Citations

INTRODUCTION: The American College of Gastroenterology assembled a multidisciplinary task force to evaluate the current state and future direction of artificial intelligence (AI) in gastroenterology, hepatology, and endoscopy leading to the development of consensus-based recommendations for responsible AI integration in clinical practice. METHODS: A total of 32 subject-matter experts and 12 industry partners, representing diverse practice settings and expertise, conducted subgroup literature reviews across 5 key areas (endoscopy, practice management clinical applications, training and education, inflammatory bowel disease and liver disease, ethics and equity). Draft statements were developed and rated on a 5-point Likert scale using a modified Delphi process. A consensus was set at ≥70% combined agreement. Nonconsensus items were revised and revoted electronically. RESULTS: A total of 43 statements, 40 (93%) reached consensus in round 1 and the remaining 3 achieved consensus after round 2. Evidence supports computer-aided detection improving adenoma detection rate and miss rate in controlled studies, with mixed real-world impact and insufficient long-term outcomes (e.g., interval colon cancer rate). Recommendations emphasize thorough validation and reduction of bias by heterogeneous Data sets. Outside endoscopy, ambient AI scribes, natural language processing (NLP)-enabled coding, workflow optimization, and previous authorization support show potential. Training recommendations endorse a structured AI curriculum while preserving independent procedural competence to avoid deskilling. In inflammatory bowel disease and hepatology, AI could help improve diagnostic accuracy, help predict risk of disease progression, and help guide therapy. Equity, governance, and reimbursement statements call for chain-of-custody data protections, specialty-society oversight, and payment models that reward quality and cost reduction. DISCUSSION: This consensus outlines how AI can augment rather than replace clinical expertise while promoting safety, transparency, interoperability, and equity. Priorities include pragmatic and prospective trials, multi-institutional data-sharing consortia, bias mitigation, and workforce training to enable trustworthy and clinically impactful AI adoption in gastroenterology, liver, and endoscopy care.

ABSTRACT Objectives While maxillary sinus fungal balls (MSFB) can be associated with odontogenic conditions (MSFBO), MSFBO clinical and dental features have not been compared to odontogenic sinusitis (ODS). This multicenter study aimed to compare characteristics of MSFB, MSFBO, and ODS. Methods A multicenter international retrospective cohort study was conducted on adults with MSFBs and ODS who underwent sinus surgery. First in MSFBs, it was determined whether different dental conditions were more likely in FB versus non‐FB sides. Second, clinical features and dental pathologies were compared between MSFBO and ODS. For analyses, dental conditions were considered individually and as two groups: infectious pathologies and dental/oral procedures with indwelling metallic materials. Results After exclusions, there were 203 MSFBs and 163 ODS. Among MSFBs, 141 were MSFBOs. FB sides were associated with sinus protrusion of root canal treatment (RCT) materials ( p = 0.040) and dental implants ( p = 0.040). Compared to MSFBO, ODS patients were younger, more likely to have MS purulence (OR = 40.9, p < 0.010), more likely associated with apical periodontitis (OR = 2.59, p = 0.010) and oroantral fistulas (OR = 6.94, p = 0.020), and less likely associated with extruded RCT materials (OR = 0.01, p = 0.010) and protruded midface screws (OR < 0.01, p = 0.010). Comparing purulent MSFBO and ODS, ODS was more associated with infectious dental pathologies ( p < 0.009). Conclusion Compared to MSFBs, MSFBOs were associated with RCT extrusion and implant protrusion. Compared to MSFBOs, ODS was more likely purulent and associated with infectious dental pathologies. While ODS is often distinct from MSFBO, the two conditions can coexist, and surgeons must determine whether patients have infectious dental pathology requiring treatment with both conditions. Level of Evidence 4.

Abstract Background Native vertebral osteomyelitis (NVO) is a life-threatening spinal infection with rising incidence and significant morbidity. Despite its growing burden, long-term data on clinical characteristics, management trends, and outcomes remain limited. Methods We conducted a 26-year multicenter retrospective cohort study of adults (≥18 years) diagnosed with NVO at Mayo Clinic sites between 1999 and 2024. Demographic, microbiologic, treatment, and outcome data were analyzed across five time periods. Predictors of treatment failure were assessed using a multivariable competing risk model. Results Among 1255 patients (median age 67; 66% male), lumbosacral involvement was most common (65%), and 21% had multilevel involvement. Pathogens were identified in 77%, most commonly Staphylococcus aureus (49%; Methicillin-susceptible S. aureus 37%, methicillin-resistant S. aureus 13%). Over time from 1999–2004 to 2020–2024, Gram-negative bacilli increased from 6% to 14% (P = .048). Comorbidities including chronic kidney disease (10% to 21%), active chemotherapy (6% to 11%), and immunosuppression (8% to 17%) increased significantly. Additionally, 1-year treatment failure declined (16% to 10%). In multivariable analysis, diabetes mellitus (subdistribution hazard ratio [sHR] 1.92, 95% CI 1.18–3.13) and multilevel involvement (sHR 1.67, 95% CI 1.17–2.38) were associated with increased incidence of treatment failure, while concurrent infections (sHR 0.57, 95% CI 0.37–0.87) and higher Charlson Comorbidity Index (sHR 0.62, 95% CI 0.43–0.90) were associated with lower failure. Conclusions This large multicenter cohort highlights increasing host complexity, shifting microbiology, and predictors of failure, emphasizing the importance of early risk stratification and tailored strategies, such as multidisciplinary evaluation and close follow-up of high-risk patients to improve outcomes.

Chronic traumatic encephalopathy (CTE) is a neurodegenerative disease associated with exposure to repetitive head impacts (RHIs), characterized by tau tangles around small blood vessels at the depths of the sulci. Currently, CTE can be diagnosed only postmortem , but can present with an array of cognitive, behavioral, mood, and motor symptoms. However, traumatic brain injury is also associated with increased risk of Alzheimer’s disease (AD) and may lead to comorbid neuropathology. Characterization of the in vivo biomarkers of CTE is a necessary next step to facilitate accurate diagnoses. We examined the profile of cerebrospinal fluid (CSF) biomarkers of amyloid-β, total tau (tTau), and phospho-tau (pTau) in a cohort of former professional (PRO, n = 100) and college (COL, n = 40) football players at high risk of CTE compared to asymptomatic unexposed controls (UE, n = 43). CSF was collected under controlled conditions using collection, processing, and cryostorage kits provided by the DIAGNOSE CTE Research Project Biomarker Core, and concentrations of Aβ 40 , Aβ 42 , tTau, and pTau (pTau 181 , pTau 217 , pTau 231 ) were measured at the University of Gothenburg, Sweden, using immunoassays. Associations between CSF biomarker levels with football history, and diagnosis of traumatic encephalopathy syndrome (TES) were examined using linear regression, and corrected for age, education, APOE -ε4 allele status, race, and body mass index. Our analysis revealed that football exposure affected both CSF Aβ 40 ( p = 0.039) and Aβ 42 ( p = 0.038), particularly among those under 60 years of age in the PRO compared to the UE exposure group. Among former football players, estimates of RHI exposure were not generally associated with CSF Aβ, tTau, and pTau biomarker levels. CSF Aβ 40 ( p = 0.0041) and Aβ 42 ( p = 0.011) were lower in former football players with TES diagnosis compared to unexposed participants, although CSF Aβ, tTau, and pTau biomarker levels did not differ between former players with and without a TES diagnosis. Among former football players, reduced CSF Aβ 40 ( p = 0.011) and Aβ 42 (p = 6e-04) were observed in those with cognitive impairment compared to those with neurobehavioral dysregulation. The findings of significant associations of reduced CSF Aβ levels with RHI in elite football players are in line with recent postmortem studies; however, the lack of relationship with CSF tTau and pTau species observed to be altered in the setting of AD suggests that the pathological features of CTE reflected in fluid biomarkers are complex and require further study. The overlapping comorbid age-dependent features of neurodegeneration that occur in those at risk for CTE suggest that tau pathology in CTE is not reliably reflected by currently available fluid biomarkers and that the use of multiple biomarkers related to the compound characteristics of CTE may be required for early detection.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Background In pediatric patients presenting after blunt trauma, the incidence of clinically significant cervical spine injury (CSI) is approximately 1%. Although multidetector CT (MDCT) is widely accepted for cervical spine clearance in adults, its utility in children remains uncertain. The purpose of this study is to evaluate the sensitivity of MDCT in identifying clinically significant CSI in pediatric patients, stratified by age groups: adolescents (12 years to 17 years) and children (0 years to 11 years). Methods We designed a national, multicenter, prospective observational study to assess the diagnostic performance of MDCT in detecting clinically significant CSI in pediatric trauma patients. Data are being collected from participating centers on imaging findings, clinical outcomes, and the presence of confirmed CSIs after blunt trauma. The analysis plan includes stratification by age group and calculation of sensitivity, specificity, and predictive values of MDCT for CSI. Results This abstract outlines the background, methodology, and analytical framework of the study. Data collection and analysis are ongoing. This study represents the largest known cohort of pediatric patients undergoing cervical spine imaging after blunt trauma and is the first prospective study of its kind focused exclusively on this population. Conclusions This study will provide critical data to inform guidelines for pediatric cervical spine clearance after blunt trauma. By evaluating the sensitivity of MDCT in detecting clinically significant CSI, the findings aim to support evidence-based imaging strategies and improve the safety and efficiency of pediatric trauma care.

Purpose This study assessed the association between holding an additional graduate degree beyond a Doctor of Medicine (MD) or Doctor of Osteopathic Medicine (DO) and residency match outcomes. Specifically, the authors examined graduate degree attainment trends among residency applicants and evaluated whether graduate degree holders experience lower match rates than non-holders. Methods A retrospective, observational analysis was conducted using publicly available data from the National Resident Matching Program's Charting Outcomes in the Match reports (2016-2024). The 10 specialties with the highest applicant volumes were analyzed, encompassing 80 136 matched and 6820 unmatched U.S. MD and DO senior applicants. Trends in graduate degree attainment were evaluated using linear regression models. Match rates were stratified by graduate degree status and compared using two-proportion z-tests based on aggregated matched and unmatched counts for each specialty and overall. Results From 2016 to 2024, the proportion of graduate degree holders entering the match increased significantly for MD (15.77% to 18.29%, P = .0008) and DO (19.93% to 23.31%, P = .0151) applicants. Across all 10 specialties, graduate degree holders matched at lower rates than non-holders. Among MD applicants, graduate degree holders matched at 92.57% compared with 94.12% for non-graduates (P < .0001), with specialty-specific differences ranging from 0.22% in Psychiatry to 4.61% in Anesthesiology; five specialties demonstrated statistically significant disparities. Among DO applicants, graduate degree holders matched at 84.54% compared with 88.64% for non-graduates (P < .0001), with specialty-specific differences ranging from 1.44% in Family Medicine to 10.48% in Obstetrics and Gynecology; five specialties also reached statistical significance. Conclusions The proportion of graduate degree holders in the residency match is increasing, and these applicants experience lower match rates than non-holders. These findings challenge the assumption that additional graduate education provides a competitive advantage and underscore the need for further research into the applicant-level factors contributing to these disparities.

Key Points Data were collected from a cohort of 759 patients with autosomal dominant polycystic kidney disease that were followed for a median of 10.2 years. Prognostic models were developed to predict kidney failure using routinely obtained clinical information and externally validated. Risk predictions had good discrimination and calibration over a time horizon of 15 years. Background Autosomal dominant polycystic kidney disease (ADPKD) is a common cause of kidney failure. Progression is highly variable, and accurate prognostic information is needed to guide early treatment decisions. The objective of this study was to develop a multivariable predictive model for progression to kidney failure. Methods We developed prognostic models using Cox regression for the outcome of kidney failure, defined as eGFR <15 ml/min per 1.73 m 2 , dialysis, or kidney transplantation. The development dataset consisted of participants in the Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease (CRISP) and Halt Progression of Polycystic Kidney Disease study A (HALT-A) studies. The validation dataset consisted of patients with ADPKD in the Mayo clinical registry aged 15–49 years, with eGFR ≥60 ml/min per 1.73 m 2 . Predictor variables in the base model were age, sex, creatinine or eGFR, ADPKD genotype, and Mayo Imaging Class. Clinical and laboratory data were evaluated in the full model. Results The development cohort included 759 patients with baseline eGFR of 91±29 ml/min per 1.73 m 2 (mean±SD), of whom 16% reached end point after median (interquartile range) follow-up of 10.2 (5.5–16.7) years. The validation cohort included 535 patients with baseline eGFR of 90±31 ml/min per 1.73 m 2 (mean±SD), of whom 11% reached end point after median (interquartile range) follow-up of 5.5 (1.5–13.7) years. The full model, including age, sex, serum creatinine, Mayo Imaging Class, total carbon dioxide, hemoglobin, diastolic BP, and body mass index, had a C-index of 0.81 (95% confidence interval, 0.72 to 0.90) in the validation cohort and 0.75 (95% confidence interval, 0.62 to 0.88) when ADPKD genotype was also included. Risk predictions from base and full models were well-calibrated out to 15 years. Conclusions In persons with early ADPKD and preserved eGFR, a model using routinely obtained clinical information quantified risk of kidney failure over 15 years.