Citations

ABSTRACT Background While vaccination is a key strategy to mitigate the severity of coronavirus disease 2019 (COVID‐19) in children, the risk factors for symptomatic, medically attended (hereon referred to as “symptomatic”) COVID‐19 and the impact of vaccination are not well defined among pediatric solid organ transplant recipients (PSOTR). Methods PSOTR aged six months through 21 years at 11 centers in the Pediatric Infectious Diseases Transplant Network (PIDTRAN) were analyzed retrospectively for symptomatic COVID‐19 between July 2021 and May 2023. Using a Cox proportional hazards model, risk factors associated with COVID‐19‐associated hospitalization, in‐hospital oxygen use, mechanical ventilation, and the impact of COVID‐19 vaccination were analyzed. Results Of 1370 PSOTR, 410 (29%) had symptomatic COVID‐19 infection. Among those with symptomatic infection, 115 (28%) were hospitalized, 35 required in‐hospital oxygen, and three required mechanical ventilation. In the study, 45% were unvaccinated against COVID‐19. Compared to unvaccinated PSOTR, incompletely vaccinated PSOTR had 56% lower hazard (95% CI 0.26, 0.72, p = 0.001) of COVID‐19‐associated hospitalization whereas completely vaccinated did not have a statistically significant difference in hazard of hospitalization. Receipt of at least one dose of the bivalent vaccine was also associated with 92.5% lower hazard (95% CI 0.010, 0.55, p = 0.011) of hospitalization. Risk factors for hospitalization included chronic kidney disease, underlying heart disease, neurodevelopmental delay, and lymphocytopenia. Conclusions Most PSOTR with symptomatic COVID‐19 did not require hospitalization or respiratory support. Several comorbidities and lymphocytopenia are associated with severe COVID‐19 in PSOTR. COVID‐19 vaccination, mostly, protected PSOTR against COVID‐19‐associated hospitalization, but vaccine uptake among PSOTR was low. image

ABSTRACT Background Chimeric antigen receptor T‐cell (CAR‐T) therapy has revolutionised the treatment of hematologic malignancies, and its use is expanding rapidly into numerous other disease states including autoimmune diseases. However, CAR‐T therapy is associated with a spectrum of immune‐related toxicities. In addition to the already well characterized cytokine release syndrome and immune effector cell‐associated neurotoxicity syndrome, it has become apparent that rarely, CAR‐T can cause gastrointestinal mucosal inflammation, termed immune effector cell‐mediated enterocolitis (IEC‐EC). Aims This state‐of‐the‐art review highlights the CAR‐T mechanism and details the epidemiology, pathophysiology, clinical manifestations, endoscopic and histopathologic features, and management of IEC‐EC. Methods This review presents the current state of knowledge through a comperhensive and detailed synthesis of all case series reported in the literature to date. Results Occurring in up to approximately 6% of patients typically following B cell maturation antigen‐targeted CAR‐T therapy, IEC‐EC presents with severe diarrhoea and malabsorption, responds poorly to treatment, and portends a dire prognosis. Multi‐disciplinary management should centre on early diagnosis, supportive cares, assessment and treatment of infections, and step‐up pharmacotherapy, often featuring biologics and small molecules drawn from the inflammatory bowel disease pharmacologic armamentarium. Conclusions Clinicians should maintain a high degree of vigilance for IEC‐EC in patients presenting with gastrointestinal symptoms following CAR‐T treatment. Early recognition and multi‐disciplinary treatment may improve patient outcomes.

ABSTRACT Introduction Postoperative mortality commonly follows complications that are not prevented, recognised or managed effectively. Ward‐based nursing care is central to surveillance, escalation and rescue, but population‐level evidence using shift‐level staffing data is limited. This national population‐based cohort study examined the association between surgical ward nurse staffing and postoperative outcomes. Methods Adults aged 18 years or older undergoing inpatient surgery under general or neuraxial anaesthesia in public hospitals in Aotearoa New Zealand between 2022 and 2024 were included. Prospectively recorded TrendCare staffing data were linked to administrative health datasets. The exposure was shift‐level staffing variance, defined as the difference between required and available nursing care hours on surgical wards in the treating hospital during admission. The primary outcome was 90‐day postoperative mortality. Secondary outcomes were postoperative complications and failure to rescue. Results The cohort included 202 428 patients undergoing 223 415 surgical admissions. Within 90 days, 6296 admissions resulted in death (2.8%). Complications occurred in 41 722 admissions (18.7%), with failure to rescue in 15.1%. Of 281 147 surgical ward shifts, 122 186 (43.5%) were understaffed. After adjustment, each one‐nurse reduction in staffing per shift was associated with higher odds of mortality (aOR: 1.13, 95% CI: 1.07–1.18), complications (aOR: 1.07, 95% CI: 1.05–1.10) and failure to rescue (aOR: 1.07, 95% CI: 1.00–1.14). Modelling estimated that correcting observed staffing deficits was associated with 182 fewer deaths annually. Conclusion Lower surgical ward nurse staffing was associated with increased postoperative mortality, complications and failure to rescue. Nurse staffing is a modifiable system factor associated with postoperative safety and should be prioritised to improve surgical outcomes.

Introduction: Understanding mid-term test-retest reliability and within-subject variability is important for interpreting changes observed in longitudinal and intervention studies. The reliability of resting-state functional magnetic resonance imaging (rs-fMRI) is known to vary across measures and brain regions. However, how reliability differs across functional networks and connectivity- and amplitude-based measures, and whether multi-echo acquisition and processing modify these patterns, remain incompletely characterized. Methods: Twenty-two healthy volunteers underwent two rs-fMRI sessions 15.7 ± 4.0 days apart on a Compact 3T scanner. Multi-echo, middle-echo, and independently acquired single-echo datasets were compared, with multi-echo independent component analysis additionally evaluated as a denoising approach. Functional connectivity (FC) and three amplitude-based measures were evaluated using the Schaefer 400 parcellation. Reliability was systematically assessed using intraclass correlation coefficient (ICC), within-subject standard deviation (wSD), and systematic bias at edge or regional, and network levels. Results: Acquisition-dependent differences in reliability were generally modest. Multi-echo acquisition and processing increased functional connectivity strength and the magnitude of amplitude-based measures and improved inferior cortical coverage, but these enhancements did not consistently translate into substantially higher ICC or lower wSD. In contrast, reliability showed clear network-dependent differences. FC reliability varied markedly across network pairs and was not explained by connectivity strength alone; pairs involving the default mode and control networks generally showed more favorable profiles than several somatomotor and visual network pairs. Fractional amplitude of low-frequency fluctuations (fALFF) also showed network-dependent reliability, with the most favorable regional reproducibility observed in the default mode and control networks and lower reproducibility in the somatomotor and visual networks. Conclusion: These findings provide practical mid-term reliability benchmarks for rs-fMRI on a Compact 3T scanner and show that measurement stability varies more clearly across measures and functional networks than across acquisition approaches.

Breast biopsy markers have evolved from simple metallic devices to sophisticated multimaterial tools that have become essential for breast cancer care, demonstrating their clinical benefits in surgical planning, radiation targeting, and cost reduction.

Rotating magnetic fields (RMFs) are widely used to actuate untethered microrobots, yet delivering clinically relevant RMFs at human scale remains challenging. Here, we create a quantitative framework for human‐scale RMF delivery using robot‐arm‐mounted permanent magnets. It links anatomical separation, surface‐clearance constraints, magnet geometry, rotational inertia, and robot‐arm limitations to define a feasible RMF operating envelope. Magnet geometry is most important when target separation is comparable to magnet size; in this regime, diametrically magnetized cylinders provide the most efficient field delivery at constant magnet volume. At larger separations, field delivery converges toward dipole‐like scaling and becomes primarily governed by total magnet volume. Across the dominant microrobot operating envelope (5–30 mT, 1–30 Hz), required magnet mass ranges from sub‐kilogram values for limb and intracranial targets to more than 30 kg for deep thoracic access. As magnet size increases, rotational inertia rapidly emerges as the dominant mechanical constraint, with limb and intracranial targets remaining feasible whereas some thoracic scenarios exceed practical mechanical limits. We demonstrate a representative actuator designed within the proposed framework tested on a human‐scale vascular phantom under flow. This work provides a foundation for codesigning translational microrobots and their magnetic drive platforms tailored for relevant anatomical targets.

Abstract Anthracycline-induced cardiotoxicity (AIC) remains a dose-limiting complication of cancer treatment, often leading to irreversible heart failure, yet effective cardioprotective therapies remain limited. Graph-driven drug repurposing offers a rapid pathway to identify cardioprotective therapies, but different computational models often generate divergent candidate lists that exceed experimental validation capacity. We applied a novel "Union-then-Filter" framework to prioritize therapeutics for AIC using AI-based approaches and evaluated candidates in zebrafish models. Three state-of-the-art graph learning models (TxGNN, CompGCN, and RLR) were trained on the PrimeKG to generate an initial candidate pool. A Large Language Model (LLM) agent automated evidence synthesis across 4,286 PubMed abstracts for the top 50 drugs from each model. Candidates were stratified using dual decision criteria and filtered against existing clinical trials. The pipeline narrowed 150 initial candidates to four novel candidates: Cysteine, Dasatinib, Tranilast, and Tretinoin. Prospective in vivo validation was subsequently conducted using an adult AIC (aAIC) zebrafish model. Phenotypic screening via echocardiography revealed that Cysteine, Tranilast, and Tretinoin significantly restored ejection fraction (EF) (overall one-way ANOVA: \(\:F\left(\text{4,95}\right)=47.66,\:\:p<0.0001\); Tukey's post hoc: \(\:\:\:p<0.01\) for all three treatments vs. DOX+ control) and normalized cardiac remodeling markers in doxorubicin-treated subjects (Kruskal-Wallis: \(\:{\chi\:}^{2}\left(4\right)=17.21,\:\:p=0.0018\); Dunn’s post hoc: \(\:\:\:p<0.01\) for all three comparisons vs. DOX control). This study demonstrates the translational utility of an LLM-integrated AI pipeline for drug repurposing and highlights zebrafish AIC as an efficient bridge between in silico prediction and in vivo phenotypic validation in cardio-oncology.

Importance Thirty-day hospital readmission is used to guide postdischarge care; however, a single binary 30-day estimate does not distinguish when risk occurs from when intervention is most actionable, with implications for allocation of postdischarge resources. Objective To evaluate time-structured hospital readmission risk within 30 days after discharge and implications for clinical utility. Design, Setting, and Participants Retrospective prognostic study of adults with hospital discharges from 2017 to 2024 (from 19 hospitals within a US health system for the development cohort) and 2008 to 2019 (from Medical Information Mart for Intensive Care IV for the external cohort) with 30-day follow-up. Analyses were conducted from November 2025 through June 2026. Exposure Postdischarge prediction window, including landmark intervals of 0 to 7, 8 to 14, 15 to 21, and 22 to 30 days and cumulative horizons through days 7, 14, 21, and 30 after discharge. Main Outcomes and Measures First all-cause hospital readmission before death during each landmark interval and by each cumulative horizon. Risk estimates were derived using clinical information available at hospital discharge. Performance was assessed using discrimination, calibration, decision curves, and capacity-constrained analyses. Results Among 617 841 discharges in the development cohort, the median (IQR) patient age was 65 (50-76) years, and 315 220 discharges (51.0%) occurred among female patients. The 30-day readmission rate was 16.3% (95% CI, 16.2%-16.5%), with 68 797 readmissions (68.2%) occurring within 14 days. Cumulative-horizon analyses characterized readmission risk through days 7, 14, 21, and 30, whereas landmark interval-specific analyses showed lower positive predictive values (PPVs) beyond day 7. At 5% intervention capacity, landmark PPVs were 58.3% (95% CI, 57.4%-59.1%) for days 0 to 7, 16.0% (95% CI, 15.5%-16.6%) for days 8 to 14, 14.5% (95% CI, 13.9%-15.0%) for days 15 to 21, and 12.9% (95% CI, 12.4% to 13.5%) for days 22 to 30; numbers needed to prevent 1 readmission were 8.6, 31.3, 34.6, and 38.6, respectively. Conclusions and Relevance In this prognostic study of adult hospital discharges, hospital readmission risk varied over time and was not captured by a single binary 30-day estimate. These findings suggest that time-structured readmission modeling can characterize when readmission risk occurs, but additional work is needed before such models can reliably guide interventions during specific postdischarge intervals.

ABSTRACT Background Percutaneous left atrial appendage occlusion (LAAO) is an alternative strategy for stroke prevention in patients with nonvalvular atrial fibrillation (AF) with contraindications to long‐term oral anticoagulation therapy. However, evidence comparing the long‐term outcomes of LAAO with those of direct oral anticoagulants (DOAC) remains limited. Methods A systematic search was conducted across PubMed, Scopus, and the Cochrane databases through April 2026. Co‐primary outcomes were major adverse cardiovascular and cerebrovascular events (MACCE; composite of cardiac death, stroke, or systemic embolism) and net adverse clinical events (NACE; composite of MACCE and non‐procedure‐related bleeding). Secondary endpoints included individual components of co‐primary endpoints, ischemic and hemorrhagic stroke, all‐cause death, major or clinically significant bleeding (procedure + non‐procedure related), and stroke or systemic embolism. The random‐effects model was used to generate risk ratios (RRs) and 95% CIs. Results Four randomized controlled trials comprising 5890 AF patients and a median follow‐up of 3 years were included. There was no significant difference between LAAO and DOAC therapy in the risk of MACCE (RR 1.17; 95%CI 0.96–1.41; I 2 = 0%) or NACE (RR 0.89; 95%CI 0.65–1.24; I 2 = 85%). Both LAAO and DOAC therapy were similar in risk of cardiac death, stroke, systemic embolism, hemorrhagic stroke, ischemic stroke, all‐cause mortality, stroke or systemic embolism, and pericardial effusion. LAAO was associated with a lower risk of non‐procedure‐related bleeding (RR 0.60; 95%CI 0.47–0.76; I 2 = 59%). Conclusion LAAO demonstrated efficacy comparable to DOAC therapy in reducing the risk of MACCE, NACE, and ischemic events, while significantly reducing the risk of non‐procedure‐related bleeding. Our findings support a tailored approach to stroke prevention in AF, wherein LAAO serves as an effective alternative for patients with contraindications to DOAC therapy.