Citations

ABSTRACT Background Delirium affects up to one‐third of hospitalized older adults and is associated with adverse outcomes. Despite its clinical importance and the availability of validated screening tools, current care gaps extend beyond under‐recognition to inconsistent risk stratification, workforce constraints, documentation burden, fragmented intervention delivery, and practical challenges with monitoring of response. We review how artificial intelligence (AI) could bridge these gaps and distinguish model development and validation, real‐world clinical implementation, and emerging concepts in delirium care. Results Prediction models leveraging multimodal health record data, including structured variables and unstructured clinical notes, report good discrimination for delirium risk stratification, but only a few models have been integrated into clinical practice. A live multimodal machine learning model increased targeted delirium detection, yet a pre‐post comparative study found a longer length of stay; improved recognition alone therefore does not equate with improved outcomes. Natural language processing, large language models, computer vision, ambient sensing, and wearable technologies enable more continuous, objective, and less labor‐intensive assessment compared with traditional screening methods, but evidence remains limited with concerns about false positives and generalizability. AI‐supported delirium management through reinforcement learning and digital twins is currently largely conceptual. Responsible AI adoption requires a clearly defined intended use, external validation, action pathways, equitable performance, privacy and security, consent and transparency, clinician oversight, patient preferences, and post‐deployment monitoring. Conclusion AI is most defensible as an adjunct that connects evidence‐based delirium care to reliable execution rather than as a replacement for clinical assessment. Prospective comparative studies should evaluate patient outcomes, resource use, and balancing measures.

Abstract Purpose Large language models (LLMs) have proven performance for certain diagnostic tasks; however, limited studies have evaluated their consistency in recommending appropriate medication regimens for a given diagnosis. Medication management is a complex task that requires synthesis of drug formulation and complete order instructions for safe use. Here, the performance of GPT-4o, an LLM available with OpenAI’s ChatGPT, was tested on 3 medication management tasks. Methods GPT-4o performance was tested on 3 medication tasks: identifying available formulations for a given generic drug name, identifying drug-drug interactions (DDIs) for a given medication regimen, and preparing a medication order for a given generic drug name. For each experiment, the model’s raw text response was captured exactly as returned and evaluated using clinician evaluation in addition to standard LLM metrics, including Term Frequency-Inverse Document Frequency (TF-IDF) vectors, normalized Levenshtein similarity, and Recall-Oriented Understudy for Gisting Evaluation (ROUGE-1/ROUGE-L) F1 score between each response and its reference string. Results For the first task of drug-formulation matching, GPT-4o had 49% accuracy for generic medications being matched to all available formulations, with an average of 1.23 omissions per medication and 1.14 hallucinations per medication. For the second task of drug-drug interaction identification, the accuracy was 54.7% for identifying the DDI pair. For the third task, GPT-4o generated order sentences containing no medication or abbreviation errors in 65.8% of the cases. Conclusion Model performance for basic medication tasks was consistently poor. This evaluation highlights the need for domain-specific training through clinician-annotated datasets and a comprehensive evaluation framework for benchmarking performance.

Abstract Objective To assess the efficacy and safety of fenfluramine in patients with Dravet syndrome (DS) stratified by age, number of previously attempted antiseizure medications (ASMs), and SCN1A pathogenic variant status. Methods In this post hoc analysis, data from three randomized controlled trials (RCTs) in patients with DS (2–18 years) were pooled and stratified by age (<4; ≥4 years), number of previous ASMs (1–3; 4–6; ≥7), and SCN1A pathogenic variant status ( SCN1A +; SCN1A −). Stratified groups were assessed and compared with the pooled placebo group (change in monthly convulsive seizure frequency [MCSF], longest convulsive seizure‐free interval, and Clinical Global Impression–Improvement [CGI–I] scale scores rated by parents/caregivers and investigators), and safety (treatment‐emergent adverse events [TEAEs]: frequency, days to onset, and proportion resolved). Results Among 348 patients included in the RCTs, 216 were randomized to fenfluramine (0.7 mg/kg/day, n = 88; 0.4 mg/kg/day [with stiripentol], n = 43; 0.2 mg/kg/day, n = 85) and 132 to placebo. Compared with placebo, fenfluramine treatment (all doses combined) resulted in greater MCSF reductions, greater increases in longest convulsive seizure‐free intervals, and a higher proportion of parents/caregivers and investigators reporting clinically meaningful improvement (“Much Improved”, “Very Much Improved”) on CGI–I scores across all stratified groups. CGI–I scores were consistent across fenfluramine doses in most stratified groups, but patients with the fewest number of previous ASMs had the greatest frequency of clinically meaningful improvement on investigator‐rated CGI–I scores. Safety outcomes were similar across all strata. Most TEAEs resolved by end‐of‐study. Significance Fenfluramine treatment was associated with improved seizure outcomes and global functioning compared with placebo regardless of age, number of previous ASMs, and SCN1A status in patients with DS. Fenfluramine was well‐tolerated; no new safety signals were identified. Further studies with larger sample sizes (including adults) and a priori inferential analyses of stratified groups are warranted. Plain Language Summary Patients with Dravet syndrome struggle with seizures and everyday life. In three studies, patients aged 2–18 years received fenfluramine or placebo (sugar pill). Fenfluramine lowered seizures without many side effects. Researchers combined results from these studies to see how fenfluramine worked in different patient groups based on age, number of previous medications, and a gene called SCN1A . They looked at seizure reduction and whether doctors felt patients had improved. In all groups, fenfluramine worked better than placebo, with similar side effects. Researchers believe fenfluramine helped these patients, but some groups were small, so these results need to be confirmed.

Primary mediastinal B-cell lymphoma (PMBCL) is a rare form of large B-cell lymphoma (LBCL) with around 90% of patients cured with frontline treatment. For relapsed or refractory (R/R) disease, the optimal treatment is unclear. CD19 chimeric antigen receptor-T cell (CAR-T) has been established as the preferred second line (2L) treatment for primary refractory or early relapsing LBCL based on the overall survival benefits observed in the landmark phase III trials. However, PMBCL patients were underrepresented on these pivotal studies. This study evaluated outcomes of 252 patients treated with 2L therapies for R/R PMBCL at 14 US institutions between 2001 and 2025. Platinum-based salvage with intent to proceed to high dose therapy and autologous stem cell transplant (HDT/ASCT) (platinum cohort) and CD19 CAR-T (CAR-T cohort) were given as 2L therapy in the real-world setting in 157 and 26 patients, respectively. Overall response rate (ORR), complete response (CR) rate and median progression-free survival (PFS) were significantly higher in the CAR-T cohort compared with the platinum cohort (ORR: 91.3% vs 44.2%, p &lt;0.001; CR 65.2% vs 14.7%, p&lt;0.001; median PFS not reached vs 3.5 months, hazard ratio (HR) 0.28, 95% CI 0.15-0.54, p=0.001). No significant difference was observed in overall survival. This study demonstrated superior response rate and PFS of CD19 CAR-T over platinum-based salvage with intent to proceed to HDT/ASCT as 2L treatment for R/R PMBCL.

Abstract Objective Surgery is an effective, yet underutilized treatment for children with drug‐resistant epilepsy. Although predictors of surgical outcomes are well described, the decision to recommend surgery varies by institution. We aim to evaluate the rates of not recommending surgery, identify associated patient characteristics, and quantify variability across centers. Methods We queried the Pediatric Epilepsy Research Consortium Surgery database, a prospective multicenter cohort of children (0–18 years) undergoing initial evaluation for epilepsy surgery. Patients with documented surgical decisions were included. Demographic, clinical, and presurgical evaluation variables were compared by surgical recommendation status. Logistic regression identified factors associated with not recommending surgery. Mixed‐effects models quantified between‐center variability. Results Among 2480 patients across 29 centers, 532 (21%) were not recommended epilepsy surgery (median center rate 17%, interquartile range [IQR] 10%–28%). After accounting for patient characteristics associated with surgical candidacy, substantial variation in decision‐making remained across centers, with a median twofold difference in the odds of not recommending surgery between otherwise similar patients evaluated at different institutions (Median Odds Ratio = 2.25; Intraclass Correlation Coefficient = .18). The clinical characteristics most strongly associated with not recommending surgery included monthly or less frequent seizures (odds ratio [OR] 2.17, 95% confidence interval [CI] 1.75–2.69), non‐structural etiology (OR 2.02, 95% CI 1.56–2.61), and taking ≤2 anti‐seizure medications (ASMs) (OR 1.67, 95% CI 1.34–2.08, all p 's < .01). These characteristics showed minimal clustering across centers (ICCs < .05). Significance One in five children evaluated for epilepsy surgery are not recommended to pursue surgical treatment. Although clinical factors influence decision‐making, they do not explain the substantial variation in recommendations across pediatric epilepsy centers. Similar children evaluated at different institutions had significant differences in the odds of not being recommended surgery, suggesting that institutional decision‐making contributes importantly to surgical candidacy.

Importance Pyoderma gangrenosum (PG) is a rare neutrophilic dermatosis characterized by sterile ulcerative skin lesions. Multiple comorbidities and clinical features have been associated with PG, but no standardized guidelines exist for classifying PG phenotypes. Objective To develop an expert-established classification framework for PG phenotypes to inform treatment guidelines and future research endeavors. Evidence Review In this modified Delphi consensus study that included 23 board-certified dermatologists and Medical Dermatology Society members with expertise in PG, panelists completed 5 rounds of anonymous, iterative online surveys that were administered from December 2023 through July 2025. Before the beginning of the consensus exercise, a literature review was performed by nonvoting researchers to summarize existing data on PG clinical associations and comorbidities. A PubMed search from inception to September 2023 identified observational studies, narrative reviews, systematic reviews, and meta-analyses describing PG clinical associations and comorbidities that were published in English. Experts indicated their agreement with proposed PG phenotypes and disease modifiers with a consensus threshold of 70% or greater. Anonymous comments and aggregated results were presented in each subsequent round. In the final round, a framework of PG phenotypes and disease modifiers was proposed for agreement. Findings Twenty-three board-certified dermatologists and Medical Dermatology Society members with expertise in PG completed 5 rounds of iterative surveys. Consensus was reached on the final set of PG phenotypes and disease modifiers, with 83% of experts in agreement. PG phenotypes were overall classified into 2 major groups: PG with autoinflammatory syndromes and nonsyndromic PG. Nonsyndromic PG included 4 phenotypes: inflammatory bowel disease–associated PG, PG in association with hematologic cancers and blood dyscrasias, drug-induced PG, and other (including idiopathic) PG. Disease modifiers of PG phenotype presentations included involvement of special sites (head/neck, genitals, or peristomal skin) and extracutaneous manifestations. Conclusions and Relevance This expert-established, descriptive framework provides a standardized classification system for distinct PG phenotypes and its modifiers. This nomenclature may inform upcoming clinical guidelines and allow for consistency in reporting epidemiological research and outcomes among patients with PG.

Abstract Objective Epilepsy duration is a modifiable risk factor in the outcome of definitive epilepsy surgery; however, an analogous effect in palliative procedures has not been shown. We reviewed the Pediatric Epilepsy Surgery Database data for an association between epilepsy duration and seizure reduction in palliative procedures. Methods Patients enrolled between January 2018 and April 2025 who underwent their first epilepsy surgery with palliative intent with 6 months of follow‐up were included. Procedures included neuromodulation, corpus callosotomy, hemispherotomy, lesionectomy, and lobectomy where surgical intent was not seizure freedom. Outcomes of seizure freedom, 90% seizure reduction, and 50% seizure reduction were considered at 6–12 months and >12 months from surgery. Duration from epilepsy onset to surgery was compared for patients above and below each outcome threshold at each time point. Logistic regression analysis for the association between epilepsy duration and seizure reduction adjusted for potential confounders including procedure type, etiology, and other clinical factors. Logistic regression analysis was performed on the overall cohort and subgroups of patients with each procedure. Results A total of 588 patients were included. Initial univariate analysis suggested that epilepsy duration at time of surgery was significantly associated with seizure freedom and 90% seizure reduction at both 6–12 months and >12 months. After adjusting for confounders, only seizure freedom at >12 months was significantly associated with duration of epilepsy. When individual procedures were considered, only lobectomy was sensitive to duration of epilepsy in multivariate analysis, with significant impacts on >50% and >90% seizure reduction at >12 months. Lesional epilepsy predicted seizure freedom at >12 months. Neuromodulation and corpus callosotomy were less likely to achieve seizure reduction than other procedures. Significance We did not find an association between early epilepsy surgery and seizure reduction. This reflects the heterogeneity of our population, including different types of surgical procedures and lesional and nonlesional epilepsies.

Abstract Background Complications such as intermittent pouchitis (IP) and chronic inflammatory disorders of the pouch (CP) are common after ileal pouch-anal anastomosis (IPAA), particularly among patients with both ulcerative colitis and primary sclerosing cholangitis (PSC). There are no standardized approaches for prophylaxis against these complications for patients with PSC undergoing IPAA. We compared outcomes among patients with PSC and IPAA who received antibiotic or immunosuppressive therapies to those who did not. Methods We designed a retrospective cohort study that included patients with ulcerative colitis and PSC from 7 tertiary care centers that underwent IPAA between 1994 and 2023. Patients were categorized on whether they received medications following IPAA that may provide primary prophylactic benefit, such as antibiotics, probiotics, immunomodulators, or biologic medications; and the proportion of patients developing IP and CP was evaluated. Results A total of 172 patients were included in the cohort, and 13 (7.6%) patients received antibiotics or immunosuppressant medications. Antibiotics and probiotics were the most common therapy (5 patients, 2.9%), followed by biologics, small-molecule inhibitors, immunomodulators, or mesalamine (all 1 patient, 0.6%). Compared to patients not receiving antibiotics or immunosuppression, patients receiving antibiotics or immunosuppression were significantly less likely to develop IP (69.2% vs 91.2%; P = .03; odds ratio 0.22; 95% CI, 0.06-0.80) and CP (23.1% vs 56.0%, P = 0.04; OR 0.24, 95% CI, 0.06-0.89). Conclusions In this retrospective cohort of patients with ulcerative colitis and PSC undergoing IPAA, usage of concomitant antibiotics or immunosuppression was low. However, use of concomitant antibiotics or immunosuppression may decrease the burden of inflammatory conditions of the pouch in these high-risk patients.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.