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PubMed2026

Validation of a Turkish Translation of the Stress in Emergency Healthcare Professionals: The Stress Factors and Manifestations Scale.

AIM: The primary duties of emergency healthcare professionals (EHPs) are to provide emergency patient care to acutely ill and injured individuals. Due to the nature of their work, EHPs operate under constant stress, often requiring rapid decision-making, swift action, and the delivery of necessary medical care in life-or-death situations, sometimes under inadequately safe conditions. Therefore, the aim of this study is to determine the validity and reliability of the Emergency Healthcare Professional Stress Factors and Symptoms (SEHP:SFMS) Scale in Turkish for identifying stress factors and symptoms in emergency medical care professionals providing emergency patient care services. DESIGN: A methodological study design was used in this study. METHODS: The study was conducted with the participation of 211 EHPs from employees working in emergency care institutions affiliated with the Muğla Provincial Health Directorate between November 2023 and June 2024. Data were collected via a face-to-face survey. Data were analysed using Lawshe content validity ratio, Kaiser-Meyer-Olkin coefficient, Bartlett test, exploratory factor analysis, principal component analysis, Varimax factor rotation method, confirmatory factor analysis, Cronbach's α internal consistency coefficient, convergent validity, discriminant validity, test-retest, and Spearman correlation coefficient tests. RESULTS: The linguistic translation and cultural adaptation of the SEHP:SFMS showed strong performance. The scope validity index of the scale is 0.83. The item-total correlation values of the scale were found to be between 0.486 and 0.794, and the factor loadings were between 0.474 and 0.816. Confirmatory factor analysis fit indices: χ2 = 248.727; df = 101; n = 211; p = 0.000; χ2/df = 2.463; RMSEA = 0.083; CFI = 0.914, SRMR = 0.052, which was found to be compatible and acceptable with the proposed 3-factor model. The Cronbach's α reliability coefficient of the scale was 0.931, and the total variance was 61.97%. CONCLUSIONS: SEHP:SFMS is a valid and reliable tool to assess stress factors and symptoms of Turkish emergency healthcare professionals. Its use improves the quality of emergency care. PATIENT OR PUBLIC CONTRIBUTION: These study findings have been used to create a tool with Turkish validity and reliability that allows for the examination of stress factors among healthcare professionals working in emergency and critical services. Identifying and reducing stress factors among healthcare professionals is crucial for the delivery of quality healthcare services. It can also be used to develop targeted interventions and ongoing strategies to facilitate improved clinical supervision and mentoring. IMPLICATION FOR NURSING PRACTICE: Nurses in emergency departments, which are among the most stressful, dynamic, intense, life-saving, and critical environments in healthcare institutions, and where life-saving treatment is administered, are at high risk of experiencing psychological trauma. Trauma experienced in the work environment is a significant problem for nursing. The consequences of trauma negatively affect nurses and institutions. Studies show that post-traumatic stress, anxiety, depression, and burnout are commonly observed in emergency department nurses. In this sense, understanding the stress and stress factors experienced by nurses can guide future interventions. The results of this study are considered important in making visible the stress and stress factors experienced by nurses in the emergency department, and also in guiding managers and nurses working in this field in terms of preventive and protective measures.

Humans↗

PubMed2026

Evaluating a culturally adapted question prompt list to improve end-of-life communication among indonesian migrant caregivers: A randomized controlled trial with qualitative insights.

OBJECTIVE: Indonesian caregivers serve as essential providers of end-of-life (EOL) care in Taiwan. But often face communication challenges due to language, cultural, and hierarchical barriers. This study evaluated the effectiveness of a culturally adapted Question Prompt List (QPL). METHODS: This study employed a two-arm randomized controlled trial design supplemented with qualitative interviews. The study was conducted in a hospice ward and home care setting within a medical center in Taiwan. A total of sixty Indonesian caregivers were recruited and randomly assigned to either the intervention group (n = 30) or the control group (n = 30). The intervention group received routine end-of-life (EOL) education along with a culturally adapted Question Prompt List (QPL), which consisted of 37 items covering domains including the dying process, emotional support, communication, symptom management, and care decision-making. The control group received routine EOL education. Outcome measures included caregiving preparedness, communication self-efficacy, satisfaction, and question-asking behavior. In addition, semi-structured interviews were conducted with eight participants, and the data were analyzed using thematic content analysis. RESULTS: Analysis of covariance revealed no statistically significant between-group differences in caregiving preparedness (F = 1.58, p = .215 [-0.41, 0.44]) or communication selfefficacy (F = 0.83, p = .366 [-0.44, 0.79]). However, communication satisfaction was significantly higher in the intervention group (F = 4.19, p < .05 [0.04, 0.44]). The number of questions asked was also significantly higher in the intervention group (t = -4.35, p < .001 [-5.41, -1.98]). Thematic analysis of qualitative data identified 4 themes and 14 subthemes, illustrating how the QPL reduced anxiety, clarified care needs, and improved confidence. CONCLUSIONS: A culturally adapted QPL can enhance communication engagement and satisfaction among migrant caregivers. PRACTICE IMPLICATIONS: Integrating culturally tailored QPLs into caregiver education and palliative care practice may promote more inclusive and effective communication.

Humans↗

PubMed2026

Artificial intelligence in treatment prediction for skeletal Class III malocclusion: A systematic review.

In skeletal Class III patients, treatment options range from orthodontics to orthognathic surgery. Choosing the optimal approach requires a comprehensive clinical evaluation, which may be supported by AI tools. The aim of this study was to assess the performance of AI models in predicting the need for orthognathic surgery and in identifying predictors influencing treatment decisions. A PRISMA-guided electronic database search (PubMed, Web of Science; 2009-2024; English/French) was performed to identify studies using machine learning (ML) or deep learning (DL) on cephalometric and clinical data. After screening and assessment for eligibility, 15 studies were critically appraised. Model performance was summarized using accuracy, sensitivity, specificity, and the area under the curve (AUC). ML algorithms (particularly Random Forest and XGBoost) and DL models (ResNet-based convolutional neural networks (CNNs)) achieved high accuracy for predicting surgical need. Frequently selected predictors included Wits appraisal, ANB angle, the maxillomandibular ratio (Mx/Md), overjet, and the divergence of the lower gonial angle. AI methods show promise for assisting treatment decisions in Class III malocclusion, with Random Forest and XGBoost performing well on tabular cephalometric data and CNNs on imaging. Larger, multicentre datasets and external validation are needed to improve reliability, address bias, and support clinical implementation.

Humans↗

PubMed2026

Non-genetic Risk Factors for Allopurinol-Induced Severe Cutaneous Adverse Reaction (SCAR): A Systematic Review.

BACKGROUND: Allopurinol-induced severe cutaneous adverse reactions (SCARs) are rare but potentially life threatening, particularly in Asian populations. While the genetic marker HLA-B*58:01 is a well-established risk factor, non-genetic factors may also contribute. This systematic review synthesizes evidence on associations between non-genetic risk factors and allopurinol-induced SCAR. METHODS: We searched MEDLINE, Scopus, Cochrane Library and Web of Science from inception to 29 June 2026 for observational studies examining non-genetic risk factors for SCAR, defined as Stevens-Johnson Syndrome, Toxic Epidermal Necrolysis, Acute Generalised Exanthematous Pustulosis, or Hypersensitivity Syndrome/Drug Reaction with Eosinophilia and Systemic Symptoms. Adults aged ≥ 18 years were included. Pooled odds ratios (ORs) with 95% confidence intervals (CIs) were calculated using a random-effects model; heterogeneity was assessed with I2. Mean differences were calculated for continuous variables. NIH Study Quality Assessment Tool was used for quality assessment of the studies. RESULTS: Twenty-six studies were included. Female sex (20 studies; 3340 SCAR cases, 562,647 controls) was associated with an increased risk of allopurinol-induced SCAR (OR 2.06; 95% confidence interval (CI) 1.25-3.38). Chronic kidney disease (16 studies; 1625 SCAR cases, 553,804 controls) was also significantly associated with SCAR (OR 3.78; 95% CI 1.99-7.17). Five studies (177 SCAR cases, 1368 controls) reported higher allopurinol doses among SCAR cases than tolerant controls (mean difference 19.61 mg; 95% CI 2.97-36.24). No significant associations were observed for age or concomitant diuretic use in the primary meta-analyses. Substantial heterogeneity was observed across studies. Sensitivity analyses demonstrated consistent findings for most factors, although concomitant diuretic use became significantly associated with SCAR after exclusion of non-Asian and zero-event studies. CONCLUSION: CKD, female sex, and higher allopurinol dose were identified as significant non-genetic risk factors for allopurinol-induced SCAR. These findings support consideration of non-genetic factors alongside pharmacogenomic screening in future risk-stratification strategies. However, substantial heterogeneity and potential publication bias limit the certainty of the available evidence. Well-designed studies evaluating non-genetic predictors as primary outcomes are needed to develop robust integrated risk prediction models for clinical decision making.

Journal Article↗

PubMed2026

Preoperative intramuscular testosterone and urethrocutaneous fistula formation after primary hypospadias repair.

INTRODUCTION: Preoperative androgen stimulation is widely used before hypospadias repair to increase penile dimensions and optimise surgical conditions. However, its impact on postoperative complications, particularly urethrocutaneous fistula formation, remains controversial. OBJECTIVE: To evaluate the association between preoperative intramuscular testosterone therapy and urethrocutaneous fistula formation in children undergoing primary hypospadias repair. STUDY DESIGN: This was a retrospective comparative analysis of prospectively collected clinical data from 111 boys undergoing primary hypospadias repair at a single tertiary pediatric urology center. Patients were divided into two groups: those who did not receive hormonal therapy (Group 1, n = 55) and those who received intramuscular testosterone enanthate (2 mg/kg administered 5 and 2 weeks before surgery; Group 2, n = 56). Preoperative penile measurements, operative characteristics, and postoperative complications were compared. The primary outcome was urethrocutaneous fistula formation. The mean follow-up duration was 11.9 months (median 7 months). RESULTS: Preoperative testosterone therapy was associated with significant increases in glans diameter and stretched penile length at the time of surgery. The hormone-treated group had a significantly higher proportion of proximal hypospadias (p = 0.001), underwent more complex urethroplasty procedures, and had longer operative times (p = 0.007). Postoperative edema and local inflammatory changes were more frequently observed in the hormone-treated group. Despite these differences, urethrocutaneous fistula occurred in four patients in each group (7.3% vs 7.1%, p = 0.357), with no statistically significant difference between groups. DISCUSSION: Despite greater baseline anatomical severity and operative complexity in the hormone-treated group, preoperative testosterone administration was not associated with an increased risk of urethrocutaneous fistula. These findings suggest that improved tissue bulk and vascularity may offset the potential adverse effects of transient inflammatory changes. CONCLUSION: Selective preoperative intramuscular testosterone therapy was not associated with increased urethrocutaneous fistula risk and may be considered a reasonable adjunct in appropriately selected patients undergoing primary hypospadias repair. CLINICAL/TRANSLATIONAL APPLICABILITY: These findings provide clinical reassurance that preoperative testosterone can be used selectively in patients with smaller penile dimensions or anticipated technical difficulty without increasing fistula risk, thereby supporting shared decision-making in clinical practice.

Humans↗

PubMed2026

Cost-Effectiveness and the Economics of Genomic Testing and Molecularly Matched Therapies.

Cost-effectiveness analysis of precision oncology can help guide value-driven care. Next-generation sequencing is increasingly cost-efficient over single gene testing because diagnostic algorithms require multiple individual gene tests to determine biomarker status. Matched targeted therapy is often not cost-effective due to the high cost associated with drug treatment. However, genomic profiling can promote cost-effective care by identifying patients who are unlikely to benefit from therapy. Additional applications of genomic profiling such as universal testing for hereditary cancer syndromes and germline testing in patients with cancer may represent cost-effective approaches compared with traditional history-based diagnostic methods.

Humans↗

PubMed2026

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

PubMed2025

Application of causal discovery of factors driving dissolved oxygen in estuarine environments.

Dissolved oxygen (DO) concentrations in estuarine bottom waters are a manifestation of multiple, interacting physical and biogeochemical processes, yet identifying their independent contributions remains challenging. Here, we analyze monthly water quality monitoring data from eight stations across Long Island Sound from 1994 to 2022 using a causal discovery framework (PCMCI+) and transformation of forcing variables. Our goal is to identify and isolate variables that causally influence bottom DO and improve predictive models by minimizing overfitting and multicollinearity. PCMCI+ reveals surface-layer temperature as the most important and consistent negative driver of bottom DO, followed by stratification. Wind events exhibit only brief relief by advection and mixing, while river discharge shows no direct causal link to DO, making it less influential than previously thought. Biogeochemical variables, including chlorophyll-a (Chl-a), nitrate and nitrite, and particulate carbon, influence DO through both contemporaneous and time-lagged pathways, often with signs that shift depending on the process. The derived models were evaluated by comparing skill scores, mean squared error, and Akaike Information Criterion. Both model types perform well, with coefficient of determination values exceeding 0.90 at multiple stations using only 3-5 predictors. Our analysis reveals that the best causal predictors are surface-layer temperature, stratification, Chl-a, and particle carbon. This approach provides a scalable framework for improving prediction models and understanding the mechanistic links that control the seasonal variability of DO in estuarine systems.

Estuaries↗

PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗

PubMed2026

Overcoming the hurdles: A systematic review of barriers to self-initiated exercise in trauma recovery.

There is substantial quantitative evidence in support of exercise as beneficial for trauma recovery, particularly in targeting the neurobiological mechanisms disrupted by trauma. It is therefore important to understand the circumstances under which individuals may avoid exercise, ultimately preventing them from accessing the wellbeing benefits. Some qualitative articles have identified the factors which may prevent an individual from choosing to engage in exercise outside of a structured intervention (self-initiated exercise), but there lacks a synthesis across these differing articles. This systematic review aimed to synthesise qualitative evidence on trauma survivors' experience of barriers to self-initiated exercise. A systematic search of six databases was conducted to identify peer-reviewed qualitative findings on the perceived barriers to self-initiated exercise engagement, with six articles meeting the inclusion criteria. Thematic synthesis revealed three key themes: Searching for Safety, Staying With The Trauma, and Costs of Exercise and Trauma. In their decision to exercise, trauma survivors negotiate many barriers: the physiological, social, and environmental threats to their safety, trauma-related dissociation, and the costs of both exercise and trauma weighed against competing recovery needs. The small number of included studies reflects the emerging nature of research in this area, but it may limit the transferability of the findings. Nonetheless, as the first of its kind, this systematic review collates the experience of barriers as a first meaningful, exploratory step towards addressing them in future research. Taken together, the findings underscore the importance of a trauma-informed approach to ensure exercise remains unimpeded for trauma survivors.

Humans↗

PubMed2026

Evaluation of intravenous sedation in dental implant surgeries: A prospective cohort study.

PURPOSE: This study aimed to evaluate the impact of intravenous sedation on patient-centered outcomes during implant and bone augmentation surgeries. METHOD: A prospective observational cohort study included 40 patients undergoing placement of ≥3 implants, with or without bone augmentation. Patients underwent surgery under either intravenous sedation (n = 20) or local anesthesia alone (n = 20), according to routine clinical decision-making and patient preference. The sedation group received intravenous sedation with a multimodal regimen comprising remimazolam, dexmedetomidine, alfentanil, and low-dose esketamine, whereas the control group received local anesthesia only. Patient-reported outcome measures, hemodynamic parameters (SBP, DBP, HR, SpO2), postoperative pain (0-10 scale), and OHRQoL (OHIP-14) were recorded from baseline through 7 days post-surgery. RESULTS: Intravenous sedation was associated with significantly lower intraoperative pain (0.5 [IQR: 0∼2.75] vs. 3.25 ± 2.40, p = 0.003), anxiety (1 [IQR: 0∼2.75] vs. 4 [IQR: 3∼6], p = 0.001), and experienced discomfort (2 [IQR: 1∼3.75] vs. 4.15 ± 2.16, p = 0.016), and shortened perceived treatment duration (2.90 ± 2.34 vs. 5 [IQR: 4∼5], p = 0.020). Early postoperative pain was lower in the sedation group from Days 1-4 (p = 0.003-0.010). Hemodynamic parameters were more stable under sedation, with lower SBP (116.42 ± 13.32 vs. 144.11 ± 17.42 mmHg, p < 0.001), DBP (73.21 ± 10.28 vs. 82.37 ± 11.03 mmHg, p = 0.012), and HR (71.00 [IQR: 62.50∼79.25] vs. 85.00 ± 10.72 bpm, p = 0.021). OHRQoL scores favored the sedation group in swallowing, diet, malaise, and daily activities, particularly during the first three postoperative days (p=0.006-0.040). CONCLUSION: Intravenous sedation may enhance the patient experience during implant and/or bone augmentation procedures by reducing intraoperative pain and anxiety, improving hemodynamic stability, and promoting better early-postoperative recovery and OHRQoL. These findings suggest that intravenous sedation provides a safe and effective alternative for implant dentistry surgery, particularly for anxious or pain-sensitive individuals.

Humans↗

PubMed2026

Facilitators and Barriers to Volunteers' Involvement in Palliative Care: A Qualitative Meta-Synthesis.

OBJECTIVE: This study aims to systematically synthesize qualitative evidence on facilitators and barriers to volunteer involvement in palliative care services, providing insights to inform strategies for strengthening volunteer support systems. METHODS: PubMed, Web of Science, Embase, Cochrane Library, Medline, EBSCO, ProQuest, China National Knowledge Infrastructure, Wanfang, VIP, and Sinomed were searched from inception to December 2025 to identify qualitative studies examining factors influencing volunteer participation in palliative care. Methodological quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Qualitative Research. Data were analyzed using Thomas and Harden's thematic synthesis approach and managed using NVivo 12.0 software, following the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines. RESULTS: Thirty-one studies involving 1042 participants were included, yielding 68 findings. Facilitators included intrinsic motivation and meaning-making at the individual level; supportive relationships and teamwork at the interpersonal level; structured support and professional recognition at the organizational level; social recognition and resource integration at the community level; and institutional safeguards and governmental incentives at the policy level. Barriers included emotional burden and limited competencies at the individual level; relationship conflicts and insufficient collaboration at the interpersonal level; management deficiencies at the organizational level; community resource imbalances at the community level; and inadequate regulations and incentives at the policy level. CONCLUSION: Volunteer participation in palliative care is influenced by multiple interacting factors. Strengthening training and support systems, enhancing team collaboration, and improving institutional frameworks may help sustain volunteer engagement and improve the quality of palliative care services.

Palliative Care↗

PubMed2026

Artificial Intelligence Cannot Replace Peer Reviewers but May Help Editors Triage: A Comparative Analysis of a Large Language Model and Human Reviewer Recommendations at the American Journal of Sports Medicine.

BACKGROUND: The peer review system faces increasing strain from rising manuscript volumes, reviewer fatigue, and well-documented interreviewer disagreement. Large language models (LLMs) have shown potential to support the peer review process, but their ability to replicate editorial decisions at high-impact medical journals and their utility as manuscript screening tools remain unknown. PURPOSE: To compare the agreement between an LLM and the final editorial decision on manuscripts submitted to the American Journal of Sports Medicine and to evaluate the potential of LLMs as a manuscript screening tool. STUDY DESIGN: Cross-sectional agreement study. METHODS: Fifty-four manuscripts randomly selected from submissions to the American Journal of Sports Medicine (September 2024-October 2024) were reviewed by a locally deployed LLM (Ministral 3 14B; Mistral AI) using a standardized prompt. The artificial intelligence (AI) produced a categorical recommendation (reject, cascade, revision, or accept) and a numerical score (0-100) for each manuscript. Agreement with the final editorial decision was assessed by Cohen kappa (4-category model) for pooled human reviewers (n = 139 reviews) and the AI (n = 54). Screening performance was evaluated by positive predictive value (PPV), sensitivity, and specificity. RESULTS: Pooled human reviewers demonstrated fair agreement with the final decision (κ = 0.181 [P < .001]; 42.4% agreement), while the AI demonstrated slight, nonsignificant agreement (κ = 0.126 [P = .099]; 37.0% agreement). The AI recommended revision for 61.1% of manuscripts, of which 72.7% were ultimately rejected or cascaded, demonstrating systematic "revision bias." When the AI recommended rejection, 54.5% of those manuscripts were ultimately rejected and 27.3% were cascaded; when the AI recommended cascade, 50% were rejected and 50% were cascaded. However, when the AI recommended rejection or cascade (n = 21), 90.5% received a final decision of rejection or cascade (PPV, 90.5%; specificity, 81.8%). Manuscripts with an AI score <70 were rejected or cascaded 88.0% of the time (PPV, 88.0%). CONCLUSION: AI cannot replicate the nuanced judgment of human peer reviewers at a high-impact sports medicine journal. When AI recommended rejection or cascade, 90.5% of manuscripts received that final decision (descriptive PPV, 90.5%; 95% CI, 71.1%-97.3%), suggesting potential utility as an exploratory first-pass screening tool warranting further validation in larger cohorts. However, AI could not reliably distinguish manuscripts destined for outright rejection from those that would be cascaded to a sister journal-an important limitation for editorial triage applications.

Sports Medicine↗

PubMed2025

Enhanced fracture detection on radiographs with AI assistance for clinicians: a systematic review and meta-analysis.

BACKGROUND: Emergency radiographic interpretation for fractures is prone to missed or misdiagnoses. Artificial intelligence (AI) is expected to become a powerful tool to assist clinicians in fracture detection. PURPOSE: A systematic review and meta-analysis was performed to assess whether AI improves clinicians' ability to detect fractures on radiographs. MATERIALS AND METHODS: A literature search was conducted in PubMed, Web of Science, and Cochrane Library for studies published between January 1, 2010, and October 10, 2025. A meta-analysis of diagnostic accuracy studies was performed using a Summary Receiver Operating Characteristic (SROC) curve. The quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. Subgroup analysis and meta-regression were conducted to explore potential sources of heterogeneity. RESULTS: A total of 26 studies were included . The pooled sensitivity of clinicians increased from 77% (95% CI: 72-81) to 87% (95% CI: 83-90) with AI assistance, while the pooled specificity improved from 88% (95% CI: 85-90) to 92% (95% CI: 89-94). The corresponding AUC values were 0.90 (95% CI: 0.87-0.92) before and 0.95 (95% CI: 0.93-0.97) after AI assistance. Eight studies were rated as high risk of bias. Subgroup analysis and meta-regression identified potential sources of heterogeneity, including fracture location, AI model type, high risk of bias, and reference standards. CONCLUSION: AI assistance significantly improves clinicians' diagnostic performance in detecting fractures on radiographs for extremity and trunk fractures.

Humans↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗

PubMed2026

Characteristics of children with ureteroceles presenting for urological evaluation in the modern medical era.

INTRODUCTION: Historically, children with ureteroceles presented symptomatically and were managed surgically. It is unclear if this changed in the modern medical era of prenatal imaging and shared decision making. We aimed to describe the presentation and management of ureteroceles during initial urological evaluation of children in the era of widespread prenatal ultrasonography. PATIENTS AND METHODS: We retrospectively reviewed records of children (<18 years old [yo]) initially evaluated at our center with a ureterocele (2011-2020). We analyzed demographics, renal anatomy, initial presentation for evaluation, and initial management with non-parametric statistics. Febrile urinary tract infections (fUTIs, ≥ 38 °C) were classified as 1) urosepsis (positive urine culture admitted to pediatric intensive care), 2) documented (positive urine culture) or 3) family-reported. RESULTS: We identified 188 children (65% female). Median age at presentation was 1.2 months old (mo) (IQR 18 days-4.4 mo). Antenatally-detected congenital anomalies of the kidney and urinary tract (aCAKUT) were noted in 143 (76%) children with a confirmed postnatal diagnosis of ureterocele. Overall, 129/188 (69%) children presented without symptoms and 59 (31%) presented with symptoms. fUTI was the most common symptomatic presentation (46/188, 24%): urosepsis (6 children), documented (30), and family-reported (10). Children with aCAKUT presented earlier than those without aCAKUT (27 days vs. 1.6 yo, p < 0.0001). They were also less likely to present with symptoms (11% vs. 96%, p < 0.0001), including fUTIs (7% vs. 78%, p < 0.0001). In total, 108 children (57%) were initially managed with transurethral incision, 73 (39%) were observed, and 7 (4%) had reconstructive surgery. Asymptomatic children with aCAKUT (42%) and symptomatic children without aCAKUT (37%) were more likely to be observed than symptomatic children with aCAKUT (7%, p = 0.02). Among 143 children with aCAKUT, those on antibiotic prophylaxis were less likely to present with a history of a fUTI compared to those not on prophylaxis (4/106 vs. 6/37, 4% vs. 16%, p = 0.02). COMMENT: We present a large observational study describing clinical and anatomical characteristics of children presenting with ureteroceles in a medical era of ubiquitous prenatal ultrasonography. Our retrospective study was limited by incomplete documentation of all antenatal ultrasonography and adherence with antibiotic prophylaxis. Long-term clinical outcomes will be the focus of future work. CONCLUSION: In contrast to historical cohorts, most children presented to urologists with asymptomatic ureteroceles diagnosed with aCAKUT. Most children without aCAKUT presented with a fUTI. Overall, 39% of children were initially observed, indicating an increased use of observation in the modern medical era.

Humans↗

PubMed2026

Real-world clinical utility of exome sequencing in pediatric drug-resistant epilepsy: Experience from a tertiary center in Thailand.

BACKGROUND: Genomic testing has increasingly contributed to the diagnosis and management of pediatric drug-resistant epilepsy (DRE), particularly in patients with suspected genetic etiologies. This study evaluated the diagnostic yield and real- world clinical utility of whole-exome sequencing (WES) in children with DRE. METHODS: Children with DRE and seizure onset before 15 years of age were enrolled between January 2020 and December 2023. Clinical data, including demographics, seizure characteristics, developmental history, electroencephalography (EEG), brain magnetic resonance imaging (MRI), and prior investigations, were reviewed. WES was performed in all probands and, when available, their parents. Variants were interpreted according to standard guidelines. Clinical utility and 1-year seizure and developmental outcomes were assessed from follow-up records. RESULTS: Fifty-six patients (23 males, 33 females) were included. The median age at seizure onset was 1 year (interquartile range [IQR] 0.3-4 years), and 96.4% had developmental comorbidities. Pathogenic or likely pathogenic variants were identified in 39% (22/56), with the highest diagnostic yield in children with seizure onset before 3 years of age. Channelopathies accounted for most genetically solved cases (68%), predominantly involving sodium channel genes. Genetic diagnoses provided clinical utility in 73% (16/22) of solved cases by guiding treatment and precision management. At 1-year follow-up, genetically solved patients showed more favorable seizure and developmental outcomes than those with genetically unsolved patients. CONCLUSION: WES achieved a 39% diagnostic yield and substantial clinical utility in pediatric DRE, particularly in early-onset and channelopathy-related disorders. These findings support early molecular diagnosis to facilitate genotype-informed management in appropriately selected children. However, the more favorable developmental and seizure outcomes observed in genetically solved patients should be interpreted with caution, as they may have been influenced by multiple factors beyond genetic diagnosis. In resource-limited settings, careful clinical phenotyping remains essential for treatment decisions and for prioritizing children for genomic testing.

Clinical utility↗

PubMed2026

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lung cancer, glioma, and hairy cell leukemia. The most prevalent variant, BRAF-V600E, induces constitutive activation of the MAPK signaling pathway, promoting tumor progression and influencing therapeutic responsiveness. Accurate detection of BRAF alterations is therefore essential for molecular classification, prognostic assessment, treatment selection, and resistance surveillance. This review summarizes the molecular heterogeneity of BRAF mutations and critically evaluates current diagnostic methodologies. Conventional approaches such as allele-specific PCR and Sanger sequencing are compared with advanced quantitative platforms, including high-resolution melting analysis, droplet digital PCR, and next-generation sequencing, with emphasis on analytical sensitivity, mutation coverage, and clinical applicability. Emerging technologies such as CRISPR-based assays, rolling circle amplification systems, and nanoparticle-based biosensors and point-of-care diagnostic platforms are also discussed for their potential to enhance ultra-sensitive detection, particularly in liquid biopsy settings. These emerging tools are highlighted for their potential to enable ultra-sensitive, rapid, and decentralized mutation detection, particularly in liquid biopsy settings. Key challenges, including intratumoral heterogeneity, low allele-frequency variants, FFPE-associated artifacts, and clonal evolution under therapeutic pressure, are examined within a translational framework. In addition, we examine critical barriers to clinical implementation, including standardization, cost, and global accessibility of molecular diagnostics, and outline potential solutions through scalable technologies and decentralized testing strategies. We propose that optimal BRAF testing requires a mutation subclass-informed and clinically integrated strategy combining comprehensive baseline profiling with longitudinal molecular monitoring. Future diagnostic paradigms will likely integrate multi-omics data and artificial intelligence (AI)-assisted interpretation to refine precision oncology implementation. Looking forward, we propose that optimal BRAF testing will require integration of multi-omics profiling with AI-assisted interpretation, enabling automated variant classification, real-time clinical decision support, and improved prediction of therapeutic response and resistance.

Humans↗