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Magnetic Resonance Imaging (MRI) is the preferred modality for evaluating Lumbar Spinal Stenosis (LSS), yet grading remains subjective and inconsistent. Currently, no standardized reporting system, such as the American College of Radiology Reporting and Data systems (RADS), exists for LSS. The objective of this study is to assess the impact of a structured educational intervention using a classification system, on correctness and interobserver reliability of MRI LSS grading among radiology and non-radiology spine physicians. Health Insurance Portability and Accountability Act-compliant, Institutional Review Board-approved retrospective study analyzed 114 lumbar disc levels. Thirty-seven physicians across six specialties (musculoskeletal radiology (MR), neuroradiology (NR), radiology residents (RR), orthopedic surgery, neurosurgery (NS) and physiatry (PH)) graded stenosis (none, mild, moderate, severe) in two phases: pre-intervention (routine practice) and post-intervention following training with a classification system. Cases correct and discrepant by more than one grade (ex: mild-severe) were compared to a reference standard. Descriptive statistics and analyses included paired t-test, Wilcoxon test and intraclass correlation coefficient (ICC). Pre-intervention, overall correctness was 54.5% and improved to 61.2% post-intervention (p = 0.006). Cases discrepant more than one grade decreased from 3.7% to 2.0% (p = 0.002). Interobserver reliability improved significantly, with ICC increasing from 0.71 (95% CI: 0.65-0.76) to 0.75 (95% CI: 0.70-0.80); p = 0.030. Pre-intervention, musculoskeletal group had the highest percentage of cases correct (67.7%) and lowest discrepant cases (1.6%) and post-intervention, NR had the highest correct (64.9%) and lowest discrepant (0.7%). MR had the highest ICC pre (0.774 (0.709 to 0.829)) and post-intervention (0.781 (0.720 to 0.834)). Education and implementation of a standardized MRI LSS classification system significantly improved grading concordance and interobserver reliability across a large multidisciplinary physician cohort.
It has been reported that the introduction of thirteen-valent pneumococcal conjugate vaccine (PCV13) had an influence on antibiotic resistance rates of invasive pneumococcal disease (IPD). Recent data about antibiotic resistance in IPD are scarce. The aim of the current study was to analyse the impact of PCV13 introduction and COVID-19 pandemic on antibiotic resistance in IPD and the effects of antibiotic resistance on mortality. Furthermore, we correlate vaccine and non-vaccine serotypes with antibiotic resistance. We included 8747 IPD cases from a Swiss nationwide IPD surveillance database for 2012-2022. Regression analyses were performed to examine significant trends over time and to identify serotypes and patient characteristics associated with antibiotic resistance. The proportion of non-susceptibility to erythromycin (IRR: 0.9, p < 0.001) and cotrimoxazole (IRR: 0.9, p < 0.001) decreased from 2012 to 2022. Penicillin non-susceptibility remained constant with a dip in 2022 (2012: 9.2%, 2022: 4.7%). PCV13 serotypes 6B, 9V, 14, 19A and 19F were significantly associated with non-susceptibility while the non-PCV13 serotype 15A, 23B, 24/F and 6C were associated with resistance to at least two antibiotic groups. Antibiotic non-susceptibility was not associated with death but meningitis was associated with penicillin non-susceptibility. Antibiotic resistance in IPD decreased over time without increases during the COVID-19 pandemic, while a strong association between serotypes and antibiotic resistance persists. Introduction of vaccines with extended serotype coverage may further affect antibiotic resistance rates underlining the importance of continued surveillance.
Medical dramas are widely consumed by medical students globally and may constitute an informal or hidden curriculum influencing professional identity, empathy, and ethical reasoning. Palestinian medical students represent an understudied population navigating a resource-constrained and geopolitically complex healthcare context. To investigate the perceptions of Palestinian medical students regarding medical dramas, including viewing habits, assessments of clinical and ethical realism, psychological and behavioural impacts, and the potential role of such media as an informal educational resource. A cross-sectional study was conducted among 638 undergraduate medical students from five universities in the West Bank, Palestine, using convenience and snowball sampling. Data were collected via an online structured questionnaire adapted and culturally validated from the Czarny et al. (2008) instrument, incorporating forward-back translation, pilot testing (n = 15), and internal consistency assessment (Cronbach's alpha = 0.81). Descriptive statistics and Chi-square tests were applied. Mean age was 21.1 ± 1.65 years; 66.8% were female. Most participants (73.4%) had watched medical dramas, primarily via digital streaming platforms. While 77.3% perceived clinical scenes as only slightly or moderately realistic, 41.9% considered ethical content to be moderately accurately depicted. Approximately 46.6% reported increased empathy and 47.2% reported increased study motivation. Drama viewers were significantly more likely to rate informal sources-family (p < 0.001), friends (p = 0.021), and online news (p = 0.037)-as important for ethical guidance, compared with non-viewers. Palestinian medical students engage substantially with medical dramas and appraise their content critically. Associations between drama viewing and increased empathy, study motivation, and reliance on informal ethical guidance sources suggest a potential hidden-curriculum effect. Given the cross-sectional design and convenience sampling, causal inferences cannot be drawn. These findings support cautious integration of medical dramas into bioethics and professionalism curricula as supplementary teaching tools.
Across sub-Saharan Africa, and Nigeria in particular, young women and adolescent girls aged 15 to 24 continue to face a disproportionate risk of HIV - and a large part of that risk comes down to unprotected sex. Knowing about HIV is widely assumed to lead to safer behaviour, yet the evidence that knowledge actually translates into condom use is far from straightforward. This study takes a closer look at that relationship, comparing comprehensive HIV knowledge and condom non-use among unmarried adolescent girls and young women (AGYW) in Nigeria across three points in time. We drew on data from the Nigeria Demographic and Health Surveys conducted in 2008, 2013, and 2018. Condom non-use at last sexual intercourse - a standard DHS indicator - served as our measure of risky sexual behaviour. The analysis focused on sexually active unmarried women in two age groups: adolescent girls aged 15 to 19, and young women aged 20 to 24. We excluded participants with missing or unclear responses for the outcome variable or key covariates. Weighted descriptive statistics and survey-weighted binary logistic regression models were run separately for each age group and survey year, with all analyses accounting for the clustered, stratified sampling design of the NDHS. Stata 16.1 was used throughout. HIV knowledge improved over the study period, particularly among young women in the older age group, while trends in condom use followed a less predictable pattern. Among adolescent girls, comprehensive HIV knowledge was not meaningfully linked to condom use in 2008, but that association became statistically significant by 2013 and held through 2018. Importantly, though, condom non-use actually rose in 2018 even as knowledge levels reached their highest point - a clear sign that knowing is not the same as doing. Socioeconomic status and region of residence were both significantly associated with condom use. Comprehensive HIV knowledge among unmarried AGYW in Nigeria has grown, but it has not reliably translated into condom use. This gap between what young women know and what they are able to do points to barriers that go well beyond information - structural, social, and economic forces that shape the choices available to them. Closing that gap will require interventions that take those realities seriously.
Hearing and vision impairments are modifiable risk factors for cognitive decline, yet their longitudinal contributions to mild cognitive impairment (MCI) and dementia remain unclear. This study examined differential associations of baseline sensory function and longitudinal sensory trajectories with cognitive status at Wave 9. Nine waves of data (2006-2022) from the Korean Longitudinal Study of Aging were analyzed, including 11,146 participants aged 45 years and older. Parallel process latent growth modeling was used to examine associations between baseline hearing and vision, their rates of change over time, and cognitive status at the final wave (cognitively normal, MCI, dementia). More rapid hearing decline was significantly associated with a higher likelihood of being classified in the dementia group. Poorer baseline vision was associated with a higher likelihood of being classified in the MCI group. In contrast, baseline hearing and longitudinal vision decline were not significantly associated with MCI or dementia classification, respectively. These findings indicate that longitudinal hearing decline shows a stronger association with dementia classification than visual impairment, whereas poorer baseline visual function may be more strongly associated with earlier-stage cognitive status.
Students from low-income and underrepresented backgrounds face structural barriers to entering medicine, including limited access to early clinical exposure, physician guidance, and professional networks. To address these disparities, medical students at the Warren Alpert Medical School of Brown University created a year-long Clinical Mentorship Program (CMP) for high school students in Woonsocket, Rhode Island. The intervention combined monthly after-school instruction on basic science content and clinical skills by medical students with structured hospital-based shadowing and guided discussion with resident physicians. Using a mixed-methods pre-post design, the intervention evaluated changes in educational motivation, clinical self-efficacy, medical knowledge, awareness of other academic enrichment programs, and physician access and comfort. High school students demonstrated significant gains in motivation to attend college, understanding of cardiopulmonary anatomy and physiology, understanding of physician roles, comfort interacting with physicians, self-reported physician access, and awareness of local educational opportunities. Qualitative findings highlighted the importance of experiential learning, guided shadowing, a clearer understanding of medical careers, and persistent structural barriers. These findings suggest that community-based programs that leverage local resources, networks, and infrastructure to combine medical education with guided clinical exposure may be feasible entry points into the medical pipeline for students confronting complex socioeconomic disadvantages.
Take Home Illustration. Heart Failure Pharmacotherapy Across the TAVR Continuum. GDMT recommendations across the pre-, peri-, and post-procedural phases of TAVR. The recommendations are based on available evidence for each drug class regarding safety, efficacy, and impact on clinical outcomes. BB = beta blocker; HF = heart failure; GDMT = guideline directed medical therapy; HFpEF = heart failure with preserved ejection fraction; HFrEF = heart failure with reduced ejection fraction; MRA = mineralocorticoid receptor antagonist; RASi = renin angiotensin system inhibitor; SGLT2i = sodium glucose transporter 2 inhibitor; TAVR = transcatheter aortic valve replacement. Transcatheter aortic valve replacement (TAVR) is an increasingly common treatment option for severe symptomatic aortic stenosis. However, heart failure often persists because of incomplete reversal of myocardial remodeling, fibrosis, and diastolic dysfunction. TAVR corrects valvular afterload but does not resolve the underlying myocardial disease. Guideline-directed medical therapy (GDMT), including renin-angiotensin system inhibitors (RASi), sodium-glucose cotransporter-2 inhibitors (SGLT2i), mineralocorticoid receptor antagonists (MRAs), and beta-blockers (BBs), has a strong mechanistic rationale and potential clinical benefit, although evidence in TAVR populations remains heterogeneous and is largely observational. Nonetheless, accumulating data support continuation and early optimization of GDMT in the pre-, peri-, and post-TAVR periods, with the most consistent benefit observed for RASi and SGLT2i. Key uncertainties remain regarding optimal timing, patient selection, and class-specific effects. This State-of-the-Art Review integrates current evidence and proposes a framework to guide GDMT use across the TAVR continuum while defining priorities for future randomized trials Condensed Abstract: Post-TAVR heart failure frequently persists because of residual myocardial disease. GDMT, including RASi, SGLT2i, MRAs, and BBs, may improve outcomes but remains underutilized and inconsistently addressed in current guidelines. GDMT should ideally be continued when tolerated and optimized early across the TAVR continuum, particularly RASi and SGLT2i. Therapy should be tailored to heart failure phenotype across the TAVR continuum. Randomized trials are needed to define optimal implementation strategies.
This prospective repeated-measures quasi-experimental educational study, conducted across two consecutive first-year medical school cohorts, aimed to develop and implement case-based learning (CBL) modules using three-dimensional (3D) models and magnetic resonance imaging (MRI) within an extended reality (XR) environment. The intervention integrated anatomical variations and anomalies to enhance immediate learning and long-term knowledge retention. MRI data from selected donors at the John A. Burns School of Medicine (JABSOM) were used to create XR-CBL modules. First-year medical students from the classes of 2024 (Cohort 2021) (n = 61) and 2025 (Cohort 2022) (n = 67) participated. Before the session, students received an email detailing the activity. During the gross anatomy laboratory, they accessed a website to explore cases featuring learning objectives, clinical and radiological data, 3D models, and MRIs. The XR experience utilized desktop-based XR technology. An assessment was administered before, immediately after, and eight weeks post-intervention. Students also completed a mixed-format feedback survey. A repeated-measures ANOVA revealed a significant effect of the intervention on student performance across both cohorts. For Cohort 2021, Wilks' Lambda = 0.384, F (2, 59) = 47.27, p < 0.001, partial η² = 0.616. For Cohort 2022, Wilks' Lambda = 0.30, F (2, 65) = 72.72, p < 0.001, partial η² = 0.691. Follow-up pairwise comparisons with Bonferroni adjustments indicated significant improvements from pre-test to post-test and from pre-test to post-post-test for both cohorts (p < 0.01). There was no significant difference between the post-test and post-post-test scores (p = 1.00). In Cohort 2021, mean scores significantly increased from pre-test (3.9 ± 1.9) to post-test (6.2 ± 2.6) and were maintained at post-post-test (6.3 ± 1.7). Similarly, Cohort 2022 demonstrated significant gains from pre-test (4.3 ± 1.6) to post-test (7.6 ± 2.2), with high retention at post-post-test (6.3 ± 2.4). Pairwise comparisons confirmed that improvements from baseline were significant (p < 0.01), while no significant decay occurred between post- and post-post-assessments (p = 1.00). Incorporating multimodal resources, including anatomical variations and anomalies through CBL, into the gross anatomy laboratory was associated with significant score improvements and positive student perceptions. Learners reported that the interactive, imaging-based tools helped them better understand complex anatomical relationships, particularly when anatomical variability was highlighted.
A decision coach (DC) is a trained healthcare professional who provides non-directive support to patients in health-related decision-making. The decision coach role can be integrated into shared decision-making (SDM) processes, but is not an inherent component of SDM, as both may be applied independently depending on the clinical context. Numerous trained DCs are nurses who have transitioned from their roles as patient educators to knowledgeable, skilled decision facilitators. Thus, developing core competencies has become increasingly crucial for DC training, especially patient-centered care in nursing education. This study aimed to evaluate DC competencies in SDM by examining accessibility, performance, and perceived directional relationships among competency domains. This mixed-methods study combined a narrative literature review and expert consultations to identify key DC competency criteria. Subsequently, a cross-sectional questionnaire survey was administered to healthcare professionals at two hospitals in Taiwan between April 2023 and February 2024. Accessibility-performance analysis (APA) and the decision-making trial and evaluation laboratory (DEMATEL)-based network relation map (NRM) approach were applied to evaluate competency accessibility, performance, and perceived directional relationships across domains. A total of 149 healthcare professionals, including physicians, nurses, and other clinical staff, completed the valid questionnaires. The reliability of the overall criteria was measured at 0.965. The findings suggest that the professional knowledge (PK) aspect demonstrated perceived directional associations with the outcome evaluation (OE), process management (PM), and guidance skills (GS) aspects within the network structure, whereas the GS aspect was more likely to be associated with other competency domains. Each of the four aspects has a criterion critical to improving DCs' competencies: value (PK1), listening skill (GS2), shared decision-making resources (PM3), and practical decision-making results (OE3). From healthcare professionals' perspectives, professional knowledge was the competency domain most closely associated with perceived directional relationships among other competency aspects within the network structure. The integrated APA-NRM approach delivers evidence-based prioritization and practical pathways for developing DC competencies and guiding training strategies. Not applicable.
Recent cognitive neuroscience research has uncovered some similarities and some differences between general semantic memory (GS; e.g., knowledge about family in general) and personal semantic memory (PS; e.g., knowledge about my family in particular). To better understand the representational content and cognitive processes of PS and their relation to general semantics, we adapted a staple of General semantic memory research, the Property Generation task. In a first study, we randomly assigned 240 adult participants to a traditional General semantics perspective (e.g., listing the properties of families and bedrooms in general) or to a PS perspective (e.g., my family, my bedroom) in a between-subjects design. In a second, replication study, 124 participants completed the task in a within-subject design, taking each perspective for different concepts. Relative to the General semantics condition, the PS condition was associated with more features; these were more semantically distant from each other, and included adjectives more frequently and nouns less frequently. However, the two conditions had substantial (~46%) overlap in the frequency of their features. The findings contribute to the identification of the cognitive differences (e.g., semantic richness) and similarities (e.g., correspondence in semantic features) between personal and general semantic memory. Des recherches récentes en neurosciences cognitives ont mis en évidence des similitudes et des différences entre la mémoire sémantique générale (SG ; p. ex., les connaissances sur la famille en général) et la mémoire sémantique personnelle (SP ; p. ex., les connaissances sur ma propre famille). Afin de mieux comprendre le contenu des représentations et les processus cognitifs de la SP, ainsi que leur relation à la SG, nous avons adapté un outil classique de la recherche en mémoire sémantique générale : la tâche de génération de propriétés. Dans une première étude, 240 participants adultes ont été assignés aléatoirement à une perspective de sémantique générale (p. ex., lister les propriétés des familles et des chambres en général) ou à une perspective de sémantique personnelle (p. ex., ma famille, ma chambre), selon un plan inter-sujets. Dans une seconde étude de réplication, 124 participants ont réalisé la tâche avec un plan intra-sujets, en adoptant chaque perspective pour des concepts différents. Comparativement à la condition de SG, la condition de sémantique personnelle était associée à un plus grand nombre de propriétés de concepts, les propriétés étaient sémantiquement plus distantes les unes des autres, et comprenaient plus fréquemment des adjectifs et moins fréquemment des noms. Les deux conditions présentaient néanmoins un chevauchement substantiel (~46 %) dans la fréquence des propriétés produites. Ces résultats contribuent à cerner les différences cognitives (p. ex., la richesse sémantique) et les similitudes (p. ex., la correspondance des propriétés sémantiques) entre la mémoire des sémantiques personnelles et la mémoire des sémantiques générales.
Understanding dimensions of both sinus tarsi (ST) and tarsal canal (TC) in normal and flatfeet may influence the design, usage and possible control of postoperative complications of arthroereisis. This study was to assess 3D features of the tarsal sinus and canal complex (TSCC) in both normal control and flatfeet in children under non-weightbearing and weightbearing conditions. Three-dimensional (3D) computer-aided design modeling from WBCT scans of 22 children with flexible flatfeet (age 9-14) and 14 with normal control feet (age 9-15) were used to evaluate volume and dimensions of TSCC. Correlations between Meary's angle, hindfoot alignment, and volume of TSCC were calculated on non-weightbearing and weightbearing CT scans. The volume of TSCC was smaller in the flatfoot group compared with the control group both under weightbearing and non-weightbearing conditions. From non-weightbearing to weightbearing the volume of TSCC decreased by 19.1% in the flatfoot group and 13.1% in the control group while the long axis of TSCC moved superiorly and anteriorly with internal rotation in both groups. When bearing weight, TSCC volume was negatively linearly correlated with the hindfoot alignment and Meary's angle. This study demonstrates that weightbearing has different influences in 3D features of the tarsal sinus and canal complex in children with control and flatfeet. These findings may help understanding biomechanics of pediatric flatfoot and guiding treatment in particular when arthroereisis is used. Level III, Retrospective Comparative Study.
While use of shared decision-making (SDM) is widely accepted and applied in practice, it is unknown how core elements of SDM are reflected in clinical documentation. This knowledge gap is particularly relevant in the setting of surgery in children, where parents serve as proxy decision-makers. We analyzed transcribed audio-recorded outpatient encounters and corresponding medical documentation for pediatric patients undergoing evaluation for elective surgery. Visit transcripts and medical record documentation of the corresponding clinical encounter were coded for two core elements of shared decision-making: parental concerns and preferences. We assessed the frequency (visit-level and instance-level) and content of these elements expressed in verbal communication and in clinical documentation. Of 109 visits, concerns and preferences were discussed in nearly half of encounters (Visit level: Concerns n = 46, 42%; Preferences n = 49, 45%). Most verbally-expressed concerns (e.g., "we're worried about her breathing"; "…she sleeps with me. I'm constantly shaking her. She scares me a lot") focused on symptoms and surgical risk whereas preferences (e.g., "I would just rather take them out"; "I'd definitely rather go the conservative route") centered on treatment decisions. Of the total unique instances of stated concerns (n = 74) and preferences (n = 62), about half were recorded in the medical record (Instance-level: Concerns n = 34, 46%; Preferences n = 28, 49%). These findings show that parent preferences and concerns that are discussed during pediatric surgical encounters are not routinely reflected in clinical documentation. Thoughtful documentation of family perspectives may enhance transparency, support communication across the health continuum, and contribute to high quality patient- and family-centered care.
The ratio of red blood cell distribution width to albumin (RAR) is a systemic blood-based marker associated with adverse health outcomes. Although cross-sectional studies have suggested a link between RAR and depression, its longitudinal association with the incidence and long-term course of late-life depression has not yet been established. We aimed to address this knowledge gap using data from a large cohort of older adults. This longitudinal cohort study used data from the Health and Retirement Study (2016-2022). The analysis of incident depression included 6,151 U.S. adults aged ≥ 60 years who were free of depression at baseline. Multivariable Cox regression was used to assess the association, and restricted cubic splines were applied to examine the dose-response relationship. In a subcohort of 5,588 participants, group-based trajectory modeling was used to identify depressive symptom trajectories, and their association with baseline RAR was examined using multinomial logistic regression. During a median follow-up of 6 years, 1,287 participants developed incident depression. In the fully adjusted model, each 1-unit increase in baseline RAR was associated with a 19% higher risk of incident depression (HR = 1.19; 95% CI: 1.06-1.33). Compared with the lowest quartile, the highest RAR quartile was associated with a higher risk of incident depression (HR = 1.20; 95% CI: 1.01-1.42). The dose-response analysis indicated a linear relationship (P for non-linearity = 0.961). Four distinct symptom trajectories were identified: "Non-depressed" (28.11%), "Low-stable" (40.89%), "Moderate-progressive" (25.42%), and "High-progressive" (5.58%). Compared with the "Non-depressed" group, higher baseline RAR was associated with greater odds of membership in the "High-progressive" (OR = 1.31; 95% CI: 1.11-1.55) and "Moderate-progressive" (OR = 1.36; 95% CI: 1.07-1.73) groups. In this large, nationally representative cohort of older adults, higher baseline RAR was longitudinally associated with an increased risk of incident depression and a subsequent long-term trajectory of worsening depressive symptoms.
Two 2'FY-RNA aptamers with distinct sequences were selected for specific binding to pyoverdine-Pf5 (PVD-Pf5), increasing chromophore fluorescence upon binding. They also recognized the peptide portion of pyoverdines, as shown by their differential specificity for related variants. Computational analysis and experimental data (NMM binding, CD spectra) identified G-quadruplex structures that were thermally metastable but reformed in the presence of PVD-Pf5. Further structural studies mainly with one aptamer revealed imino proton peaks in 1D H-NMR and pressure stability up to 2 kbar. Electrophoretic evidence identified dimeric G-quadruplexes formed by the 2'FY-RNA aptamers and their RNA equivalents. While cations were necessary for PVD-Pf5 binding, they were not required for G-quadruplex formation. Given the established role of G-quadruplexes as protein interaction sites, multimeric G-quadruplexes offer a potential framework for structure-based regulatory mechanisms in cellular RNAs. In addition to previously characterized multimeric G-quadruplexes, these aptamers contribute novel sequences that expand the repertoire of known multimeric G-quadruplexes.
Artificial intelligence (AI) is increasingly integrated into radiology, but pediatric imaging remains underrepresented in implementation studies. To assess the current status, barriers, and enablers of AI adoption in Pediatric Radiology from a global leadership perspective. A cross-sectional international survey of department leaders and division chiefs from pediatric radiology centers worldwide was conducted. The questionnaire included 14 items across domains of AI deployment, enablers, barriers, ethical concerns, stakeholder involvement, and future directions. Descriptive statistics were used for analysis. Eighteen institutions completed the survey (69% response rate). Sixteen centers (88.9%) reported implementing at least one AI tool, with bone age assessment remaining the most widely used application (44.4%). Other applications included image segmentation and quantification (22.2%), imaging protocol optimization (16.7%), and natural language processing (16.7%). The mean clinical impact rating was 3.56/5, with only 16.7% describing AI as "transformational." The most frequently cited barriers were lack of pediatric-specific datasets (83.3%), integration challenges (66.7%), high cost or unclear return on investment (ROI) (50%), and cybersecurity concerns (44.4%). Enablers were primarily human rather than technical, with vendor maturity and integration (72.2%) and internal champions (66.7%) most frequently highlighted. Regional variation was observed, with NLP/reporting clustered in North America and transformational impact ratings concentrated in the Asia-Pacific centers. A slim majority (55.6%) agreed that pediatric AI research currently overemphasizes model development over clinical integration, ethics, and sustainability. Global pediatric radiology leaders report cautious but growing AI adoption. Addressing pediatric data scarcity, enhancing multicenter collaboration, and prioritizing clinical integration and sustainability will be essential for safe and effective deployment. Question How are leading pediatric radiology centers worldwide implementing AI, and what institutional barriers and enablers determine successful clinical integration? Findings Most centers deploy at least one AI tool, but perceived impact remains modest due to pediatric data scarcity and workflow integration challenges. Clinical relevance Addressing pediatric-specific dataset limitations through multicenter collaboration, empowering institutional AI champions, and prioritizing clinical integration over model development alone will be essential for ensuring AI benefits children as effectively as adults.
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Sarcopenia, cachexia, and malnutrition are common in patients on immune checkpoint inhibitors (ICIs). GLP-1 receptor agonists (GLP-1 RAs) are increasingly used for weight management in patients with obesity, including those with cancer. Whether GLP-1 RA use at ICI initiation relates to wasting-related outcomes in patients without diabetes is unknown. We examined whether GLP-1 RA supply at ICI start was linked to wasting-related diagnoses and acute-care use. We used target-trial emulation with TriNetX US data. Adults with cancer and obesity/overweight starting an ICI were included. Baseline diabetes in the prior 12 months were excluded, with a 90-day GLP-1 RA washout. Exposure was a GLP-1 RA prescription or administration within a prespecified 30-day peri-initiation window before or after ICI initiation, versus none. Cohorts were 1:1 propensity score matched and followed up to 36 months; associations were estimated with intention-to-treat Cox models. After matching, 1974 patients were analyzed (987 per group). Over 36 months, GLP-1 RA overlap was associated with fewer immune-related adverse events (HR 0.63, 95% CI 0.50-0.79); hospitalization (HR 0.67, 0.51-0.89), ICU (HR 0.69, 0.53-0.90), and emergency department visits (HR 0.68, 0.53-0.89) were also lower. GLP-1 RA add-on at ICI initiation was associated with fewer recorded wasting-related diagnoses and less acute-care use. The all-cause mortality reduction is exploratory, likely reflecting channeling bias rather than causation. These findings support prospective evaluation of GLP-1 RAs as supportive-care add-on therapy in ICI-treated patients with obesity.
To develop and internally validate a radiology-centered machine-learning model using preoperative MRI and clinical characteristics to predict arthroscopic meniscal repairability. A retrospective cohort of 491 patients who underwent knee MRI followed by arthroscopy between 2018 and 2023 was analyzed. Preoperative predictors included demographic variables, injury mechanism, and a comprehensive set of MRI-derived features. Meniscal morphology, bone marrow edema, joint effusion, cruciate ligament integrity, cartilage degeneration, tear displacement, ramp lesion, and extrusion distance were systematically assessed by two musculoskeletal radiologists. Interobserver agreement was evaluated using Cohen's kappa and intraclass correlation coefficients (ICCs). Least absolute shrinkage and selection operator (LASSO) regression was used to identify the most informative predictors. Logistic regression, random forest, gradient boosting machine (GBM), and support vector machine (SVM) models were trained using five-fold stratified cross-validation with hyperparameter tuning via grid search. Model performance was evaluated using area under the receiver operating characteristic curve (AUC) with 95% confidence intervals, calibration metrics (calibration slope, intercept, and Brier score), and decision curve analysis (DCA). LASSO selected 13 preoperative predictors spanning eight clinically relevant domains. Logistic regression achieved the highest cross-validated performance (AUC = 0.777, 95% CI 0.735-0.819), followed by SVM (AUC = 0.771), random forest (AUC = 0.770), and GBM (AUC = 0.755). Multivariable logistic regression identified ACL injury (OR 0.38, 95% CI 0.25-0.57, p < 0.001), high-grade cartilage degeneration (OR 0.42, 95% CI 0.28-0.63, p < 0.001), greater BMI (OR 1.08 per kg/m2, 95% CI 1.03-1.13, p = 0.002), male sex (OR 0.51, 95% CI 0.33-0.78, p = 0.002), and ≥ 3 mm tear displacement (OR 0.44, 95% CI 0.29-0.67, p < 0.001) as independent predictors of non-repairability. Calibration analysis demonstrated good agreement between predicted and observed probabilities (calibration slope 0.95, intercept -0.08, Brier score 0.21). DCA demonstrated that logistic regression and random forest provided the greatest clinical net benefit across practical threshold probabilities. A radiology-based machine-learning model integrating detailed preoperative MRI features can accurately predict meniscal repairability with internally validated performance and may assist surgeons in optimizing arthroscopic decision-making and surgical planning pending prospective external validation.
To evaluate local tumor control and determinants of treatment success following magnetic resonance (MR)-guided microwave ablation (MWA) of liver malignancies. This single-center retrospective study evaluated prospectively included patients undergoing MR-guided MWA between September 2021 and February 2025. Procedures were performed under general anesthesia using a 1.5-Tesla MR scanner and two MR-compatible MWA systems. Complications were assessed according to CIRSE. Technical success was defined as total lesion coverage on MR imaging one day post-ablation. Local recurrence and hepatic tumor progression were analyzed using follow-up liver MR imaging every three months. Determinants of treatment success included lesion size, tumor entity, ablation duration, MWA system, lesion and antenna conspicuity (6-point Likert scale), adjacent vascular structures, liver cirrhosis, and antenna position (central/non-central). Forty-eight liver lesions in 40 patients (median age 62.5 years, 70.0% male) were treated. MWA systems 1 and 2 were used in 33/48 (68.8%) and 15/48 lesions (31.3%), respectively. Technical success was achieved in 46/48 lesions (95.8%), with one peri-procedural complication (CIRSE grade 3, 2.5%). Mean follow-up was 21.0 ± 10.9 months, with one patient lost to follow-up. Local recurrence occurred in 4/47 lesions (8.5%), all treated with system 1, while no recurrence was observed with system 2 (p = 0.173). As the only relevant determinant of treatment success, adjacent vascular structures were associated with higher local recurrence rates (p = 0.019). No local recurrence occurred in lesions < 20 mm. MR-guided MWA of liver tumors is safe, achieving high technical success and local tumor control. Adjacent vascular structures increase the risk of local recurrence and may warrant more aggressive treatment. Question Whether MR-guided MWA provides reliable local tumor control for liver malignancies and which procedural or anatomical factors influence treatment success. Findings MR-guided MWA achieved high technical success, low complication rates, and strong local tumor control; local recurrence occurred in lesions ≥ 20 mm and with low-power MWA systems, as well as adjacent vascular structures, significantly increased risk of local recurrence. Clinical relevance Prospectively acquired single-center cohorts of MR-guided MWA with real-time position monitoring in a standardized MR workflow, highlighting the impact of technical factors and the importance of lesion selection based on device-specific ablation characteristics.
Hospital-acquired infections (HAIs) remain a major global concern, contributing significantly to increased morbidity, mortality, and healthcare costs. Among the causative pathogens, Escherichia coli (E. coli) is one of the most frequently isolated microorganisms, particularly in urinary tract infections (UTIs), bloodstream infections, and surgical site infections. Early and accurate prediction of E. coli infection in hospitalized patients remains a significant clinical challenge, yet it has the potential to substantially improve patient outcomes. In addition, identifying patient-related risk factors can support targeted infection control strategies. This study aims to evaluate a no-code machine learning (ML) approach for early prediction of E. coli infection and to identify associated risk factors. ML techniques provide a powerful alternative by enabling the analysis of high-dimensional and heterogeneous datasets, facilitating the discovery of hidden patterns and supporting individualized risk prediction. In this study, a total of 300 clinical samples was collected as a training dataset from hospitalized patients between July 2024 and February 2025 across multiple units of Zagazig University Hospital, Sharkia, Egypt. An independent internal validation dataset of 100 samples was collected during May 2026 from the same hospital, its purpose was to evaluate model generalizability on completely unseen data. Bacterial isolates were identified using standard biochemical methods. Data analysis was performed using the Orange visual programming platform, implementing a modular ML pipeline that integrates data preprocessing, feature handling, model training, and performance evaluation within a no-code environment. The Naive Bayes model, shows potential for predicting E. coli infection in hospitalized patients. The model is intended to predict E. coli infection at the time of specimen collection, before culture results are finalized, depending on clinical data. However, further validation in larger, multi-center prospective cohorts is needed before clinical implementation.