Search Results (2,208)

Toxoplasma gondii is a globally prevalent zoonotic parasite with major public health and veterinary impacts. In Egypt, One Health data on its distribution among blood donors and livestock are limited. This multicentric cross-sectional study aimed to determine the seroprevalence of Toxoplasma gondii among asymptomatic blood donors and livestock across six different Egyptian governorates and to identify the associated risk factors. Serum samples of 2000 asymptomatic blood donors and 500 animals (cattle and buffaloes) were tested for anti-Toxoplasma gondii IgG and IgM antibodies using ELISA. Sociodemographic and behavioral data were collected using a structured questionnaire. Overall IgG seroprevalence in blood donors was 41.8%, with IgM seropositivity at 2.1%. Significant regional variation was observed (p < 0.001), ranging from 66.5% in Alexandria to 16% in Cairo. The most significant risk factors were consumption of undercooked meat, contact with cats, and engagement in agricultural activities (p < 0.001). Among livestock, IgG and IgM seroprevalence were 7.2% and 5.2%, respectively, indicating active parasite circulation. The presence of seropositivity among apparently healthy donors raises concerns regarding transfusion safety. These findings highlight substantial and regionally heterogeneous Toxoplasma gondii exposure in Egypt. A One Health approach integrating public health education, food safety measures, and targeted screening of high-risk populations and animals is essential to reduce disease burden. Full article

Background: Transmitted drug resistance (TDR) remains a critical challenge in HIV-1 management, particularly in treatment-naïve populations. Baseline genotypic resistance testing is recommended to optimize antiretroviral therapy (ART), yet data from Saudi Arabia remain limited. This study aimed to characterize HIV-1 genetic diversity and baseline resistance-associated mutations among newly diagnosed, ART-naïve individuals. Methods: We conducted a multi-centre, retrospective cross-sectional study across three hospitals in Saudi Arabia between January 2023 and December 2024. Adult, treatment-naïve patients with confirmed HIV infection who underwent genotyping using Sanger sequencing were included. Mutations in reverse transcriptase (RT), protease (PI), and integrase (INSTI) genes were analyzed using the Stanford HIV Drug Resistance Database. Demographic, clinical, and virological data were collected, and comparative analyses between regions were performed. Results: A total of 614 patients were included, predominantly male (85.5%) and aged 25–44 years. Most patients presented with high viral loads (≥10,000 copies/mL, 89.7%), and 25.3% had CD4 counts <200 cells/mm³. HIV-1 subtype distribution was highly diverse, with subtype C (19.5%), CRF02_AG (15.6%), and subtype G (12.7%) predominating. Although mutations were frequently detected (RT: 85.2%, PI: 94.7%, INSTI: 36.4%), the majority were subtype-associated polymorphisms rather than major drug resistance mutations. Clinically significant mutations including M184V/I (1.17%), K103N (0.83%), and K65R (0.17%) were observed at low frequencies. No major INSTI resistance mutations were detected. Multi-class mutation patterns were common but largely driven by accessory variants. Conclusions: Despite the high prevalence of detected mutations, clinically significant TDR remained low, occurring in approximately 2.8% of patients. Most detected variants were polymorphic or accessory mutations, while susceptibility to INSTIs remained largely preserved. Continued baseline genotyping and molecular surveillance remain important to monitor emerging resistance patterns. Full article

Background/Objectives: This study aims to analyze safety and effectiveness of imipenem/cilastatin sodium (IPM/CS) as an off-label embolic agent in acute lower gastrointestinal bleeding (LGIB). Methods: This is a multicentric prospective study including patients treated in emergency with endovascular embolization for acute LGIB. IPM/CS particles were prepared using one vial containing 500 mg/500 mg of IPM/CS in powder diluted with 5 mL of pure iodine contrast agent. Inclusion criteria were: acute bleeding managed with IMP/CS embolization, unfeasible/ineffective endoscopic management, availability of a pre-procedural contrast-enhanced Computed Tomography (CT) scan, pre- and post-procedural blood count, pre- and post-procedural hemodynamic balance evaluation, and follow-up to 30 days. Exclusion criteria were: patients treated in elective conditions, LGIB embolization performed without IMP/CS, IMP/CS adoption after other embolics, incomplete clinical–laboratoristic follow-up, and age < 18 years. Technical success was intended as angiographic disappearance of extravasation or significant reduction/stasis of blood flow to the target; clinical success was considered as hemoglobin values increase and/or stop transfusions and/or hemodynamic restoration. Result: Twenty-one patients were enrolled; bleeding etiologies included angiodysplasia, diverticular disease, gastrointestinal tumor-related bleeding, and post-surgical hemorrhage. Technical success rate was 100%, and clinical success rate at 30 days was 85.7%. Rebleeding occurred in three patients: two managed with surgery and one with coil re-embolization. Neither major and IPM/CS related complications occurred. Conclusions: In this study IPM/CS was a safe and feasible embolic agent in selected patients with acute LGIB; no bowel ischemia occurred during the 30 day follow-up. Future studies with larger samples are required to confirm these findings to include IPM/CS as an off-label alternative embolic agent in LGIB. Full article

Background/Objectives: Ground-level falls (GLFs) are the leading cause of injury-related deaths in older adults, yet a validated bedside tool for early mortality risk stratification remains unavailable. The Braden scale, recorded routinely at intensive care unit (ICU) admission, has shown prognostic value across several critical illness populations. This study aimed to determine whether the admission Braden score is associated with in-hospital mortality in ICU patients admitted following a GLF, and to derive a simple bedside clinical risk score. Methods: A single-centre retrospective cohort study was conducted in a 216-bed mixed ICU over a four-year period (January 2020–June 2024). Adult patients admitted to the ICU following a GLF occurring outside the hospital were included. The primary outcome was in-hospital mortality. Multivariable logistic regression was used, and a five-component integer-weighted bedside risk score was derived. Internal validation was performed by 1000-fold bootstrap resampling. Results: Among 500 patients (median age 83 years; 63.3% female), 84 (16.8%) died. The admission Braden score was significantly lower in non-survivors (median 12 vs. 13; p < 0.001) and was an independent predictor of mortality after multivariable adjustment (adjusted OR 0.821 per one-point increase; 95% CI 0.706–0.954; p = 0.010). A five-component bedside risk score—incorporating the Braden score, INR, emergency admission, serum sodium, and procalcitonin—achieved a bootstrap-corrected AUC of 0.833 (95% CI 0.780–0.881) and stratified patients across a 16-fold mortality gradient (5.0% to 79.4%). Conclusions: The admission Braden score is associated with in-hospital mortality. When combined with four routine variables, discriminative performance improved. This score has undergone internal validation only. External validation in multicentre prospective cohorts is warranted before clinical use. Full article

Alzheimer’s disease (AD) is the most prevalent neurodegenerative disorder worldwide, affecting approximately 56.9 million people in 2021 and projected to reach 152 million by 2050. Its defining pathological features, amyloid-beta plaques and neurofibrillary tangles, accumulate for up to two decades before cognitive symptoms emerge, placing the preclinical and mild cognitive impairment (MCI) stages at the centre of the early detection problem. Despite this, current diagnostic practice in routine clinical settings remains unreliable, with post-mortem studies placing the specificity of clinical AD diagnosis between 44.3 and 70.8% even in specialist memory clinics. Machine learning (ML) and deep learning (DL) applied to neuroimaging and electrophysiological data have emerged as candidate tools for closing this diagnostic gap, yet whether the accuracy figures reported in published studies translate into clinically useful performance on independent data remains unresolved. This study presents a structured comparative review of machine learning and deep learning methods reported across four publicly available Alzheimer’s disease datasets, namely the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Open Access Series of Imaging Studies (OASIS), the OpenNeuro ds004504 electroencephalography (EEG) dataset, and the Kaggle Alzheimer’s magnetic resonance imaging (MRI) dataset. Thirteen model families are examined through the published literature rather than through new experiments, and for each model and dataset combination, the best accuracy reported in the source study is recorded alongside the model’s mathematical formulation. All performance figures reported in this abstract and throughout the paper are taken from the published studies reviewed, not from new experiments conducted by the authors. Across the reviewed studies, deep learning architectures pre-trained on ImageNet and fine-tuned on neuroimaging data are reported to produce the highest accuracy on MRI classification tasks. Residual Network (ResNet)-101 is reported at 98.21 percent on ADNI and 97.45 percent on OASIS, while the IncepRes fusion architecture reaches 98.35% on OASIS by combining multi-scale feature extraction from InceptionV3 with residual connectivity from ResNet152V2. Traditional machine learning classifiers remain competitive on tabular clinical and biomarker data, with Extreme Gradient Boosting (XGBoost) reaching 91% on ADNI multiclass features. Logistic Regression achieves 82 to 85% on binary ADNI classification and is the only classifier in this review that provides explicit per-feature prediction contributions without post hoc tooling. Gaussian Naïve Bayes achieves 80 to 83% on the same task. On the OpenNeuro EEG dataset, K-nearest neighbours (KNN) with singular value decomposition (SVD) entropy features achieves 91% binary accuracy, with feature engineering quality determining performance more reliably than classifier architecture. Eight principal findings emerge from the cross-dataset analysis. Binary classification consistently outperforms multiclass by 10 to 30% across all datasets, reflecting the genuine biological ambiguity of the mild cognitive impairment category. Dataset size and augmentation predict reported accuracy more reliably than model architecture. Ensemble methods outperform individual classifiers by 5 to 8% in nearly every imaging study. Deeper architectures can overfit small clinical cohorts. EEG models trail MRI models by approximately 10 to 15% on comparable binary tasks. Cross-dataset generalisation has not been systematically evaluated in most studies, and the few that have tested it report accuracy drops of 5 to 10% or more when models encounter data from different scanners or cohorts. Eight recurring limitations constrain the clinical utility of these findings. Small sample sizes and limited demographic diversity, severe class imbalance inflating raw accuracy metrics, poor cross-dataset generalisation driven by scanner heterogeneity, limited deep learning interpretability, the dominance of binary over multiclass tasks, the absence of longitudinal modelling despite available datasets, inadequate standardisation of preprocessing and evaluation protocols, and the signal-to-noise ratio constraints specific to EEG recordings of elderly patients collectively define the gap between benchmark performance and clinical readiness. Future work must prioritise multi-centre training cohorts, multimodal fusion architectures, longitudinal progression modelling, and standardised interpretability evaluation as non-optional requirements for any system intended for clinical deployment. Full article

Background: Patient-derived functional models have emerged as promising translational platforms capable of reproducing tumour-specific treatment sensitivity patterns, which could be used to personalise neoadjuvant treatment for patients with rectal cancer. Herein, we aimed to summarise the current comparative evidence in a meta-analytical framework on radiotherapy response between preclinical platforms and matched patient data. Methods: A systematic review was performed according to PRISMA principles to identify studies evaluating patient-derived functional models for the prediction of radiotherapy or chemoradiotherapy response in rectal cancer. Study characteristics, experimental protocols, predictive performance and clinical correlations were extracted. An exploratory hierarchical summary receiver operating characteristic (HSROC) meta-analysis was performed using studies providing sufficient data. Results: Eight studies involving patient-derived organoids and zebrafish patient-derived xenograft models were included. Most studies evaluated locally advanced rectal cancer treated with neoadjuvant chemoradiotherapy. The included studies demonstrated concordance rates ranging from 78% to 100% between ex vivo functional responses and matched clinical treatment outcomes. Reported predictive performance was favourable, with Yao et al. demonstrating 85.0% concordance, 78.0% sensitivity and 92.0% specificity, while Hsu et al. reported 87.5% sensitivity and 100% specificity using radiobiological modelling. Exploratory HSROC analysis demonstrated overall favourable discriminatory performance for prediction of treatment resistance and poor response. Conclusions: Patient-derived functional models, particularly PDOs, demonstrate promising potential as predictive biomarkers for radiotherapy and chemoradiotherapy response in rectal cancer. Although the current evidence remains exploratory and is limited by methodological heterogeneity and small cohorts, these platforms represent a promising translational strategy in precision radiation oncology, warranting prospective multicentre validation. Full article

Background: Preoperative inflammatory biomarkers, particularly the neutrophil-to-lymphocyte ratio (NLR), are established prognostic markers in oral cavity squamous cell carcinoma (OCSCC), yet their relevance at the biologically distinct timepoint of disease recurrence is unknown. We evaluated blood biomarkers measured at recurrence. Methods: From a retrospective cohort of 168 surgically treated OCSCC patients, 70 (41.7%) developed recurrence (49 local, 21 distant). NLR, lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), plasma fibrinogen, albumin and the prognostic nutritional index (PNI) at relapse were analysed against 5-year overall survival; multivariate logistic regression was adjusted for age and recurrence type. Results: Forty-nine of 70 patients (70.0%) died within 5 years. Fibrinogen was higher in deceased patients (median 595 vs. 464 mg/dL; p = 0.007) and was the only biomarker to retain independent significance (OR 1.005 per mg/dL; 95% CI 1.000–1.010; p = 0.038); in contrast, NLR lost significance (p = 0.156). LMR was significant univariately (p = 0.036); PLR, albumin and PNI were not. Conclusions: In this exploratory single-centre cohort, higher plasma fibrinogen at recurrence was independently associated with 5-year mortality, whereas inflammatory ratios were not. These hypothesis-generating findings warrant validation in larger, multicentre cohorts. Full article

Background/Objectives: Lead acrylic shields (LASs) enhance radiation protection, with variation of their usage among different specialties. This prospective multicentric observational study aimed to explore patterns of ocular radiation exposure and LAS usage among interventionalists from different disciplines and to assess behavioral dose changes in a longitudinally monitored subgroup. Methods: From July 2019 to July 2020, ocular doses (protected and unprotected) were measured in 15 interventionalists from four specialties (radiology, neuroradiology, cardiology and vascular surgery) across 2286 procedures using thermoluminescent dosimeters. Procedure type, operator position, total body dose, fluoroscopy time, dose area product, LAS usage and dose exceedances were documented. Ocular doses of five interventionalists, who participated in our previous study, allowed a longitudinal comparison of radiation doses and protective behavior. Results: Cumulative annual unprotected ocular doses ranged from 0 to 59 mSv, with five participants exceeding the annual limit of 20 mSv, whereas protected doses (0 to 18 mSv) remained within the limits. Procedural LAS usage was seen in 89% of radiologists and 82% of vascular surgeons. Participants with 100% LAS usage recorded minimal measurable ocular doses, whereas lower LAS compliance resulted in higher ocular doses. Longitudinal subgroup data analyses showed a decrease in ocular dose per procedure in all five participants, suggesting a potential learning effect, without statistical significance. Conclusions: Unprotected ocular doses exceeded the annual occupational eye lens dose limit in several participants, whereas protected doses remained within recommended limits in all participants. No specialty demonstrated universally lower ocular doses, while consistent LAS use proved highly effective in reducing the dose in all groups. Longitudinal findings suggest that structured dose monitoring and repeated training may support behavioral improvements in radiation protection over time. Full article

Background: Sudden sensorineural hearing loss (SSHL) is an acute auditory disorder with multifactorial causes. This study aimed to investigate the association between regional air pollution levels and SSHL case occurrence in our cohort. Methods: A total of 223 individuals diagnosed with sudden sensorineural hearing loss (SSHL) between 2016 and 2025 were included in the study at the Ear, Nose and Throat Clinic of Sivas Cumhuriyet University. An internal medicine specialist excluded metabolic causes based on concurrent laboratory tests and medical history records. The monthly averages of the following air pollution parameters were obtained from the central monitoring stations of the Ministry of Environment, Urbanisation and Climate Change in Sivas: PM₁₀, SO₂, PM_2.5, NOx, NO, CO and NO₂. The cumulative risk was then calculated by a public health specialist. The data were analyzed with a significance level set at 0.05. Results: A total of 223 patients with SSHL (mean age: 52.71 ± 7.38 years; 52.5% male) were analyzed, of whom 55.2% had left-ear involvement. Hearing thresholds differed significantly in both ears after treatment at all frequencies (250–6000 Hz) (p = 0.001), with the greatest mean change observed at 2000 Hz. Post-treatment hearing scores also showed statistically significant differences in both ears, and strong positive correlations were observed between pre- and post-treatment hearing levels (p < 0.001). Although there was no statistically significant seasonal variation in SSHL case distribution (p > 0.05), a significant association was identified between annual variations in air pollution levels and SSHL case occurrence. Conclusions: In this single-centre retrospective study, an association was identified between region-al air pollution levels and SSHL case occurrence. Given the retrospective single-centre design, ecological exposure assessment, and potential residual confounding, these findings should be interpreted as hypothesis-generating rather than as evidence of in-dividual-level causation or preventability. Larger multicentre studies incorporating individual exposure assessment are needed to further clarify this association. Full article

Background: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents the hepatic manifestation of systemic metabolic dysfunction and has become one of the leading causes of chronic liver disease worldwide. Although obesity is a major determinant of MASLD, the metabolic and lifestyle context in which the disease develops may vary across different geographical and dietary environments. The present study aimed to evaluate the prevalence of MASLD among adults with metabolic dysfunction from two European cohorts, to compare the clinical, metabolic, lifestyle, and psychological characteristics of participants with MASLD from Romania and Italy, and to explore differences according to MASLD status within each cohort. In addition, intestinal permeability was exploratorily assessed in a subgroup of the Italian cohort. Methods: This prospective multicentre observational study included 132 adults undergoing metabolic and hepatic evaluation in Romania (n = 52) and Italy (n = 80). Hepatic steatosis was assessed using SteatoTest in the Romanian cohort and ultrasonography in the Italian cohort. Anthropometric and metabolic parameters were recorded in all participants. Dietary quality was evaluated using the MEDI-LITE questionnaire, physical activity using the International Physical Activity Questionnaire (IPAQ), depressive symptoms using the Patient Health Questionnaire-9 (PHQ-9), and health-related quality of life using the 36-Item Short Form Health Survey (SF-36). Intestinal permeability was evaluated in the Italian cohort using the lactulose/mannitol absorption test. Results: MASLD was identified in 80.8% of participants from the Romanian cohort and in 66.3% of participants from the Italian cohort. Among patients with MASLD, Italian participants exhibited significantly higher body mass index, waist circumference, fasting insulin, total cholesterol, LDL cholesterol, and diastolic blood pressure compared with Romanian participants, whereas HDL cholesterol levels were significantly higher in the Romanian cohort. Sex-stratified analyses revealed significant sex-related differences in anthropometric and metabolic parameters within both cohorts. In both geographical populations, participants with MASLD demonstrated lower adherence to the Mediterranean diet, lower physical activity levels, higher depressive symptom burden, and less favorable quality-of-life indicators compared with participants without MASLD. Exploratory analyses of intestinal permeability in the Italian cohort did not reveal significant differences according to MASLD or obesity status. Conclusions: MASLD was highly prevalent in both Romanian and Italian adults with metabolic dysfunction. Patients with MASLD exhibited distinct metabolic and lifestyle profiles across the two geographical cohorts, supporting the potential contribution of environmental and lifestyle-related factors to MASLD heterogeneity. Lower adherence to the Mediterranean diet, reduced physical activity, and increased psychological burden were consistently associated with MASLD in both populations. Exploratory intestinal permeability analyses did not demonstrate significant differences according to MASLD or obesity status in the Italian cohort. Full article

Background/Objectives: Workplace violence (WPV) is a major occupational health hazard and psychosocial safety concern in psychiatric nursing, yet evidence integrating exposure, worker well-being, and workforce stability within a single theory-informed model remains limited in Saudi Arabia. This study examined associations between WPV and proximal occupational outcomes (burnout, job satisfaction, and absenteeism) and distal outcomes (quality of life [QoL] and turnover intentions) among psychiatric nurses and tested burnout as a statistical mediator of the WPV–turnover intentions association. Methods: A multicentre cross-sectional census survey was conducted across three psychiatric facilities in northern Saudi Arabia between June and August 2025 (N = 171). Participants reported WPV exposure over the preceding 12 months using Arabic versions of standardised instruments, including validated Arabic versions where available and a forward–backward-translated WVSQ. Linear, negative binomial, and logistic regression models examined outcome associations and factors associated with WPV exposure; the PROCESS macro (Model 4, 5000 bootstrap resamples) tested statistical mediation. Results: Most nurses reported at least one WPV incident in the preceding 12 months, most commonly verbal abuse. Younger age, male sex, shorter psychiatric nursing experience, lower perceived staffing adequacy, and inadequate security were associated with higher WPV exposure. WPV exposure was associated with lower QoL across all WHOQOL-BREF domains, higher burnout, lower job satisfaction, higher absenteeism, and stronger turnover intentions. Burnout showed a partial statistical mediation pattern in the WPV–turnover intentions association. Because the study was not specifically powered for the indirect effect, the mediation result should be interpreted with caution. Conclusions: In this cross-sectional study, WPV was a pervasive occupational exposure among Saudi psychiatric nurses and was associated with poorer QoL and higher turnover intentions, with burnout showing a partial statistical mediation pattern. Multilevel prevention, safer staffing, and structured post-incident psychological support are needed to support psychiatric nurses’ well-being and workforce retention. Full article

Background: Oral potentially malignant disorders (OPMDs) have a complex, but not consistently consistent, risk of transformation to oral squamous cell carcinoma (OSCC). The histopathologic grading of dysplasia is the traditional means of prognosis although there is considerable inter-observer variability and the tool has poor predictive value. Thus, image-based AI-based methods such as computational pathomics (CP), clinical-photograph deep learning (CDL), and optical or spectroscopic image analysis via machine learning (ML) or deep learning (DL) have been proposed as potential non-invasive risk stratification methods. Aim of the review is to identify the current state of the evidence for AI applications in the field of image-based diagnosis and treatment of OPMDs, their methodological characteristics and predictive accuracy, and priorities for future research. Methods: the scoping review was conducted using Joanna Briggs Institute methodology and PRISMA-ScR guidelines. The PubMed/MEDLINE, Scopus, Web of Science and Embase databases were searched between January 2018 and March 2026. Inclusion criteria were studies that used quantitative image analysis, ML or DL to diagnose, prognosticate, or stratify risk of OPMD in OPMD cohorts. A pre-piloted form was used to extract data which were then synthesized descriptively. Results: the 423 records identified included 24 (16 primary image-based studies and 8 contextual reviews) that met the inclusion criteria. The majority of studies were retrospective (15/16), and computational pathomics (n = 10), clinical-photograph deep learning and optical/spectroscopic imaging (n = 4) were emphasized. There was no study that used the conventional radiologic radiomics (CT, MRI, CBCT, or PET/CT) in OPMD cohorts. Overall, predictive performance was good, with AUROC values ranging from 0.73 to 0.96 for the detection of malignant transformation, 0.94 to 0.97 for OPMD versus OSCC discrimination, and 0.90 to 0.97 for dysplasia grading. Only 44% contained external validation, only 6% were prospective, and only limited adherence was made to IBSI, TRIPOD-AI and CLAIM standards. Conclusions: AI-based image recognition for OPMDs shows good predictive performance, and it has yet to be developed to a mature stage of the process. Future multicentre study, image standardisation, external validation and better reporting standards are needed. Remarkably, radiologic radiomics is an important and unexplored research gap in OPMD risk prediction. Full article

Background: Accurate delineation of ductal carcinoma in situ (DCIS) remains a key challenge in surgical planning. Although contrast-enhanced mammography (CEM) improves lesion detection, its clinical role in informing individualized surgical strategies remains unclear. This study evaluated the impact of CEM on preoperative assessment and surgical planning, with particular emphasis on whether its effect varies across patient subgroups. Methods: This multicentre pilot observational cohort study included 102 patients: 51 prospective patients undergoing preoperative CEM and mammography (MMG) and 51 retrospective controls assessed with MMG alone. Imaging-derived lesion size and planned resection volume were compared with pathological size using correlation analysis, intraclass correlation coefficient (ICC), and Bland–Altman methods. Surgical outcomes were assessed, and subgroup analyses explored differences according to CEM enhancement status. Results: CEM showed improved correlation with pathological DCIS size compared with MMG (ρ = 0.54 vs. 0.37), with the strongest agreement in CEM-positive lesions (ρ = 0.67; ICC 0.745). However, its clinical impact was not uniform. At the population level, CEM did not significantly change planned resection volume or surgical thresholds. In contrast, in CEM-positive patients, CEM was associated with larger planned resections, proportional to pathological tumor burden. Reoperation rates were lower in the CEM cohort (5.9% vs. 17.6%), without statistical significance, and margin status was comparable. Conclusions: The impact of CEM on surgical planning in DCIS is heterogeneous and largely confined to patients with enhancing lesions. These findings suggest that the value of CEM may lie in its selective use, where it can refine assessment of disease extent in specific subgroups rather than in routine application. Further studies incorporating predictive approaches are needed to support risk-adapted imaging strategies. Full article

Necrotising enterocolitis is a highly challenging condition in neonatal surgery, with a substantial proportion of affected infants requiring operative intervention with a significant associated morbidity and mortality. Radiological evidence of perforation represents a clear indication for surgery; however, in many other cases, the disease presentation and progression are heterogenous, with significant diagnostic and prognostic uncertainty. The surgical assessment and decision making in these cases relies on integrated judgement of the clinical trajectory, examination, and biochemical and radiological findings, as well as consideration of the comorbidities and gestational age. Although many have been proposed in the literature, there remains to be any universal validated thresholds or criteria for reliably identifying those infants who may be ‘failing medical management’ and are likely to develop intestinal necrosis. Similarly, comparisons of different surgical approaches (stoma, primary anastomosis, and damage-control strategies) and outcome reporting are often confounded by the disease severity index and patient selection, as well as the generally observational nature of studies within the field. Improved standardisation of disease and severity definitions, and the development of validated prognostic tools, will facilitate the earlier identification of infants most likely to benefit from surgery, which in turn could reduce delays to theatre and improve the outcomes. Multi-centre collaborative datasets provide important evidence in the path to achieving this aim, by providing valuable cohort and outcome data, which also contribute to informed shared decision making with parents and families. Full article

Introduction: Genetic susceptibility shapes paediatric oral health, yet candidate variants remain scattered across phenotype-specific studies. Aim: To synthesise genetic association evidence for oral and craniofacial phenotypes with paediatric onset, and to propose a candidate single-nucleotide polymorphism (SNP) panel to inform future risk-stratification research supporting precision prevention in paediatric dentistry. Methodology: A PRISMA 2020-informed systematic search of PubMed, Web of Science, and Scopus (2015–2024) identified genome-wide association studies (GWASs), meta-analyses, and replicated candidate-gene studies reporting SNP-phenotype associations for paediatric oral traits. Variants were assigned to five trait clusters and graded Strong, Moderate, or Weak against pre-specified replication, study design, and effect-estimate criteria. Phenotypic, population, and methodological heterogeneity precluded quantitative pooling; narrative synthesis was performed. Results: The candidate panel comprises 22 SNPs across five trait clusters: eruption and number; morphology, agenesis, and craniofacial growth; enamel structure and caries; periodontal inflammation; and pain sensitivity. Twelve variants (Tier 1) meet genome-wide significance or meta-analytic replication thresholds; ten (Tier 2) have moderate or exploratory evidence, designated for research-grade use pending prospective paediatric validation. Conclusion: This evidence-graded 22-SNP panel offers a reproducible candidate framework for future genetic risk-stratification research in paediatric dentistry, not a validated clinical test. Prospective multicentre validation, population-level calibration, and implementation studies are required before clinical adoption. The article reports a systematic evidence synthesis and panel design rationale, not assay or clinical validation data. Full article