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Deriving Biological Meaning and Clinical Application for Pediatric Sepsis with Data-driven Analysis
No full textPediatric sepsis is a life-threatening syndrome characterized by abnormal immune response to infection, resulting in organ failure and mortality. However, the success of regular therapies of pediatric sepsis has been hindered by the unavoidable heterogeneity within the patient population. To enable advanced precision medicine treatment, it is of great importance to identify patients at high risk and unravel the potential biological mechanisms driving the heterogeneity. In line with this need, this study leveraged clinical, genetic, and epigenetic data to first identify pediatric sepsis patients at high risk of severe outcomes and then detect biological markers associated with the phenotype of interest.
Beyond the conventional empirical pediatric sepsis phenotypes, Aim 1 of this study applied a machine learning approach to bedside clinical features and derived four computable pediatric sepsis phenotypes, PedSep-A, B, C, and D, which exhibited distinct infection resources and sites, inflammations, metabolisms, organ failures, and mortalities. Among them, PedSep-D was distinguished by significantly more severe outcomes compared to other phenotypes. Following this discovery, gene-based analysis in Aim 2 identified several deleterious variants in one exome-wide significant (LTBP4, p < 5E-8) and two suggestive (PLA2G4E and CCDC157, p < 5E-7) genes associated with PedSep-D, demonstrating the contribution of rare variants in pediatric sepsis severity. Finally, epigenome-wide association analysis in Aim 3 identified one genome-wide significant (cg16704797, p < 9E-8) and 24 suggestive significant (p < 1E-5) differentially methylated CpGs (DMCs), and one significant differentially methylated region (DMR) associated with PedSep-D. Functional analysis of the identified DMCs indicated their roles in regulating gene expression, immune cell activation, and lipid metabolisms.
This study has promoted our current knowledge of heterogeneity in pediatric sepsis and forwarded our understanding of disease pathology from perspectives of genetics and epigenetics. Furthermore, the accomplishment of this work contributed to addressing several gaps between current results from established studies and future applications in clinical programs to inform better development of precision medicine. The public health significance of findings gained from this study is particularly profound, offering the potential to revolutionize the way sepsis is diagnosed and treated in children, ultimately leading to more effective and efficient healthcare interventions
New York City Neonatal Herpes Database Migration: The Data Modernization Process and Implications of 2006-2019 Neonatal Herpes Data into Maven
No full textWith an approximated 60% fatality rate among untreated cases, neonatal herpes is a public health crisis that requires effective time-sensitive surveillance. However, it is not nationally notifiable. A limited number of states require its surveillance, each with different procedures for reporting. This results in limited information regarding the neonatal herpes incidence and a lack of historical information from which comparative trends can be determined and interventions can be designed.
New York City began recording reported neonatal herpes cases in an Access database in 2006. Since then, surveillance has been transferred to their centralized surveillance database, Maven, creating a need for neonatal herpes information from 2006 to 2019 to be migrated into Maven. Access records were first assigned Person IDs. A crosswalk document was created to match Access variables to Maven variables, and variable transfers were categorized into six types. Variables were imported into SAS, cleaned, and transformed to Maven variables. After multiple iterations were coded through SAS for variables in repeatable forms, appropriate parent questions were opened, and Maven labels were added, the created datasets were exported as comma separated text (.csv) files and imported into Maven.
The migration procedure resulted in 178 Access variables being migrated into 140 Maven variables. Migration challenges included correcting variables with substandard data entry errors, migrating variables with multiple iterations, and migrating variables that required manual reformatting. These errors were most found in laboratory information variables. The largest limiting factor in data quality was how information was collected outside of the health department. The roadblocks listed above can be mediated by ensuring public health reports are: (1) standardized among different laboratories/hospitals; (2) compatible with local public health reporting; (3) directly electronically reportable to the local health department.
Stricter reporting laws are needed to establish a consistent definition of neonatal herpes. Establishing a nationally notifiable status could inform its incidence rate over time and help establish interventions to decrease the rate of neonatal herpes. Modernized databases paired with stricter reporting laws can impart immense public health impact by improving surveillance efforts and decreasing the staggering morbidity and mortality rates of this important public health issue
Impact of COVID-19 on Adverse Outcomes for Congestive Heart Failure Inpatients in the Northeast Mid-Atlantic Using NIS 2020 Database
No full textBackground: The Coronavirus disease 2019 (COVID-19) is an infectious disease created by the SARS-CoV-2 virus. Although COVID-19 now remains an endemic disease, its adverse impacts on patients with congestive heart failure (CHF) have not been fully studied. This research uses the National Inpatient Sample (NIS) 2020 database to identify in-hospital outcomes of 109,667 CHF patients (104,015 without COVID-19, 5,652 with COVID-19) admitted to Northeast Mid-Atlantic hospitals (New York, Pennsylvania, New Jersey) in that year.
Methods: We utilized multivariable logistic regression models in analyzing 30-day in-hospital mortality (our primary outcome of interest) for CHF patients with and without COVID-19, adjusting for covariates. We also performed similar multivariable logistic regression models for several secondary in-hospital outcomes. We applied random forest in analyzing the importance of COVID-19, together with other baseline covariates, for predicting 30-day in-hospital mortality. Survival analysis was used to analyze time-to-in-hospital death in CHF patients with and without COVID-19.
Results: Our multivariable logistic regression analyses found that COVID-19 is significantly associated with an increased odds ratio for 30-day in-hospital mortality (OR = 7.20, 95% CI 6.67 - 7.77). Random forest analyses also found COVID-19 as the most important variable for the mean decrease accuracy metric of 30-day in-hospital mortality prediction. Our survival analysis reported that the survival curves of in-hospital mortality are significantly different for CHF patients with COVID-19 and those without COVID-19 (log-rank p < 0.001). The median time-to-in-hospital death for CHF patients with COVID-19 is 25 days (95% CI 23 - 27 days), while the median time-to-in-hospital death for those without COVID-19 is more than 30 days. Our secondary analyses also show significant differences in vasopressor use, sudden cardiac arrest, acute kidney injury on hemodialysis (HD), cardiogenic shock, and mechanical circulatory support (MCS) for CHF patients with and without COVID-19.
Public Health Significance: Understanding the severity of COVID-19 on CHF patients' in-hospital outcomes and how deadly COVID-19 ranked as one of the top risk factors for in-hospital mortality is critical for the clinical care of CHF patients during the pandemic. This also provides insights into the mitigation process for vulnerably chronic individuals during future disruptive public health crises
Identifying Risk Factors of Fall Risk Increasing Drug Use and Fall and Fall Injury Risk in Racially and Ethnically Diverse Adults Over 50
No full textBACKGROUND: Over 25% of older adults (65 years) fall every year, which can lead to injuries and disability. Fall risk increasing drugs (FRIDs), frequently defined through the Swedish National Board of Health and Welfare (SNBHW) and the CDC’s STEADI-Rx, are often initiated in midlife and have increased in prevalence among older adults mainly due to antihypertensive, antidepressant, and anticonvulsant use. Whether factors associated with use of FRIDs differ by definition is unknown. Additionally, associations between FRIDs and fall/fall injury risk are not fully understood in midlife or the oldest ages.
OBJECTIVES: This dissertation aimed to: identify risk factors associated with FRID use in older adults using SNBHW and STEADI-Rx definitions; and determine the association of FRIDs on self-reported fall/fall injury risk in Black and White men and women 79 years, and in multi-ethnic middle-age and early-old-age women.
METHODS: Participants included community-dwelling older adults in the Health, Aging, and Body Composition (Health ABC) Study (n=1352, 83±3 years) and those with <=2 years follow-up (n=1273, 83±4 years) for falls/fall injuries; and community-based multi-ethnic middle-age and early-old-age women in the Study of Women’s Health Across the Nation (SWAN, n=2010, Visits 13/14 and 15, 62±4 years). Multivariable logistic regression and negative binomial regression modeled risk factors associated with FRID use (yes/no) and count, respectively, for Health ABC. Multivariable generalized estimating equations modeled FRID use/count for fall/fall injury risk in Health ABC and SWAN.
RESULTS: Risk factors of FRID use were similar across definitions, including lifestyle/behavioral factors and conditions of multimorbidity. After removing antihypertensives from the STEADI-Rx definition, other FRID use and higher FRID count were associated with higher fall and fall injury risk vs. no falls in adults >=79 years. Among midlife and early-old-age women, physical activity or depressive symptoms, body pain, and vitality attenuated the association of FRID use and count, respectively, with fall injury risk to non-significance.
CONCLUSIONS: Results suggest activity or depressive symptoms, body pain, and vitality explains the associations of FRID use with fall/fall injury risk in midlife and early-old-age women, but not among adults >=79 years. Future interventions should evaluate fall/fall injury prevention through deprescribing FRIDs in older adults
Exploring the Burden on Family Caregivers from Racial and Ethnic Minority Groups Caring for Adults During the COVID-19 Pandemic in the United States: A Comprehensive Thematic Literature Review
No full textThe COVID-19 pandemic not only strained healthcare systems but significantly impacted the lives of those responsible for providing care to family members with health conditions, illnesses, or disabilities. Exacerbated by the pandemic, racial and ethnic minority family caregivers (REMFCGs) have faced unprecedented challenges and increased caregiver burden. REMFCGs already contend with a myriad of challenges in their caregiving roles, including navigating complex healthcare systems, managing multiple responsibilities, and coping with financial strain. However, the pandemic has intensified these challenges, placing additional stressors on caregivers' physical, emotional, and financial well-being. In this thematic literature review, 10 articles from Medline and APA PsycInfo® were reviewed to assess the impact the COVID-19 pandemic had on racial and ethnic minority caregivers. The results suggest there was a negative impact on REMFCGs’ mental and physical health and financial well-being from the COVID-19 pandemic. Suggesting that prioritizing the well-being of caregivers, especially those from racial and ethnic minority backgrounds, is essential as they often bear increased levels of stress, stigma, and disparities. By adopting inclusive strategies that cater to the needs of both caregivers and care recipients, we can create a more nurturing and supportive environment for all involved. Understanding the profound challenges faced by racial and ethnic minority family caregivers during the COVID-19 pandemic is crucial for informing targeted interventions and support services. By addressing the unique needs of this demographic, public health efforts can mitigate disparities, alleviate caregiver burden, and promote overall well-being, thereby fostering a more equitable and resilient healthcare system
Ensuring Patient Safety: Navigating EU MDR Compliance and Global Policy in Healthcare
No full textEnsuring patient safety remains the forefront priority in healthcare, pushing for a deeper understanding of regulatory frameworks, epidemiological methods, and the broader socioeconomic contexts shaping healthcare practices. This essay navigates the complexities of patient safety within the framework of European Medical Device Regulation (EU MDR) compliance and global healthcare policies, addressing three key competencies: applying epidemiological methods, interpreting data analysis, and discussing underlying organizational and stakeholder actions.
Emphasizing the critical role of regulatory compliance and global policy initiatives, this essay begins by exploring the significance of patient safety within the medical device landscape. The discussion of epidemiology practices, such as surveillance, risk analysis, and intervention evaluation, in ensuring the safety of medical devices will shape the broader discourse.
In addition, the interpretation of real-world evidence is a crucial component in informing evidence-based decision-making in public health research, policy formulation, and practice. EU MDR embodies how data identified trends impact regulatory decisions and guide healthcare interventions.
Lastly, the influence of organizational, industry, and stakeholder actions greatly impact care decisions and patient safety. The varying perspectives of political influence, economic incentives, ethnic disparities, and historical context shape healthcare practices and policies. The evolution of EU MDR provides a comprehensive framework of these factors that influence patient safety initiatives
A Comparison of Maximum Load, Tensile Strength, and Modulus of Elasticity of Orthodontic Archwires
No full textIntroduction Changes in the composition of orthodontic archwires have broadened their properties and characteristics. Along with the composition of wires, properties are affected by the geometric diameter of the wire. Maximum load, ultimate tensile strength, and modulus of elasticity are wire characteristics that can play a role in defining how these wires are able to be used in orthodontic treatment. The objective of this study is to discover if these wires can be used interchangeably based on these tested characteristics and to discover if diameter and shape alters any of these aforementioned alloys’ characteristics. Methods. Tensile testing was conducted on 140 wire samples of Nickel Titanium (NiTi), Titanium Molybdenum (TMA), and Stainless Steel archwires. Within each alloy, dimensions of .016in, .018in, .016x.022in2, and .018x.025in2 were tested. Values for Maximum Load, Ultimate Tensile Strength, and Modulus of Elasticity were obtained. Results. Overall, there were some significant differences seen within alloy groups with different dimensions. Round wires for TMA and NiTi wires showed a significantly higher values ultimate tensile strength and modulus of elasticity when compare to their rectangular counterparts. Stainless steel wires did not show this pattern. Conclusion. Dimension and shape did alter the values for some alloys of wires. Additionally, based on the 3 tested values, we cannot conclude that different alloys can be used interchangeably due to the large disparities in values between the alloy groups
Understanding International Student Enrollment at a Research One Public Land-Grant Institution in Appalachia
No full textU.S. higher education institutions (HEIs) are experiencing decreasing student enrollment. HEIs have cited decreasing birth rates, which began in 2008 following the Great Recession, as a main factor for the decline. Student enrollment in some mid-Atlantic states specifically is forecasted to drop by as much as 7.5% by 2029 (Kline, 2019). Like domestic student enrollment, international student enrollment has seen decline since before the COVID-19 global pandemic (Widener, 2020). This fact has added another blow to U.S. HEIs that have relied on international students as both a revenue source (Najar & Saul, 2016) and a means to meeting institutional strategic goals of diversity, global engagement, and talent from this population (Altbach & de Wit, 2020).
Because international student enrollment at Frederick Union University (FUU) (pseudonym) has declined over the past several years, this dissertation in practice addressed how the English Language Institute (pseudonym) made a change to its application and enrollment processes in an attempt to increase international student enrollment in its programs. Utilizing improvement science, a Zoom orientation session and supplementary on-demand chatting on WhatsApp were made available to applicants after they have received the IEP admission letter and before they arrived in a small mid-Atlantic city in a mid-Atlantic state. The purpose of this a Plan-Do-Study-Act cycle was to see if additional communication with applicants made them more likely to matriculate after being accepted. Mixed methods instruments were used to gauge the effectiveness of the intervention. Results from surveys and interviews led to subsequent adjustments to the Zoom orientation session throughout the period of inquiry. Although an innovative idea was implemented, the university was not able to handle the change due to the state of flux produced by ongoing “academic transformation” at the institution
Background Topic Knowledge as a Possible Moderator of the Testing Effect: an Experimental Investigation
No full textA large body of research has established a testing effect: testing of information results in better long-term retention than restudying. Given the relevance of such effects for education, there is interest in the conditions and learner differences that may moderate the utility of testing, like pre-existing knowledge. It is possible that (a) the testing effect is stronger for those who are more novice because testing is so effective that it helps novice learners catch up to expert learners or (b) the testing effect works equally well for everyone because it is so robust that all learners can benefit from it. In two experiments, college students read texts and were tested on them one week later. I orthogonally manipulated study strategy (retrieval practice versus restudying) and availability of background material for a given topic. In Experiment 2 only, feedback availability was orthogonally manipulated during testing. I found that participants had significantly better retention when they studied via retrieval practice and received feedback (Experiment 2). This demonstrates that immediate feedback is beneficial for learners, at least over a one-week retention interval. Further, when collapsing across categories of feedback, I found that participants had better retention when they received background topic material, regardless of which study strategy was used (Experiment 2) or performed significantly better when studying via restudying (Experiment 1). These results suggest that the learning benefits of testing do not depend on having high levels of existing domain knowledge
Design Space Exploration of High-Throughput Graph- and Signal-Processing Architectures using High-Level Synthesis and FPGAs
No full textData-intensive apps are becoming ever more prevalent due to the increasing amount of information available from sources such as social media and high-resolution sensors. The need to rapidly process this data and provide insights cannot be met easily through traditional computing methods. Accelerating apps through the use of custom hardware and specialized techniques is key for more efficient processing as datasets continue to grow in scale. This research focuses on creating high-throughput acceleration architectures for Intel FPGA devices using the oneAPI high-level synthesis (HLS) toolkit. We target two areas of research: graph processing and signal processing. The two chosen graph operations are breadth-first search (BFS) and minimum-spanning-tree (MST). The signal processing investigation focuses on accelerating the Fast Fourier Transform (FFT). Custom, partition-based methods are designed and developed for the acceleration of BFS and MST. Through design space exploration, we evaluate overall performance and productivity gains achieved by leveraging the oneAPI tools. Results showcase BFS performance of up to 75 million traversed edges per second, achieving up to 3.0× speedup over the Intel Xeon 6128 CPU baseline. Despite falling short of related hardware description language (HDL) research, the HLS methods created use 5.85× fewer lines of code compared to the HDL implementations. MST designs exhibit speedups of ∼1.5× when compared to the CPU baseline. To accelerate FFT using oneAPI and FPGA, a feedforward architecture was implemented and optimized. A design space exploration is performed to evaluate varying FFT resolutions, from 64k-point up to 512k-point in size. We find that a resolution of 256k-point provides a balance between resource utilization and performance, however, its performance lags behind that of the Fastest Fourier Transform in the West (FFTW) and Intel oneMKL libraries when executed in parallel on an eight-core Intel Xeon Platinum 8256 processor. Through the creation of these architectures, we are able to demonstrate the high productivity available with the oneAPI toolkit by evaluating different configurations of the designs with only minor changes to the code base