Medicine and Health Sciences Commons^™

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Carolina Rudisill, Alexander C. Mclain Ph.D.

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

A Bayesian Susceptible-Infectious-Hospitalized-Ventilated-Recovered Model To Predict Demand For Covid-19 Inpatient Care In A Large Healthcare System, Stella Coker Watson Self Ph.D., Ms, Rongjie Huang, Shrujan Amin, Joseph Ewing, Caroline Rudisill, Alexander C. Mclain

Faculty Publications

The COVID-19 pandemic has strained healthcare systems in many parts of the United States. During the early months of the pandemic, there was substantial uncertainty about whether the large number of COVID-19 patients requiring hospitalization would exceed healthcare system capacity. This uncertainty created an urgent need to accurately predict the number of COVID-19 patients that would require inpatient and ventilator care at the local level. As the pandemic progressed, many healthcare systems relied on such predictions to prepare for COVID-19 surges and to make decisions regarding staffing, the discontinuation of elective procedures, and the amount of personal protective equipment (PPE) …

Survival Of Epithelial Ovarian Cancer In Black Women: A Society To Cell Approach In The African American Cancer Epidemiology Study (Aaces), Joellen M. Schildkraut, Courtney Johnson, Lauren F. Dempsey, Bo Qin, Paul Terry, Maxwell Akonde, Edward S. Peters, Hannah Mandle, Michele L. Cote, Lauren Peres, Patricia Moorman, Ann G. Schwartz, Micheal Epstein, Jeffrey Marks, Melissa Bondy, Andrew B. Lawson, Anthony Alberg, Elisa V. Bandera

Faculty Publications

Purpose

The causes for the survival disparity among Black women with epithelial ovarian cancer (EOC) are likely multi-factorial. Here we describe the African American Cancer Epidemiology Study (AACES), the largest cohort of Black women with EOC.

Methods

AACES phase 2 (enrolled 2020 onward) is a multi-site, population-based study focused on overall survival (OS) of EOC. Rapid case ascertainment is used in ongoing patient recruitment in eight U.S. states, both northern and southern. Data collection is composed of a survey, biospecimens, and medical record abstraction. Results characterizing the survival experience of the phase 1 study population (enrolled 2010–2015) are presented.

Results …

Crisisready's Novel Framework For Transdisciplinary Translation: Case-Studies In Wildfire And Hurricane Response, Andrew Schroeder, Caleb Dresser, Akash Yadav, Jennifer Chan, Shenyue Jia, Caroline Buckee, Satchit Balsari

Institute for ECHO Articles and Research

Extreme weather events including wildfires and hurricanes are becoming increasingly hazardous due to climate change, and often result in transient or permanent population displacements. Disaster-related disruptions in infrastructure, workforce, wages, and social networks can combine with population displacements to result in interruptions in health care access and prolonged impacts on morbidity and mortality. The data needed to make health systems and emergency management approaches more resilient to these hazards, and more responsive to the needs of affected populations, are sequestered in silos across private corporations and public agencies. In two case studies, we describe how our research team at CrisisReady …

Detection Of Stroke With Retinal Microvascular Density And Self-Supervised Learning Using Oct-A And Fundus Imaging, Samiksha Pachade, Ivan Coronado, Rania Abdelkhaleq, Juntao Yan, Sergio Salazar-Marioni, Amanda Jagolino, Charles Green, Mozhdeh Bahrainian, Roomasa Channa, Sunil A Sheth, Luca Giancardo

Faculty, Staff and Student Publications

Acute cerebral stroke is a leading cause of disability and death, which could be reduced with a prompt diagnosis during patient transportation to the hospital. A portable retina imaging system could enable this by measuring vascular information and blood perfusion in the retina and, due to the homology between retinal and cerebral vessels, infer if a cerebral stroke is underway. However, the feasibility of this strategy, the imaging features, and retina imaging modalities to do this are not clear. In this work, we show initial evidence of the feasibility of this approach by training machine learning models using feature engineering …

Computer Clinical Decision Support That Automates Personalized Clinical Care: A Challenging But Needed Healthcare Delivery Strategy, Alan H Morris, Christopher Horvat, Brian Stagg, David W Grainger, Michael Lanspa, James Orme, Terry P Clemmer, Lindell K Weaver, Frank O Thomas, Colin K Grissom, Ellie Hirshberg, Thomas D East, Carrie Jane Wallace, Michael P Young, Dean F Sittig, Mary Suchyta, James E Pearl, Antinio Pesenti, Michela Bombino, Eduardo Beck, Katherine A Sward, Charlene Weir, Shobha Phansalkar, Gordon R Bernard, B Taylor Thompson, Roy Brower, Jonathon Truwit, Jay Steingrub, R Duncan Hiten, Douglas F Willson, Jerry J Zimmerman, Vinay Nadkarni, Adrienne G Randolph, Martha A Q Curley, Christopher J L Newth, Jacques Lacroix, Michael S D Agus, Kang Hoe Lee, Bennett P Deboisblanc, Frederick Alan Moore, R Scott Evans, Dean K Sorenson, Anthony Wong, Michael V Boland, Willard H Dere, Alan Crandall, Julio Facelli, Stanley M Huff, Peter J Haug, Ulrike Pielmeier, Stephen E Rees, Dan S Karbing, Steen Andreassen, Eddy Fan, Roberta M Goldring, Kenneth I Berger, Beno W Oppenheimer, E Wesley Ely, Brian W Pickering, David A Schoenfeld, Irena Tocino, Russell S Gonnering, Peter J Pronovost, Lucy A Savitz, Didier Dreyfuss, Arthur S Slutsky, James D Crapo, Michael R Pinsky, Brent James, Donald M Berwick

Faculty, Staff and Student Publications

How to deliver best care in various clinical settings remains a vexing problem. All pertinent healthcare-related questions have not, cannot, and will not be addressable with costly time- and resource-consuming controlled clinical trials. At present, evidence-based guidelines can address only a small fraction of the types of care that clinicians deliver. Furthermore, underserved areas rarely can access state-of-the-art evidence-based guidelines in real-time, and often lack the wherewithal to implement advanced guidelines. Care providers in such settings frequently do not have sufficient training to undertake advanced guideline implementation. Nevertheless, in advanced modern healthcare delivery environments, use of eActions (validated clinical decision …

An Imaging Mass Spectrometry Investigation Into The N-Linked Glycosylation Landscape Of Pancreatic Ductal Adenocarcinoma And The Development Of Associated Tools For Enhanced Glycan Separation And Characterization, Colin Mcdowell

MUSC Theses and Dissertations

The severity of pancreatic ductal adenocarcinoma (PDAC) is largely attributed to a failure to detect the disease before metastatic spread has occurred. CA19-9, a carbohydrate biomarker, is used clinically to surveille disease progression, but due to specificity challenges is not suitable for early discovery. As CA19-9 and other prospective markers are glycan epitopes, there is great clinical interest in understanding the glycobiology of pancreatic cancer. Unfortunately, few studies have been able to link glycosylation changes directly to pancreatic tumors and instead have focused on peripheral glycan alterations in the serum of PDAC patients. To address this gap in our understanding, …

Issues In Melanoma Detection: Semisupervised Deep Learning Algorithm Development Via A Combination Of Human And Artificial Intelligence, Xinyuan Zhang, Ziqian Xie, Yang Xiang, Imran Baig, Mena Kozman, Carly Stender, Luca Giancardo, Cui Tao

Faculty, Staff and Student Publications

BACKGROUND: Automatic skin lesion recognition has shown to be effective in increasing access to reliable dermatology evaluation; however, most existing algorithms rely solely on images. Many diagnostic rules, including the 3-point checklist, are not considered by artificial intelligence algorithms, which comprise human knowledge and reflect the diagnosis process of human experts.

OBJECTIVE: In this paper, we aimed to develop a semisupervised model that can not only integrate the dermoscopic features and scoring rule from the 3-point checklist but also automate the feature-annotation process.

METHODS: We first trained the semisupervised model on a small, annotated data set with disease and dermoscopic …

Advancing Access To Healthcare Through Telehealth: A Brownsville Community Assessment, Edna Ely-Ledesma, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

(1) Background: This paper focuses on the development of a community assessment for telehealth using an interprofessional lens, which sits at the intersection of public health and urban planning using multistakeholder input. The paper analyzes the process of designing and implementing a telemedicine plan for the City of Brownsville and its surrounding metros. (2) Methods: We employed an interprofessional approach to CBPR which assumed all stakeholders as equal partners alongside the researchers to uncover the most relevant and useful knowledge to inform the development of telehealth community assessment. (3) Results: Key findings include that: physicians do not have the technology, …

Experiences Of Parents With Opioid Use Disorder During Their Attempts To Seek Treatment: A Qualitative Analysis, Christine Bakos-Block, Angela J Nash, A Sarah Cohen, Tiffany Champagne-Langabeer

Faculty, Staff and Student Publications

In the U.S., 12.3% of children live with at least one parent who has a substance use disorder. Prior research has shown that men are more likely to seek treatment than women and that the barriers are different; however, there is limited research focusing specifically on opioid use disorder (OUD). We sought to understand the barriers and motivators for parents with OUD. We conducted a qualitative study by interviewing parents with OUD who were part of an outpatient treatment program. Interviews followed a semi-structured format with questions on access to and motivation for treatment. The interviews were recorded and transcribed …

Effect Of Temperature Cycling Pretreatment On The Thermal Stability Of Sm2(Co, Fe, Zr, Cu)17 Magnets In The Mild Temperature Range, Hulin Wu, Zhimei Long, Zhongsheng Li, Kaiqiang Song, Chaoqun Li, Dalong Cong, Bin Shao, Xiaowei Liu, Jianchun Sun, Yilong Ma

Faculty, Staff and Student Publications

The irredeemable magnetic losses of Sm(Co, Fe, Zr, Cu)7.8 permanent magnets caused by oxidation are very important for their practical application. In this work, the simulated results with R2 ≥ 98% based on the data of the temperature cycling test and the long-term isothermal test for the original samples confirmed that the magnetic flux losses reached 9.38% after the 5000th cycle in range R.T.–300 °C, and 7.15% after oxidated at 180 °C for 10 years, respectively. Demagnetization curves showed that the low-temperature oxidation mainly led to the remanence attenuation, while the coercivity remained relatively stable. SEM observation and EDS …

Groundwater Remediation Using Modified Biochar, Kers Ung-Watson, Ismail Abdulraheem, Nikki Tibayan, Suraj Pochampally

Undergraduate Research Symposium Posters

Biochar, a lightweight black residue made of carbon, has proved to be an effective adsorbent to remove TCE from groundwater. Not only is it an economical substitute for conventional adsorbents but it can be created by using a variety of organic materials. For this project, it will rely on walnut shell feedstock to create biochar as this had the best ability to adsorb TCE.

Effects Of A Behavioral Intervention On Physical Activity, Diet, And Health-Related Quality Of Life In Pregnant Women With Elevated Weight: Results Of The Hipp Randomized Controlled Trial, Sarah Wilcox Phd, Jihong Liu, Gabrielle Turner-Mcgrievy Ph.D., Rd, Alycia K. Boutte, Ellen Wingard Msph, Rd, Ld

Faculty Publications

Background

Physical activity (PA), diet, and health-related quality of life (HRQOL) are related to maternal and infant health, but interventions to improve these outcomes are needed in diverse pregnant women with elevated weight.

Methods

Health In Pregnancy and Postpartum (HIPP) was a randomized controlled trial. Women who were pregnant (N=219, 44% African American, 56% white) with overweight or obesity but otherwise healthy were randomized to a behavioral intervention grounded in Social Cognitive Theory (n=112) or to standard care (n=107). The intervention group received an in-depth counseling session, a private Facebook group, and 10 content-based …

High-Frequency Ultrasound In Patients With Seronegative Rheumatoid Arthritis, Junkui Wang, Miao Wang, Qinghua Qi, Zhibin Wu, Jianguo Wen

Faculty, Staff and Student Publications

This study aimed to investigate the value of high-frequency ultrasound (HFUS) in differentiation of the seronegative rheumatoid arthritis (SNRA) and osteoarthritis (OA) and in the diagnosis of SNRA. 83 patients diagnosed with SNRA (SNRA group) and 40 diagnosed with OA (OA group) who received HFUS were retrospectively analyzed. The grayscale (GS) scores, power Doppler (PD) scores, and bone erosion (BE)scores were recorded, and added up to calculate the total scores of US variables. The correlations of the total scores of US variables with the 28-joint disease activity score (DAS28), erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) were analyzed. The …

Poliovirus Detection In Las Vegas Wastewater, Sage Boss, Hayley Baker, Ching-Lan Chang

Undergraduate Research Symposium Posters

Wastewater surveillance for poliovirus is a useful tool for spatial surveillance and evaluation of immunization efficacy. Polio testing in wastewater has been conducted since the 1980s in Finland and Israel, and the virus was recently discovered in New York. With increasing concern regarding the vaccination of children against the virus, there has been worry that polio cases could once again present themselves in the Las Vegas Valley. By testing for the virus in wastewater, we can monitor any new cases or outbreaks that occur and inform authorities as to the location and viral count. The wastewater samples were collected at …

Designing And Synthesizing A Warhead-Fragment Inhibitory Ligand For Ivyp1 Through Fragment-Based Drug Discovery, Samuel Moore

Symposium of Student Scholars

Fragment-based drug discovery (FBDD) is a powerful tool for developing anticancer and antimicrobial agents. Within this, magnetic resonance spectroscopy (NMR) provides a comprehensive qualitative and quantitative approach to screening and validating weak and robust binders with targeted proteins, making NMR among the most attractive strategies in FBDD. Inhibitor of vertebrate lysozyme (Ivyp1) of P. aeruginosa serves as an excellent target because of its active cellular location and implications in clinical prognosis for cystic fibrosis and immunocompromised patients. This study uses current NMR and biophysical techniques to develop a covalent, fragment-linked warhead inhibitor for Ivyp1 through synthetic methods, warhead linking, and …

Open-Source Benchmarking Of Ibd Segment Detection Methods For Biobank-Scale Cohorts, Kecong Tang, Ardalan Naseri, Yuan Wei, Shaojie Zhang, Degui Zhi

Faculty, Staff and Student Publications

In the recent biobank era of genetics, the problem of identical-by-descent (IBD) segment detection received renewed interest, as IBD segments in large cohorts offer unprecedented opportunities in the study of population and genealogical history, as well as genetic association of long haplotypes. While a new generation of efficient methods for IBD segment detection becomes available, direct comparison of these methods is difficult: existing benchmarks were often evaluated in different datasets, with some not openly accessible; methods benchmarked were run under suboptimal parameters; and benchmark performance metrics were not defined consistently. Here, we developed a comprehensive and completely open-source evaluation of …

A High-Accuracy Detection System: Based On Transfer Learning For Apical Lesions On Periapical Radiograph, Yueh Chuo, Wen-Ming Lin, Tsung-Yi Chen, Mei-Ling Chan, Yu-Sung Chang, Yan-Ru Lin, Yuan-Jin Lin, Yu-Han Shao, Chiung-An Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Apical Lesions, one of the most common oral diseases, can be effectively detected in daily dental examinations by a periapical radiograph (PA). In the current popular endodontic treatment, most dentists spend a lot of time manually marking the lesion area. In order to reduce the burden on dentists, this paper proposes a convolutional neural network (CNN)-based regional analysis model for spical lesions for periapical radiographs. In this study, the database was provided by dentists with more than three years of practical experience, meeting the criteria for clinical practical application. The contributions of this work are (1) an advanced adaptive threshold …

Exposure Of Egyptian Rousette Bats (Rousettus Aegyptiacus) And A Little Free-Tailed Bat (Chaerephon Pumilus) To Alphaviruses In Uganda, Rebekah C. Kading, Erin M. Borland, Eric C. Mossel, Teddy Nakayiki, Betty Nalikka, Jeremy P. Ledermann, Mary B. Crabtree, Nicholas A. Panella, Luke Nyakarahuka, Amy T. Gilbert, Julian C. Kerbis-Peterhans, Jonathan S. Towner, Brian R. Amman, Tara K. Sealy, Barry R. Miller, Julius J. Lutwama, Robert M. Kityo, Ann M. Powers

United States Department of Agriculture Wildlife Services: Staff Publications

The reservoir for zoonotic o’nyong-nyong virus (ONNV) has remained unknown since this virus was first recognized in Uganda in 1959. Building on existing evidence for mosquito bloodfeeding on various frugivorous bat species in Uganda, and seroprevalence for arboviruses among bats in Uganda, we sought to assess if serum samples collected from bats in Uganda demonstrated evidence of exposure to ONNV or the closely related zoonotic chikungunya virus (CHIKV). In total, 652 serum samples collected from six bat species were tested by plaque reduction neutralization test (PRNT) for neutralizing antibodies against ONNV and CHIKV. Forty out of 303 (13.2%) Egyptian rousettes …

Predicting The Outcomes Of Internet-Based Cognitive Behavioral Therapy For Tinnitus: Applications Of Artificial Neural Network And Support Vector Machine, Hansapani Rodrigo, Eldré W. Beukes, Gerhard Andersson, Vinaya Manchaiah

School of Mathematical & Statistical Sciences Faculty Publications

Purpose:

Internet-based cognitive behavioral therapy (ICBT) has been found to be effective for tinnitus management, although there is limited understanding about who will benefit the most from ICBT. Traditional statistical models have largely failed to identify the nonlinear associations and hence find strong predictors of success with ICBT. This study aimed at examining the use of an artificial neural network (ANN) and support vector machine (SVM) to identify variables associated with treatment success in ICBT for tinnitus.

Method:

The study involved a secondary analysis of data from 228 individuals who had completed ICBT in previous intervention studies. A 13-point reduction …

Artificial Intelligence In The Medical Field: Medical Review Sentiment Analysis, Nicholas Podlesak

Honors Capstones

In this research project, natural language processing techniques’ ability to accurately classify medical text was measured to reinforce the relevance of artificial intelligence in the medical field. Sentiment analyses (analyses to determine whether the text was positive or negative) were performed on the prescription drug reviews in an open-source dataset using four different models: lexical, a neural network, a support vector machine, and a logistic regression model. Each model’s effectiveness was gauged by its ability to correctly classify unlabeled drug reviews (i.e., a percentage representing accuracy). The machine learning models were able to accurately classify the text, while the lexical …

A Human Oral Fluid Assay For D- And L- Isomer Detection Of Amphetamine And Methamphetamine Using Liquid-Liquid Extraction, Brian Robbins, Rob E. Carpenter, Mary Long, Jacob Perry

Human Resource Development Faculty Publications and Presentations

Medical providers are increasingly confronted with clinical decision-making that involves (meth)amphetamines. And clinical laboratories need a sensitive, efficient assay for routine assessment of D- and L-isomers to determine the probable source of these potentially illicit analytes. This paper presents a validated method of D- and L-isomer detection in human oral fluid from an extract used for determination of a large oral fluid assay (63 analytes) on an older AB SCIEX 4000 instrument. Taken from the positive extract, D- and L-analytes were added. The method for extraction included addition of internal standard and a 2-step …

2022 - The Third Annual Fall Symposium Of Student Scholars

Symposium of Student Scholars Program Books

The full program book from the Fall 2022 Symposium of Student Scholars, held on November 17, 2022. Includes abstracts from the presentations and posters.

Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury

Electronic Theses and Dissertations

Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …

Alpha, Beta-Unsaturated Aldehydes: The Underrepresented Markers Of Disease., Saurin Sutaria

Electronic Theses and Dissertations

The peroxidation of unsaturated fatty acids is a widely recognized metabolic process that creates a complex mixture of volatile organic compounds including aldehydes. Elevated levels of reactive oxygen species in cancer cells promote random lipid peroxidation, which leads to an increase in a variety of aldehydes. Many of these volatile aldehydes are exhaled and are of interest as potential markers of disease. Chapter 1 presents a review of reported aldehydes in the exhaled breath of lung cancer patients. alpha,beta-Unsaturated aldehydes, detected primarily when derivatized during exhaled breath preconcentration, are underreported in the reviewed articles. Chapter 1 concludes with our hypothesis …

Drug Abuse Ontology To Harness Web-Based Data For Substance Use Epidemiology Research, Usha Lokala, Francois Lamy, Raminta Daniulaityte, Manas Gaur, Amelie Gyrard, Krishnaprasad Thirunarayan, Ugur Kursuncu, Amit Sheth

Computer Science and Engineering Faculty Publications

Background: Web-based resources and social media platforms play an increasingly important role in health-related knowledge and experience sharing. There is a growing interest in the use of these novel data sources for epidemiological surveillance of substance use behaviors and trends. Objective: The key aims were to describe the development and application of the drug abuse ontology (DAO) as a framework for analyzing web-based and social media data to inform public health and substance use research in the following areas: determining user knowledge, attitudes, and behaviors related to nonmedical use of buprenorphine and illicitly manufactured opioids through the analysis of web …

Metabolic Alterations And Cardiovascular Risk After Hepatitis C Cure In Subjects With Or At Risk For Hiv, Christophe Maxime Fokoua Dongmo

Legacy Theses & Dissertations (2009 - 2024)

Background. Hepatitis C virus (HCV) infection engenders substantial metabolic changes. These changes are altered when the virus is cleared after successful treatment. We measured these metabolic alterations that occur after HCV cure; further, we assessed whether these alterations differed in subgroups defined by patients’ characteristics.

Evaluating The Health Impacts Of Fruit And Vegetable Intake At The Individual Level And Food Pantry Level Among Food Pantry Users, Jiacheng Chen

Legacy Theses & Dissertations (2009 - 2024)

Background: Chronic diseases impose heavy burdens on individuals and the healthcare system in the US. Many factors were found to be associated with chronic diseases, including demographics, family history, social environmental factors, and individual behavioral factors such as diet and physical activity. Among those factors, fruit and vegetable intake can have substantial health impacts via a variety of causal pathways. Fruit and vegetable (F&V) consumption is generally lower among individuals living in households experiencing food insecurity and rely on food assistance programs. Decreased F&V intake among food pantry users may negatively impact health. However, conducting quantitative analysis on this population …

Npgreat: Assembly Of The Human Subtelomere Regions With The Use Of Ultralong Nanopore Reads And Linked Reads, Eleni Adam, Desh Ranjan, Harold Riethman

Computer Science Faculty Publications

Background: Human subtelomeric DNA regulates the length and stability of adjacent telomeres that are critical for cellular function, and contains many gene/pseudogene families. Large evolutionarily recent segmental duplications and associated structural variation in human subtelomeres has made complete sequencing and assembly of these regions difficult to impossible for many loci, complicating or precluding a wide range of genetic analyses to investigate their function.

Results: We present a hybrid assembly method, NanoPore Guided REgional Assembly Tool (NPGREAT), which combines Linked-Read data with mapped ultralong nanopore reads spanning subtelomeric segmental duplications to potentially overcome these difficulties. Linked-Read sets of DNA sequences identified …

Rapid Detection Of Recurrent Non-Muscle Invasive Bladder Cancer In Urine Using Atr-Ftir Technology, Abdullah I. El-Falouji, Dalia M. Sabri, Naira M. Lofti, Doaa M. Medany, Samar A. Mohamed, Mai Alaa-Eldin, Amr Mounir Selim, Asmaa A. El Leithy, Haitham F. Kalil, Ahmed El-Tobgy, Ahmed Mohamed

Chemistry Faculty Publications

Non-muscle Invasive Bladder Cancer (NMIBC) accounts for 80% of all bladder cancers. Although it is mostly low-grade tumors, its high recurrence rate necessitates three-times-monthly follow-ups and cystoscopy examinations to detect and prevent its progression. A rapid liquid biopsy-based assay is needed to improve detection and reduce complications from invasive cystoscopy. Here, we present a rapid spectroscopic method to detect the recurrence of NMIBC in urine. Urine samples from previously-diagnosed NMIBC patients (n = 62) were collected during their follow-up visits before cystoscopy examination. Cystoscopy results were recorded (41 cancer-free and 21 recurrence) and attenuated total refraction Fourier transform infrared (ATR-FTIR) …