Citations

ABSTRACT Aims Muscle morphology provides important information in differentiating disease aetiology, but its measurement remains challenging because of the lack of an efficient and objective method. This study aimed to quantitatively refine the morphological features of muscle fibres in neuromuscular diseases using machine learning. Methods In this retrospective study, we analysed muscle biopsy specimens on haematoxylin and eosin‐staining. Machine learning–based software was developed to segment muscle fibre contours and perform automated muscle morphometry and subsequent graph theory–based spatial analysis of atrophied fibre grouping. A decision tree–based framework, LightGBM, was trained to predict underlying aetiologies based on morphometric and spatial variables. Results The study included 100 muscle samples, including 20 normal muscles, 49 myopathies and 19 neuropathies. The fine‐tuned segmentation model, YOLOv8, achieved a mask average precision of 0.819. The muscle morphometry revealed the significance of fibre circularity. The mean circularity was higher in the myopathy group, and the SD of circularity was elevated in the neuropathy group. Although most cases were consistent with textbook findings, atypical presentations, such as dermatomyositis with angular atrophy and amyotrophic lateral sclerosis with round atrophy, were objectively documented. Spatial analysis quantified grouped atrophy, showing the potential to feature specific atrophy patterns. The LightGBM model successfully predicted the final clinical diagnosis of the myopathies and neuropathies with an accuracy of 0.852, which exceeded that of 0.808 by human annotation. Conclusion Automated muscle morphometry and spatial analysis provide quantification of muscle morphology and patterns of atrophy, which will facilitate objective and efficient investigation of neuromuscular diseases.

The National Cancer Database (NCDB) is a large data set of cancer patients treated in the United States. In recent decades, many papers have utilized this database to study disparities in cancer care and outcomes. In this review, we present the strengths and limitations of using the NCDB to study cancer disparities, which should be taken into account by researchers who use the NCDB in this setting.

AbstractRegistered nurses increasingly work in remote care and digital interaction roles, offering flexibility and expansion of their scope of practice. These roles may expose nurses to digital compassion fatigue, a phenomenon proposed to be characterized by the negative psychological and emotional impact of caring for patients remotely through the use of technology.The first objective of this work is to propose the phenomenon of “digital compassion fatigue” as a potentially further evolved and differentiated form of “compassion fatigue.” The second objective is to produce a comparative analysis of attributes, antecedents, and consequences through literature reviews.An evolutionary concept analysis approach was selected as a guide for exploring, discussing, and defining the new concept of digital compassion fatigue. Concept analysis was selected given the need for a framework that accounts for the dynamic nature of technology and practice. The process of conducting a concept analysis includes consideration of diverse and multidisciplinary perspectives. As a result, those in caring, educational, and/or support service roles (e.g., social work, counseling, and teaching) for which distance suffering and technostress could feasibly be present were also included in the literature searches and reviews. Health care-specific studies often included nurses in the sample but may not have differentiated their specific insights or data points in the results.The concept analysis explored the attributes, antecedents, and consequences of digital compassion fatigue, differentiating it from its evolutionary parent, compassion fatigue. Key antecedents included technostress, distant suffering, and the unique challenges of delivering care remotely. A major confounding variable was the COVID-19 pandemic, which may have heightened or introduced new technology-related stressors or highlighted the existence of digital compassion fatigue.Further defining and understanding digital compassion fatigue is crucial for developing effective strategies to support nurses who may experience it or who are at risk.

PURPOSE Immune checkpoint inhibitors (ICIs) have significantly improved outcomes in various malignancies. However, the high cost of these therapies limits access for much of the global population. This systematic review aims to evaluate the efficacy of low-dose ICIs compared with standard doses in different malignancies, addressing financial and access barriers in global cancer care. METHODS We conducted a systematic review of studies comparing the efficacy of low-dose versus standard-dose ICI regimens in advanced solid tumors. A comprehensive search was performed across multiple electronic databases, including retrospective and prospective studies. Excluded were animal studies, editorials, conference papers, book chapters, and other immunotherapy modalities. Outcomes assessed included overall survival (OS), progression-free survival, and objective response rate. Results were summarized descriptively due to study heterogeneity. RESULTS From 1,010 screened articles, four studies with 435 Asian patients were included, covering a variety of solid tumors. All included studies were with a low quality of evidence and a high risk of bias due to retrospective design. Two studies used weight-based dosing (pembrolizumab <2 mg/kg and nivolumab <2.15 mg/kg), showing similar OS to standard dosing in non–small cell lung cancer (NSCLC) and renal cell carcinoma, respectively. Flat dose regimens in two studies (nivolumab 20 mg or 100 mg once every 3 weeks and pembrolizumab 100 mg once every 3 weeks) also demonstrated comparable OS in NSCLC. CONCLUSION Low-dose ICIs may offer equivalent clinical benefits to standard dosing, potentially reducing costs and expanding access in developing countries. Although awaiting more representative randomized clinical trials, weight-based ICI regimens could be a viable alternative in low- and middle-income countries.

ABSTRACT Disruptions in the metabolism of cholesterol and other lipids are strongly implicated in the pathogenesis of neurological disease. The CNS is highly enriched in cholesterol, which is primarily synthesized de novo . Cholesterol synthesis is also rate limiting for myelin regeneration. Given that knockout of the thrombin receptor (Protease Activated Receptor 1 (PAR1)) accelerates myelin regeneration, here we sought to determine the potential regulatory actions of PAR1 in CNS cholesterol and lipid metabolism in the intact adult CNS and during myelin regeneration. We present quantitative PCR and RNAseq evidence from murine spinal cords at the peak of myelination and in adulthood showing PAR1 knockout is associated with increased gene expression for cholesterol biosynthesis (Hmgcs1, Hmgcr, Sqle, and Dhcr7), lipid transport (ApoE, Abca1, and Ldlr), and intracellular processing (Lcat, Npc1, and Npc2) at one or more time points examined. An upregulation of genes involved in the synthesis of other lipids enriched in the myelin membrane, specifically Fa2h, Ugt8a, and Gal3st1, was also observed in PAR1 knockouts. Transcription factors essential for lipid and cholesterol production (Srebf1 and Srebf2) were also increased in PAR1 knockout spinal cords at the postnatal day 21 peak of myelination and at day 45. GC–MS and LC–MS quantification of lipids demonstrated coordinate increases in the abundance of select cholesterol and lipid species in the spinal cords of PAR1 knockout mice, including enrichment of esterified cholesterol, together with sphingomyelins and sphingolipids. Co‐localization of the SREBP1 and SREBP2 transcription factors, as well as HMGCS1, a rate‐limiting enzyme in cholesterol biosynthesis, to glia during remyelination post‐lysolecithin or cuprizone‐mediated demyelination showed a prominent regulatory role for PAR1 in Olig2+ oligodendrocytes. PAR1 knockouts also demonstrated elevated levels of SREBP2 in more mature GST3+ oligodendrocytes and SREBP1 in GFAP+ astrocytes during remyelination post‐lysolecithin. These findings demonstrate novel roles for PAR1 as a regulator of CNS cholesterol and lipid metabolism and its potential as a therapeutic target to increase cholesterol availability to improve myelin regeneration. image

Advanced heart failure (HF) significantly diminishes quality of life (QoL) due to severe symptom burden and psychological distress. This meta-analysis investigates the impact of palliative care interventions on QoL, psychological well-being, symptom burden, and mortality in adults with advanced HF. A systematic search of major databases through August 2024 identified 13 randomized controlled trials involving 1541 participants from the USA, China, Iran, and Sweden. Palliative care significantly improved QoL scores compared with usual care [mean difference (MD) = 1.36; 95% confidence interval (CI), 0.89–1.83; P < 0.00001], with notable improvements using the Kansas City Cardiomyopathy Questionnaire. Palliative care significantly reduced anxiety scores (MD = −0.39; 95% CI, −0.66 to −0.11), P = 0.006), especially when assessed with the Edmonton Symptom Assessment Scale. While no significant differences were observed for dyspnea or depression ( P =0.56, P = 0.23, respectively). Mortality rates did not differ significantly between groups ( P = 0.61). These findings highlight the potential of palliative care, particularly interventions incorporating symptom management and psychological support, to enhance QoL and reduce anxiety in advanced HF patients. However, further research is required to standardize these interventions and evaluate their long-term outcomes.

Hypertension is the leading modifiable risk factor for atrial fibrillation (AF) and is estimated to be present in >70% of AF patients. This Frontiers Review was prepared by 29 expert members of the AF-SCREEN International Collaboration to summarize existing evidence and knowledge gaps on links between hypertension, AF, and their cardiovascular sequelae; simultaneous screening for hypertension and AF; and the prevention of AF through antihypertensive therapy. Hypertension and AF are inextricably connected. Both are easily diagnosed, often silent, and frequently treated inadequately. Together, they additively increase the risk of ischemic stroke, heart failure, and many types of dementia, resulting in greater all-cause mortality, considerable disease burden, and increased health care expenditures. Automated upper arm cuff blood pressure devices with implemented technology can be used to simultaneously detect both hypertension and AF. However, positive screening for AF with an oscillometric blood pressure monitor still requires ECG confirmation. The current evidence suggests that high-risk individuals aged ≥65 years or with treatment-resistant hypertension could benefit from AF screening. Since antihypertensive therapy effectively lowers AF risk, particularly in individuals with left ventricular dysfunction, hypertension should be the key target for AF prediction and prevention rather than merely a comorbidity of AF. Nevertheless, several important gaps in knowledge need to be filled over the next years, including the ideal method and selection of patients for simultaneous screening of hypertension and AF and the optimal antihypertensive drug class and blood pressure targets for AF prevention.

Introduction: Online self-scheduling of medical appointments is increasingly common. An automated waitlist can be used for patients who desire an earlier appointment time if one becomes available after they are scheduled. Our study examines outcomes of an automated waitlist and self-rescheduling process. Methods: We studied outcomes of an automated waitlist self-rescheduling process in which patients with existing appointments elected to be placed on an automated waitlist for an earlier appointment offer. When software found earlier dates for the same visit type, patients were then notified through an automated process and could self-reschedule. We reviewed appointments for which patients were sent new offers when earlier appointment slots were found. We compared the accepted appointment offers with the original scheduled appointments and determined the number of days that the appointment had been moved up. Results: Spanning the calendar year 2023 there were 1 019 698 appointment offers generated by an automated waitlist process for 229 998 appointments and sent to 164 248 patients. The waitlist process automatically found open appointments as they became available and sent the first new appointment offer within 2 days after being placed on the waitlist for 74 736 (32.5%) of the 229 998 waitlisted appointments. Patients sent back at least 1 response for 104 554 (45.4%) of the waitlisted appointments. Of the responses, 56 636 accepted one of the sent offers for an accept rate of 24.6% (56 636/229 998). For accepted, moved-up visits, appointments were self-rescheduled earlier by a mean of 22.6 days (95%CI; 22.2, 22.9, P < .0001). Conclusion: New appointments can be successfully self-rescheduled using an automated waitlist process that allows patients to accept or decline new appointment offers. This process can increase the efficiency of scheduling and decrease appointment wait time for patients desiring more timely access to healthcare. In addition, this process can be successfully applied across several different appointment type categories.