Employer Perspective on Pain Fellowship Education: A Survey to Understand the Current State of Pain Medicine Training.

Background: Pain medicine care has expanded to encompass a wider range of conditions, necessitating updated education and training for pain specialists to utilize emerging technologies effectively. A national survey was conducted through several verified Pain organizations regarding pain physician employers' perspectives on pain medicine fellowship training and education. The survey aimed to gather insights from a diverse range of geographic locations, practice types (academic and private practice), and practice settings.

Explainable predictions of a machine learning model to forecast the postoperative length of stay for severe patients: machine learning model development and evaluation.

Background: Predicting the length of stay in advance will not only benefit the hospitals both clinically and financially but enable healthcare providers to better decision-making for improved quality of care. More importantly, understanding the length of stay of severe patients who require general anesthesia is key to enhancing health outcomes.

Objective: Here, we aim to discover how machine learning can support resource allocation management and decision-making resulting from the length of stay prediction.

Kidney replacement therapy trends in end-stage kidney disease patients in South Korea during the COVID-19 pandemic.

Background/aims: The corona virus disease 2019 posed a major risk for end-stage kidney disease (ESKD) cases. Our study aimed to assess changes in kidney replacement therapy (KRT) trends and healthcare access for these patients during the pandemic.

Methods: We retrospectively analyzed nationwide data from July 2017 to June 2022 to assess changes in KRT and ESKD incidence.

Human cytomegalovirus harnesses host L1 retrotransposon for efficient replication.

Genetic parasites, including viruses and transposons, exploit components from the host for their own replication. However, little is known about virus-transposon interactions within host cells. Here, we discover a strategy where human cytomegalovirus (HCMV) hijacks L1 retrotransposon encoded protein during its replication cycle.

Trainee Insight into Pain Fellowship Programs: A Critical Evaluation of the Current Educational System by the APPD.

Background: Since 1992, when the Accreditation Council of Graduate Medical Education (ACGME) acknowledged pain medicine as a subspecialty, the field has experienced significant growth in its number of programs, diversity of sponsoring specialties, treatment algorithms, and popularity among applicants. These shifts prompted changes to the educational model, overseen by program directors (PDs) and the ACGME. The pool of pain fellowship applicants also changed during that period.

Time series forecasting of weight for diuretic dose adjustment using bidirectional long short-term memory.

Loop diuretics are prevailing drugs to manage fluid overload in heart failure. However, adjusting to loop diuretic doses is strenuous due to the lack of a diuretic guideline. Accordingly, we developed a novel clinician decision support system for adjusting loop diuretics dosage with a Long Short-Term Memory (LSTM) algorithm using time-series EMRs.

COVID-19 infection in patients with end-stage kidney disease undergoing renal replacement therapies in Korea.

Background: The global coronavirus disease 2019 (COVID-19) pandemic has placed patients with end-stage kidney disease (ESKD) at heightened risk owing to their vulnerability to infections. Our study focused on patients with ESKD, examining COVID-19 incidence, hospitalization, and mortality in relation to their renal replacement therapy (RRT) type and identifying factors influencing COVID-19 hospitalization.

Methods: We conducted a retrospective cohort study using health insurance claims data from the Health Insurance Review and Assessment Service for patients with ESKD between July 2017 and June 2022.

Human ST3Gal II and ST6GalNAc IV genes increase human serum-mediated cytotoxicity to xenogeneic cells.

Carbohydrate-antigens widely existed on glycoproteins and glycosphingolipids of all mammalian cells play a crucial role in self-defense and immunity. Xeno-reactive antibodies included in natural human sera play a protecting role in an acute phase-rejection of xenotransplantation. In this study, we investigated the effect of an alteration of glycosylation-pattern, caused by human sialyltransferases such as hST3Gal II or hST6GalNAc IV, on human serum mediated cytotoxicity in pig kidney PK15 cells.

The current state of training in pain medicine fellowships: An Association of Pain Program Directors (APPD) survey of program directors.

Introduction: The Accreditation Council for Graduate Medical Education (ACGME) approved the first pain medicine fellowship programs over three decades ago, designed around a pharmacological philosophy. Following that, there has been a rise in the transition of pain medicine education toward a multidisciplinary interventional model based on a tremendous surge of contemporaneous literature in these areas. This trend has created variability in clinical experience and education amongst accredited pain medicine programs with minimal literature evaluating the differences and commonalities in education and experience of different pain medicine fellowships through Program Director (PD) experiences.

Influencing Factors on Career Preparation Behavior of Nursing Students in the Post COVID-19 Era.

This study aims to determine the factors influencing the career preparation behavior of nursing students in the post-COVID-19 era and to provide a basis for preparation strategies to enhance nursing students' nursing professionalism and career preparation behaviors. This is a descriptive cross-sectional study that measures major satisfaction, self-efficacy, nursing image, nursing professionalism, nursing image and intuition, and career preparation to identify factors influencing nursing students' career preparation behavior in the post-COVID-19 era. An online survey was conducted to collect the data.

Forecasting Hospital Room and Ward Occupancy Using Static and Dynamic Information Concurrently: Retrospective Single-Center Cohort Study.

Background: Predicting the bed occupancy rate (BOR) is essential for efficient hospital resource management, long-term budget planning, and patient care planning. Although macro-level BOR prediction for the entire hospital is crucial, predicting occupancy at a detailed level, such as specific wards and rooms, is more practical and useful for hospital scheduling.

Objective: The aim of this study was to develop a web-based support tool that allows hospital administrators to grasp the BOR for each ward and room according to different time periods.

Are polypharmacy side effects predicted by public data still valid in real-world data?

Background And Objective: Although interest in predicting drug-drug interactions is growing, many predictions are not verified by real-world data. This study aimed to confirm whether predicted polypharmacy side effects using public data also occur in data from actual patients.

Methods: We utilized a deep learning-based polypharmacy side effects prediction model to identify cefpodoxime-chlorpheniramine-lung edema combination with a high prediction score and a significant patient population.

Nurse-led self-care interventions for older adults with multiple chronic conditions: A protocol for a systematic review and network meta-analysis.

The importance of self-care interventions is progressively recognized, marked by a rapidly aging population that results in growing demands on costly tertiary and institutional care services, placing substantial pressure on health and social care systems. Against this background, in this study, we will provide evidence for the impact of self-care interventions on health-related quality of life by focusing on interventions led by nurses who can employ integrated approaches. Several databases, including Ovid MEDLINE, Cochrane, CINAHL, Embase, and PubMed, will be searched along with gray literature to prevent biased results.

Variants in the WDR44 WD40-repeat domain cause a spectrum of ciliopathy by impairing ciliogenesis initiation.

WDR44 prevents ciliogenesis initiation by regulating RAB11-dependent vesicle trafficking. Here, we describe male patients with missense and nonsense variants within the WD40 repeats (WDR) of WDR44, an X-linked gene product, who display ciliopathy-related developmental phenotypes that we can model in zebrafish. The patient phenotypic spectrum includes developmental delay/intellectual disability, hypotonia, distinct craniofacial features and variable presence of brain, renal, cardiac and musculoskeletal abnormalities.

Machine learning models to predict the warfarin discharge dosage using clinical information of inpatients from South Korea.

As warfarin has a narrow therapeutic window and obvious response variability among individuals, it is difficult to rapidly determine personalized warfarin dosage. Adverse drug events(ADE) resulting from warfarin overdose can be critical, so that typically physicians adjust the warfarin dosage through the INR monitoring twice a week when starting warfarin. Our study aimed to develop machine learning (ML) models that predicts the discharge dosage of warfarin as the initial warfarin dosage using clinical data derived from electronic medical records within 2 days of hospitalization.

The Impact of the Rapid Blood Culture Identification Panel on Antibiotic Treatment and Clinical Outcomes in Bloodstream Infections, Particularly Those Associated with Multidrug-Resistant Micro-Organisms.

We evaluated the impact of the FilmArray blood culture identification (BCID) panel on the time taken to administer effective antibiotics and the clinical outcomes of bloodstream infections. We retrospectively screened patients with bloodstream infections who underwent BCID testing and compared them to a historical control group that received conventional culture testing. A total of 144 and 214 patients who underwent BCID and conventional cultures, respectively, were compared.

Understanding the molecular mechanisms of odorant binding and activation of the human OR52 family.

Structural and mechanistic studies on human odorant receptors (ORs), key in olfactory signaling, are challenging because of their low surface expression in heterologous cells. The recent structure of OR51E2 bound to propionate provided molecular insight into odorant recognition, but the lack of an inactive OR structure limited understanding of the activation mechanism of ORs upon odorant binding. Here, we determined the cryo-electron microscopy structures of consensus OR52 (OR52), a representative of the OR52 family, in the ligand-free (apo) and octanoate-bound states.

LDP-GAN : Generative adversarial networks with local differential privacy for patient medical records synthesis.

Electronic medical records(EMR) have considerable potential to advance healthcare technologies, including medical AI. Nevertheless, due to the privacy issues associated with the sharing of patient's personal information, it is difficult to sufficiently utilize them. Generative models based on deep learning can solve this problem by creating synthetic data similar to real patient data.

Molecular basis for PHF7-mediated ubiquitination of histone H3.

The RING-type E3 ligase has been known for over two decades, yet its diverse modes of action are still the subject of active research. Plant homeodomain (PHD) finger protein 7 (PHF7) is a RING-type E3 ubiquitin ligase responsible for histone ubiquitination. PHF7 comprises three zinc finger domains: an extended PHD (ePHD), a RING domain, and a PHD.