Validation of an artificial intelligence-based algorithm for predictive performance and risk stratification of sepsis using real-world data from hospitalised patients: a prospective observational study.

Objective: The heterogeneous nature of sepsis renders determining its underlying causes difficult, which may delay diagnosis and intervention. VitalCare-SEPsis Score (VC-SEPS) is a deep learning-based algorithm that predicts sepsis and monitors patient conditions based on electronic medical record data. However, few studies have prospectively compared medical artificial intelligence software algorithms and traditional scoring systems to predict sepsis.

Prospective external validation of a deep-learning-based early-warning system for major adverse events in general wards in South Korea.

Background: Acute deterioration of patients in general wards often leads to major adverse events (MAEs), including unplanned intensive care unit transfers, cardiac arrest, or death. Traditional early warning scores (EWSs) have shown limited predictive accuracy, with frequent false positives. We conducted a prospective observational external validation study of an artificial intelligence (AI)-based EWS, the VitalCare - Major Adverse Event Score (VC-MAES), at a tertiary medical center in the Republic of Korea.

Development of Labeling Algorithm for Early Prediction of Acute Kidney Injury.

Acute kidney injury is a prevalent and severe complication in hospitalized patients, contributing to increased morbidity and mortality. While numerous predictive models exist, they primarily focus on identifying AKI after its onset rather than forecasting it in advance. We developed a labeling algorithm to capture the earliest onset time of in-hospital AKI based on KDIGO 2012 criteria to address this limitation.

Synthetic Versus Biologic Mesh for Complex Open Ventral Hernia Repair: 3-Year Follow-Up of a Pilot Randomized Controlled Trial.

Background: Biologic mesh is often used in complex hernia repair, but there has been limited clinical evidence to date to support this practice. The aim of this study was to compare clinical and patient-reported outcomes of biologic versus synthetic mesh for complex open ventral hernia repair (OVHR) at 3 years.

Methods: Patients from a single center, randomized, controlled, pilot trial comparing biologic versus synthetic mesh in complex OVHR were followed for 3 years.

A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system.

The array of complex and evolving patient data has limited clinical decision making in the emergency department (ED). This study introduces an advanced deep learning algorithm designed to enhance real-time prediction accuracy for integration into a novel Clinical Decision Support System (CDSS). A retrospective study was conducted using data from a level 1 tertiary hospital.

Addressing statistical challenges in the analysis of proteomics data with extremely small sample size: a simulation study.

Background: One of the most promising approaches for early and more precise disease prediction and diagnosis is through the inclusion of proteomics data augmented with clinical data. Clinical proteomics data is often characterized by its high dimensionality and extremely limited sample size, posing a significant challenge when employing machine learning techniques for extracting only the most relevant information. Although there is a wide array of statistical techniques and numerous analysis pipelines employed in proteomics data analysis, it is unclear which of these methods produce the most efficient, reproducible, and clinically meaningful results.

Development of a Rapid Detection Method for Ethylene Glycol and Glycolic Acid in Feline Samples: A Response to Increasing Antifreeze Poisoning Incidents in Korea.

Recently, cases of antifreeze poisoning in companion animals, particularly cats, have surged in the Republic of Korea. Ethylene glycol (EG), the toxic primary component of antifreeze, is metabolized into glycolic acid (GA), leading to severe metabolic acidosis, acute kidney injury, and death. Traditional detection methods, although effective, are often time-consuming owing to complex sample preparation.

Association Between Cardiorespiratory Fitness and Trend of Age-Related Rise in Arterial Stiffness in Individuals With and Without Hypertension or Diabetes.

Background: This study aimed to investigate whether higher cardiorespiratory fitness (CRF) can modify the trend of age-related rise in arterial stiffness in individuals with and without hypertension (HTN) or diabetes.

Methods: The study included 4,935 participants who underwent maximal cardiopulmonary exercise testing with respiratory gas analysis in a health screening program. CRF was directly measured using peak oxygen uptake during the cardiopulmonary exercise test, while arterial stiffness was evaluated using brachial-ankle pulse wave velocity (baPWV).

In Vitro Self-Circularization Methods Based on Self-Splicing Ribozyme.

In vitro circular RNA (circRNA) preparation methods have been gaining a lot of attention recently as several reports suggest that circRNAs are more stable, with better performances in cells and in vivo, than linear RNAs in various biomedical applications. Self-splicing ribozymes are considered a major in vitro circRNA generation method for biomedical applications due to their simplicity and efficiency in the circularization of the gene of interest. This review summarizes, updates, and discusses the recently developed self-circularization methods based on the self-splicing ribozyme, such as group I and II intron ribozymes, and the pros and cons of each method in preparing circRNA in vitro.

Reduction of Overactive Bladder Medications in Spinal Cord Injury With Self-Administered Neuromodulation: A Randomized Trial.

Purpose: Our goal was to evaluate if self-administered bladder neuromodulation with transcutaneous tibial nerve stimulation could safely replace overactive bladder medications in people with spinal cord injury.

Materials And Methods: We performed a 3-month, randomized, investigator-blinded, tibial nerve stimulation vs sham-control trial in adults with spinal cord injury and neurogenic bladder performing intermittent catheterization and taking overactive bladder medications. The primary outcome was a reduction in bladder medications while maintaining stable bladder symptoms and quality of life based on pre/post Neurogenic Bladder Symptom Score and the Incontinence Quality of Life questionnaire, respectively.

Cost Analysis for Robotic and Open Gastrectomy.

Objective: To determine the magnitude of the perioperative costs associated with robotic gastrectomy (RG).

Background: A robotic surgery platform has a high implementation cost and requires maintenance costs; however, whether the overall cost of RG, including all perioperative costs, is higher than conventional open gastrectomy (OG) remains unknown.

Methods: Patients who underwent a major gastrectomy during February 2018 through December 2021 were retrospectively identified.

Novel Artificial Intelligence-Based Technology to Diagnose Asthma Using Methacholine Challenge Tests.

Purpose: The methacholine challenge test (MCT) has high sensitivity but relatively low specificity for asthma diagnosis. This study aimed to develop and validate machine learning (ML) models to improve the diagnostic performance of MCT for asthma.

Methods: Data from 1,501 patients with asthma symptoms who underwent MCT between 2015 and 2020 were analyzed.

Proximity extension assay proteomics and renal single cell transcriptomics uncover novel urinary biomarkers for active lupus nephritis.

Objective: To identify urinary biomarkers that can distinguish active renal involvement in Lupus Nephritis (LN), a severe manifestation of systemic lupus erythematosus (SLE).

Methods: Urine from 117 subjects, comprised of inactive SLE, active non-renal lupus, active LN, and healthy controls, were subjected to Proximity Extension Assay (PEA) based comprehensive proteomics followed by ELISA validation in an independent, ethnically diverse cohort. Proteomic data is also cross-referenced to renal transcriptomic data to elucidate cellular origins of biomarkers.

Impact of COVID-19 on nationwide pediatric complicated sinusitis trends throughout 2018-2022.

Objectives: To describe and analyze the trends of pediatric sinusitis cases from 2018 to 2022 across the country utilizing the Pediatric Hospital Information System (PHIS) database focusing on volumes, socioeconomics, and severity of cases.

Study Design: Retrospective Cohort Study.

Methods: A retrospective cohort study using the Pediatric Health Information System (PHIS) database, which consists of 50 children's hospitals was performed.

Real-time monitoring strategies for optimization of transcription and quality control of RNA.

RNA-based therapeutics and vaccines are opening up new avenues for modern medicine. To produce these useful RNA-based reagents, transcription (IVT) is an important reaction that primarily determines the yield and quality of the product. Therefore, IVT condition should be well optimized to achieve high yield and purity of transcribed RNAs.

Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial.

Background: Two characteristics of commonly used outcomes in medical research are zero inflation and non-negative integers; examples include the number of hospital admissions or emergency department visits, where the majority of patients will have zero counts. Zero-inflated regression models were devised to analyze this type of data. However, the performance of zero-inflated regression models or the properties of data best suited for these analyses have not been thoroughly investigated.

Efficient circular RNA engineering by end-to-end self-targeting and splicing reaction using group I intron ribozyme.

Circular RNA (circRNA) has various advantages over linear mRNA that is gaining success as a new vaccine and therapeutic agent. Thus, circRNA and its engineering methods have attracted attention recently. In this study, we developed a new circRNA engineering method by end-to-end self-targeting and splicing (STS) reaction using group I intron ribozyme.

Biologic Versus Synthetic Mesh in Ventral Hernia Repair: Participant-Level Analysis of Two Randomized Controlled Trials at Twenty-Four to Thirty-Six Months.

Biologic mesh has been used increasingly in complex ventral hernia repair despite limited evidence at low risk of bias supporting its use. We performed a participant-level analysis of published randomized controlled trials (RCTs) comparing biologic to synthetic mesh with complex ventral hernia repair at 24 to 36 months. Primary outcome was major complication (composite of mesh infection, recurrence, reoperation, or death) at 24 to 36 months post-operative.

Comprehensive proteomics and platform validation of urinary biomarkers for bladder cancer diagnosis and staging.

Background: Bladder cancer (BC) is among the most common cancers diagnosed in men in the USA. The current gold standards for the diagnosis of BC are invasive or lack the sensitivity to correctly identify the disease.

Methods: An aptamer-based screen analyzed the expression of 1317 proteins in BC compared to urology clinic controls.

Evaluation of cost data associated with pediatric cochlear implantation (CI) throughout 2016-2021.

Introduction: Cochlear Implants (CI) are a mainstay in the treatment of severe sensorineural hearing loss with proven cost-effectiveness and improved quality of life. However, costs associated with CI are variable. During the Covid-19 pandemic, elective surgeries decreased.

Pros and Cons of In Vitro Methods for Circular RNA Preparation.

mRNA is gaining success as a new therapeutic agent and vaccine. However, mRNA has limitations in stability. To overcome the shortcomings of mRNA, circular RNA is emerging as a new modality.

Isolation and Barcoding of Trace Pollen-free DNA for Authentication of Honey.

Adulteration and mislabeling of honey to mask its true origin have become a global concern. Pollen microscopy, the current gold standard for identifying honey's geographical and plant origins, is laborious, requires extensive training, and fails to identify filtered honey and honey spiked with pollen from a more favorable plant to disguise its origins. We successfully isolated pollen-free DNA from filtered honey using three types of adsorbents: (i) anti-dsDNA antibodies coupled to magnetic microspheres; (ii) anion-exchange adsorbent; and (iii) ceramic hydroxyapatite.