR = 4.39, p = 0.041) post—its intervention. HT similarly equalized disparities, except for perception, which remained linked to education. The significant improvements in knowledge were (LIBOG: z = 2.85, p = 0.004; HT: z = 3.10, p = 0.002). Even though health talks achieved higher overall knowledge gains, no statistically significant difference in overall effectiveness was observed between the two methods (Wilcoxon W = 102.0, p = 0.107). Acceptability of the board game was high, with over 80% of participants reporting satisfaction. Conclusions: The S-S-LIBOG board game was not inferior to the traditional health talk, showing particular strengths in enhancing attitudes and perceptions. Its interactive and culturally adapted design makes it a feasible adjunct to conventional health education methods. Future studies should examine long-term impacts and application in more diverse populations. This study was retrospectively registered by the Pan African Clinical Trial Registry on 10 October 2025; with the Trial Registration number PACTR202510512711680. Full article

Background/Objective: The global burden of gastrointestinal (GI) cancers is rising sharply among the elderly, with a projected doubling of incidence and mortality by 2050. Given the heterogeneity of aging and the limitations of traditional performance scales such as ECOG or KPS, integrating geriatric assessment (GA) into oncology has become essential for tailoring safe and effective treatment strategies in this population. This paper provides a practical framework for implementing geriatric assessment and management (GAM) in GI oncology, particularly in resource-limited settings, and highlights validated screening instruments suitable for clinical integration. Methods: A systematic search was performed across PubMed, Scopus, and Web of Science databases for publications between January 2019 and August 2025 using combinations of the keywords geriatric assessment, gastrointestinal cancer, frailty screening, elderly, oncology, and comprehensive geriatric assessment. International and regional clinical practice guidelines from ASCO, ESMO, and SIOG were reviewed in detail. Articles were included when they addressed validated screening tools, oncology focused strategies, or clinical outcomes associated with GA-based interventions. Studies focusing exclusively on non-oncologic geriatric populations were excluded. Relevant data were extracted regarding study design, population, tool validation, predictive performance, and feasibility. Results: GA improves prediction of treatment-related toxicity, supports individualized treatment planning, and enhances quality of life and functional outcomes. Two-step screening approaches, initial frailty screening followed by comprehensive geriatric assessment for those with positive results, were found most effective. Practical GA models and telehealth-based applications were identified as feasible even in low- and middle-income contexts. Conclusions: Integrating GA into GI oncology fosters patient-centered, evidence-based care that optimizes treatment tolerance, reduces complications, and aligns therapeutic goals with patient values. Institutional commitment, interdisciplinary collaboration, and targeted training are pivotal for establishing GA as a standard of care across diverse healthcare settings. Full article

Background: Pulmonary embolism (PE) remains a major cause of cardiovascular morbidity and mortality. Classical risk factors explain only part of the interindividual variability in thrombotic risk. Non-O blood groups are associated with higher plasma levels of von Willebrand factor and factor VIII, suggesting a potential prothrombotic mechanism. This systematic review and limited meta-analysis examined the relationship between ABO blood group and PE risk. Methods: Following PRISMA 2020 guidelines, PubMed, Embase, and Web of Science were searched through August 2025 for observational studies reporting ABO blood group and objectively confirmed PE in adults. Eligible designs included cohort, case–control, and registry-based studies. Two reviewers independently extracted data and assessed risk of bias using the Newcastle–Ottawa Scale. Comparable effect estimates were pooled using a random-effects model (DerSimonian–Laird method, inverse-variance weighting). Results: Four studies met inclusion criteria, comprising more than 300,000 participants from North America, Europe, and Asia. All reported a higher incidence of PE among non-O compared with O blood groups. Pooled analysis of two large population-based cohorts yielded a summary relative risk of 1.36 (95% CI 1.20–1.54; I² = 2.6%), indicating a modest but consistent association. Data on recurrence, severity, and mortality were limited and heterogeneous. Conclusions: Non-O blood groups are associated with an approximately 30–40% higher risk of PE across diverse populations. While evidence is insufficient for causal inference, ABO phenotype represents a biologically plausible and readily available marker that may complement multifactorial models of thromboembolic risk. Full article

Background/Objectives: As of April 2025, La Réunion is facing a second major chikungunya virus (CHIKV) outbreak, following the 2005–2006 epidemic that infected nearly one-third of the population. IXCHIQ^®, a live-attenuated, single-dose vaccine, offers an opportunity for targeted immunization to complement vector control efforts. Using surveillance data up to 23 February 2025 (week 7), we estimated the potential scale of the 2024–2025 chikungunya outbreak in La Réunion and how much of the burden could have been averted by an emergency vaccination campaign at different detection thresholds. Methods: A stochastic SEIR–SEI host–vector model was calibrated to weekly case counts (weeks 46/2024–7/2025). We projected the epidemic under three vaccination-trigger scenarios (≥100, ≥3000, ≥40,000 detected cases) and two incremental vector-control assumptions (10% and 20% reductions in biting rate). Several mosquito-related parameters—extrinsic incubation period, offspring number, and mortality rate—were temperature-dependent, based on daily temperatures in La Réunion. Vaccination was applied homogeneously, using a 14.5% coverage to reflect the proportion of the population targeted in the initial public health recommendation. Results: Our findings indicate that without vaccination, up to 27.5% of the population could become infected. If vaccination would begin after 100 detected cases, 75% of infections could be prevented. Delaying until 3000 or 40,000 cases reduced effectiveness to 41% and 11%, respectively. Conclusions: Our results show that timely emergency vaccination can substantially reduce outbreak size. This underscores the importance of preparedness and rapid response by public health authorities in high-risk regions. Full article

Background: Advances in intensive care have markedly improved survival from acute critical illness. Nevertheless, the subsequent trajectory of these patients is heterogeneous: while most recover and are eventually discharged, approximately 10% remain dependent on life-support systems, forming a distinct group classified as chronic critical illness (CCI). These patients experience prolonged ICU stays, high mortality, and poor long-term outcomes. Prognostication in CCI remains challenging, as traditional severity scores based on admission data seem to lose prognostic accuracy progressively over longer ICU stays. This is particularly relevant in traumatic brain injury (TBI), where patients constitute a significant proportion of the CCI population and require specialized prognostic approaches. Objective: To develop and validate prognostic models for in-hospital mortality in patients with TBI who progress to chronic critical illness, comparing the performance of a traditional admission-based (left-aligned) model with a novel dynamic (right-aligned) model utilizing data from the week preceding the outcome. Methods: A real-world data analysis was conducted using the Russian Intensive Care Dataset (RICD v2.0). The cohort included 430 ICU admissions of adult TBI patients with a stay of ≥7 days. Multivariable logistic regression was used to develop two nomograms: one using parameters from ICU admission and another using data from 7 days prior to discharge or death. Model performance was assessed via ROC analysis, sensitivity, specificity, and predictive values. Results: The left-aligned model, based on admission data (coronary artery disease, multiorgan failure, CRP), showed moderate discriminative capacity (AUROC 0.720). In contrast, the right-aligned model, incorporating dynamic parameters from the pre-outcome period (lymphocyte count, platelet count, urea, CRP), demonstrated excellent predictive performance (AUROC 0.889), with 90.0% sensitivity and 98.6% negative predictive value. A high score on the right-aligned nomogram was associated with a 19.7-fold increased risk of mortality within the subsequent week. Conclusions: For patients with CCI following TBI, a dynamic prognostic model based on data from the immediate pre-outcome period significantly outperforms traditional admission-based models. The high negative predictive value of the right-aligned model provides a reliable tool for identifying patients with a low short-term risk of mortality, supporting a paradigm shift towards dynamic risk stratification in chronic critically ill patients. Full article

This study assesses air quality and health impact in Hanoi, Vietnam, using the Community Multiscale Air Quality (CMAQ) model and health impact assessment to evaluate the effectiveness of traffic emission reduction strategies under two scenarios. An updated emission inventory was used as the input data for the CMAQ model. The Weather Research and Forecasting (WRF-CMAQ) model (version 5.4), incorporating the CB6 chemical mechanism, was applied alongside a calibrated meteorological model to simulate pollutant dispersion. The model achieved strong performance in PM_2.5 simulation, with a correlation coefficient (R) of 0.78, an index of agreement (IOA) of −0.5, a Normalized Mean Bias (NMB) of 7.11%, and a normalized mean error (NME) of 28.51%. Seasonal analysis revealed higher concentrations of CO, NO₂, O₃, and SO₂ in January compared to July, driven by traffic and industrial emissions. Improved air quality in July was attributed to favorable meteorological conditions, such as increased rainfall and clean airflows from the sea. Spatial distribution highlighted elevated pollutant levels in urban areas, while PM_2.5 was significantly influenced by long-range transport and atmospheric processes. However, fine dust concentrations remained high in suburban areas, driven by secondary emissions and nearby industrial zones. An emission reduction scenario based on the Hanoi city policy decree focusing on traffic sources demonstrated its potential to reduce NO₂, SO₂, and PM_2.5 concentrations, though the impacts varied across time and space. Health impact due to population exposure to PM_2.5 shows that the densely populated suburbs surrounding the urban core have the largest impact in terms of mortality and cardiovascular diseases hospitalization. As PM_2.5 has the largest impact on these two health endpoints, only PM_2.5 impact assessment is performed. Health impact due to air pollution is higher in January (dry season) with estimated 625 deaths and 124 cardiovascular diseases (cvd) hospitalization as compared with estimated 94 deaths and 18 cvd hospitalization in July (wet season). One of the research questions posed by the city authority is whether converting diesel buses to electric buses can yield environmental and health benefits. Our work shows that the scenario based on Hanoi city decree of replacing 50% of fossil fuel combustion buses with electric buses by 2035 does not yield perceptible change in mortality health effect. This is due to emission from buses being small as compared to those from the whole transport sector and other sectors. This study emphasizes the need for integrated, targeted emission control strategies to address spatial and temporal variability in pollution. The findings offer valuable insights for policymakers to develop effective measures in urban planning for improving air quality and protecting the health of people in Hanoi. Full article

Background and Objectives: Despite modern therapy algorithms, ST-elevation myocardial infarction (STEMI) substantially contributes to cardiovascular morbidity and mortality worldwide. Early Risk assessment is crucial to guide therapy allocation, especially in countries with limited healthcare resources. Electrocardiographic parameters such as QRS fragmentation (fQRS) evolved as an important prognostic marker. The underlying mechanisms and specific risk factors for the occurrence of fQRS in patients with STEMI undergoing PCI have not been analyzed yet. Materials and Methods: Between 09/2020 and 06/2021, out of 179 consecutive patients with STEMI undergoing primary percutaneous coronary intervention (pPCI), 122 patients were included in this study. The occurrence of fQRS was analyzed and correlated to clinical as well as biochemical parameters. Results: In this population, the fQRS pattern was present in 33.6% (n = 41) of patients. Besides gender, no statistically significant differences in baseline characteristics or comorbidities were observed between the two groups. In univariable logistic regression analysis, both glomerular filtration rate (GFR) (p = 0.050) and C-reactive protein (CRP) (p = 0.014) were significantly associated with the presence of fQRS. However, in the multivariable logistic regression model, only CRP levels on admission remained independently associated with fQRS (OR = 3.44, 95% CI: 1.95; 6.05), (p = 0.029). Conclusions: In this analysis, a correlation between fQRS and CRP levels in patients with STEMI undergoing pPCI could be demonstrated. Consequently, fQRS might serve as a marker for extensive inflammation in the context of myocardial ischemia. Full article

The global burden of heart failure (HF) continues to escalate, with a lifetime risk approaching one in four adults in the United States. Concurrently, advances in cancer therapeutics have created a burgeoning population of long-term survivors, who now face the significant morbidity and mortality of chemotherapy-induced cardiovascular disease (CVD). This review addresses the critical overlap of these two pathologies, which share fundamental drivers such as oxidative stress, inflammation, and metabolic dysregulation. Epigallocatechin gallate (EGCG), the most abundant and biologically active polyphenol in green tea, has demonstrated pleiotropic bioactivity in preclinical models, encompassing potent antioxidant, anti-inflammatory, and anti-apoptotic properties. The central aim of this review is to provide a critical and comprehensive synthesis of the evidence supporting EGCG’s dual protective role. This review dissects its molecular mechanisms in modulating key pathways in HF and cardio-oncology, evaluates its translational potential, and importantly, delineates the significant gaps that must be addressed for its clinical application. This analysis uniquely positions EGCG not merely as a nutraceutical, but as a multi-target molecular therapeutic capable of simultaneously addressing the convergent pathological cascades of heart failure and cancer-related cardiotoxicity. The synthesis of preclinical evidence with a critical analysis of its translational barriers offers a novel perspective and a strategic roadmap for future research. Full article

Background: Vaccination reduces Coronavirus disease-19 (COVID-19) infection severity. We evaluated COVID-19 vaccine uptake and effectiveness in people with immune mediated inflammatory diseases (pIMIDs) versus the general population. Methods: Using population-based administrative health records, we identified cohorts between 2004 and 2022 with an IMID (rheumatoid arthritis n = 10,405, systemic autoimmune rheumatic disease n = 5888, inflammatory bowel disease n = 7911, multiple sclerosis n = 3665, psoriasis n = 23,948) who were matched (1:5) by age, sex, and region to general population comparators (n = 243,490) without these IMIDs. Between 1 January 2021 and 31 March 2022, rates of COVID-19 vaccine administration, hospitalizations with COVID-19 (Hosp-C), and all-cause mortality were assessed amongst pIMIDs and comparators using multivariable models. Results: More pIMIDs were vaccinated than comparators (87.3% vs. 84.7%, p < 0.0001). IMID diagnosis, increasing age, female sex, higher socioeconomic status, urban residence, immunotherapy use, and comorbidities were associated with increased odds of receiving at least two vaccine doses. pIMIDs had higher rates of Hosp-C (79 per 100,000, 95% confidence interval (CI) 77.8–80.2) than comparators (51 per 100,000, 95% CI 50.5–51.3; rate ratio 1.55; 95% CI 1.53, 1.58) and greater mortality [pIMID 1758 deaths, 3.61%; comparators (6346 deaths, 2.61%), RR 1.39 95% CI 1.32, 1.46)]. In multivariable analyses, vaccinated status was associated with less Hosp-C (OR 0.27, CI 0.23, 0.32) and death (HR 0.27 CI 0.24, 0.29); the association did not differ between IMID and comparator groups. Conclusions: Although COVID-19 vaccination reduced the risk of Hosp-C and death in both pIMIDs and comparators, pIMIDs remained at higher risk for both. Since SARS-CoV-2 is now endemic, these findings may inform ongoing vaccination recommendations. Full article

Recent investigations on the relationship between economic performance and COVID-19 mortality showed positive and negative associations of those variables on a national level. We propose a model that is composed of two branches to explain this contradiction: In this model, (1) higher GDP causes higher healthcare capabilities and lower COVID-19 mortality, and (2) higher GDP is associated with older populations which causes higher COVID-19 mortality. Accordingly, we speculate that (1) national economic performance (modelled through GDP) simultaneously acts as an attenuator (branch 1) and amplifier (branch 2) of COVID-19 mortality and that (2) the interaction between branches explains contradictory observations. To investigate our assumptions, we carried out partial correlation analyses for 79 countries. Results showed that in countries with below average healthcare capabilities (these are low GDP countries), age was a significantly stronger predictor of mortality than in countries with above average healthcare capabilities. By contrast, in countries with above average population age (these are high GDP countries), healthcare capabilities were significantly stronger predictors of mortality than in countries having below average population age. As a result, the attenuating effect of branch 1 dominated in high GDP countries, whereas the amplifying effect of branch 2 dominated in low GDP countries which explains contradictory outcomes of other studies. Full article

Background: Necrotizing enterocolitis (NEC) remains a leading cause of morbidity and mortality in very low birthweight (VLBW) infants. Human milk feeding and standardized feeding protocols are protective, but clinical practice varies, particularly in fortifier choice. Whether human milk-derived fortifiers reduce NEC risk compared with cow milk-derived fortifiers remains unclear. Methods: We conducted a systematic state-of-evidence review and meta-analysis, searching PubMed, Web of Science, and Scopus through July 2025. Eligible studies included RCTs and observational cohorts of VLBW infants comparing an exclusive human milk diet (EHMD) including human milk-derived fortifiers to cow milk-derived diets. Two reviewers independently screened and extracted data. Both RCTs and observational studies were included to evaluate consistency of effect estimates across designs and to account for heterogeneity in control group feeding practices. Pooled odds ratios (ORs) with 95% CIs were calculated using a Sidik–Jonkman random-effects model. Sensitivity analyses by study design and exclusion of infant formula from controls were performed. Results: Twenty studies (five RCTs, 15 observational; n = 6794 infants) met inclusion criteria, most enrolling infants born ≤1250 g. Compared with cow milk-containing diets, EHMD was associated with lower odds of Bell Stage ≥ 2 NEC (OR: 0.59; 95% CI: 0.42, 0.81; p < 0.001; n = 4625) and surgical NEC (OR: 0.43; 95% CI: 0.32, 0.58; p < 0.0001; n = 4754). In direct comparisons of fortifier type with a base diet of human milk, estimates suggested lower odds of Bell Stage ≥ 2 NEC by 35% (OR: 0.65; 95% CI: 0.44, 0.97; p = 0.03, n = 2102) and surgical NEC by 49% (OR: 0.51; 95% CI: 0.26, 0.98; p = 0.04; n = 1659) with human milk-derived fortifiers. Effect estimates were generally consistent across study designs, although precision and statistical significance varied. Conclusions: EHMD with human milk-derived fortifiers was associated with lower odds of medical and surgical NEC in VLBW infants, with most evidence from infants born ≤1250 g, reflecting current clinical use in the highest-risk population. Although the number and sample sizes of RCTs remain limited, the consistency of effect estimates across both RCTs and observational studies, together with significance of pooled analyses, strengthens confidence in these findings. Pragmatic and registry-based studies using standardized fortification protocols may provide the most efficient pathway to strengthen the evidence base. Full article