Search Results (23,663)

Background: Digital surgery integrates advanced imaging, computational modeling, additive manufacturing, and intraoperative navigation technologies. Although widely explored, most platforms remain fragmented and lack regulatory cohesion. The B-onic Platform was conceived as a unified workflow that enables surgical planning, device personalization, and intraoperative navigation within a regulatory-compliant framework. Objective: This study aimed to present a comprehensive single-center clinical evaluation of the implementation of the B-onic Platform in a large single-center cohort, focusing on efficiency, patient safety, and surgeon-reported outcomes. Methods: A retrospective review of 308 consecutive surgical plans was performed at La Paz University Hospital (Madrid, Spain) between 2020 and 2024 and compared with institutional historical controls from 2018 to 2019. Procedures included maxillofacial surgery, traumatology, reconstructive surgery, and other specialties. The platform incorporated imaging-based CAD modeling, 3D-printed biomodels and guides, and immersive validation through the NavigatorPro XR module. Outcomes analyzed were preoperative planning time, operative duration, 30-day complication and rehospitalization rates, intraoperative blood loss, and surgeon-reported perception of anatomical understanding and intraoperative confidence. Results: Mean preoperative planning time was reduced by 34% (−42 h; 95% CI: −48 to −36 h; p < 0.01) compared with historical controls. Mean operative duration decreased from 226 ± 74 min to 181 ± 61 min (−45 min; 95% CI: −52 to −38 min; p < 0.001). The 30-day postoperative complication rate decreased from 12.9% to 10.7% (absolute reduction 2.2%; 95% CI: 0.2–4.1%; p = 0.037), while rehospitalization rates declined from 9.1% to 4.3% (p = 0.012). Mean length of hospital stay decreased from 6.8 ± 3.1 to 5.2 ± 2.3 days (p = 0.022), and intraoperative blood loss was reduced by 12–30% across specialties (p = 0.008). NavigatorPro XR halved validation time for guides and implants (71.8 ± 22.4 h vs. 35.6 ± 18.9 h; p < 0.001). Ninety-two percent of surveyed surgeons reported improved 3D anatomical understanding and enhanced intraoperative safety. Conclusions: The B-onic Platform has transitioned from a prototype to a consolidated system, integrated into routine practice with significant gains in efficiency, safety, and training value. These findings support the potential of the platform as a precision surgery model; however, further multicenter prospective studies are required to confirm scalability. Full article

The 2025 approval of the selective NaV1.8 blocker suzetrigine for acute pain marked a pivotal advance in analgesic drug development. Yet the subsequent failure of Vertex’s next-generation NaV1.8 inhibitor VX993 to demonstrate clinical analgesia underscores enduring challenges in translating mechanistic promise into patient benefit. This review examines why promising targets and compounds, spanning NaV and TRP channels, often falter and outlines a path toward more reliable target selection and validation. I first summarize the pain pathway, from nociceptor transduction through spinal processing to cortical perception, emphasizing how inflammation and peripheral sensitization reshape excitability. Historically serendipitous, pain drug discovery now prioritizes molecular precision. Most approved chronic pain therapies act in the CNS and are limited by modest efficacy and adverse effects. Nociceptor-enriched targets (NaV1.7/1.8/1.9; TRP channels) remain attractive, yet redundancy among NaV subtypes and the necessity of blocking targets at the correct anatomical sites complicate translation. Human genetics and multi-omics provide a powerful, unbiased engine for target discovery. Rare high-impact variants offer strong causal hypotheses, while common polygenic contributions illuminate broader susceptibility. Large biobanks increasingly reveal a mismatch between legacy pain targets and genetically supported candidates across neuronal and non-neuronal cells. Human DRG transcriptomics highlight NaV channel redundancy. Human in vitro electrophysiology and PK/PD analyses show suzetrigine achieves ~90–95% NaV1.8 engagement, yet neurons can still fire unless additional channels are blocked. Species differences and drug distribution (including BBB/PNS penetration and P-gp efflux) critically influence efficacy; centrally accessible blockade (e.g., for NaV1.7 or TRPA1) may be necessary to achieve robust analgesia, challenging peripherally restricted strategies. Osteoarthritis illustrates how obesity-driven metabolic inflammation, synovial immune activation, subchondral bone remodeling, and specific nociceptor subtypes converge to drive mechanical pain. Multi-omic integration across diseased human tissues can pinpoint causal processes and cell types, enabling more selective and safer target choices. I propose a practical framework for target validation that integrates: (i) rigorous human genetic support; (ii) cell-type and site-of-action mapping; (iii) human-relevant electrophysiology and PK/PD with verified target engagement; (iv) species-appropriate models; (v) consideration of modality (small molecule, biologic, RNA, targeted protein degradation). Advancing genetically and anatomically aligned targets, tested at the right sites and exposures, offers the best path to genuinely effective, better-tolerated pain therapeutics. Full article

Background: HIMALAYA demonstrated that STRIDE (Single Tremelimumab Regular Interval Durvalumab) significantly improved overall survival (OS) compared with sorafenib in participants with unresectable hepatocellular carcinoma (HCC). This retrospective, real-world cohort study evaluated outcomes with STRIDE in veterans with HCC. Methods: Patients diagnosed with HCC between 1 January 2008 and 28 February 2024 who received ≥1 dose of STRIDE for unresectable disease were included. Data were collected from the Veteran Affairs Corporate Data Warehouse. Safety and efficacy were evaluated overall and for subgroups of patients with Child–Pugh A versus Child–Pugh B cirrhosis, viral versus non-viral HCC, and those with versus without prior non-systemic therapies. Results: Overall, 107 patients (100.0% male) were included. Median (interquartile range) age was 72.2 (68.0–76.1) years. There were 22 Grade 3–4 adverse events reported (three in patients with Child–Pugh B cirrhosis). Median OS (95% CI) was 12.4 (9.1–22.1) months and 5.2 (1.5–9.3) months in patients with Child–Pugh A (n = 81; 75.7%) and Child–Pugh B cirrhosis (n = 26; 24.3%), respectively. In patients with viral (n = 64; 59.8%) versus non-viral etiology (n = 43; 40.2%), median OS (95% CI) was 10.5 (7.0–25.6) months versus 9.0 (4.6–16.0) months, respectively. In patients without (n = 30; 28.0%) versus with prior non-systemic therapies (n = 77; 72.0%), median OS (95% CI) was 7.7 (2.8–17.3) months versus 11.1 (7.6–‍17.6) months, respectively. Conclusions: These results suggest that STRIDE is well tolerated and may offer a survival benefit to a broad range of patients with unresectable HCC, representing populations that are more reflective of real-world clinical practice. Full article

Accurate liver and tumor segmentation from abdominal computed tomography (CT) scans is essential for diagnosis and treatment planning; however, centralized deep learning approaches are often constrained by privacy regulations and inter-institution data-sharing limitations. To address these challenges, we propose a skip-free feature-forward collaborative segmentation framework called Feature-Forward Residual U-Net (FF-ResUNet), in which each institution executes the encoder locally and transmits only compact bottleneck representations to a central server. High-resolution encoder features and skip connections remain strictly within institutional boundaries, reducing privacy exposure and communication overhead. The server reconstructs segmentation masks using a multi-scale dilated residual decoder with progressive upsampling and returns lightweight updates for encoder refinement. FF-ResUNet is evaluated on the Liver Tumor Segmentation (LiTS) Challenge dataset, with cross-domain testing on 3D-IRCADb and AMOS-CT to assess robustness under distribution shifts and simulated multi-institution collaboration. On LiTS, the proposed framework achieves a liver Dice score of 0.952 ± 0.015 and a tumor Dice score of 0.737 ± 0.060, with a tumor HD95 of 10.9 ± 4.1 mm. Cross-domain experiments demonstrate stable generalization to unseen datasets, while multi-client simulations show improved performance as the number of participating institutions increases before saturation. Compared with skip-based collaborative U-Net architectures, FF-ResUNet reduces communication payload by 92–98% per training iteration while maintaining competitive segmentation accuracy. These results indicate that FF-ResUNet provides an effective balance between segmentation performance, communication efficiency, and privacy preservation evaluated under simulated multi-institution collaborative settings, supporting practical multi-center clinical deployment in bandwidth- and policy-constrained healthcare environments. Full article

Background: Accurate identification of patients at high risk of perioperative blood transfusion is essential for optimizing patient blood management (PBM) strategies in oncological surgery. However, the performance of standard PBM eligibility criteria in real-world oncological settings remains incompletely characterized. Material and Methods: We conducted a retrospective, single-center analysis of 4228 consecutive patients undergoing elective oncological surgery of any complexity or liver transplantation over a 9-month period to assess transfusion need and estimate access to preoperative patient blood management (PBM) strategies to improve anemia management. Transfusion events were assessed within 24 h after surgery (PS24) and during the perioperative period (PO; 48 h before to 72 h after surgery). Two PBM eligibility strategies were applied to the same patient cohort and compared: (A) an observational approach, based on predefined PBM indicators (transfusion rate and transfusion index by surgical complexity), and (B) a multivariable modeling approach based on pre- and intraoperative anesthesiology assessment to estimate individual transfusion risk. Predictive performance of both strategies was evaluated using accuracy, Cramér’s V, area under the receiver-operating characteristic curve (AUC-ROC), and Brier score. Results: Overall, 7.7% of patients received transfusion within PS24 and 9.2% during PO. According to the observational approach, 23.8% of patients were classified as PBM-eligible, accounting for 89.2% of PS24 transfusions and 87.1% of PO transfusions. In the multivariable modeling approach, independent predictors of transfusion included surgical type (e.g., sarcoma surgery: OR 22.8 for PS24; OR 6.3 for PO; vs. senology surgery OR 1 for PS24; OR 1 for PO, respectively), anemia severity (moderate anemia: OR 64.3 and OR 107.9, respectively and mild anemia OR 3.38 and OR 3.65, respectively), high surgical complexity, operative time >3 h (>3 h: OR 8.83 and OR 8.65, respectively vs. <3 h OR 1 and OR 1, respectively), and ICU admission risk. The observational approach demonstrated stronger alignment with actual transfusion events (Cramér’s V = 0.44–0.47) and higher overall accuracy (90.8–92.3%); in contrast, a multivariable modeling approach showed superior discrimination (AUC = 0.94–0.95) and lower Brier scores, indicating better individual risk prediction. Conclusions: In a large real-world cohort of oncological surgical patients, standard PBM eligibility criteria effectively identified the majority of patients requiring perioperative transfusion. While multivariable modeling provided greater predictive precision, the observational PBM approach demonstrated strong clinical alignment and practical applicability. Integrating both strategies may support more effective transfusion risk stratification and PBM planning in oncological surgery. Full article

Fentanyl is a potent analgesic widely used in clinical practice. Fentanyl and its analogues are seriously abused and are emerging in the illegal drug market, leading to numerous intoxication cases. However, assessment of the potency of the pharmacological effect of these novel fentanyl analogues remains limited and inconsistent across studies. The development of novel analgesics has largely relied on the assessment of mu opioid receptor (MOR) binding affinity, with insufficient verification through the assessment of antinociceptive effects. This study evaluated the antinociceptive effects of 25 fentanyl analogues to investigate the relationship between chemical structure and antinociceptive effect. In this study, hot plate tests were conducted in mice to generate time–effect and dose–effect curves for the evaluation of the antinociceptive effect of fentanyl and its analogues. The results demonstrated that the antinociceptive effects of fentanyl analogues were dose- and time-dependent. The potency of the antinociceptive effect observed in this study generally aligned with the corresponding MOR binding affinities reported in the literature, although several analogues exhibited discrepancies. Structural modifications in different regions of the fentanyl scaffold affect the antinociceptive potency to different degrees, and the duration of action also varied across fentanyl analogues. Furthermore, opioid-induced hyperalgesia (OIH) was observed following administration of several fentanyl analogues, raising potential concerns regarding their abuse liability and development for analgesic purposes. Taken together, this study systematically evaluated and compared the antinociceptive effects of fentanyl analogues. The findings clarify the relationship between chemical structure and the antinociceptive effect, providing valuable insights for drug regulation and the development of novel analgesics. Full article

Background/Objectives: Psilocybin has re-emerged as a promising intervention for neuropsychiatric disorders including major depressive disorder, treatment-resistant depression, anxiety associated with life-threatening illness, obsessive compulsive disorder, and substance use disorders. However, conventional randomized controlled trials (RCTs)—the current gold standard in evidence-based medicine—may not adequately capture the therapeutic complexity of psilocybin, which depends not only on pharmacological action but also on contextual, psychological, and interpersonal factors. This critical narrative review aimed to evaluate the adequacy of existing clinical research frameworks for assessing psilocybin’s therapeutic potential and to explore alternative methodologies that may better reflect real-world clinical conditions. Methods: Using the Web of Science Core Collection database, we identified and analysed the ten most cited clinical studies on psilocybin published between 2015 and 2025 inclusive. Additional literature was included through reference cross-checking, systematic reviews, meta-analyses, and interdisciplinary sources covering neurobiology, history, and real-world evidence (RWE). The review synthesizes clinical outcomes, methodological constraints, and epistemic considerations relevant to psychedelic-assisted therapy. Results: Evidence from highly cited trials demonstrates rapid and sustained antidepressant and anxiolytic effects of psilocybin, with notable benefits also observed in addiction treatment. However, significant methodological limitations were identified, including selection bias, challenges in placebo design and blinding, small sample sizes, and the underrepresentation of diverse populations. Psilocybin outcomes were strongly influenced by subjective experience and contextual factors such as set and setting. Emerging RWE studies revealed heterogeneous patterns of response and provided insights unattainable through RCTs alone. Conclusions: Psilocybin shows considerable therapeutic promise, but current RCT methodologies capture only part of its clinical effects. Comprehensive evaluation will require larger and more diverse clinical trials, long-term follow-up, standardized psychotherapeutic protocols, and the integration of RWE to reflect real-world practice. Psychedelic-assisted therapy should be conceptualized as a complex intervention that combines pharmacological and psychotherapeutic components. Full article

Background: The introduction of targeted therapy in oncology has led to several challenges. These medicines are relatively new in clinical practice and are not well known to specialists with regard to adverse drug reactions (ADRs) and potential drug–drug interactions (pDDIs). In addition, cancer affects multiple body systems, including weight loss, anemia, liver and kidney function, depression, and pain. Patients frequently have comorbidities, leading to polypharmacy and the use of special foods, nutritional supplements, and herbal products for self-medication. Identification of pDDIs is essential, as concomitant use of multiple medicinal products increases the risk of ADRs and may compromise treatment. Objective: This study aims to retrospectively review and analyze data on ADRs and pDDIs in the treatment of non-small cell lung cancer (NSCLC) with epidermal growth factor receptor (EGFR) inhibitors and to evaluate the relationship between them. Method: EudraVigilance and UpToDate^® Lexidrug™ application were used to screen suspected ADRs and pDDIs, respectively. Descriptive statistical analysis was performed. Results: After reviewing Line Listing Reports (LLRs) from 2021 to 2023 in EudraVigilance, the number of suspected adverse drug reactions (ADRs) reported was higher when drug interactions classified as risk categories D and X were identified, compared with cases involving EGFR inhibitor monotherapy or other drug combinations. Of the 144 cases involving category D and/or X interactions, 63 demonstrated a possible association with the reported ADRs of EGFR inhibitors. The most common pDDIs detected were erlotinib–ranitidine (14 cases, category D) and osimertinib–amiodarone (13 cases, category D). Conclusions: Although EGFR inhibitors improve overall and progression-free survival in NSCLC, screening for pDDIs before treatment is essential to improve safety and quality of life. Full article

Background/Objectives: Group A Streptococcus (GAS) pharyngitis is a frequent cause of morbidity in pediatric populations, which requires timely identification to prevent complications such as acute rheumatic fever. Rapid antigen detection tests (RADTs) are practical alternatives to throat culture. This study evaluates the diagnostic performance of the RapidFor™ Strep A test. Methods: This prospective clinical study enrolled 389 pediatric patients aged < 18 years with symptoms suggestive of streptococcal pharyngitis. Two throat swabs were collected from each patient: one for rapid antigen testing with RapidFor™ Strep A and one for culture. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Results: Throat culture was positive in 95 of 389 patients (24.4%). The RapidFor™ Strep A test demonstrated a sensitivity of 98.95% (95% confidence interval [CI]: 94.28–99.81%) and a specificity of 96.26% (95% CI: 93.43–97.90%). The PPV was 89.52%, and the NPV was 99.65%. Agreement with culture was excellent (κ = 0.919); in particular, false-positive results accounted for 2.8% and false-negative results accounted for 1.05%. Fever was the strongest clinical indicator associated with positive results. Conclusions: The RapidFor™ Strep A test showed very high diagnostic accuracy compared with throat culture, including an excellent NPV (99.6%), which supports its reliability for ruling out GAS pharyngitis in pediatric settings. The test is an effective screening tool that facilitates timely antibiotic therapy. Full article

Background: Artificial intelligence (AI) is poised to fundamentally reshape healthcare delivery, offering unprecedented advancements in diagnostics, treatment personalization, and operational efficiency. However, a growing body of international research reveals a critical “optimism–knowledge gap”: healthcare professionals are enthusiastic about AI’s potential but possess limited technical knowledge and practical experience. This gap compromises the safe and effective implementation of AI tools. The Italian healthcare context presents a unique and amplifying challenge, as it is defined by the stringent “human-in-the-loop” oversight mandated by the Garante per la protezione dei dati personali (Italy’s Data Protection Authority). This legal framework makes clinician competence not just a goal, but a prerequisite for regulatory compliance. Objective: This study aimed to provide an exploratory quantitative assessment of AI awareness, practical application, and understanding of its limitations among a sample of clinicians in Italy. It specifically sought to compare the preparedness of hospital-based clinicians and general practitioners (GPs) and to identify the workforce’s perceived educational needs within this unique legal environment. Methods: A descriptive, cross-sectional survey was conducted from February to August 2025. Using a non-probability convenience sampling method via professional networks, the survey yielded 362 total responses. Data were analyzed descriptively and inferentially using Chi-square (${\chi }^2$) tests to compare cohort responses on familiarity, practical exposure, knowledge of limitations, and interest in further training. Results: A universal and high demand for education was found, with 89.9% of all respondents being “Moderately” or “Very” interested in learning more about AI. This optimism coexists with dangerously low practical exposure. The gap was most profound among GPs, 44.1% of whom have “Never” used an AI tool—a rate significantly higher than hospital clinicians (34.9%; ${\chi }^2=3.14$, p = 0.045). Furthermore, 32.6% of GPs admitted that they “understand some benefits but not the limitations.” Conclusions: Italian clinicians mirror the global optimism–knowledge gap. These findings underscore the urgent need for structured, continuous education in AI literacy to address ethical and regulatory imperatives within the Italian healthcare system. Full article

Background: Endoscopic assessment is central to the management of inflammatory bowel disease (IBD), particularly within treat-to-target strategies. However, conventional high-definition white-light endoscopy (HD-WLE) is limited by interobserver variability and its inability to reliably reflect microscopic inflammation or predict long-term outcomes. Over the last decade, multiple technological innovations have reshaped the role of endoscopy in both disease activity monitoring and dysplasia surveillance. Methods: This narrative review provides a comprehensive and clinically oriented overview of emerging endoscopic technologies in IBD, including image-enhanced endoscopy, ultra-high-magnification techniques, artificial intelligence (AI), and molecular imaging. We discuss their diagnostic performance, prognostic implications, and potential integration into clinical practice. Results: Image-enhanced endoscopy improves visualization of subtle mucosal and vascular alterations and demonstrates stronger correlation with histological activity compared with HD-WLE alone. Confocal laser endomicroscopy and endocytoscopy enable in vivo microscopic assessment of epithelial architecture and barrier integrity, redefining remission beyond macroscopic healing. AI systems have shown expert-level performance in grading inflammatory severity in ulcerative colitis and high sensitivity in capsule endoscopy for Crohn’s disease, supporting objective and reproducible assessment. In surveillance, targeted high-definition inspection has replaced random biopsies, while adjunctive optical and AI-based tools enhance lesion detection and characterization. Molecular imaging introduces a predictive dimension by enabling visualization of drug–target engagement and dysplasia-specific pathways. Conclusions: Endoscopy in IBD is evolving from a descriptive modality toward a multimodal precision tool integrating enhanced imaging, AI-driven standardization, and molecular profiling. Although further validation and cost-effectiveness studies are required, these innovations have the potential to improve therapeutic stratification, surveillance strategies, and long-term patient outcomes. Full article

Background/Objectives: With growing waves of migration, children speaking a home language different from the language of school literacy have become increasingly common in Western education systems. In this context, understanding and monitoring bilinguals’ reading development is crucial to inform both educational and clinical practices and ensure equitable services. The present study contributes to the literature by investigating learning patterns in single-word reading across primary school grades. Monolingual and bilingual children learning to read in an alphabetic orthography were examined. Methods: The sample consisted of 565 typically developing monolingual and bilingual primary school children from grades 1–5 (bilinguals = 162). Participants completed a computerised Lexical Decision task (LDT) recording accuracy and response times, and standardised tests of reading and cognition. A parental questionnaire was used to gather socio-demographic and linguistic information. Results: Response bias-corrected accuracy rates in the LDT revealed an increase in sensitivity across school years after correcting for potential confounds (SES, vocabulary, nonverbal intelligence). No significant effect of bilingualism was observed. Response times for correct responses also decreased consistently across grades after controlling for the same confounds. Although no significant main effect of bilingualism emerged, an interaction with grade revealed a greater decrease in response times for second-grade bilinguals compared to monolingual peers. Conclusions: Monolingual and bilingual children showed comparable sensitivity rates and reading times, suggesting similar decoding skill acquisition. However, an earlier decrease in response times for bilinguals points to a facilitatory effect in the early stages of reading development, consistent with a bilingual advantage during skill learning. Full article

Self-curing poly(methyl methacrylate) (PMMA) remains widely used for provisional restorations and denture bases; however, its limited mechanical strength and susceptibility to water-related degradation restrict long-term performance. This study investigated the concentration-dependent reinforcement of self-curing PMMA with polyetheretherketone (PEEK) particles and evaluated mechanical properties and physicochemical stability. PMMA specimens containing different PEEK concentrations were fabricated and tested for flexural strength, compressive strength, surface hardness, water sorption, and water solubility according to standardized protocols. Mechanical performance demonstrated a concentration-dependent enhancement, with moderate PEEK incorporation significantly improving strength parameters compared to the control group. Excessive filler loading, however, did not yield proportional improvements. Water sorption and solubility values remained within clinically acceptable and ISO-recommended limits. These findings suggest that controlled PEEK reinforcement provides a feasible approach to enhancing the mechanical durability of self-curing PMMA without compromising physicochemical stability. The study offers a practical material modification strategy for improving interim prosthetic materials in clinical dentistry. Full article

Objective: Nutrition is a key determinant of women’s health across all life stages. Clinical practice remains heterogeneous because of lack of evidence and non-homogeneous guidelines. Despite growing research on micronutrient supplementation, skeptical opinions persist around universal versus individualized approaches, optimal dosages, and life-stage-specific recommendations. Material and methods: This is a modified Delphi process conducted under the supervision of the Italian Association of University Gynecologists and Obstetricians (AGUI). Thirteen Italian experts in gynecology and obstetrics completed two rounds of anonymous online surveys (September–November 2025). The questionnaire, developed through a scoping review, covered six domains: pre-/periconception, pregnancy, postpartum, routine supplementation in non-pregnant women, nutrition in gynecological conditions, and menopause. Consensus was defined as ≥75% agreement on a 10-point Likert scale. Quantitative data were summarized descriptively, and qualitative comments contextualized findings. Results: Experts strongly supported personalized nutritional strategies across all life stages. Consensus was reached on individualized micronutrient supplementation in the preconception period and on the prescription of active folates for women undergoing assisted reproduction. In pregnancy, agreement emerged for universal DHA supplementation (200–300 mg/day); however, universal vitamin D supplementation lacked consensus except in gestational diabetes. In the postpartum period, iron supplementation for non-breastfeeding women reached consensus, while micronutrient recommendations for breastfeeding women remained uncertain. Strong agreement supported personalized dietary approaches for PCOS, endometriosis, and gestational diabetes, including inositol use, while evidence for interventions in severe premenstrual syndrome remained insufficiently supported. In menopause, consensus was reached for macronutrient adjustments and universal calcium and vitamin D supplementation. Conclusions: This Delphi consensus highlights shared expert perspectives on nutritional care in women and identifies key evidence gaps, particularly regarding vitamin D in physiological pregnancy, postpartum micronutrient needs during breastfeeding, and nutritional strategies for premenstrual disorders. Unified life-course guidelines and future research on standardized nutritional assessments are necessary for nutritional approach management. Full article

Background and Aims: Egg-derived proteins and peptides have been investigated for various health outcomes, yet no comprehensive meta-analysis has synthesized this evidence to guide clinical practice. This study aimed to evaluate the efficacy of oral egg-derived protein and peptide supplementation on health outcomes, including serum albumin and phosphorus in dialysis patients, and visceral fat area, blood pressure, muscle protein synthesis, and cognitive function in adults. Methods: PubMed, Embase, Cochrane Library, and Web of Science were searched through January 2026 for RCTs. Random-effect meta-analyses, sensitivity analyses, and publication bias assessments were performed. Risk of bias was evaluated using the RoB 2 tool. Evidence certainty was evaluated using GRADE. Results: Thirty RCTs (n = 1938) were included. In dialysis patients, egg white supplementation significantly increased serum albumin (MD: +0.42 g/dL [95% CI: 0.12–0.72]; I² = 82.4%; four RCTs; GRADE: very low) and decreased serum phosphorus (MD: −2.04 mg/dL [−2.50, −1.58]; I² = 22%; two RCTs; GRADE: low). Leave-one-out sensitivity analysis showed consistency. Lactic-fermented egg white peptide reduced the visceral fat area (MD: −11.6 cm² [−18.5, −4.8]; two RCTs; GRADE: very low). NWT-03 egg protein hydrolysate showed no significant effect on blood pressure (MD: +0.5 mmHg [−1.8, +2.7]; two RCTs). Publication bias was not detected. Conclusions: Egg-derived protein supplementation provides clinical benefits in dialysis patients with hypoalbuminemia, but evidence is lacking supporting its routine use in healthy adults or other clinical populations. Full article