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Abstract A growing population of older adults and improved effective treatments for inflammatory rheumatic diseases will increase the demand for more healthcare resources that already struggle with staggering outpatient clinic waiting times. Transformative delivery care models that provide sustainable healthcare services are urgently needed to meet these challenges. In this mini-review article, a proposed Lifelong Treatment Model for a decentralized follow-up of outpatient clinic patients living with rheumatoid arthritis is presented and discussed. Our conceptual model follows four steps for a transformative care delivery model supported by an Integrated Practice Unit; (1) Diagnosis, (2) Treatment, (3) Patient Empowered Disease Management, and (4) Telehealth. Through an Integrated Practice Unit, a multidisciplinary team could collaborate with patients with rheumatoid arthritis to facilitate high-value care that addresses most important outcomes of the patients; (1) Early Remission, (2) Decentralization, (3) Improved Quality of Life, and (4) Lifelong Sustain Remission. The article also addresses the growing challenges for the healthcare delivery system today for patients with rheumatoid arthritis and proposes how to reduce outpatient clinic visits without compromising quality and safety.

Objectives To evaluate the proficiency of a HIPAA-compliant version of GPT-4 in identifying actionable, incidental findings from unstructured radiology reports of Emergency Department patients. To assess appropriateness of artificial intelligence (AI)-generated, patient-facing summaries of these findings. Materials and Methods Radiology reports extracted from the electronic health record of a large academic medical center were manually reviewed to identify non-emergent, incidental findings with high likelihood of requiring follow-up, further sub-stratified as "definitely actionable" (DA) or "possibly actionable—clinical correlation" (PA-CC). Instruction prompts to GPT-4 were developed and iteratively optimized using a validation set of 50 reports. The optimized prompt was then applied to a test set of 430 unseen reports. GPT-4 performance was primarily graded on accuracy identifying either DA or PA-CC findings, then secondarily for DA findings alone. Outputs were reviewed for hallucinations. AI-generated patient-facing summaries were assessed for appropriateness via Likert scale. Results For the primary outcome (DA or PA-CC), GPT-4 achieved 99.3% recall, 73.6% precision, and 84.5% F-1. For the secondary outcome (DA only), GPT-4 demonstrated 95.2% recall, 77.3% precision, and 85.3% F-1. No findings were "hallucinated" outright. However, 2.8% of cases included generated text about recommendations that were inferred without specific reference. The majority of True Positive AI-generated summaries required no or minor revision. Conclusion GPT-4 demonstrates proficiency in detecting actionable, incidental findings after refined instruction prompting. AI-generated patient instructions were most often appropriate, but rarely included inferred recommendations. While this technology shows promise to augment diagnostics, active clinician oversight via "human-in-the-loop" workflows remains critical for clinical implementation. [ABSTRACT FROM AUTHOR]

Optimization of proton exchange membrane water electrolyzers (PEMWE) has become a focus of researchers looking for a reliable way to generate power. A vital component to PEMWE operation is the porous transport layer (PTL) on the anode side, which is where oxygen is produced. The PTL must allow water access to the catalyst layer and remove oxygen simultaneously. In this work, a previously developed imaging technique is used to generate bilayer PTL structures. A multiscale modeling approach was used to study the effect of a bilayer PTL on oxygen evolution and PEMWE performance. First, a micro scale model was used to predict oxygen transport pathways through different PTL structures. Results showed that the bilayer PTL results in higher oxygen saturation and faster oxygen transport through the PTL. Second, a macro scale model was used to predict performance using bilayer PTLs. Predictions showed potential values between 10 and 20 mV below single layer potential values. This points to the bilayer improving PEMWE operation. Findings from this work show how the addition of a mesoporous layer to a PTL substrate will improve oxygen transport and removal from the catalyst surface, which will improve PEMWE performance. [ABSTRACT FROM AUTHOR]

Jee Wook Kim,1,2 Min Soo Byun,3 Dahyun Yi,3 Jun Ho Lee,4 Kang Ko,4 Gijung Jung,5 Dong Young Lee3,4,6 On behalf of the KBASE Research Group 1Department of Neuropsychiatry, Hallym University Dongtan Sacred Heart Hospital, Hwaseong, Republic of Korea; 2Department of Psychiatry, Hallym University College of Medicine, Chuncheon, Republic of Korea; 3Institute of Human Behavioral Medicine, Medical Research Center, Seoul National University, Seoul, Republic of Korea; 4Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea; 5Department of Nursing, Graduate School, Kyung Hee University, Seoul, Republic of Korea; 6Department of Psychiatry, Seoul National University College of Medicine, Seoul, Republic of Korea Purpose: We aimed to investigate the relationships of cerebral amyloid beta (Aβ) deposition and neurodegeneration (ND) with subjective memory complaints (SMCs) in cognitively normal (CN) individuals, focusing specially on the modulating effects of vascular risk (VR) on those relationships. Participants and methods: A total of 230 CN elderly individuals underwent comprehensive clinical assessments including the Subjective Memory Complaints Questionnaire (SMCQ), VR assessment, and multimodal brain imaging including [11C] Pittsburgh compound B positron emission tomography (PET), [18F] fluorodeoxyglucose-PET, and magnetic resonance imaging. Results: We found a significant overall positive association between cerebral Aβ retention and SMCQ score. In addition, we found a significant cerebral Aβ retention × VR interaction effect on the SMCQ score. Subgroup analyses showed that the Aβ–SMC association was found only in VR-negative, and not in VR-positive, individuals. We found no relationship between ND and SMCQ. Conclusion: Our findings suggest that SMC in CN elderly individuals reflects early accumulation of Aβ in the brain. Given the modulating effect of VR on the Aβ–SMC relationship, SMC can be used as a meaningful marker of early Aβ deposition in individuals without VR. Keywords: subjective memory complaints, amyloid beta, vascular risk, Alzheimer’s disease, cognitively normal

Abstract Background Morel-Lavallee lesions (MLLs) are rare internal degloving injuries typically caused by blunt traumatic injuries and most commonly occur around the hips and in association with pelvic or acetabular fractures. MLL is often overlooked in the setting of poly-trauma; therefore, clinicians must maintain a high degree of suspicion and be familiar with the management of such injuries, especially in obese poly-trauma patients. Case presentation We present a 30-year-old female pedestrian struck by a motor vehicle who sustained multiple long bone fractures, a mesenteric hematoma, and full-thickness abdominal skin friction burn which masked a significant underlying abdominal MLL. The internal degloving caused significant devascularization of the overlying soft tissue and skin which required surgical drainage of hematoma, abdominal wall reconstruction with tangential excision, allografting, negative pressure wound therapy, and ultimately autografting. Conclusion MLL is a rare, often overlooked, internal degloving injury. Surgeons must maintain a high index of suspicion when dealing with third degree friction burns as they may mask underlying injuries such as MLL, and a delay in diagnosis can lead to increased morbidity.