Medicine and Health Sciences Commons^™

A Comparison Of Concurrent Training And Moderate Intensity Continuous Training In Patients With Coronary Artery Disease, Amanda Alfaro-Chaverri, John Quindry, Charles Dumke, Brian Loyd

Graduate Student Theses, Dissertations, & Professional Papers

Moderate intensity continuous training (MICT) is the most studied method in cardiac rehabilitation (CR) for patients with coronary artery disease (CAD). Traditionally, resistance training has been utilized as a secondary role in CR. Recent interest in the topic suggests that MICT and resistance training should be applied collectively, an approach termed concurrent training (CT). The collective understanding of the potential of CT in CR patients is currently lacking.

Purpose: The aim of this professional paper is to analyze scientific evidence regarding the efficacy and safety of CT versus MICT. The analysis will focus on five primary measurements: exercise capacity, cardiovascular …

Reducing Mortality Among African American Mothers Related To Postpartum Hemorrhage By Implementing Early Education And Risk Assessments, Don'ya Truesdale

Theses and Dissertations

African American women are at the highest risk for hemorrhaging during childbirth (Okunlola, 2022). A hemorrhage can occur among postpartum mothers for many reasons, with the main causes being uterine atony, tissue trauma, and clotting issues. However, risks for Black mothers differ. The comorbid and social factors within the Black community greatly influence the likelihood of Black mothers experiencing postpartum hemorrhage. Additionally, the lack of assessment and attention catered towards those risk factors lead to an increased mortality among African American (AA) mothers compared to Caucasian mothers and all other ethnicities. Nonetheless, as maternal risk assessments and education increase, mortality …

A Scoping Review Of Perceptions And Fears Experienced By Families With Children With Developmental Disabilities In Sub-Saharan Africa., Isaac Twum Boamah

Theses and Dissertations

The prevalence of perception and fear surrounding families with children with developmental disabilities in Sub-Saharan Africa reveal a complex interplay of cultural, social, economic, and healthcare factors. This interplay of factors results in stigma, which often leads to societal misconceptions and discrimination, exacerbating the challenges faced by affected families. This study seeks to identify the individual and family perception of developmental disabilities, document the stigma experienced by the individual and their families, and document the resources available to help alleviate the plight faced by the individuals and their families. It further seeks to find gaps in the literature on developmental …

Medical Students Attending Schools Along The Us-Mexico Border: Experiences From Bilingual And Monolingual Students, Roger Banda Jr, Aaron Silva, Ney Alliey Rodriguez

MEDI 9331 Scholarly Activities Clinical Years

We present a study that aims to capture experiences of bilingual and monolingual medical students exposed to patient populations with limited English proficiency along the US-Mexico border. The study surveyed US-Medical students at The University of Texas Rio Grande Valley in the clerkship years of medical education. A total of 121 medical students were surveyed consisting of both bilingual and monolingual students of which 32 responded (26%). Of the students surveyed, 0% reported being certified as medical language interpreters. 24% reported feeling somewhat uncomfortable and 10% extremely uncomfortable while interpreting, 48% reported sometimes making errors in translation, and 33% reported …

The Oral-Microbiome-Brain Axis: A Thorough Review On The Relationship Between Periodontitis And Alzheimer’S Disease And A Proposed Innovative Application Of Biomagnetism As A Means Of Alternative Therapy., Taha Al Hassan, Noah Al-Hassan, Maria Quiñones-Peña, Juan Lopez-Alvarenga, Seratna Guadarrama-Beltran

MEDI 9331 Scholarly Activities Clinical Years

The relationship between periodontitis and Alzheimer's disease (AD) has garnered significant attention due to the potential influence of chronic oral inflammation on neurodegenerative processes. Our hypothesis is supported by the oral-microbiome-brain axis and highlights the possibility that chronic periodontitis contributes to cognitive decline by promoting systemic inflammation and neuroinflammation, mediated by specific pathogenic microorganisms within the oral microbiome. Our findings reveal a strong association between elevated levels of Porphyromonas gingivalis and Treponema denticola, red complex bacteria, and markers of systemic inflammation, such as C-reactive protein (CRP) and pro-inflammatory cytokines. Additionally studies have demonstrated that beta amyloid plaque in rat …

Characterizing Nanopore Sequencing Artifacts With Deep Learning, David Zhou

Master's Projects

Oxford Nanopore sequencing is a revolutionary new technology for sequencing DNA molecules in long stretches. However, it has a significantly higher error rate than conventional short-read sequencing, resulting in numerous sequencing artifacts. These artifacts can be indistinguishable from low frequency somatic variants, which is a roadblock for cancer diagnosis using liquid biopsies. In this study, benchmarked human genome samples from Genome in a Bottle were used to create a dataset of labeled variants, including artifacts and true variants. Variant features, including sequence context, were used to train various deep learning models. The multi-input neural network combining sequence context features and …

Response To Intervention: The Effect Of Sensory Processing Tier 1 And Tier 2 Occupational Therapy Intervention, Workshops & Consultation On Kindergarten Students, Kieran Bolger, Cindy Zhang, Julia Dariychuk, Janine Yu, Zuriel Chester

Master's Projects

Sensory modulation is critical for self-regulation in learning environments where children may experience unexpected or atypical sensory stimuli leading to disruptive behaviors often misunderstood or misinterpreted by teachers (Mac Donald & Baist, 2021; Smith & Douglass, 2022). Teachers often lack understanding of sensory processing and evidence-based strategies to address the behavioral challenges related to sensory processing (Cahill et al., 2014; Gee & Nwora, 2011; Mac Donald & Baist, 2021). Occupational therapists practitioners (OTPs) are beneficial team members that are skilled in addressing sensory processing (Cahill, 2010) and can partner with teachers to increase their understanding and utilization of sensory processing …

Isokinetic Testing: Why It Is More Important Today Than Ever, Kevin E. Wilk, Christopher A. Arrigo, George J. Davies

Physical Therapy Faculty Publications

Isokinetics is a proven method to train and objectively assess the capability of muscle groups, particularly at the knee. The current re-injury rates and less than optimal return to sport percentages seen following anterior cruciate ligament surgery highlights the need for greater focus on what tests and methods are used to make these critical decisions. Isokinetics remains the best single method to objectively determine dynamic muscle strength, power, rate of force development and endurance. These factors make it well-suited to play a crucial role in influencing the appropriate patient progression through a rehabilitation program and assisting in determining return to …

Protein-Centric Omics Analysis Reveals Circulating Complements Linked To Non-Viral Liver Diseases As Potential Therapeutic Targets, Yingzhou Shi, Hang Dong, Shiwei Sun, Xiaoqin Wu, Jiansong Fang, Jianbo Zhao, Junming Han, Zongyue Li, Huixiao Wu, Luna Liu, Wanhong Wu, Yang Tian, Guandou Yuan, Xiude Fan, Chao Xu

Faculty, Staff and Student Publications

BACKGROUND/AIMS: To evaluate the causal correlation between complement components and non-viral liver diseases and their potential use as druggable targets.

METHODS: We conducted Mendelian randomization (MR) to assess the causal role of circulating complements in the risk of non-viral liver diseases. A complement-centric protein interaction network was constructed to explore biological functions and identify potential therapeutic options.

RESULTS: In the MR analysis, genetically predicted levels of complement C1q C chain (C1QC) were positively associated with the risk of autoimmune hepatitis (odds ratio 1.125, 95% confidence interval 1.018-1.244), while complement factor H-related protein 5 (CFHR5) was positively associated with the risk …

Disentangling Accelerated Cognitive Decline From The Normal Aging Process And Unraveling Its Genetic Components: A Neuroimaging-Based Deep Learning Approach, Yulin Dai, Yu-Chun Hsu, Brisa S Fernandes, Kai Zhang, Xiaoyang Li, Nitesh Enduru, Andi Liu, Astrid M Manuel, Xiaoqian Jiang, Zhongming Zhao, Alzheimer’S Disease Neuroimaging Initiative

Faculty, Staff and Student Publications

BACKGROUND: The progressive cognitive decline, an integral component of Alzheimer's disease (AD), unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and AD between different chronological points.

OBJECTIVE: To disentangle the normal aging effect from the AD-related accelerated cognitive decline and unravel its genetic components using a neuroimaging-based deep learning approach.

METHODS: We developed a deep-learning framework based on a dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. …

Preparing Healthcare Education For An Ai-Augmented Future, Jiajie Zhang, Susan H Fenton

Faculty, Staff and Student Publications

Artificial intelligence (AI) fundamentally transforms healthcare education as a knowledge enterprise, creating a distributed cognitive system composed of the human brain, which remains relatively unchanged, and AI-based knowledge and cognitive functions, which have accelerated exponentially in scale and power. Education must focus on developing skills to collaborate with AI and on achieving outcomes like problems solved and discoveries made. Curriculum and education policies also need to adapt to this transformation.

Statins Are Rarely Prescribed For Incidentally Discovered Covert Cerebrovascular Disease: A Retrospective Cohort In A Large Electronic Health Record (Ehr) Identified Using Natural Language Processing, Lester Y Leung, Eric Puttock, David F Kallmes, Patrick Luetmer, Sunyang Fu, Chengyi X Zheng, Hongfang Liu, Wansu Chen, David M Kent

Faculty, Staff and Student Publications

Introduction: While incidentally discovered covert cerebrovascular diseases (id-CCD) are associated with future stroke, it is not known if patients with id-CCD are prescribed statins.

Methods: Patients age ≥50 with id-CCD on neuroimaging from 2009 to 2019 with no prior ischaemic stroke, transient ischaemic attack or dementia were identified using natural language processing in a large real-world cohort. Robust Poisson multivariable regression was used to assess statin prescription among patients without prior statins.

Results: Among 2 41 050 patients, 74 975 patients (31.1%; 4.7% with covert brain infarcts (CBI); 29.0% with white matter disease (WMD)) had id-CCD. 53.5% (95% CI 53.2 …

The Enact Network Is Acting On Housing Instability And The Unhoused Using The Open Health Natural Language Processing Toolkit, Daniel R Harris, Sunyang Fu, Andrew Wen, Alexandria Corbeau, Darren Henderson, Jordan Hilsman, David Oniani, Yanshan Wang

Faculty, Staff and Student Publications

Housing is an environmental social determinant of health that is linked to mortality and clinical outcomes. We developed a lexicon of housing-related concepts and rule-based natural language processing methods for identifying these housing-related concepts within clinical text. We piloted our methods on several test cohorts: a synthetic cohort generated by ChatGPT for initial infrastructure testing, a cohort with substance use disorders (SUD), and a cohort diagnosed with problems related to housing and economic circumstances (HEC). Our methods successfully identified housing concepts in our ChatGPT notes (recall = 1.0, precision = 1.0), our SUD population (recall = 0.9798, precision = 0.9898), …

Descriptor:Benchmarking Secure Neural Network Evaluation Methods For Protein Sequence Classification (Idash24), Arif Harmanci, Luyao Chen, Miran Kim, Xiaoqian Jiang

Faculty, Staff and Student Publications

To uniformly test and benchmark the secure evaluation of transformer-based models, we designed the iDASH24 homomorphic encryption track dataset. The dataset comprises a protein family classification model with a transformer architecture and an example dataset that is used to build and test the secure evaluation strategies. This dataset was used in the challenge period of iDASH24 Genomic Privacy Competition, where the teams designed secure evaluation of the classification model using a homomorphic encryption scheme. Combined with the benchmarking results and companion methods, iDASH24 dataset is a unique resource that can be used to benchmark secure evaluation of neural network models.

Feasible Diet And Circadian Interventions Reduce In Vivo Progression Of Flt3-Itd-Positive Acute Myeloid Leukemia, Megan Rodriguez, Baharan Fekry, Brianna Murphy, Mary Figueroa, Tiewei Cheng, Margaret Raber, Lisa Wartenberg, Donna Bell, Lisa Triche, Karla Crawford, Huaxian Ma, Kendra Allton, Ruwaida Ahmed, Jaime Tran, Christine Ranieri, Marina Konopleva, Michelle Barton, Cesar Nunez, Kristin Eckel-Mahan, Joya Chandra

Faculty, Staff and Student Publications

BACKGROUND: Acute myeloid leukemia (AML) with an internal tandem duplication in the fms-like tyrosine kinase receptor 3 gene (FLT3-ITD) is associated with poor survival, and few studies have examined the impact of modifiable behaviors, such as nutrient quality and timing, in this subset of acute leukemia.

METHODS: The influence of diet composition (low-sucrose and/or low-fat diets) and timing of diet were tested in tandem with anthracycline treatment in orthotopic xenograft mouse models. A pilot clinical study to test receptivity of pediatric leukemia patients to macronutrient matched foods was conducted. A role for the circadian protein, BMAL1 (brain and muscle ARNT-like …

Transdisciplinary Perspectives For Health Systems Science, Jiang Bian, Nan Liu, Shauna M Overgaard, Rema Padman, Peter A D Steel, Victoria Tiase, Clifford Alan Whitcomb, Jiajie Zhang, Yiye Zhang

Faculty, Staff and Student Publications

Health systems science uses systems thinking as part of a transdisciplinary approach that transcends traditional disciplinary boundaries. It integrates and synthesizes knowledge from multiple disciplines to address real-world problems in healthcare with pragmatic solutions. This editorial defines health systems from the perspectives of systems thinking, science, and engineering, discusses their current challenges and opportunities, and envisions how health systems science as a field can advance the continuous learning and improvement of health systems.

Prioritizing Clinically Significant Lung Cancer Somatic Mutations For Targeted Therapy Through Efficient Ngs Data Filtering System, Jinlian Wang, Hui Li, Hongfang Liu

Faculty, Staff and Student Publications

In the realm of lung cancer treatment, where genetic heterogeneity presents formidable challenges, precision oncology demands an exacting approach to identify and hierarchically sort clinically significant somatic mutations. Current Next-Generation Sequencing (NGS) data filtering pipelines, while utilizing various external databases for mutation screening, often fall short in comprehensive integration and flexibility needed to keep pace with the evolving landscape of clinical data. Our study introduces a sophisticated NGS data filtering system, which not only aggregates but effectively synergizes diverse data sources, encompassing genetic variants, gene functions, clinical evidence, and an extensive body of literature. This system is distinguished by a …

Sequencing Conversational Turns In Peer Interactions: An Integrated Approach For Evidence-Based Conversational Agent For Just-In-Time Nicotine Cravings Intervention, Tavleen Singh, Michael Truong, Kirk Roberts, Sahiti Myneni

Faculty, Staff and Student Publications

BACKGROUND: Risky health behaviors place an enormous toll on public health systems. While relapse prevention support is integrated with most behavior modification programs, the results are suboptimal. Recent advances in artificial intelligence (AI) applications provide us with unique opportunities to develop just-in-time adaptive behavior change solutions.

METHODS: In this study, we present an innovative framework, grounded in behavioral theory, and enhanced with social media sequencing and communications scenario builder to architect a conversational agent (CA) specialized in the prevention of relapses in the context of tobacco cessation. We modeled peer interaction data (n = 1000) using the taxonomy of behavior …

Linking Cancer Clinical Trials To Their Result Publications, Evan Pan, Kirk Roberts

Faculty, Staff and Student Publications

The results of clinical trials are a valuable source of evidence for researchers, policy makers, and healthcare professionals. However, online trial registries do not always contain links to the publications that report on their results, instead requiring a time-consuming manual search. Here, we explored the application of pre-trained transformer-based language models to automatically identify result-reporting publications of cancer clinical trials by computing dense vectors and performing semantic search. Models were fine-tuned on text data from trial registry fields and article metadata using a contrastive learning approach. The best performing model was PubMedBERT, which achieved a mean average precision of 0.592 …

Community Scientist Program Provides Bi-Directional Communication And Co-Learning Between Researchers And Community Members, Jessica Alvarado, Larkin L Strong, Birnur Buzcu-Guven, Leonetta B Thompson, Erica Cantu, Chelsea C Carrier, Chiamaka D Chukwu, Cassandra L Harris, Luz K Melendez, Crystal L Roberson, Angela M Ross, Sophia C Russell, Pablo Sanchez, Amirali Tahanan, Blair C Zdenek, Belinda M Reininger, Lorna H Mcneill

Faculty, Staff and Student Publications

Community involvement in research is key to translating science into practice, and new approaches to engaging community members in research design and implementation are needed. The Community Scientist Program, established at the MD Anderson Cancer Center in Houston in 2018 and expanded to two other Texas institutions in 2021, provides researchers with rapid feedback from community members on study feasibility and design, cultural appropriateness, participant recruitment, and research implementation. This paper aims to describe the Community Scientist Program and assess Community Scientists' and researchers' satisfaction with the program. We present the analysis of the data collected from 116 Community Scientists …

New-Onset Diabetes Is A Predictive Risk Factor For Pancreatic Lesions In High-Risk Individuals: An Observational Cohort Study, Seyda Baydogan, Chirayu Mohindroo, Merve Hasanov, Maria F Montiel, Pompeyo Quesada, Irina M Cazacu, Adrianna A Luzuriaga Chavez, Maureen E Mork, Wenli Dong, Lei Feng, Y Nancy You, Banu Arun, Eduardo Vilar, Powel Brown, Matthew H G Katz, Suresh T Chari, Anirban Maitra, Eric P Tamm, Michael P Kim, Manoop S Bhutani, Florencia Mcallister

Faculty, Staff and Student Publications

BACKGROUND AND OBJECTIVES: Pancreatic cancer (PC) is the third cause of cancer-related deaths. Early detection and interception of premalignant pancreatic lesions represent a promising strategy to improve outcomes. We evaluated risk factors of focal pancreatic lesions (FPLs) in asymptomatic individuals at hereditary high risk for PC.

METHODS: This is an observational single-institution cohort study conducted over a period of 5 years. Surveillance was performed through imaging studies (EUS or magnetic resonance imaging/magnetic resonance cholangiopancreatography) and serum biomarkers. We collected demographic characteristics and used univariate and multivariate logistic regression models to evaluate associations between potential risk factors and odd ratios (ORs) …

Systemic Treatment Of Patients With Metastatic Breast Cancer: Asco Resource-Stratified Guideline Q And A, Sana Al Sukhun, Bogda Koczwara, Sarah Temin, Banu K Arun

Faculty, Staff and Student Publications

The Systemic Treatment of Patients with Metastatic Breast Cancer: @ASCO Resource-Stratified Guideline Q and A presents takeways, rationale, and key recommendations based on #JCOGO full guideline for patients by menopausal and marker status.

Developing Medical Genetics In A Low-Income Country: Unveiling The Journey Of The Pakistani Society Of Medical Genetics And Genomics (Psmg), Aisha Furqan, Syed A Ahmed, Rizwan Naeem, Myla Ashfaq

Faculty, Staff and Student Publications

No abstract provided.

Human Equilibrative Nucleoside Transporter 1: Novel Biomarker And Prognostic Indicator For Patients With Gemcitabine-Treated Pancreatic Cancer, Jianchun Xiao, Fangyu Zhao, Wenhao Luo, Gang Yang, Yicheng Wang, Jiangdong Qiu, Yueze Liu, Lei You, Lianfang Zheng, Taiping Zhang

Faculty, Staff and Student Publications

AIM: This article aimed to find appropriate pancreatic cancer (PC) patients to treat with Gemcitabine with better survival outcomes by detecting hENT1 levels.

METHODS: We collected surgical pathological tissues from PC patients who received radical surgery in our hospital from September 2004 to December 2014. A total of 375 PC tissues and paired adjacent nontumor tissues were employed for the construction of 4 tissue microarrays (TMAs). The quality of the 4 TMAs was examined by HE staining. We performed immunohistochemistry analysis to evaluate hENT1 expression in the TMAs. Moreover, we detected hENT1 expression level and proved the role of hENT1 …

Visualsphere: A Web-Based Interactive Visualization System For Clinical Research Data, Shiwei Lin, Shiqiang Tao, Wei-Chun Chou, Guo-Qiang Zhang, Xiaojin Li

Faculty, Staff and Student Publications

Clinical research data visualization is integral to making sense of biomedical research and healthcare data. The complexity and diversity of data, along with the need for solid programming skills, can hinder advances in clinical research data visualization. To overcome these challenges, we introduce VisualSphere, a web-based interactive visualization system that directly interfaces with clinical research data repositories, streamlining and simplifying the visualization workflow. VisualSphere is founded on three primary component modules: Connection, Configuration, and Visualization. An end-user can set up connections to the data repositories, create charts by selecting the desired tables and variables, and render visualization dashboards generated by …

Mouse Models Of Chronic Lymphocytic Leukemia And Richter Transformation: What We Have Learnt And What We Are Missing, Maria Teresa Sabrina Bertilaccio, Shih-Shih Chen

Faculty, Staff and Student Publications

Although the chronic lymphocytic leukemia (CLL) treatment landscape has changed dramatically, unmet clinical needs are emerging, as CLL in many patients does not respond, becomes resistant to treatment, relapses during treatment, or transforms into Richter. In the majority of cases, transformation evolves the original leukemia clone into a diffuse large B-cell lymphoma (DLBCL). Richter transformation (RT) represents a dreadful clinical challenge with limited therapeutic opportunities and scarce preclinical tools. CLL cells are well known to highly depend on survival signals provided by the tumor microenvironment (TME). These signals enhance the frequency of immunosuppressive cells with protumor function, including regulatory CD4

A Real-World Disproportionality Analysis Of Everolimus: Data Mining Of The Public Version Of Fda Adverse Event Reporting System, Bin Zhao, Yumei Fu, Shichao Cui, Xiangning Chen, Shu Liu, Lan Luo

Faculty, Staff and Student Publications

Background: Everolimus is an inhibitor of the mammalian target of rapamycin and is used to treat various tumors. The presented study aimed to evaluate the Everolimus-associated adverse events (AEs) through data mining of the US Food and Drug Administration Adverse Event Reporting System (FAERS).

Methods: The AE records were selected by searching the FDA Adverse Event Reporting System database from the first quarter of 2009 to the first quarter of 2022. Potential adverse event signals were mined using the disproportionality analysis, including reporting odds ratio the proportional reporting ratio the Bayesian confidence propagation neural network and the empirical Bayes geometric …

Comprehensive Analysis Of Craniopharyngioma: Epidemiology, Clinical Characteristics, Management Strategies, And Role Of Radiotherapy, Amir Mushtaq, Mohsin Fayaz, Abdul Rashid Bhat, Abbas F Abdul Hussein, Gianluca Ferini, Giuseppe Emmanuele Umana, Gianluca Scalia, Feroze Ahmad Mir, Aizul Khursheed, Bipin Chaurasia

Faculty, Staff and Student Publications

BACKGROUND/AIM: Craniopharyngiomas pose challenges in diagnosis and management due to their rare occurrence and diverse clinical manifestations. This study aimed to provide a comprehensive analysis of cranio-pharyngioma, including its epidemiological trends, clinical presentations, radiological characteristics, surgical interventions, and the role of radiotherapy.

PATIENTS AND METHODS: A retrospective observational study was conducted on 23 patients diagnosed with craniopharyngioma at our hospital from August 2017 to July 2019. Data regarding demographics, clinical presentation, radiological findings, surgical interventions, and adjuvant therapies were collected and analyzed.

RESULTS: Craniopharyngiomas exhibited a bimodal age distribution, with peaks in childhood and late adulthood. Clinical presentations varied between …

A Relay Velocity Model Infers Cell-Dependent Rna Velocity, Shengyu Li, Pengzhi Zhang, Weiqing Chen, Lingqun Ye, Kristopher W Brannan, Nhat-Tu Le, Jun-Ichi Abe, John P Cooke, Guangyu Wang

Faculty, Staff and Student Publications

RNA velocity provides an approach for inferring cellular state transitions from single-cell RNA sequencing (scRNA-seq) data. Conventional RNA velocity models infer universal kinetics from all cells in an scRNA-seq experiment, resulting in unpredictable performance in experiments with multi-stage and/or multi-lineage transition of cell states where the assumption of the same kinetic rates for all cells no longer holds. Here we present cellDancer, a scalable deep neural network that locally infers velocity for each cell from its neighbors and then relays a series of local velocities to provide single-cell resolution inference of velocity kinetics. In the simulation benchmark, cellDancer shows robust …

Linking Artificial Sweetener Intake With Kidney Function: Insights From Nhanes 2003-2006 And Findings From Mendelian Randomization Research, Zhuoling Ran, Yuxuan Zheng, Lin Yu, Yuxian Zhang, Zhenjiang Zhang, Huijie Li, Xuhan Li, Jing Song, Li Zhang, Ran Zhang, Chang Lu, Yang Gong, Jian Gong

Faculty, Staff and Student Publications

BACKGROUND: The current investigation examines the association between artificial sweetener (AS) consumption and the likelihood of developing chronic kidney disease (CKD), along with its impact on kidney function.

METHODS: We utilized data from the National Health and Nutrition Examination Survey from 2003-2006 to conduct covariance analysis and weighted adjusted logistic regression, aiming to assess the association between artificial sweetener intake and CKD risk, as well as kidney function indicators. Subsequently, we employed Mendelian randomization methods to validate the causal relationship between the intake of artificial sweeteners, CKD risk, and kidney function indicators. Instrumental variable analysis using inverse-variance weighting and Robust …