Citations

Abstract Purpose We evaluated healthcare resource utilization (HCRU) and costs in patients with eosinophilic granulomatosis with polyangiitis (EGPA). Methods Patients with newly diagnosed EGPA (2017–2021), ≥12 months’ pre-diagnosis health plan enrollment, and ≥1 inpatient or ≥2 outpatient claims with an EGPA diagnosis were included. Follow-up was from EGPA diagnosis until disenrollment or database end. HCRU and health insurer payment costs during follow-up were compared with those for matched cohorts of general insured patients without EGPA (comparison A) and without EGPA but with severe uncontrolled asthma (SUA; comparison B). Results In comparison A, all-cause HCRU was higher in the EGPA cohort (n = 213) versus matched patients (n = 779) for all clinical encounters/pharmacy claim types; annualized, mean total all-cause costs were 16-fold higher ($117,563/patient) versus matched patients ($7,520/patient). In comparison B, all-cause HCRU was higher for the EGPA cohort (n = 182) versus the matched SUA cohort (n = 640) for all clinical encounters/pharmacy claim types, with 5-fold higher mean total all-cause costs ($118,127/patient vs $22,286/patient). In both EGPA cohorts, HCRU and associated costs increased between the baseline and follow-up periods. Conclusions These findings highlight the need for more effective treatments to reduce the clinical and economic burden of EGPA.

INTRODUCTION: Nosocomial infections (NIs) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have failed to identify high-risk patients. We aimed to develop machine learning (ML) models to predict NI. METHODS: The CLEARED consortium consists of prospectively enrolled cirrhosis inpatients from >120 centers. Using day-of-admission clinical data, 3 ML approaches (random forest [RF], extreme gradient boosting, and neural networks [NNs]) were used to predict NI. Data were split 80:20 for training and testing stratified by the outcome. Models were compared using area under the receiver operating characteristic curve (AUC). RESULTS: In total, 8,263 patients (55.90 ± 13.34 years; 64.1% men) from 127 centers in 37 countries were included. NI developed in 869 (10.5%), a median of 6 (4–11) days of postadmission. Major NIs were respiratory (29.6%) and urinary tract infection (15.7%), and spontaneous bacterial peritonitis (13.5%). NIs occurred more frequently in patients from low/low-middle income countries and those with severe liver disease, alcohol etiology, and admission infections. NIs were associated with inpatient mortality (31.9% vs 8.1%, P < 0.001) and liver transplantation (4.8% vs 1.9%, P < 0.001). Although the RF model (AUC 0.69) showed good calibration (Brier score 0.09), outperforming extreme gradient boosting, neural network, and LR models (AUC 0.66 for all; LR comparison P = 0.043), no model achieved AUC ≥0.80 for clinical utility. At 10% predicted probability threshold, the RF model demonstrated only 75.4% sensitivity, 52.9% specificity, and 15.9% positive predictive value (PPV). DISCUSSION: NIs cannot be accurately predicted from day-of-admission data using ML models, even in a large, prospective, global cirrhosis cohort. Every hospitalized patient with cirrhosis should receive protocolized infection control measures.

Abstract Aims Heart failure is prevalent; however, there is no cost-effective screening option. Against formal echocardiography, we assessed the diagnostic performance of focused cardiac ultrasound (FoCUS), performed by novice users guided and interpreted by artificial intelligence (AI) for the assessment of left ventricular ejection fraction (LVEF). Methods and results We prospectively enrolled 496 adults referred for diagnostic echocardiography. Novice operators (without clinical or imaging experience) underwent a 4-h imaging workshop, then performed FoCUS using a point-of-care device (Philips Lumify) utilizing real-time AI-image guidance (UltraSight). Images were assessed by AI-image interpretation software (Mayo Clinic), and two expert blinded echocardiologists. Median age was 67, 39% female, and body mass index range 17–56 kg/m2. Forty-one subjects (8.3%) exhibited moderate or greater LV dilatation and 28 (5.6%) had LVEF &lt;40%. The median scan time was 4 min (IQR 3–5). Adequate views were achieved in 95.0% and 97.4% of subjects for AI interpretation and expert analysis, respectively. A two-step diagnostic screening process for low EF in which only abnormal AI reads or uninterpretable scans were reviewed by experts (15.1%) had a sensitivity 96.2%, specificity 95.4%, PPV 54.3%, and NPV 99.8%. A subsequent prospective validation study of 344 subjects demonstrated similar results (sensitivity 100%, specificity 99.4%). Conclusion In this early feasibility investigation, AI-guidance technology embedded on a handheld device, enabled novice users without clinical or imaging experience to acquire sufficient quality images to accurately assess LVEF with minimal training. The technology evaluated in this study may hold promise for AI-guidance and interpretation to facilitate low-cost screening for cardiac dysfunction.

ABSTRACT In 2018, the International Niemann‐Pick Disease Alliance (INPDA) and the International Niemann‐Pick Disease Registry (INPDR) developed and published comprehensive clinical management guidelines to support inclusive and standardized care pathways in Niemann‐Pick disease type C (NPC)—an ultra‐rare, autosomal recessive, neurovisceral lysosomal disorder. Since then, advances in diagnostics, care, and the approval of two novel disease‐modifying agents have underscored the need to revise these guidelines to ensure safe, consistent, and high‐quality care for those affected by NPC. In response, the INPDA and INPDR convened a multidisciplinary Guidelines Development Group (GDG) comprising individuals with NPC expertise from 14 countries across five continents, representing a broad range of specialties, as well as patients and families involved in NPC care. Informed by a comprehensive literature review and two meetings, the GDG systematically reviewed, revised, and updated the 2018 guideline statements, re‐evaluating the level of evidence, strength of recommendations, and expert agreement for each. The resulting 2025 consensus clinical management guidelines constitute a timely, up‐to‐date, and internationally applicable resource for the diagnosis, treatment, and holistic management of individuals with NPC. These guidelines serve as a critical resource for specialist centers, hospital‐based medical teams, staff involved in NPC patient care, family physicians and other primary caregivers, and, importantly, patients and their families.

BACKGROUND: Radiofrequency (RF) ablation of premature ventricular complexes (PVCs) originating from the left ventricular summit may be unsuccessful, highlighting the need for alternative approaches. We aimed to assess the efficacy and safety of a novel dual-modality focal catheter in treating left ventricular summit PVCs in patients who had failed previous RF ablation. METHODS: Patients were prospectively enrolled and underwent a redo ablation procedure using an irrigated, contact-force sensing, dual-modality focal catheter (TactiFlex Duo, Abbott) under compassionate use indication. The ablation strategy, including the choice of energy modality (monopolar pulsed field [PF], RF, or both), was left to the operator’s discretion. Safety assessments included serial biomarkers, renal function, and CMR within 36 hours. Efficacy was defined as ≥80% reduction in PVC burden with symptom resolution at 3-month follow-up. RESULTS: Six consecutive patients (4 men; mean age, 53.8±15 years) with symptomatic left ventricular summit PVCs and a prior failed RF ablation (range, 1–2) were prospectively enrolled. All PVCs had an inferior axis, with a left bundle V1 morphology observed in 4 of 6 cases (mean burden, 30.1±5.3%). Acute suppression of PVCs was achieved in all cases. Acute suppression with a single PF application in the great cardiac vein-anterior interventricular vein occurred in 2 patients, while 3 patients required additional RF, PF, or combined RF+PF applications at adjacent sites. One patient with an inaccessible great cardiac vein-anterior interventricular vein was successfully treated in the left ventricular outflow tract with RF+PF application. Transient, reversible left anterior descending vasospasm was observed during PF delivery in 2 of 5 cases that underwent PF application adjacent to a coronary artery, despite pretreatment with intracoronary nitroglycerin without ECG or hemodynamic sequelae. All patients had durable suppression of PVCs at follow-up. CONCLUSIONS: In its first human application, dual-modality ablation was feasible and effective for refractory left ventricular summit PVCs. Transient coronary vasospasm occurred, though it was reversible and without acute clinical consequences.

Objective Meaningful assessments of how large language models (LLMs) incorporate clinical guidelines require large-scale testing over many queries. Here, we evaluate the prevalence of clinical guideline omissions and hallucinations in a large sample of diagnostic LLM outputs. Methods We used simulated case vignettes and zero-shot prompting to generate diagnostic outputs and rationales from GPT-4.1 and DeepSeek-V3. English case vignettes were created for hypercholesterolaemia and type-2 diabetes mellitus. Each vignette contained identical medical information, while sociodemographic characteristics varied in terms of sex, ethnicity and location. We calculated the prevalence of existing and hallucinated clinical guidelines in LLM outputs across disease, LLM and sociodemographic characteristics. Results We analysed a total of 12 197 LLM outputs, which quantifies three hazard areas: omissions (up to 97% for DeepSeek-V3 and 46% for GPT-4.1), hallucinations (up to 9%) and inconsistencies (guideline citation rate ranging from 0% to 78.39% across sociodemographic vignettes). Omission and hallucination rates were generally similar across vignettes with different sex or ethnicity data, yet were particularly sensitive to patient location. Discussion This study highlights significant variability in clinical guideline prediction across two different diseases, three different sociodemographic variables and two LLMs, even when the LLMs were instructed by identical prompts, establishing clinical guideline prediction in LLM outputs as a stochastic event. Conclusion The stochastic nature of LLMs creates a unique challenge for evidence generation and clinical deployment. Being able to measure and capture this stochasticity within high-quality research designs will be a prerequisite to advancing the responsible deployment of LLMs in healthcare.

Importance Accurate prediction of patient mortality after kidney transplant is an unmet need. Objective To develop and validate an integrative prediction model that predicts short- and long-term patient mortality for kidney recipients. Design, Setting, and Participants This international cohort study included patients who underwent transplants between 2004 and 2023 from 14 academic medical centers from Europe and the US. The derivation cohort consisted of 1566 consecutive adult kidney recipients in a deeply phenotyped cohort prospectively recruited in 1 French center between 2004 and 2014. External validation cohorts consisted of 10 951 kidney recipients from 7 centers in France, 3 centers in Europe, and 3 centers in North America who underwent kidney transplants between 2006 and 2023. Data were analyzed from January 2023 to June 2025. Main Outcome and Measures All-cause mortality was assessed, and 121 candidate prognostic factors, comprising demographics and clinical, biological, imaging, and immunological parameters, were collected. Results Among 12 517 kidney transplant recipients, including 1566 in the derivation cohort (mean [SD] age, 50.05 [14.31] years; 942 male [60.15%]) and 10 951 in validation cohorts (mean [SD] age, 53.32 [13.97] years; 6766 male [61.78%]), 2486 patients (19.9%) died after a median (IQR) follow-up of 5.08 (2.97-7.00) years. Fourteen prognostic factors (including clinical, biological, and imaging risk factors) were independently associated with patient death (eg, patient age: hazard ratio per 1-year increase in age, 1.07 [95% CI, 1.06-1.08]; P &amp;lt; .001) and were combined into a risk prediction model (mBox). The model exhibited accurate calibration and discrimination in the derivation cohort, with C statistics of 0.82 (95% CI, 0.77-0.87) and 0.80 (95% CI, 0.78-0.82) at 1 and 10 years, respectively, after the transplant. Abbreviated models were developed and validated to ensure model generalizability. Performance of abbreviated models was confirmed in external validation cohorts from France (C statistic, 0.76 [95% CI, 0.73-0.78]), Europe (C statistic, 0.74 [95% CI, 0.72-0.76]), the US (C statistic, 0.74 [95% CI, 0.70-0.78]), the Greater Paris University Hospital database (C statistic, 0.79 [95% CI, 0.77-0.81]), and the University of California at San Francisco database (C statistic, 0.70 [95% CI, 0.65-0.74]). The model was also validated in a series of subpopulations (eg, women vs men: C statistic, 0.81 [95% CI, 0.77-0.84] vs 0.79 [95% CI, 0.77-0.82]) and clinical scenarios (eg, before COVID-19 era: C statistic, 0.79 [95% CI, 0.77-0.81]) with good and stable performance. Conclusions and Relevance In this study, an accurate prediction model for mortality among kidney recipients, computable at the time of transplant, was developed and externally validated. Results suggest that this model may help stratify patient risk of death, allowing for improved medical decisions.

Abstract Purpose: Neurocognitive and endocrine dysfunction are potential complications of cranial irradiation. However, risk factors are poorly understood, impeding accurate prognostication and exploration of potential preventive interventions. The objective of this study was to evaluate the prognostic value of various vascular and genotypic risk factors for the development of radiation-related toxicities. Methods: This single-institution retrospective cohort study included patients with metastatic and malignant primary brain tumors who received cranial irradiation as part of their initial tumor-directed therapy. Demographic and treatment characteristics were collected, as well as putative vascular and genotypic risk factors. Univariate, multivariate, and machine-learning analyses were performed using five pre-specified measures of radiation-related toxicity. The primary outcome was change in mini-mental status exam (MMSE). Results: Eighty patients (53% male, mean age 55.7, 53% primary and 44% metastatic brain tumors) were included. Elevated homocysteine and ApOE4genotype were the strongest predictors of MMSE decline in the multivariate model (OR 3.96 [6.5-200, p<0.001 and 2.85 [1.92-27.6], p=0.004). Elevated homocysteine was associated white matter change on MRI and both physician and patient assessment. ApoE4allele was associated with new endocrine deficiency, and physician assessment. An online nomogram provides risk predictions for each of the five late toxicity outcomes: (https://afranklin22.shinyapps.io/PRMMSERadiationRiskFactors/) Conclusion: Two pre-treatment laboratory values (elevated homocysteine and ApOE genotype) were strongly associated with post-radiation neurocognitive and endocrine dysfunction using a variety of simple but clinically meaningful definitions of dysfunction. Our predictive algorithm can aid clinicians in stratifying baseline risk and should be validated in prospective trials.

Abstract Pancreatic cancer disproportionately affects Black individuals in the United States, but they have limited representation in genetic studies of pancreatic ductal adenocarcinoma (PDAC). To address this gap, we performed admixture mapping and genome-wide association analysis (GWAS) in genetically inferred African ancestry individuals (1,030 cases and 889 controls). Admixture mapping identified three regions with a significantly higher proportion of African ancestry in cases compared to controls (5q33.3, 10p1, 22q12.3). GWAS identified a genome-wide significant association at 5p15.33 ( CLPTM1L , rs383009:T>C, T Allele Frequency=0.51, OR:1.45, P value=1.24×10 -8 ), a locus previously associated with PDAC. Known loci at 5p15.33, 7q32.3, 8q24.21 and 7q25.1 also replicated (P value <0.01). Multi-ancestral fine-mapping identified two potential causal SNPs (rs3830069 and rs2735940) at 5p15.33. Collectively these findings identified novel PDAC risk loci and expanded our understanding of this deadly cancer in underrepresented populations, emphasizing the multifactorial nature of PDAC risk including inherited genetic and non-genetic factors. Statement of Significance To understand how genetic variation contributes to PDAC risk in Black people in North American, we studied individuals of genetically-inferred African ancestry. We identified novel risk loci and differences in the contribution of known loci. This demonstrates that ancestry-informed genetic analyses improve our understanding of PDAC risk and enhances discovery.

BACKGROUND AND OBJECTIVES: Perioperative protocols facilitate earlier discharge without compromising safety in nonfunctioning pituitary adenomas, but no large multicenter studies in the United States have investigated protocols regarding Cushing disease (CD). We sought to characterize perioperative protocols and how their implementation influences clinical outcomes in patients with CD. METHODS: A retrospective analysis was conducted using data from the Registry of Adenomas of the Pituitary and Related Disorders consortium comprising 13 US academic pituitary centers. Institutions were surveyed regarding perioperative procedures for patients undergoing transsphenoidal tumor resection for CD. The impacts of institutional procedures and approaches to implementation on length of stay (LOS) and unplanned 90-day readmission were evaluated. RESULTS: Thirteen institutions contributed survey responses and clinical data for a total of 832 patients meeting inclusion criteria. Ten (76.9%) institutions reported having a postoperative protocol, 9 (69.2%) used a formal document to outline their protocol, and 3 (23.1%) had protocols implemented into hospital policy. Mean LOS was significantly reduced in centers with an established protocol (3.14 vs 3.42 days, P = .032), and more so with a formal document (3.10 vs 3.48 days, P = .001) or hospital policy (2.72 vs 3.36 days, P < .001). Patients treated after protocol implementation experienced shorter LOS ( P < .001). Other factors associated with reduced LOS were presence of a separate CD pathway, intraoperative checklist specific to pituitary surgery, non-narcotic pain regimen, Foley removal order, dedicated outpatient advanced practice provider follow-up, and target discharge date ≤2 days. Intraoperative checklist ( P = .045), non-narcotic pain regimen ( P = .048), nasal packing ( P = .005), and 1-day target discharge date ( P = .032) were important factors against readmission. Compared with microscopic surgery, endoscopic surgery was associated with shorter LOS but increased readmission odds. CONCLUSION: This is the first multicenter study to illustrate that implementation of perioperative protocols is associated with a reduction in LOS and readmission risk in patients with CD.