Real-world Impact Research Articles

Decoding Radiomics: A Step-by-Step Guide to Machine Learning Workflow in Hand-Crafted and Deep Learning Radiomics Studies

Although radiomics research has experienced rapid growth in recent years, with numerous studies dedicated to the automated extraction of diagnostic and prognostic information from various imaging modalities, such as CT, PET, and MRI, only a small fraction of these findings has successfully transitioned into clinical practice. This gap is primarily due to the significant methodological challenges involved in radiomics research, which emphasize the need for a rigorous evaluation of study quality. While many technical aspects may lie outside the expertise of most radiologists, having a foundational knowledge is essential for evaluating the quality of radiomics workflows and contributing, together with data scientists, to the development of models with a real-world clinical impact. This review is designed for the new generation of radiologists, who may not have specialized training in machine learning or radiomics, but will inevitably play a role in this evolving field. The paper has two primary objectives: first, to provide a clear, systematic guide to radiomics study pipeline, including study design, image preprocessing, feature selection, model training and validation, and performance evaluation. Furthermore, given the critical importance of evaluating the robustness of radiomics studies, this review offers a step-by-step guide to the application of the METhodological RadiomICs Score (METRICS, 2024)—a newly proposed tool for assessing the quality of radiomics studies. This roadmap aims to support researchers and reviewers alike, regardless of their machine learning expertise, in utilizing this tool for effective study evaluation.

Generative artificial intelligence (GAI): From large language models (LLMs) to multimodal applications towards fine tuning of models, implications, investigations

This research explores the transformative integration of artificial intelligence (AI), robotics, and language models, with a particular emphasis on the PaLM-E model. The exploration aims to assess PaLM-E’s decision-making processes and adaptability across various robotic environments, demonstrating its capacity to convert textual prompts into very precise robotic actions. In addition, the research investigates Parameter-Efficient Fine-Tuning (PEFT) techniques, such as Low-Rank Adaptation (LoRA) and Quantized Low-Rank Adaptation (QLoRA), providing a historical overview of PEFT and highlighting their significance in enhancing task performance while reducing the number of trainable parameters. The broader scope of Generative AI is examined through an analysis of influential models like GPT-3, GPT-4, Copilot, Bard, LLaMA, Stable Diffusion, Midjourney, and DALL-E. These models’ abilities to process natural language prompts and generate a wide range of outputs are thoroughly investigated. The research traces the historical evolution of AI, from its roots in science fiction to its practical applications today, with a focus on the rise of Generative AI in the 21st century. Furthermore, the research delves into the various modalities of Generative AI, covering applications in text, code, images, and more, and assesses their real-world impact on robotics, planning, and business intelligence. The implications of synthetic data generation for business analytics are also explored. The research inspects within both software and hardware landscapes, comparing local deployment on consumer-grade hardware along with cloud-based services, and underscores the benefits of local model deployment in terms of privacy protection, intellectual property security, and censorship resistance. Ethical considerations are central to this research, addressing concerns related to privacy, security, societal impact, biases, and misinformation. The research proposes ethical guidelines for the responsible development and deployment of AI technologies. Ultimately, this work reveals the deep interconnections between vision, language, and robotics, pushing the boundaries of AI capabilities and providing crucial insights for future AI model development and technological innovation. These findings are intended to guide the field through the emerging challenges of the rapidly evolving Generative AI landscape.

Impact of Home Telehealth Expansion on High-Cost Utilization Among Veterans Health Administration Patients with Diabetes.

Home telehealth (HT) services have rapidly expanded in the Veterans Health Administration (VHA), but little is known about the real-world impact of the expansion of these services on utilization. To evaluate the impact of expanding HT diabetes services in VHA on high-cost utilization. This cohort study used cross-temporal propensity score matching to identify patients with diabetes who would receive HT services (treatment group) with program expansion (treatment group) with a comparison group of patients with diabetes who did not receive HT services (control group) between 2010 and 2018. A difference-in-differences design was used to compare pre-post changes in high-cost utilization between propensity-matched groups. Data used was from the VHA's Corporate Data Warehouse. VHA patients with diabetes, n=7214 in the treatment group who received HT services, and n=1,067,138 in the control group who did not receive HT services. Emergency department (ED) visits, all-cause hospitalization, and hospitalizations for ambulatory care sensitive conditions (ACSCs). In the baseline period, patients in our sample had a mean age of 67 years old (SD=11 years), were 97% male, and 78% had a hemoglobin A1c (HbA1c) < 8%. The increase in HT use was associated with a net increase of ED visits per patient (0.215 95% CI [0.152, 0.279]), all-cause hospitalization (0.053 95% CI [0.032, 0.074]), and ACSC hospitalization (0.032 95% CI [0.019, 0.045]). Expanding HT or remote monitoring services may lead to additional needs being identified for patients, including increased access to in-person care, such as ED or hospital services.

A Novel Spring-Actuated Low-Velocity Impact Testing Setup

Evaluating the behavior of materials and their response under low-velocity dynamic impact (less than 30 m/s) is a challenging task in various industries. It requires customized test methods to replicate real-world impact scenarios and capture important material responses accurately. This study introduces a novel spring-actuated testing setup for low-velocity impact (LVI) scenarios, addressing the limitations of existing methods. The setup provides tunable parameters, including adjustable impactor mass (1 to 250 kg), velocity (0.1 to 32 m/s), and spring stiffness (100 N/m to 100 kN/m), allowing for flexible simulation of dynamic impact conditions. Validation experiments on steel plates with a support span of 800 mm and thickness of 5 mm demonstrated the system’s satisfactory accuracy in measuring impact forces (up to 714.2 N), displacements (up to 40.5 mm), and velocities. A calibration procedure is also explored to estimate energy loss using numerical modeling, further enhancing the test setup’s precision and utility. The results underline the effectiveness of the proposed experimental setup in capturing material responses during low-velocity impact events.

Quality of life improvement after radiotherapy for bone metastases assessed using real-world data: a secondary analysis of a Nationwide Multicenter Cohort Study.

Single-center studies or randomized controlled trials have evaluated the impact of radiotherapy for bone metastases on quality of life (QOL). We investigated the real-world impact of radiotherapy for bone metastases on QOL using nationwide multicenter cohort data. We conducted a prospective observational study at 26 centers in Japan. Of 333 patients who received radiotherapy for bone metastases between December 2020 and March 2021, 232 (70%) were enrolled in the study. Patient-reported QOL was evaluated at enrollment and at two- and six-month follow-up using the European Organization for Research and Treatment of Cancer (EORTC) QOL Questionnaire Core 15-Palliative and the EORTC QOL Questionnaire Bone Metastases module (QLQ-BM22). Possible predictors (patient-, tumor -, and treatment-related factors) of QOL improvement were screened using logistic regression models. QOL scores showed significant improvement at two-month follow-up in seven (global health status/QOL, emotional functioning, pain, insomnia, painful sites, pain characteristics and functional interference) of the 14 scales. Of these seven scales, mean improvement ≥ the minimal clinically important difference (defined by a change of 10 or more on the 0 to 100 scale) was seen in four scales (pain, insomnia, pain characteristics and functional interference). We did not find any predictors of QOL improvement in the functional interference scale of QLQ-BM22. Radiotherapy for bone metastases performed in daily practice is effective in improving some scales of QOL.

Post–crises capability development – the silver lining: learning from e-tailers’ adaptation to greater protection needs

Purpose This study draws lessons from e-tailer adaptations to the enhanced protection needs of employees and customers and capability development, during events such as social distancing causing crises (SDCC) and provides a conceptual framework. Design/methodology/approach A grounded theory-based approach has been used wherein 130 news articles and 48 journal papers were analyzed to understand the real-world measures and impact. Findings E-tailers adapt to provide their workforce an environment that caters to their increased need for physical and mental well-being and take measures for customers health protection. They also take initiatives toward mitigation of the high incidence of cyber fraud faced by the vulnerable customers. In the process, they develop several capabilities during and post-crises. Research limitations/implications The study focuses only on the impact of COVID-19 on e-tailing. This is a limitation and other industries and crises may be studied in the future. Practical implications The study holds significant potential for future research as the three research propositions offered can enable hypothesis generation for larger quantitative studies. The adaptation to the enhanced protection needs of employees and customers result in the development of several capabilities such as a more equitable work environment, a more loyal, productive and adaptable workforce, increased customer retention and acquisition and a better image. Hence this study has several organizational development practical implications as it provides managers lessons to survive and thrive from future crises. Originality/value Few studies have investigated e-tailers adaptations for enhanced protection needs of employees and customers and its impact during and after SDCC. This empirical study extends a body of literature which is scarce.

Impact of artificial intelligence on healthcare-associated infection control: a systematic review

Abstract Background Healthcare-associated infections (HAIs) represent a significant public health concern, correlating with increased morbidity, mortality rates and healthcare expenditures. While artificial intelligence (AI) systems offer transformative potential in enhancing HAIs detection and control practices, the actual performance effectiveness of these systems remains uncertain. This systematic review updates a previously published study from 2020 and evaluates the performance of AI-based tools for surveillance, detection, and control of HAIs. Methods PRISMA 2020 guidelines were applied. The study protocol has been registered in PROSPERO (ID: CRD42024513145). PubMed, Embase, Scopus and Web of Science were searched for experimental and observational studies assessing the performance of AI-based tools to detect and control HAIs, published in English. Results From 8,701 articles initially identified, 4,212 records were removed due to duplication. Out of 4,489 papers screened, 147 were included. Studies reported performance measures including sensitivity, specificity, positive and negative predictive values, area under the receiver operating characteristic curve, accuracy, precision, F1 score. Significant heterogeneity was found in the types of technology, infections targeted, health care settings and data sources between studies. Conclusions The increase in published evidence since the previous review reflects the growing interest and use of new technologies such as Large Language Models, showing promising performance in surveillance, early diagnosis and prediction of HAIs. However, the observed heterogeneity in study designs, targeted infections, healthcare settings, and data sources underscores the need for standardised methodologies and robust validation processes to ensure the reliability and comparability of results across different studies. Key messages • The use of AI-based tools has the potential to enhance surveillance, detection, and control of healthcare-associated infections, offering a transformative impact on healthcare systems. • Standardised methodologies and validation processes are needed to ensure comparable results across studies and to maximise the real-world impact of AI tools in HAI surveillance and control efforts.

Clinical outcomes and impact of mitral valve surgery in atrial functional mitral regurgitation: the REVEAL-AFMR registry

Abstract Background The real-world impact and effective treatment strategies of atrial functional mitral regurgitation (AFMR) are poorly understood. The aim of this study was to investigate the prevalence, clinical characteristics, and the effectiveness of mitral valve surgery in AFMR. Methods The REal-world obserVational study for invEstigAting the prevaLence and therapeutic options for Atrial Functional Mitral Regurgitation (REVEAL-AFMR) was a retrospective cohort study conducted across 26 Japanese centers. All transthoracic echocardiography performed in 2019 were reviewed and patients with moderate or severe AFMR defined by preserved left ventricular function, dilated left atrium, and absence of degenerative valvular changes. The primary composite outcomes were heart failure hospitalization and all-cause mortality. Besides traditional multivariable regression analysis, propensity score-based time-zero matching was performed to account for immortal time bias. Results In 177,235 patients who underwent echocardiography, 8,867 had moderate or severe MR. Within this group, 1,007 were diagnosed with AFMR (mean age 78±10, 56% female, 80% atrial fibrillation). Of these, 113 underwent MV surgery, with 81% receiving concurrent tricuspid valve surgery. Patients who underwent surgery were younger but had more severe MR, larger left heart chambers, and a higher prevalence of heart failure than those who remained under medical therapy. During a median follow-up of 1050 days, 28% experienced the primary outcome, and 18% died. Despite a more severe disease status, only the surgical group showed a decrease in natriuretic peptide levels at follow-up and had significantly lower rate of the primary outcome (hazard ratio 0.43 [0.29-0.64], p&amp;lt;0.001 after adjustment for 25 covariates). Propensity score-based time-zero matching also indicated a lower risk of the primary outcome in the surgical group (hazard ratio 0.39 [0.20–0.78], p=0.007). Multiple sensitivity analyses yielded consistent results. Subgroup analysis suggested a significantly greater benefit of surgery for patients with severe MR than those with non-severe MR (p for interaction=0.044). Conclusions Our registry revealed that patients with AFMR are typically old with predominantly with atrial fibrillation, facing poor outcomes. MV surgery was associated with fewer adverse events, a finding that should be validated in future clinical trials.

GST Impact: Perspectives from Registered Traders’ in District Kangra, Himachal Pradesh

This research paper evaluates traders' perceptions of the Goods and Services Tax (GST) and its impact on business operations in District Kangra, Himachal Pradesh. A structured questionnaire was utilized to conduct a comprehensive survey involving four hundred respondents. The focus was on key aspects such as tax simplification, interstate and intrastate trade, pricing strategies, profit margins, transparency in tax collection, and accounting processes. The findings reveal a generally positive perception of GST, particularly in terms of its role in simplifying taxation and enhancing trade efficiency. However, challenges remain, especially concerning compliance issues and fluctuations in profit margins. To improve trader experiences, the study recommends targeted training programs, streamlined compliance processes, and the establishment of effective feedback mechanisms. These insights contribute to a deeper understanding of the real-world impact of GST on business operations and highlight essential areas for future improvement, underscoring the need for continuous support in adapting to the evolving tax landscape.

Post-deployment performance of a deep learning algorithm for normal and abnormal chest X-ray classification: A study at visa screening centers in the United Arab Emirates

BackgroundChest radiographs (CXRs) are widely used to screen for infectious diseases like tuberculosis and COVID-19 among migrants. At such high-volume settings, manual CXR reporting is challenging and integrating artificial intelligence (AI) algorithms into the workflow help to rule out normal findings in minutes, allowing radiologists to focus on abnormal cases. MethodsIn this post-deployment study, all the CXRs acquired during the visa screening process across 33 centers in United Arab Emirates from January 2021 to June 2022 (18 months) were included. The qXR v2.1 chest X-ray interpretation software was used to classify the scans into normal and abnormal, and its agreement against radiologist was evaluated. Additionally, a digital survey was conducted among 20 healthcare professionals with prior AI experience to understand real-world implementation challenges and impact. ResultsThe analysis of 1309,443 CXRs from 1309,431 patients (median age: 35 years; IQR [29–42]; 1030,071 males [78.7 %]) in this study revealed a Negative Predictive Value (NPV) of 99.92 % (95 % CI: 99.92, 99.93), Positive Predictive Value (PPV) of 5.06 % (95 % CI: 4.99, 5.13) and overall percent agreement of the AI with radiologists of 72.90 % (95 % CI: 72.82, 72.98). In the survey, majority (88.2 %) of the radiologists agreed to turnaround time reduction after AI integration, while 82 % suggested that the AI improved their diagnostic accuracy. DiscussionIn contrast with the existing studies, this research uses a substantially large data. A high NPV and satisfactory agreement with human readers indicate that AI can reliably identify normal CXRs, making it suitable for routine applications.

Post-marketing study design to evaluate the effectiveness of the 9-valent and 4-valent HPV vaccines on serious HPV-related cervical disease in China.

The 4-valent (4 v) and 9-valent (9 v) human papillomavirus (HPV) vaccines are approved in China for females aged 9-45 years. However, the real-world impact of 4vHPV or 9vHPV vaccination for the prevention of high-grade cervical disease in Chinese women is lacking. Two post-marketing surveillance studies will be conducted to measure the occurrence of high-grade cervical lesions in Chinese women who had received ≥1 dose of the 4vHPV (aged 20-45 years) or 9vHPV (aged 16-26 years) vaccine in Ningbo, China. Vaccination data will be extracted from the Ningbo Regional Health Information Platform (NRHIP) from the date of the first 4vHPV (January 9, 2018) or the first 9vHPV (January 25, 2019) vaccination to March 31, 2021. The primary 4vHPV and 9vHPV vaccinated cohorts will include women vaccinated per protocol. The 4vHPV/9vHPV vaccinated test-negative (cervical HPV negative; ThinPrep cytology test negative) and corresponding matched unvaccinated HPV test-negative sub-cohorts will also be assessed. Outcomes will be the occurrence of new-onset cervical intraepithelial neoplasia grade 2/3, adenocarcinoma in situ, and invasive cervical cancer. This study aims to demonstrate that such a methodological approach is feasible and can be used to assess the impact of HPV vaccination in other regions across China.

Real world comparison of filgrastim to filgrastim-sndz in patients with chemotherapy-induced neutropenia.

There exists some apprehension by prescribers, healthcare providers, and other stakeholders regarding the real-world safety and effectiveness of biosimilars. While some of the apprehension is likely due to clinician knowledge gaps in the biosimilarity exercise, additional data (including those generated from the real-world) regarding safety and efficacy could reduce a clinician's perception of biosimilar uncertainty and can potentially increase biosimilar acceptance and uptake. The published literature is lacking regarding the real-world impact on healthcare costs and clinical outcomes when a single healthcare institution converts from filgrastim to filgrastim-sndz as its short-acting Granulocyte Colony Stimulating Factor (GCSF), especially within diverse populations and indications not explicitly studied through the registration trials. Specifically, both filgrastim and filgrastim-sndz possess FDA-approved indications within patients with hematologic malignancies receiving high-dose chemotherapy and in those undergoing bone marrow transplantation. As a biosimilar to filgrastim, the FDA did not require prospective, randomized controlled trials to obtain these indications for filgrastim-sndz. The purpose of this study is to describe real-world healthcare resource costs, utilization patterns, and clinical outcomes in patients with hematologic malignancies who received filgrastim-sndz or filgrastim to support neutrophil recovery following chemotherapy (i.e., induction or consolidation) or a bone marrow transplant (BMT) at Yale New Haven Hospital (YNHH). A total of 148 patients were identified and met the following criteria: at least 18 years old, Eastern Cooperative Oncology Group (ECOG) performance status of 0 to 2, absence of fever or infection, newly diagnosed acute myeloid leukemia or newly post-bone marrow transplant and received filgrastim-sndz (Zarxio®) or reference filgrastim (Neupogen®). Healthcare resource utilization outcomes were compared between biosimilar and reference filgrastim using descriptive statistics. There were no major differences between either cohort, including duration of hospitalization, the number of overall emergency room visits and additional hospital admissions with a primary diagnosis of febrile neutropenia or neutropenia within 30 days post-discharge from initial hospital admission, time to neutrophil recovery following GCSF support, and the incidence and duration of both fever and febrile neutropenia. The total cost based on treatment of all patients in each arm differed significantly with filgrastim-sndz being the most cost-effective choice. filgrastim-sndz significantly reduced healthcare utilization costs compared to reference filgrastim with similar effect on absolute neutrophil count, incidence of fever, and febrile neutropenia.

Outcomes of Providing Children Aged 7-12 Years With Access to Evidence-Based Anxiety Treatment Via a Standalone Digital Intervention Using Immersive Gaming Technology: Real-World Evaluation.

Anxiety disorders are among the most common mental health conditions in childhood, but most children with anxiety disorders do not access evidence-based interventions. The delivery of therapeutic interventions via digital technologies has been proposed to significantly increase timely access to evidence-based treatment. Lumi Nova (BfB Labs Limited) is a digital therapeutic intervention designed to deliver evidence-based anxiety treatment for those aged 7-12 years through a mobile app incorporating immersive gaming technology. We aimed to evaluate the real-world impact of providing access to Lumi Nova through UK National Health Service-funded mental health services. We analyzed precollected anonymized data routinely captured through the implementation of Lumi Nova from children aged 7-12 years, who lived in the United Kingdom and had the opportunity to use the intervention for at least 1 week over an 18-month period. Engagement indices included whether the game key was activated, number of unique sessions, time spent engaging, and number of "challenges" completed. Clinical outcomes were assessed using the Goal-Based Outcomes measure and Child Outcome Rating Scale. Demographic data were analyzed to assess the health equality implications of Lumi Nova. Of 1029 eligible families invited to use Lumi Nova, 644 (62.5%) activated their game key, of whom 374 (58.1%) completed at least one in-game graded exposure challenge. The median number of unique sessions was 6 (IQR 3-12) and the median time spent engaging with the intervention was 42 (IQR 15-79) minutes. For the subset of young people with paired outcomes, there were statistically significant small to medium improvements in goal-based outcome scores (n=224; t223=5.78, P<.001; d=0.37, 95% CI 0.25-0.52) and Child Outcome Rating Scale scores (n=123; t122=5.10, P<.001; d=0.46, 95% CI 0.27-0.65) between the first and last data points. Two in 5 young people's scores reflected a change that would be considered reliable. Analysis of demographic characteristics tentatively suggested that children from ethnic minority backgrounds and those living in the most deprived neighbourhoods may be less likely to access Lumi Nova, but children from socioeconomically deprived areas were more likely to successfully complete a challenge once they accessed the intervention (P=.02). However, the level of missing data and small number of children in some demographic groups limited meaningful statistical comparisons. This study provides initial evidence that Lumi Nova may be associated with improved outcomes for those aged 7-12 years seeking anxiety treatment in real-world settings. However, the lack of a control comparator group and information about concurrent treatments accessed by the young people, in addition to substantial attrition, limited the analysis that could be conducted and confidence in the conclusions drawn.

Intravenous iron staining: real-world incidence, preventability, and mitigation tools from a long-term quality improvement project.

Iron deficiency is the leading cause of anaemia worldwide and is increasingly treated with intravenous (IV) iron therapy. Staining from IV iron therapy is a rare but significant and preventable adverse event. To mitigate patient harm, a health-service-wide quality improvement project was implemented. This study aimed to determine the real-world impact of a quality improvement project on IV iron staining incidents and preventability. A retrospective chart audit was undertaken for all IV iron staining episodes reported in a directorate-wide clinical incident reporting database (RiskMan) between 2016 and 2022. Incidence rates of IV iron staining, preventability, and stain severity were compared pre- and post-implementation of a standardized IV iron procedure. Over 7 years, 103 IV iron stains were identified, resulting in a staining rate of 0.31 stains per 100 infusions (pre 0.27% and post 0.34%, P = .25). Implementation of the standardized IV iron procedure resulted in improvements in pharmacist review of the medication order (61.8% versus 89.7%, P < .01), use of the statewide IV iron infusion consent form (27.3% versus 76.9%, P < .01), and appropriate cannula site (14.3% versus 52.5%, P < .01). Smaller stain sizes were associated with cessation of the infusion at identification of extravasation (312 cm2 versus 35 cm2) (P = .04). Preventability was assigned to 86% of stains. The incidence rate of IV iron staining in a real-world clinical setting is 0.31%. There was increased compliance with several best practice principles and 86% of stains were preventable. Early identification and intervention of potential staining incidents results in smaller iron stains for patients. Quality improvement tools developed for this project can contribute to patient outcomes internationally.

Development of a Building Evaluation Framework for Biophilic Design in Architecture

Biophilic design has gained prominence in architecture as a strategy to integrate natural elements into built environments, aiming to improve human comfort, well-being, and environmental sustainability. This paper critically reviews existing biophilic design frameworks, identifying gaps in their integration of health outcomes and the relationship between indoor and outdoor environments, with a primary focus on indoor environmental quality (IEQ) factors such as air quality, natural light, thermal comfort, and acoustics. The review was conducted systematically, comparing frameworks using criteria such as health benefits, human–nature connections, and user satisfaction. Key findings highlight a lack of comprehensive frameworks that explicitly link biophilic design to measurable improvements in human health, comfort, and satisfaction. To address this gap, the study proposes an enhanced biophilic design framework that bridges IEQ-focused indoor environments with urban outdoor elements, prioritizing human comfort alongside environmental sustainability. The framework also emphasizes the role of post-occupancy evaluation (POE) in assessing the real-world performance of biophilic interventions, particularly in achieving user satisfaction and ensuring long-term effectiveness. This research contributes to the advancement of biophilic design by offering actionable strategies for architects, urban planners, and policymakers to adopt biophilic principles that create resilient, healthy, and sustainable spaces. Additionally, the study emphasizes the need for empirical testing and validation of the proposed framework, including POE and user surveys, to assess its real-world impact on human well-being and satisfaction, thus setting the stage for future research.

Clinical Utility of Neurophysiologic Classification (and Declassification) of Myoclonus.

Movement clinical neurophysiology studies can distinguish myoclonus, tremor, and other jerky movements; however, there has been limited demonstration of their real-world clinical impact. The aim was to investigate movement study utility in clarifying movement classification and guiding patient management. A retrospective study of myoclonus-related movement studies was performed. Of 262 patients referred for consideration of myoclonus, 105 (40%) had myoclonus, 156 (59%) had no myoclonus (the commonest alternative classifications were functional jerks and tremor), and 1 was uncertain. An additional 29 studies identified myoclonus without prior clinical suspicion. A total of 119 of 134 (89%) myoclonus patients had a specific neurophysiologic subtype identified, most commonly cortical (64, 54%). Diagnostic differential narrowed in 60% of patients, and a new diagnosis was made in 42 (14%) patients. Medication changes were made in 151 patients (52%), with improvement in 35 of 51 (67%) with follow-up. Movement studies effectively determined movement classification and identified unsuspected myoclonus, leading to changes in diagnosis and management. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Translating business research to practice: bridging the gap for real-world impact

Translating business research to practice: bridging the gap for real-world impact

Albuminuria-based stratification of end-stage kidney disease progression and mortality with sodium-glucose cotransporter 2 inhibitors (SGLT2i): A retrospective cohort study in type 2 diabetes and chronic kidney disease.

Clinical trials have shown the kidney-protective benefits of sodium-glucose cotransporter 2 inhibitors (SGLT2i). However, their real-world impact, particularly across varying levels of albuminuria, remains less well understood. This study aimed to evaluate the association of SGLT2i, compared with other oral glucose-lowering drugs, with end-stage kidney disease (ESKD) progression in patients with type 2 diabetes and chronic kidney disease (CKD) stratified by urine albumin-to-creatinine ratio (UACR) levels. Using data from a national database spanning from 2016 to 2021, the study included patients with type 2 diabetes and CKD with estimated glomerular filtration rates (eGFRs) below 60 mL/min/1.73 m2 and who started on SGLT2i or other oral glucose-lowering drugs. Patients were stratified into groups by UACR ≥300 mg/g and <300 mg/g. Propensity score matching was used to minimize confounding, and progression to ESKD was evaluated using competing risks and Cox proportional-hazards models. All-cause mortality was also analyzed. Following propensity score matching, 18,514 patients in the severely increased albuminuria group (UACR ≥300 mg/g) were tracked, with 2.6% progressing to ESKD over 3 years. In contrast, only 0.3% of the 26,946 patients with UACR <300 mg/g progressed to ESKD. SGLT2i use was associated with a 30% reduction in risk of ESKD progression, compared with the use of other oral glucose-lowering drugs, in the severely increased albuminuria group (hazard ratio[HR]: 0.70, 95% confidence interval [CI]: 0.61-0.80). In the lower albuminuria group, no significant association was evident, though there was a nonsignificant trend toward protection over time. A consistent reduction in mortality risk was observed across all albuminuria levels. SGLT2i are associated with a reduction in the progression to ESKD among patients with severely increased albuminuria, with less pronounced effects observed in those with lower albuminuria levels, suggesting variability in renal outcomes based on albuminuria severity. The consistent survival benefit across all albuminuria levels supports the potential utility of SGLT2i in diabetes and CKD treatment strategies, emphasizing the need for more targeted research.

2024 International Conference on Education, Economics, Management, and Social Sciences(EMSS 2024)

Welcome to the official website of the 2024 International Conference on Education, Economics, Management, and Social Sciences (EMSS 2024), scheduled to take place from September 25-26, 2024 in Melbourne, Australia! EMSS 2024 offers a prestigious platform for scholars, educators, researchers, and practitioners in the fields of education, economics, management, and social sciences to share their latest research insights, innovative methodologies, and cutting-edge solutions. This conference serves as a global forum to foster interdisciplinary discussions, collaborations, and the exchange of ideas on some of the most critical and emerging issues in these fields. We are proud to gather participants from various sectors who will engage in thought-provoking discussions and debates on topics of major societal relevance, including advances in educational practices, economic strategies, management approaches, and social sciences. The conference aims to provide valuable contributions to both academic research and practical applications. EMSS 2024 is committed to highlighting original, high-quality research papers that advance theoretical understanding, offer practical implications, and contribute to policy-making. Each paper has been rigorously reviewed based on its technical merit, research significance, and real-world impact, ensuring a high standard of academic excellence. We would like to extend our deepest gratitude to the esteemed members of the technical and organizing committees, whose diligent efforts in reviewing and improving the submissions have significantly elevated the quality of the conference proceedings. Additionally, we express our heartfelt thanks to the authors for their contributions, collaboration in adhering to the conference guidelines, and for sharing their unique insights and innovative research. We look forward to the intellectual exchange, networking opportunities, and collaborative potential that EMSS 2024 will bring. We hope you enjoy the conference! EMSS 2024 Conference Chairs

The Impact of QT-Prolonging Medications and Drug-Drug Interactions on QTc Interval Prolongation in Hospitalized Patients: A Case-Crossover Study.

Researchers have studied potential corrected QT interval (QTc) prolongation from drug-drug interactions (DDIs), raising unresolved questions about their real-world impact. This retrospective case-crossover study investigated the effects of QT-prolonging drugs and DDIs on QTc prolongation in hospitalized patients aged 45 years and above. The cohort comprised patients who had multiple hospitalizations and developed QTc prolongation (QTc > 500 ms or an increase of >60 ms from baseline) at least 24 hours after admission between 2011 and 2019. Conditional logistic regression compared drug exposure between hospitalizations with QTc prolongation (case window) and those without (reference window). Among 2,276 patients (mean age 71; 43.8% female), the use of QT-prolonging drugs significantly increased the risk of QTc prolongation (odds ratio: 2.42 (95% confidence interval: 1.95-3.02)). The risk was higher with drugs of "known risks" (OR: 3.78 (2.91-4.90)) and "conditional risk" (OR: 2.08 (1.65-2.62)). DDIs, particularly involving multiple "known risk" drugs (OR: 7.86 (4.96-12.45)), strong cytochrome P450 enzyme inhibitors (OR: 5.57 (2.75-11.30)), or the concurrent use of ≥4 QT-prolonging drugs with any risk (OR: 5.28 (3.96-7.03)) substantially increased the risk. Cautious prescribing for patients with multiple risk factors is important to minimize the likelihood of QTc prolongation. However, when considering enhanced monitoring or drug choices, it is crucial to carefully evaluate the overall risk of QT prolongation against the benefits of treatment to ensure optimal patient care.