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PubMed2026

Aneurysmal subarachnoid hemorrhage care in a middle-income public healthcare system: A real-world neurocritical care cohort.

BACKGROUND AND PURPOSE: Although aneurysm treatment capacity has expanded worldwide, outcomes after aneurysmal subarachnoid hemorrhage (aSAH) remain strongly influenced by neurocritical care (NCC) delivery, referral pathways, and access to specialized treatment. Contemporary data describing real-world aSAH care in resource-limited healthcare systems remain scarce. We aimed to characterize treatment patterns, NCC delivery, complications, and outcomes in a large Brazilian public referral center. METHODS: This retrospective cohort study included consecutive adults with confirmed aSAH admitted between June 2018 and March 2022 to a high-volume Brazilian tertiary referral center. Only patients admitted within five days of symptom onset were included. Demographic, clinical, radiological, treatment, complication, and outcome data were extracted from institutional records. Primary outcomes were in-hospital mortality and 3-month functional outcome assessed by the modified Rankin Scale (mRS). RESULTS: Seventy-four patients were included. Disease severity was high, with 45% presenting WFNS grades 4-5, 73% modified Fisher grade 4 hemorrhage, and 64% hydrocephalus. Endovascular treatment was performed in 73% of cases, and median time from admission to aneurysm treatment was 1 day. Despite early treatment capability, only 28% of patients were admitted to an ICU within 48 h, while 38% never received ICU care. Delayed cerebral ischemia occurred in 43%, radiologic vasospasm in 58%, ventriculitis in 22%, and infectious complications in 57%. External ventricular drainage was required in 42%, and vasoactive drugs were used in 85%. In-hospital mortality was 42%, and 66% had unfavorable 3-month outcomes (mRS 4-6). CONCLUSIONS: This real-world cohort highlights the substantial neurocritical care burden of aSAH in a middle-income public healthcare system. Despite timely access to definitive aneurysm treatment, patients experienced frequent neurological and systemic complications, emphasizing that contemporary aSAH care extends well beyond aneurysm occlusion.

Humans↗

PubMed2026

The Impact of Baseline Negative Emotions on Postoperative Quality of Life in Adolescent Idiopathic Scoliosis Patients: A 2-Year Follow-Up Study.

OBJECTIVE: Adolescent idiopathic scoliosis (AIS) is a three-dimensional spinal deformity that develops during puberty without a clear etiology. Beyond physical manifestations, AIS severely impacts adolescents' psychological and social well-being, leading to anxiety, depression, and low self-esteem. While advancements in surgical techniques have enhanced objective outcomes, existing studies on AIS have primarily focused on objective indices, with limited attention to the long-term impact of preoperative negative emotions on patient-reported subjective quality of life. METHODS: This was a retrospective cohort study. A total of 112 eligible AIS patients who underwent posterior spinal correction surgery between April and August 2023 were enrolled. Inclusion criteria included confirmed AIS, completion of 2-year follow-up, and informed consent; exclusion criteria included missing imaging/questionnaire data, comorbid psychiatric/neurological diseases, or prior spinal surgery. Patients were grouped using the Hospital Anxiety and Depression Scale (HADS) administered on admission. Quality of life was assessed preoperatively and 2 years postoperatively using the Scoliosis Research Society-22 (SRS-22, evaluating self-image, mental health, pain, function, treatment satisfaction) and Short Form 36 Health Survey (SF-36, assessing 8 physical and mental health dimensions). Statistical analysis was performed via SPSS, using independent t-tests, paired t-tests, Mann-Whitney U test, and chi-square test. p < 0.05 was considered significant. RESULTS: There were no significant differences in baseline characteristics (age, gender, BMI, surgical parameters, scoliosis type, preoperative/postoperative Cobb angles) between the two groups (all p > 0.05). Preoperatively, SRS-22 and SF-36 scores showed no inter-group differences (all p > 0.05). Postoperatively, the Negative Emotion Group had significantly lower scores in SRS-22 mental health (3.9 ± 0.3 vs. 4.5 ± 0.2) and treatment satisfaction (4.0 ± 0.3 vs. 4.6 ± 0.7), as well as SF-36 general health (68.6 ± 6.4 vs. 79.7 ± 13.3), role-emotional (61.3 ± 9.3 vs. 70.8 ± 9.7), and mental health (61.8 ± 14.3 vs. 68.9 ± 10.7) (all p < 0.05); no inter-group differences were observed in physical function-related dimensions. Both groups showed significant improvements in physical function-related dimensions postoperatively. The Non-Negative Emotion Group also exhibited significant improvements in SRS-22 self-image/pain and SF-36 bodily pain (all p < 0.05), while the Negative Emotion Group showed no significant improvements in these dimensions. CONCLUSIONS: Preoperative anxiety and depression do not affect the recovery of physical function in AIS patients after spinal correction surgery but significantly impede improvements in subjective quality of life dimensions, including mental health and treatment satisfaction. These findings highlight the need to integrate psychological assessment and targeted interventions into the perioperative management of AIS. Such a patient-centered approach will help optimize both physical and psychological outcomes, ultimately achieving comprehensive rehabilitation for AIS adolescents.

Humans↗

PubMed2026

Sexual selection purges mutation load, but not overall genetic diversity, decreasing vulnerability to extinction.

Theory suggests sexual selection will enhance population viability by purging deleterious alleles. However, direct genomic evidence for this fundamental idea is scarce and contradictory. We combined long-term experimental evolution with whole-genome resequencing to directly test how sexual selection affects mutation load, genomic divergence, and extinction risk in small populations (maximum Ne = 40) of Tribolium castaneum. After 156 generations, populations evolving under strong sexual selection carried substantially fewer deleterious alleles than populations under weak sexual selection, based on both individual-level estimates of missense and nonsense variants and population-level Rxy analyses, indicating more efficient purging of deleterious alleles. In contrast, nucleotide diversity and runs of homozygosity were similar across treatments, indicating that purging acted most strongly on deleterious variation, and that reduced mutation load in these small populations under strong sexual selection was not explained by demographic effects. Importantly, population-level mutation load estimates best explained extinction risk under inbreeding, directly linking sexual selection to purging and population viability. Genome scans of high and low sexual selection populations revealed peaks of divergence, which included genes involved in courtship, sex discrimination, and seminal fluid proteins. Our results provide direct genomic evidence that sexual selection can reduce mutation load without eroding standing genetic diversity and thus adaptive potential, while driving adaptive divergence in reproductive traits. This beneficial purging may help explain the widespread prevalence of sexual reproduction in nature despite inherent costs and have important ramifications as to how we manage populations of conservation concern.

Animals↗

PubMed2026

Evaluating the Effectiveness of an Intimate Partner Violence Training Intervention on Healthcare Providers' Preparedness, Knowledge, and Experiences: A Mixed-Methods Study From Nepal.

Intimate partner violence (IPV) places a considerable burden on health systems globally due to its profound effects on women's health, and women who experience violence often seek care from healthcare providers (HCPs). However, HCPs often lack the preparedness and confidence to respond effectively, resulting in missed opportunities for support and care. This study, conducted in Nepal, evaluated the impact of structured training intervention on HCPs' perceived preparedness, knowledge, and attitudes toward managing IPV and its mental health consequences, including self-harm and suicidal tendencies. The study was nested within a larger cluster randomized trial. A convergent mixed-methods design with a comparison group was conducted among 46 female HCPs in all public hospitals (except one) and 17 primary healthcare centers in Madhesh Province, Nepal. The intervention group (n = 24) received a 10-day intensive IPV and mental health training, while the control group (n = 22) completed 3-day training. Quantitative data were collected using a validated self-administered Physician's Readiness to Manage IPV questionnaire and IPV consequences scale. Paired and independent t-tests were applied to assess changes. Insights from key informant interviews were thematically analyzed to explore participant experiences and perceived impacts. At baseline, over 80% of participants had not received IPV management training. Post-intervention, significant improvements were observed in HCPs perceived preparedness (median change 2.1; 95% confidence interval (CI): 1.1- 2.9), knowledge (median change 2.7; 95% CI: 2.0-3.1), and awareness of IPV consequences (mean difference 1.2; 95% CI: 0.5-2.0), with greater gains in the intervention group. Qualitative findings revealed enhanced confidence in identifying IPV, addressing psychological impacts, and supporting survivors through safety planning and referral. The training significantly improved HCPs' knowledge, preparedness, and confidence to manage IPV and related mental health issues, underscoring the need to scale similar programs to frontline providers, particularly in rural and underserved settings, to strengthen health system's response to IPV.

Humans↗

PubMed2026

First insights into the role of evolutionary history in shaping venom composition of Vipera ammodytes.

Understanding intraspecific venom variation requires distinguishing the contributions of neutral population history from natural selection. This study aims to determine whether venom variation in Vipera ammodytes species complex is structured across eight phylogenetic groups. Despite a complex evolutionary history, venom composition did not differ among phylogenetic groups within the analytical framework used, suggesting that shared ancestry alone does not explain venom variation. Whether local adaptation to environmental conditions explains the observed variation remains an open question for future studies.

Animals↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

PubMed2026

Assessing the public health impact of routinely collected electronic healthcare record data in NICE guidelines: A systematic review of CPRD research.

OBJECTIVES: Evidence used in NICE guidance has traditionally prioritised randomised controlled trials, but increasing availability of electronic health record (EHR) data has expanded opportunities for real-world evidence. The Clinical Practice Research Datalink (CPRD) is a commonly used UK primary care EHR resource, yet the extent to which CPRD studies have informed NICE guidelines in the past decade is unclear. STUDY DESIGN: The systematic review was conducted in accordance with PRISMA guidelines. METHODS: We conducted a systematic review of CPRD studies in PubMed, MEDLINE, and Embase published between 04/16-09/25. For each eligible CPRD study, targeted searches of NICE guidelines were performed to identify explicit citations in NICE guidelines. Two reviewers screened and extracted data independently, resolving disagreements by consensus or third reviewer. Guideline information, number of guidelines over time, type of guidelines, and disease area guidelines (using British National Formulary (BNF) chapters) were described. RESULTS: 7181 records were identified. After de-duplication, 2704 unique CPRD studies were screened against NICE guidelines. Of these, 92 CPRD-based studies met inclusion criteria and were cited across 67 NICE documents. The annual number of NICE guidelines citing CPRD studies increased between 2016 and 2025; 1.5% of identified guidelines published in 2016 and 27.7% in 2025. The guideline citing the most CPRD studies was cancer related. The most common types of guidelines included clinical guidelines (49.3%) and technology appraisals (32.8%). Guidelines made up 12 different BNF categories, most frequently central nervous system related (23.9%; n = 16). CONCLUSION: Observational CPRD studies are increasingly referenced in NICE guidelines across multiple disease areas, supporting the growing role of EHR data in national guideline development.

Clinical studies↗

PubMed2026

Phase 1 Study Evaluating Gefurulimab Pharmacokinetics and Safety Following Delivery Via Autoinjector or Prefilled Syringe With Needle Safety Device in Healthy Adults.

PURPOSE: Gefurulimab, a novel dual-binding nanobody targeting complement component 5 (C5), is in clinical development for anti-acetylcholine receptor antibody-positive generalized myasthenia gravis. Gefurulimab has a low molecular weight, enabling subcutaneous (SC) self-administration by autoinjector (AI) or prefilled syringe with needle safety device (PFS-SD). We compared gefurulimab pharmacokinetic (PK) exposure and safety in healthy adults following a single SC dose administered by AI versus PFS-SD. METHODS: In this phase 1, open-label, randomized, parallel-group study (NCT06208488), healthy participants aged 18 to 65 years were stratified by weight and randomized equally to 1 of 6 combination groups of device and injection site (abdomen/thigh/upper arm). Participants received a single SC dose of gefurulimab on day 1 and were assessed throughout the 92-day evaluation period. Primary endpoints were PK parameters for each device: maximum observed concentration (Cmax) and area under the serum concentration-time curve (AUCinf, AUClast). PK across injection sites, pharmacodynamics, safety, immunogenicity, and device performance were also assessed. FINDINGS: Overall, 175 participants were randomized: AI (n = 87), PFS-SD (n = 88). Geometric least squares mean ratios (90% CI) comparing AI/PFS-SD for Cmax, AUCinf, and AUClast were 97.6% (94.5-100.8), 99.6% (96.1-103.3), and 98.8% (95.2‒102.6), respectively. Secondary analyses found no meaningful differences in PK parameters across injection sites. Serum-free C5 concentrations over time, treatment-emergent adverse event (TEAE) profiles, and antidrug antibody responses were similar between cohorts. Most TEAEs were mild; none led to study discontinuation. IMPLICATIONS: SC administration of gefurulimab by AI and PFS-SD was well tolerated with comparable exposure, meeting bioequivalence criteria.

Humans↗

PubMed2026

Pharmacogenomic and drug interactions risk in cardio-oncology: A precision medicine perspective for India.

Cardio-oncology patients may face complex treatment regimens due to the concurrent existence of cancer and cardiovascular disease, leading to a considerable polypharmacy burden. This significantly increases the prospect of drug-drug interactions (DDIs) and gene-drug interactions. The majority of these interactions arise from comparable pharmacokinetic and pharmacological pathways associated with drug transporters and cytochrome P450 enzymes. The significance of pharmacogenomics in tailored treatment strategies are emphasised by the fact that genetic variability enhances individual differences in drug response, safety, and efficacy. This narrative review focus on the effects of key genetic polymorphisms (e.g., DPYD, CYP2C19, and CYP2C9) on the metabolism and efficacy of commonly prescribed anticancer and cardiovascular medications such as fluoropyrimidines, clopidogrel, and warfarin. In addition it explore the role of pharmacogenomic variants on drug-drug interactions within the field of cardio-oncology. The study ultimately emphasizes the necessity of precision medicine in India to address the genetic diversity and underrepresentation in global genomic databases. The absence of pharmacogenomic testing, infrastructural deficiencies, financial constraints, and insufficient clinical integration hinder the widespread use of this technology in India. The Genome India Project and other national initiatives establish the foundation for pharmacogenomic-guided therapy. Utilizing genetic data, together with artificial intelligence-based predictive tools, for clinical decision-making may enhance medication safety and yield optimal outcomes in Indian cardio-oncology patients.

Humans↗

PubMed2026

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans↗

PubMed2026

Diagnostic communication in functional neurological disorder: A systematic review and meta-analysis of patient acceptance and clinical outcomes.

OBJECTIVES: Diagnostic disclosure is a key therapeutic moment in Functional Neurological Disorder (FND). This systematic review aimed to evaluate quantitative evidence on diagnostic acceptance, understanding, satisfaction, symptom outcomes, and healthcare utilisation following diagnostic disclosure in FND, and to conduct a meta-analysis of diagnostic acceptance. METHODS: Systematic searches of PubMed, Scopus, PsycINFO, and Web of Science identified quantitative studies in adults with FND. Screening followed predefined inclusion criteria. Data were extracted using a structured template and risk of bias was assessed using the Newcastle-Ottawa Scale. A random-effects meta-analysis of proportions was conducted using the Freeman-Tukey transformation. RESULTS: Fifteen studies were included, four of which contributed to the meta-analysis (n = 481). Reported diagnostic acceptance rates ranged from 38.7% to 90%, although the timing and method of assessment varied across studies. Pooled acceptance was 0.68 (95% CI 0.44-0.88), with substantial heterogeneity. Structured or reinforced communication was frequently associated with improved understanding and satisfaction, although its superiority for diagnostic acceptance was not established. In some studies, diagnostic acceptance was associated with more favourable clinical outcomes, although findings were inconsistent. Some studies reported reductions in healthcare utilisation or costs following satisfactory diagnostic explanation, whereas others found no sustained overall reduction. CONCLUSIONS: Diagnostic communication in FND is associated with differences in acceptance, understanding, and downstream clinical and healthcare outcomes. Approximately two-thirds of patients were reported as accepting the diagnosis following disclosure, although the timing and method of assessment varied substantially across studies. Empathic and evidence-informed communication may enhance understanding and engagement, although its effects on healthcare use and recovery remain uncertain. PRACTICE IMPLICATIONS: Diagnostic disclosure should be delivered clearly, empathically, and with reinforcement over time. Written information, reputable educational resources, and opportunities for follow-up clarification may support patient understanding and engagement, although stronger comparative evidence is needed.

Humans↗

PubMed2026

Insights into the fate and dynamics of antibiotic resistance in multidrug-resistant Bacillus cereus during in vitro simulated gastrointestinal digestion.

Bacillus cereus, an important pathogen responsible for causing foodborne diseases worldwide, releases pore-forming enterotoxins, which target host epithelial cells, leading to osmotic lysis and ultimately manifesting as diarrheal syndrome. Moreover, some B. cereus strains carry antimicrobial resistance genes that confer multidrug resistance against a spectrum of antibiotics. Characterizing the survival traits of multidrug-resistant (MDR) B. cereus strains in the intestinal microenvironment is essential for developing targeted strategies to effectively manage diarrheal foodborne diseases caused by this pathogen. This study used whole-genome sequencing (WGS) to evaluate the pre- and post-digestion toxigenic potential, antimicrobial resistance profiles, and genetic diversity of MDR B. cereus strains isolated from food samples in Guangdong Province, China. The four B. cereus isolates investigated in this study exhibited a genetic diversity, as determined by multilocus sequence typing analysis of WGS data. All four isolates produced the diarrheal toxins Hbl, Nhe, and CytK to varying levels, indicative of their potential to cause outbreaks of foodborne diseases. Each of the four isolates exhibited resistance to more than three classes of antibiotics, fulfilling the criterion for multidrug resistance. At an initial concentration of 9 log colony-forming units (CFU)/mL, the intestinal concentration of these four isolates crossed the threshold required to induce widespread diarrhea in the general population. Under rice slurry protection, all tested isolates maintained intestinal concentration beyond the threshold when the initial concentration was increased to ≥8 log CFU/mL. Moreover, the upregulations of genes associated with acid tolerance, bile tolerance and stress response were observed in the surviving MDR B. cereus isolates. Digestion markedly altered the antibiotic resistance profiles of the MDR B. cereus isolates. In the absence of a food matrix, the MDR isolates lost their resistance to imipenem, meropenem, amoxicillin-clavulanic acid, and trimethoprim-sulfamethoxazole post-digestion and was influenced by the initial concentration of the strains. In the presence of food matrix rice slurry, the effects of digestion on the antibiotic resistance of MDR B. cereus isolates can be mitigated, enabling them to maintain their antibiotic resistance to the greatest extent. Most remarkably, after digestion, the isolates Bce055 and Bce166 exhibited newly emergent resistance to cefotetan and trimethoprim-sulfamethoxazole, respectively. Our findings clarify the fate of MDR B. cereus isolates in the gastrointestinal tract and inform the development of prevention and control strategies for foodborne diseases caused by this pathogen.

Drug Resistance, Multiple, Bacterial↗

PubMed2026

Care Experience Disparities in Individuals With Lower Urinary Tract Symptoms: Systematic Review and Content Analysis.

OBJECTIVES: In this study, we aimed to characterize the landscape of the literature and describe lower urinary tract symptom (LUTS) care experiences using the Agency for Healthcare Research and Quality's (AHRQ's) patient experience framework, describe the characteristics of the studies, and identify critical knowledge gaps. METHODS: We performed a systematic search of MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus of peer-reviewed publications from 1995 to 2024. The search terms were related to LUTSs, drivers of healthcare inequities, and the domains of the AHRQ. We then performed a content analysis of the included studies. RESULTS: Of the 4597 articles reviewed, we included 11 studies in the analysis. The most studied LUTS was urinary incontinence (10/11, 91%). Of the included studies, six were comparative, and most (4/6, 66.7%) found worse care experience in patients with limited English proficiency and low socioeconomic status. When examining the studies using the care experience framework of the AHRQ, the most frequently evaluated domains of care experience were communication with clinicians (8/11, 73%) and access to care (8/11, 73%). For communication with clinicians, language barriers (3/11, 27%) and symptom minimization by clinicians (3/11, 27%) were common, especially among patients with limited English proficiency and of older age, respectively. In regard to access to care, concerns about healthcare costs (5/11, 45%) and patients' fear or embarrassment about accessing LUTS care (4/11, 36%) were commonly occurring themes, especially among racially minoritized groups. CONCLUSIONS: The findings of this systematic review demonstrated that patients with limited English proficiency, older age, low socioeconomic status, and racially minoritized backgrounds have poor LUTS care experiences.

Humans↗

PubMed2026

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans↗

PubMed2026

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium↗

PubMed2026

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗

PubMed2026

The future of pediatric vesicoureteral reflux management.

BACKGROUND AND OBJECTIVE: Vesicoureteral reflux (VUR) is a common condition in pediatric urology, yet important uncertainties persist regarding risk stratification, imaging strategies, and prevention of long-term renal damage. Emerging technologies may help address these challenges. This review provides a forward-looking overview of recent advances in artificial intelligence (AI) and immunomodulation that may influence future management of pediatric VUR. METHODS: A forward-looking literature review was performed using the PubMed database (January 2000-March 2025), focusing on studies addressing AI, immunomodulation, or vaccination in the context of VUR and urinary tract infections. Criteria of inclusion were the relevance to pediatric VUR, the novelty of the proposed concept, the potential clinical implications and, for the AI literature, the existence of a clinical evaluation of the algorithm on a dataset from patients. KEY FINDINGS AND LIMITATIONS: AI-based models show promising performance in supporting clinical decision-making, including prediction of the need for voiding cystourethrography, automated grading of VUR, estimation of recurrent urinary tract infection risk and prediction of chemoprophylaxis. These tools may facilitate more individualized diagnostic and therapeutic strategies, although current evidence is largely retrospective and requires prospective validation. Immunization and immunomodulatory approaches aim to reduce infection burden and modulate inflammatory pathways associated with renal scarring. While early experimental and adult clinical data are encouraging, pediatric-specific evidence remains limited, and clinical applicability in children with VUR is not yet established. CONCLUSION: Artificial intelligence and immunologically targeted strategies represent complementary, emerging approaches that may contribute to more personalized management of pediatric VUR. At present, both should be regarded as exploratory tools whose clinical impact will depend on further validation and appropriately designed pediatric studies.

Humans↗

PubMed2026

Medication safety in older adults in India: an integrative PhD synthesis of direct evidence and contextual implementation evidence.

BACKGROUND: Unsafe medication practices among older adults are an important global health concern, particularly in low- and middle-income countries where multimorbidity, fragmented care, self-medication, and informal healthcare provision intersect. OBJECTIVE(S): To synthesize direct evidence on medication safety among older adults in India and contextual evidence on deprescribing and community-level provider interventions relevant to safer medication use. METHODS: This PhD synthesis integrates four studies: a record-based cross-sectional study on polypharmacy and cardiovascular autonomic function in Kolkata; a six-city community study of 600 Indian older adults; a systematic review and meta-analysis on deprescribing preventive medications in frail or end-of-life older adults; and a systematic review of informal healthcare provider interventions in low- and middle-income countries. Studies I-II provided direct Indian older-adult evidence, while Studies III-IV provided indirect contextual evidence for their optimization and implementation. RESULTS: Polypharmacy was associated with higher anticholinergic burden and numerically higher cardiac autonomic neuropathy although residual confounding limits causal interpretation. In the multicity study, one-third had polypharmacy, while potentially inappropriate medications, prescribing omissions, and self-medication were common. Risks were higher with multimorbidity, recent hospitalization, care transitions, or living alone. Deprescribing showed no statistically significant increase in mortality, hospitalization, or major cardiovascular events, but heterogeneity was high and certainty low to very low. Informal-provider interventions showed the potential to improve knowledge, referral, case management, and medication-related practices. CONCLUSIONS: Medication safety among older adults in India requires an integrated continuum approach, but direct evidence supports only some components and implementation strategies that need prospective evaluation.

Humans↗