Digital Commons Network^™

Annotation And Information Extraction Of Consumer-Friendly Health Articles For Enhancing Laboratory Test Reporting, Zhe He, Shubo Tian, Arslan Erdengasileng, Karim Hanna, Yang Gong, Zhan Zhang, Xiao Luo, Mia Liza A Lustria

Faculty, Staff and Student Publications

Viewing laboratory test results is patients' most frequent activity when accessing patient portals, but lab results can be very confusing for patients. Previous research has explored various ways to present lab results, but few have attempted to provide tailored information support based on individual patient's medical context. In this study, we collected and annotated interpretations of textual lab result in 251 health articles about laboratory tests from AHealthyMe.com. Then we evaluated transformer-based language models including BioBERT, ClinicalBERT, RoBERTa, and PubMedBERT for recognizing key terms and their types. Using BioPortal's term search API, we mapped the annotated terms to concepts in …

The Current Status And Future Prospects For Conversion Therapy In The Treatment Of Hepatocellular Carcinoma, Jinfeng Bai, Ming Huang, Bohan Song, Wei Luo, Rong Ding

Faculty, Staff and Student Publications

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths worldwide. In China, most HCC patients are diagnosed with advanced disease and in these cases surgery is challenging. Conversion therapy can be used to change unresectable HCC into resectable disease and is a potential breakthrough treatment strategy. The resection rate for unresectable advanced HCC has recently improved as a growing number of patients have benefited from conversion therapy. While conversion therapy is at an early stage of development, progress in patient selection, optimum treatment methods, and the timing of surgery have the potential to deliver significant benefits. In …

The Health-Promoting Effects And The Mechanism Of Intermittent Fasting, Simin Liu, Min Zeng, Weixi Wan, Ming Huang, Xiang Li, Zixian Xie, Shang Wang, Yu Cai

Faculty, Staff and Student Publications

Intermittent fasting (IF) is an eating pattern in which individuals go extended periods with little or no energy intake after consuming regular food in intervening periods. IF has several health-promoting effects. It can effectively reduce weight, fasting insulin levels, and blood glucose levels. It can also increase the antitumor activity of medicines and cause improvement in the case of neurological diseases, such as memory deficit, to achieve enhanced metabolic function and prolonged longevity. Additionally, IF activates several biological pathways to induce autophagy, encourages cell renewal, prevents cancer cells from multiplying and spreading, and delays senescence. However, IF has specific adverse …

Emulate Randomized Clinical Trials Using Heterogeneous Treatment Effect Estimation For Personalized Treatments: Methodology Review And Benchmark, Yaobin Ling, Pulakesh Upadhyaya, Luyao Chen, Xiaoqian Jiang, Yejin Kim

Faculty, Staff and Student Publications

Big data and (deep) machine learning have been ambitious tools in digital medicine, but these tools focus mainly on association. Intervention in medicine is about the causal effects. The average treatment effect has long been studied as a measure of causal effect, assuming that all populations have the same effect size. However, no "one-size-fits-all" treatment seems to work in some complex diseases. Treatment effects may vary by patient. Estimating heterogeneous treatment effects (HTE) may have a high impact on developing personalized treatment. Lots of advanced machine learning models for estimating HTE have emerged in recent years, but there has been …

Spatial Modelling Of The Tumor Microenvironment From Multiplex Immunofluorescence Images: Methods And Applications, Gayatri Kumar, Renganayaki Krishna Pandurengan, Edwin Roger Parra, Kasthuri Kannan, Cara Haymaker

Faculty, Staff and Student Publications

Spatial modelling methods have gained prominence with developments in high throughput imaging platforms. Multiplex immunofluorescence (mIF) provides the scope to examine interactions between tumor and immune compartment at single cell resolution using a panel of antibodies that can be chosen based on the cancer type or the clinical interest of the study. The markers can be used to identify the phenotypes and to examine cellular interactions at global and local scales. Several translational studies rely on key understanding of the tumor microenvironment (TME) to identify drivers of immune response in immunotherapy based clinical trials. To improve the success of ongoing …

Gibbs Process Distinguishes Survival And Reveals Contact-Inhibition Genes In Glioblastoma Multiforme, Afrooz Jahedi, Gayatri Kumar, Lavanya Kannan, Tarjani Agarwal, Jason Huse, Krishna Bhat, Kasthuri Kannan

Faculty, Staff and Student Publications

Tumor growth is a spatiotemporal birth-and-death process with loss of heterotypic contact-inhibition of locomotion (CIL) of tumor cells promoting invasion and metastasis. Therefore, representing tumor cells as two-dimensional points, we can expect the tumor tissues in histology slides to reflect realizations of spatial birth-and-death process which can be mathematically modeled to reveal molecular mechanisms of CIL, provided the mathematics models the inhibitory interactions. Gibbs process as an inhibitory point process is a natural choice since it is an equilibrium process of the spatial birth-and-death process. That is if the tumor cells maintain homotypic contact inhibition, the spatial distributions of tumor …

A Rapid, Low-Cost, And Highly Sensitive Sars-Cov-2 Diagnostic Based On Whole-Genome Sequencing, Per A Adastra, Neva C Durand, Namita Mitra, Saul Godinez Pulido, Ragini Mahajan, Alyssa Blackburn, Zane L Colaric, Joshua W M Theisen, David Weisz, Olga Dudchenko, Andreas Gnirke, Suhas S P Rao, Parwinder Kaur, Erez Lieberman Aiden, Aviva Presser Aiden

Faculty, Staff and Students Publications

Early detection of SARS-CoV-2 infection is key to managing the current global pandemic, as evidence shows the virus is most contagious on or before symptom onset. Here, we introduce a low-cost, high-throughput method for diagnosing and studying SARS-CoV-2 infection. Dubbed Pathogen-Oriented Low-Cost Assembly & Re-Sequencing (POLAR), this method amplifies the entirety of the SARS-CoV-2 genome. This contrasts with typical RT-PCR-based diagnostic tests, which amplify only a few loci. To achieve this goal, we combine a SARS-CoV-2 enrichment method developed by the ARTIC Network (https://artic.network/) with short-read DNA sequencing and de novo genome assembly. Using this method, we can reliably ( …

Intermel: An International Biorepository And Clinical Database To Uncover Predictors Of Survival In Early-Stage Melanoma, Irene Orlow, Keimya D Sadeghi, Sharon N Edmiston, Jessica M Kenney, Cecilia Lezcano, James S Wilmott, Anne E Cust, Richard A Scolyer, Graham J Mann, Tim K Lee, Hazel Burke, Valerie Jakrot, Ping Shang, Peter M Ferguson, Tawny W Boyce, Jennifer S Ko, Peter Ngo, Pauline Funchain, Judy R Rees, Kelli O'Connell, Honglin Hao, Eloise Parrish, Kathleen Conway, Paul B Googe, David W Ollila, Stergios J Moschos, Eva Hernando, Douglas Hanniford, Diana Argibay, Christopher I Amos, Jeffrey E Lee, Iman Osman, Li Luo, Pei-Fen Kuan, Arshi Aurora, Bonnie E Gould Rothberg, Marcus W Bosenberg, Meg R Gerstenblith, Cheryl Thompson, Paul N Bogner, Ivan P Gorlov, Sheri L Holmen, Elise K Brunsgaard, Yvonne M Saenger, Ronglai Shen, Venkatraman Seshan, Eduardo Nagore, Marc S Ernstoff, Klaus J Busam, Colin B Begg, Nancy E Thomas, Marianne Berwick, Intermel Consortium

Faculty, Staff and Students Publications

INTRODUCTION: We are conducting a multicenter study to identify classifiers predictive of disease-specific survival in patients with primary melanomas. Here we delineate the unique aspects, challenges, and best practices for optimizing a study of generally small-sized pigmented tumor samples including primary melanomas of at least 1.05mm from AJTCC TNM stage IIA-IIID patients. We also evaluated tissue-derived predictors of extracted nucleic acids' quality and success in downstream testing. This ongoing study will target 1,000 melanomas within the international InterMEL consortium.

METHODS: Following a pre-established protocol, participating centers ship formalin-fixed paraffin embedded (FFPE) tissue sections to Memorial Sloan Kettering Cancer Center for …

Wastewater Pandemic Preparedness: Toward An End-To-End Pathogen Monitoring Program, Justin R Clark, Austen Terwilliger, Vasanthi Avadhanula, Michael Tisza, Juwan Cormier, Sara Javornik-Cregeen, Matthew Clayton Ross, Kristi Louise Hoffman, Catherine Troisi, Blake Hanson, Joseph Petrosino, John Balliew, Pedro A Piedra, Janelle Rios, Jennifer Deegan, Cici Bauer, Fuqing Wu, Kristina D Mena, Eric Boerwinkle, Anthony W Maresso

Faculty, Staff and Student Publications

Molecular analysis of public wastewater has great potential as a harbinger for community health and health threats. Long-used to monitor the presence of enteric viruses, in particular polio, recent successes of wastewater as a reliable lead indicator for trends in SARS-CoV-2 levels and hospital admissions has generated optimism and emerging evidence that similar science can be applied to other pathogens of pandemic potential (PPPs), especially respiratory viruses and their variants of concern (VOC). However, there are substantial challenges associated with implementation of this ideal, namely that multiple and distinct fields of inquiry must be bridged and coordinated. These include engineering, …

Elementary School Staff Perspectives On The Implementation Of Physical Activity Approaches In Practice: An Exploratory Sequential Mixed Methods Study, Timothy J Walker, Christopher D Pfledderer, Derek W Craig, Michael C Robertson, Natalia I Heredia, John B Bartholomew

Faculty, Staff and Student Publications

INTRODUCTION: A whole-of-school approach is best to promote physical activity before, during, and after school. However, multicomponent programming is often complex and difficult to deliver in school settings. There is a need to better understand how components of a whole-of-school approach are implemented in practice. The objectives of this mixed methods study were to: (1) qualitatively explore physical activity approaches and their implementation in elementary schools, (2) quantitatively assess implementation levels, and (3) examine associations between school-level physical activity promotion and academic ratings.

METHODS: We used an exploratory sequential mixed methods design. We conducted semi-structured qualitative interviews with elementary school …

Understanding The Implications Of Under-Reporting, Vaccine Efficiency And Social Behavior On The Post-Pandemic Spread Using Physics Informed Neural Networks: A Case Study Of China, Samiran Ghosh, Alonso Ogueda-Oliva, Aditi Ghosh, Malay Banerjee, Padmanabhan Seshaiyer

Faculty, Staff and Student Publications

In late 2019, the emergence of COVID-19 in Wuhan, China, led to the implementation of stringent measures forming the zero-COVID policy aimed at eliminating transmission. Zero-COVID policy basically aimed at completely eliminating the transmission of COVID-19. However, the relaxation of this policy in late 2022 reportedly resulted in a rapid surge of COVID-19 cases. The aim of this work is to investigate the factors contributing to this outbreak using a new SEIR-type epidemic model with time-dependent level of immunity. Our model incorporates a time-dependent level of immunity considering vaccine doses administered and time-post-vaccination dependent vaccine efficacy. We find that vaccine …

Assessing Pandemic Preparedness, Response, And Lessons Learned From The Covid-19 Pandemic In Four South American Countries: Agenda For The Future, Andrea Ramírez Varela, Michael Touchton, J Jaime Miranda, Juliana Mejía Grueso, Rachid Laajaj, Gabriel Carrasquilla, Martha Vives Florez, Ana María Vesga Gaviria, Ana María Ortiz Hoyos, Esteban Orlando Vanegas Duarte, Alejandra Velásquez Morales, Nubia Velasco, Silvia Restrepo Restrepo

Faculty, Staff and Student Publications

INTRODUCTION: The COVID-19 pandemic emerged in a context that lacked adequate prevention, preparedness, and response (PPR) activities, and global, regional, and national leadership. South American countries were among world's hardest hit by the pandemic, accounting for 10.1% of total cases and 20.1% of global deaths.

METHODS: This study explores how pandemic PPR were affected by political, socioeconomic, and health system contexts as well as how PPR may have shaped pandemic outcomes in Argentina, Brazil, Colombia, and Peru. We then identify lessons learned and advance an agenda for improving PPR capacity at regional and national levels. We do this through a …

Global Research Trends And Prospects Related To Tumor Microenvironment Within Triple Negative Breast Cancer: A Bibliometric Analysis, Peiting Li, Jun Li, Xiaofei Tong, Zhenyang Xiao, Wuliang Diao, Chi Zhong, Jianda Zhou, Wei Wu

Faculty, Staff and Student Publications

Background and aims: The tumor microenvironment (TME) has pivotal parts within multiple tumor models of onset/progression, such as triple-negative breast cancer (TNBC). This bibliometric analysis was developed to explore trends and research niches revolving around TME in TNBC.

Methods: Web of Science Core Collection was queried for identifying studies linked with TME in TNBC, after which the VOSviewer, CiteSpace, and R software programs were used to conduct bibliometric analyses and to generate corresponding visualizations.

Results: In total, this study included 1,604 studies published from 2005-2023. The USA and China exhibited the highest numbers of citations, and the research institutions with …

Head And Neck Cancer Predictive Risk Estimator To Determine Control And Therapeutic Outcomes Of Radiotherapy (Hnc-Predictor): Development, International Multi-Institutional Validation, And Web Implementation Of Clinic-Ready Model-Based Risk Stratification For Head And Neck Cancer, Lisanne V Van Dijk, Abdallah Sr Mohamed, Sara Ahmed, Nafiul Nipu, G Elisabeta Marai, Kareem Wahid, Nanna M Sijtsema, Brandon Gunn, Adam S Garden, Amy Moreno, Andrew J Hope, Johannes A Langendijk, Clifton D Fuller

Faculty, Staff and Student Publications

Background: Personalised radiotherapy can improve treatment outcomes of patients with head and neck cancer (HNC), where currently a 'one-dose-fits-all' approach is the standard. The aim was to establish individualised outcome prediction based on multi-institutional international 'big-data' to facilitate risk-based stratification of patients with HNC.

Methods: The data of 4611 HNC radiotherapy patients from three academic cancer centres were split into four cohorts: a training (n = 2241), independent test (n = 786), and external validation cohorts 1 (n = 1087) and 2 (n = 497). Tumour- and patient-related clinical variables were considered in a machine learning pipeline to predict overall …

A Bibliometric And Visual Analysis Of Cancer-Associated Fibroblasts, Wei-Chen Yuan, Jie-Xiang Zhang, Hai-Bin Chen, Ying Yuan, Yu-Pei Zhuang, Hong-Li Zhou, Mu-Han Li, Wen-Li Qiu, Hong-Guang Zhou

Faculty, Staff and Student Publications

Background: Cancer-associated fibroblasts (CAFs) represent the predominant stromal component within the tumour microenvironment (TME), exhibiting considerable heterogeneity and plasticity that significantly impact immune response and metabolic reprogramming within the TME, thereby influencing tumour progression. Consequently, investigating CAFs is of utmost importance. The objective of this study is to employ bibliometric analysis in order to evaluate the current state of research on CAFs and predict future areas of research and emerging trends.

Methods: Conduct a comprehensive search for scholarly publications within the Web of Science Core Collection database, encompassing the time period from January 1, 2001, to December 31, 2022. Apply …

The Phase 1/2 Trial Of Indomethacin In Chronic Pancreatitis (The Pair Trial): Protocol For A Parallel Multi-Center Randomized Controlled Trial, Samuel Han, Darwin L Conwell, Liang Li, Alejandra Cervantes, Phil A Hart, Zobeida Cruz-Monserrate, Wenrui Hao, Gregory B Lesinski, Thomas Mace, Tonya M Palermo, Jami L Saloman, Dhiraj Yadav, Santhi Swaroop Vege, Mark Topazian, Consortium For The Study Of Chronic Pancreatitis, Diabetes, And Pancreatic Cancer (Cpdpc)

Faculty, Staff and Student Publications

Background/objectives: Current treatments for chronic pancreatitis focus on symptom management and therapeutics targeting disease reversal are lacking. Given the role of the cyclooxygenase-2 (COX-2) enzyme in producing prostaglandin E2 (PGE2), a key component in the inflammatory pathway of chronic pancreatitis, this study evaluates the physiologic effect of oral indomethacin, a COX-2 inhibitor, on PGE2 levels in pancreatic fluid.

Methods: This pilot two-center randomized controlled trial seeks to examine 32 subjects with chronic pancreatitis who have no contraindications to indomethacin. Subjects will be randomized to either oral indomethacin 50 mg twice a day or placebo twice a day for a total …

Chronic Kidney Disease Prediction Using Boosting Techniques Based On Clinical Parameters, Shahid Mohammad Ganie, Pijush Kanti Dutta Pramanik, Saurav Mallik, Zhongming Zhao

Faculty, Staff and Student Publications

Chronic kidney disease (CKD) has become a major global health crisis, causing millions of yearly deaths. Predicting the possibility of a person being affected by the disease will allow timely diagnosis and precautionary measures leading to preventive strategies for health. Machine learning techniques have been popularly applied in various disease diagnoses and predictions. Ensemble learning approaches have become useful for predicting many complex diseases. In this paper, we utilise the boosting method, one of the popular ensemble learnings, to achieve a higher prediction accuracy for CKD. Five boosting algorithms are employed: XGBoost, CatBoost, LightGBM, AdaBoost, and gradient boosting. We experimented …

Henry Gas Solubility Optimization Double Machine Learning Classifier For Neurosurgical Patients, Diana T Mosa, Amena Mahmoud, John Zaki, Shaymaa E Sorour, Shaker El-Sappagh, Tamer Abuhmed

Faculty, Staff and Student Publications

This study aims to predict head trauma outcome for Neurosurgical patients in children, adults, and elderly people. As Machine Learning (ML) algorithms are helpful in healthcare field, a comparative study of various ML techniques is developed. Several algorithms are utilized such as k-nearest neighbor, Random Forest (RF), C4.5, Artificial Neural Network, and Support Vector Machine (SVM). Their performance is assessed using anonymous patients' data. Then, a proposed double classifier based on Henry Gas Solubility Optimization (HGSO) is developed with Aquila optimizer (AQO). It is implemented for feature selection to classify patients' outcome status into four states. Those are mortality, morbidity, …

Multimethod Process Evaluation Of A Community Paramedic Delivered Care Transitions Intervention For Older Emergency Department Patients, Gwen Costa Jacobsohn, Apoorva P Maru, Rebecca K Green, Angela N Gifford, Matthew D Lukasik, Tikiri Bandara, Thomas V Caprio, Amy L Cochran, Jeremy T Cushman, Courtney M C Jones, Amy J H Kind, Michael Lohmeier, Manish N Shah

Faculty, Staff and Student Publications

OBJECTIVE: We assessed fidelity of delivery and participant engagement in the implementation of a community paramedic coach-led Care Transitions Intervention (CTI) program adapted for use following emergency department (ED) visits.

METHODS: The adapted CTI for ED-to-home transitions was implemented at three university-affiliated hospitals in two cities from 2016 to 2019. Participants were aged ≥60 years old and discharged from the ED within 24 hours of arrival. In the current analysis, participants had to have received the CTI. Community paramedic coaches collected data on program delivery and participant characteristics at each transition contact via inventories and assessments. Participants provided commentary on …

Frequentist Model Averaging For Analysis Of Dose-Response In Epidemiologic Studies With Complex Exposure Uncertainty, Deukwoo Kwon, Steven L Simon, F Owen Hoffman, Ruth M Pfeiffer

Faculty, Staff and Student Publications

In epidemiologic studies, association estimates of an exposure with disease outcomes are often biased when the uncertainties of exposure are ignored. Consequently, corresponding confidence intervals (CIs) will not have correct coverage. This issue is particularly problematic when exposures must be reconstructed from physical measurements, for example, for environmental or occupational radiation doses that were received by a study population for which radiation doses cannot be measured directly. To incorporate complex uncertainties in reconstructed exposures, the two-dimensional Monte Carlo (2DMC) dose estimation method has been proposed and used in various dose reconstruction efforts. The 2DMC method generates multiple exposure realizations from …

Timing Of Invasive Mechanical Ventilation And Death In Critically Ill Adults With Covid-19: A Multicenter Cohort Study, Adam Green, Jean-Sebastien Rachoin, Christa Schorr, Phil Dellinger, Jonathan D Casey, Isabel Park, Shruti Gupta, Rebecca M Baron, Shahzad Shaefi, Krystal Hunter, David E Leaf

Faculty, Staff and Student Publications

PURPOSE: To investigate if the timing of initiation of invasive mechanical ventilation (IMV) for critically ill patients with COVID-19 is associated with mortality.

MATERIALS AND METHODS: The data for this study were derived from a multicenter cohort study of critically ill adults with COVID-19 admitted to ICUs at 68 hospitals across the US from March 1 to July 1, 2020. We examined the association between early (ICU days 1-2) versus late (ICU days 3-7) initiation of IMV and time-to-death. Patients were followed until the first of hospital discharge, death, or 90 days. We adjusted for confounding using a multivariable Cox …

Deep Learning-Based Dose Prediction For Automated, Individualized Quality Assurance Of Head And Neck Radiation Therapy Plans, Mary P Gronberg, Beth M Beadle, Adam S Garden, Heath Skinner, Skylar Gay, Tucker Netherton, Wenhua Cao, Carlos E Cardenas, Christine Chung, David T Fuentes, Clifton D Fuller, Rebecca M Howell, Anuja Jhingran, Tze Yee Lim, Barbara Marquez, Raymond Mumme, Adenike M Olanrewaju, Christine B Peterson, Ivan Vazquez, Thomas J Whitaker, Zachary Wooten, Ming Yang, Laurence E Court

Faculty, Staff and Student Publications

PURPOSE: This study aimed to use deep learning-based dose prediction to assess head and neck (HN) plan quality and identify suboptimal plans.

METHODS AND MATERIALS: A total of 245 volumetric modulated arc therapy HN plans were created using RapidPlan knowledge-based planning (KBP). A subset of 112 high-quality plans was selected under the supervision of an HN radiation oncologist. We trained a 3D Dense Dilated U-Net architecture to predict 3-dimensional dose distributions using 3-fold cross-validation on 90 plans. Model inputs included computed tomography images, target prescriptions, and contours for targets and organs at risk (OARs). The model's performance was assessed on …

Epilepsy Center Characteristics And Geographic Region Influence Presurgical Testing In The United States, Stephanie M Ahrens, Kristen H Arredondo, Anto I Bagić, Shasha Bai, Kevin E Chapman, Michael A Ciliberto, Dave F Clarke, Mariah Eisner, Nathan B Fountain, Jay R Gavvala, M Scott Perry, Kyle C Rossi, Lily C Wong-Kisiel, Susan T Herman, Adam P Ostendorf, Naec Center Director Study Group

Faculty, Staff and Student Publications

bjective

Persons with drug‐resistant epilepsy may benefit from epilepsy surgery and should undergo presurgical testing to determine potential candidacy and appropriate intervention. Institutional expertise can influence use and availability of evaluations and epilepsy surgery candidacy. This census survey study aims to examine the influence of geographic region and other center characteristics on presurgical testing for medically intractable epilepsy.

Methods

We analyzed annual report and supplemental survey data reported in 2020 from 206 adult epilepsy center directors and 136 pediatric epilepsy center directors in the United States. Test utilization data were compiled with annual center volumes, available resources, and US Census …

Readiness For Transfer: A Mixed-Methods Study On Icu Transfers Of Care, Soo-Hoon Lee, Clarice Wee, Phillip Phan, Yanika Kowitlawakul, Chee-Kiat Tan, Amartya Mukhopadhyay

Management Faculty Publications

Objective Past studies on intensive care unit (ICU) patient transfers compare the efficacy of using standardised checklists against unstructured communications. Less studied are the experiences of clinicians in enacting bidirectional (send/receive) transfers. This study reports on the differences in protocols and data elements between receiving and sending transfers in the ICU, and the elements constituting readiness for transfer.

Methods Mixed-methods study of a 574-bed general hospital in Singapore with a 74-bed ICU for surgical and medical patients. Six focus group discussions (FGDs) with 34 clinicians comprising 15 residents and 19 nurses, followed by a structured questionnaire survey of 140 clinicians …

Validity And Diagnostic Performance Of Computing Fractional Flow Reserve From 2-Dimensional Coronary Angiography Images, Vahid Mohammadi, Massoud Ghasemi, Reza Rahmani, Maryam Mehrpooya, Hamidreza Babakhani, Akbar Shafiee, Mohammad Sadeghian

The Texas Heart Institute Journal

BACKGROUND: Measurement of fractional flow reserve (FFR) is the gold standard for determining the physiologic significance of coronary artery stenosis, but newer software programs can calculate the FFR from 2-dimensional angiography images.

METHODS: A retrospective analysis was conducted using the records of patients with intermediate coronary stenoses who had undergone adenosine FFR (aFFR). To calculate the computed FFR, a software program used simulated coronary blood flow using computational geometry constructed using at least 2 patient-specific angiographic images. Two cardiologists reviewed the angiograms and determined the computational FFR independently. Intraobserver variability was measured using κ analysis and the intraclass correlation coefficient. …

Cardiac Function, Structural, And Electrical Remodeling By Microgravity Exposure, Mary R Sy, Joshua A Keefe, Jeffrey P Sutton, Xander H T Wehrens

Faculty, Staff and Students Publications

Space medicine is key to the human exploration of outer space and pushes the boundaries of science, technology, and medicine. Because of harsh environmental conditions related to microgravity and other factors and hazards in outer space, astronauts and spaceflight participants face unique health and medical challenges, including those related to the heart. In this review, we summarize the literature regarding the effects of spaceflight on cardiac structure and function. We also provide an in-depth review of the literature regarding the effects of microgravity on cardiac calcium handling. Our review can inform future mechanistic and therapeutic studies and is applicable to …

Indices Of Sarcopenic Obesity Are Important Predictors Of Finite Element Analysis-Derived Bone Strength In Older Adults With Obesity, Giulia Gregori, Arjun Paudyal, Yoann Barnouin, Alessandra Celli, Martha Belen Segoviano-Escobar, Reina Armamento-Villareal, Nicola Napoli, Clifford Qualls, Dennis T Villareal

Faculty, Staff and Students Publications

BACKGROUND: The expanding population of older adults with obesity is a public health challenge, in part, because of the increased risk of fractures despite normal or high bone mineral density. Potential factors predisposing to fractures in this group include sarcopenia associated with obesity and impaired bone quality. We aimed to determine the contribution of sarcopenic obesity (SO) indices to bone strength as assessed by microfinite element analysis (μFEA) of high-resolution peripheral quantitative computed tomography (HR-pQCT).

METHODS: One-hundred eighty-nine older (age ≥ 65 years) adults with obesity (BMI ≥ 30 kg/m

RESULTS: Both ALM/W and HGS were positively correlated explaining 28% …

Semi-Automated Construction Of Patient-Specific Aortic Valves From Computed Tomography Images, Dan Lior, Charles Puelz, Colin Edwards, Silvana Molossi, Boyce E Griffith, Ravi K Birla, Craig G Rusin

Faculty, Staff and Students Publications

This paper presents a semi-automatic method for the construction of volumetric models of the aortic valve using computed tomography angiography images. Although the aortic valve typically cannot be segmented directly from a computed tomography angiography image, the method described herein uses manually selected samples of an aortic segmentation derived from this image to inform the construction. These samples capture certain physiologic landmarks and are used to construct a volumetric valve model. As a demonstration of the capabilities of this method, valve models for 25 pediatric patients are created. A selected valve anatomy is used to perform fluid-structure interaction simulations using …

Computerized Electrocardiogram Data Transformation Enables Effective Algorithmic Differentiation Of Wide Qrs Complex Tachycardias, Anthony H Kashou, Sarah Lococo, Preet A Shaikh, Bhavesh B Katbamna, Ojasav Sehrawat, Daniel H Cooper, Sandeep S Sodhi, Phillip S Cuculich, Marye J Gleva, Elena Deych, Ruiwen Zhou, Lei Liu, Abhishek J Deshmukh, Samuel J Asirvatham, Peter A Noseworthy, Christopher V Desimone, Adam M May

2020-Current year OA Pubs

BACKGROUND: Accurate automated wide QRS complex tachycardia (WCT) differentiation into ventricular tachycardia (VT) and supraventricular wide complex tachycardia (SWCT) can be accomplished using calculations derived from computerized electrocardiogram (ECG) data of paired WCT and baseline ECGs.

OBJECTIVE: Develop and trial novel WCT differentiation approaches for patients with and without a corresponding baseline ECG.

METHODS: We developed and trialed WCT differentiation models comprised of novel and previously described parameters derived from WCT and baseline ECG data. In Part 1, a derivation cohort was used to evaluate five different classification models: logistic regression (LR), artificial neural network (ANN), Random Forests [RF], support …

Sentiment Analysis Of Insomnia-Related Tweets Via A Combination Of Transformers Using Dempster-Shafer Theory: Pre- And Peri-Covid-19 Pandemic Retrospective Study, Arash Maghsoudi, Sara Nowakowski, Ritwick Agrawal, Amir Sharafkhaneh, Mark E Kunik, Aanand D Naik, Hua Xu, Javad Razjouyan

Faculty, Staff and Student Publications

BACKGROUND: The COVID-19 pandemic has imposed additional stress on population health that may result in a change of sleeping behavior.

OBJECTIVE: In this study, we hypothesized that using natural language processing to explore social media would help with assessing the mental health conditions of people experiencing insomnia after the outbreak of COVID-19.

METHODS: We designed a retrospective study that used public social media content from Twitter. We categorized insomnia-related tweets based on time, using the following two intervals: the prepandemic (January 1, 2019, to January 1, 2020) and peripandemic (January 1, 2020, to January 1, 2021) intervals. We performed a …