Proceedings of Abstracts Engineering and Computer Science Research Conference 2019

© 2019 The Author(s). This is an open-access work distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. For further details please see https://creativecommons.org/licenses/by/4.0/. Note: Keynote: Fluorescence visualisation to evaluate effectiveness of personal protective equipment for infection control is © 2019 Crown copyright and so is licensed under the Open Government Licence v3.0. Under this licence users are permitted to copy, publish, distribute and transmit the Information; adapt the Information; exploit the Information commercially and non-commercially for example, by combining it with other Information, or by including it in your own product or application. Where you do any of the above you must acknowledge the source of the Information in your product or application by including or linking to any attribution statement specified by the Information Provider(s) and, where possible, provide a link to this licence: http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/This book is the record of abstracts submitted and accepted for presentation at the Inaugural Engineering and Computer Science Research Conference held 17th April 2019 at the University of Hertfordshire, Hatfield, UK. This conference is a local event aiming at bringing together the research students, staff and eminent external guests to celebrate Engineering and Computer Science Research at the University of Hertfordshire. The ECS Research Conference aims to showcase the broad landscape of research taking place in the School of Engineering and Computer Science. The 2019 conference was articulated around three topical cross-disciplinary themes: Make and Preserve the Future; Connect the People and Cities; and Protect and Care

A longitudinal study of adult-onset asthma incidence among HMO members

BACKGROUND: HMO databases offer an opportunity for community based epidemiologic studies of asthma incidence, etiology and treatment. The incidence of asthma in HMO populations and the utility of HMO data, including use of computerized algorithms and manual review of medical charts for determining etiologic factors has not been fully explored. METHODS: We identified adult-onset asthma, using computerized record searches in a New England HMO. Monthly, our software applied exclusion and inclusion criteria to identify an "at-risk" population and "potential cases". Electronic and paper medical records from the past year were then reviewed for each potential case. Persons with other respiratory diseases or insignificant treatment for asthma were excluded. Confirmed adult-onset asthma (AOA) cases were defined as those potential cases with either new-onset asthma or reactivated mild intermittent asthma that had been quiescent for at least one year. We validated the methods by reviewing charts of selected subjects rejected by the algorithm. RESULTS: The algorithm was 93 to 99.3% sensitive and 99.6% specific. Sixty-three percent (n = 469) of potential cases were confirmed as AOA. Two thirds of confirmed cases were women with an average age of 34.8 (SD 11.8), and 45% had no evidence of previous asthma diagnosis. The annualized monthly rate of AOA ranged from 4.1 to 11.4 per 1000 at-risk members. Physicians most commonly attribute asthma to infection (59%) and allergy (14%). New-onset cases were more likely attributed to infection, while reactivated cases were more associated with allergies. Medical charts included a discussion of work exposures in relation to asthma in only 32 (7%) cases. Twenty-three of these (72%) indicated there was an association between asthma and workplace exposures for an overall rate of work-related asthma of 4.9%. CONCLUSION: Computerized HMO records can be successfully used to identify AOA. Manual review of these records is important to confirm case status and is useful in evaluation of provider consideration of etiologies. We demonstrated that clinicians attribute most AOA to infection and tend to ignore the contribution of environmental and occupational exposures

Common Genetic Polymorphisms Influence Blood Biomarker Measurements in COPD

Implementing precision medicine for complex diseases such as chronic obstructive lung disease (COPD) will require extensive use of biomarkers and an in-depth understanding of how genetic, epigenetic, and environmental variations contribute to phenotypic diversity and disease progression. A meta-analysis from two large cohorts of current and former smokers with and without COPD [SPIROMICS (N = 750); COPDGene (N = 590)] was used to identify single nucleotide polymorphisms (SNPs) associated with measurement of 88 blood proteins (protein quantitative trait loci; pQTLs). PQTLs consistently replicated between the two cohorts. Features of pQTLs were compared to previously reported expression QTLs (eQTLs). Inference of causal relations of pQTL genotypes, biomarker measurements, and four clinical COPD phenotypes (airflow obstruction, emphysema, exacerbation history, and chronic bronchitis) were explored using conditional independence tests. We identified 527 highly significant (p 10% of measured variation in 13 protein biomarkers, with a single SNP (rs7041; p = 10−392) explaining 71%-75% of the measured variation in vitamin D binding protein (gene = GC). Some of these pQTLs [e.g., pQTLs for VDBP, sRAGE (gene = AGER), surfactant protein D (gene = SFTPD), and TNFRSF10C] have been previously associated with COPD phenotypes. Most pQTLs were local (cis), but distant (trans) pQTL SNPs in the ABO blood group locus were the top pQTL SNPs for five proteins. The inclusion of pQTL SNPs improved the clinical predictive value for the established association of sRAGE and emphysema, and the explanation of variance (R2) for emphysema improved from 0.3 to 0.4 when the pQTL SNP was included in the model along with clinical covariates. Causal modeling provided insight into specific pQTL-disease relationships for airflow obstruction and emphysema. In conclusion, given the frequency of highly significant local pQTLs, the large amount of variance potentially explained by pQTL, and the differences observed between pQTLs and eQTLs SNPs, we recommend that protein biomarker-disease association studies take into account the potential effect of common local SNPs and that pQTLs be integrated along with eQTLs to uncover disease mechanisms. Large-scale blood biomarker studies would also benefit from close attention to the ABO blood group

Targeting patients for early COVID-19 therapy; Pre-infection metabolic dysfunction, polycystic ovary syndrome and risk of severe disease in patients under 65: A Massachusetts community-based observational study.

IntroductionThe demographics of those developing severe coronavirus disease (COVID-19) outcomes are shifting to younger patients. In an observational study utilizing electronic health records from a Massachusetts group medical practice, we identified 5025 patients with confirmed COVID-19 from March 1 to December 18, 2020. Of these, 3870 were under 65 years of age. We investigated the hypothesis that pre-infection metabolic or immunologic dysregulation including polycystic ovary syndrome (PCOS) increased risk of serious COVID-19 outcomes in patients under 65 years of age.Materials and methodsWe compared those with COVID-19 related hospitalization or mortality to all other COVID-19 patients, using a case control approach. Using logistic regression and propensity score modeling, we evaluated risk of developing severe COVID-19 outcomes (hospitalization or death) in those with pre-infection comorbidities, metabolic risk factors, or PCOS.ResultsOverall, propensity score matched analyses demonstrated pre-infection elevated liver enzymes alanine aminotransferase (ALT) >40, aspartate aminotransferase (AST) >40 and blood glucose ≥215 mg/dL were associated with more severe COVID-19 outcomes, OR = 1.74 (95% CI 1.31, 2.31); OR = 1.98 (95% CI 1.52, 2.57), and OR = 1.55 (95% CI 1.08, 2.23) respectively. Elevated hemoglobin A1C or blood glucose levels were even stronger risk factors for severe COVID-19 outcomes among those aged ConclusionIncreased risk of severe COVID-19 outcomes in those < age 65 with pre-infection indicators of metabolic dysfunction heightens the importance of monitoring pre-infection indicators in younger patients for prevention and early treatment. The PCOS finding deserves further investigation. Meanwhile women who suffer from PCOS should be carefully evaluated and prioritized for earlier COVID-19 treatment and vaccination

Hypertension, medications, and risk of severe COVID‐19: A Massachusetts community‐based observational study

Abstract It remains uncertain whether the hypertension (HT) medications angiotensin‐converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARB) mitigate or exacerbate SARS‐CoV‐2 infection. We evaluated the association of ACEi and ARB with severe coronavirus disease 19 (COVID‐19) as defined by hospitalization or mortality among individuals diagnosed with COVID‐19. We investigated whether these associations were modified by age, the simultaneous use of the diuretic thiazide, and the health conditions associated with medication use. In an observational study utilizing data from a Massachusetts group medical practice, we identified 1449 patients with a COVID‐19 diagnosis. In our study, pre‐infection comorbidities including HT, cardiovascular disease, and diabetes were associated with increased risk of severe COVID‐19. Risk was further elevated in patients under age 65 with these comorbidities or cancer. Twenty percent of those with severe COVID‐19 compared to 9% with less severe COVID‐19 used ACEi, 8% and 4%, respectively, used ARB. In propensity score‐matched analyses, use of neither ACEi (OR = 1.30, 95% CI 0.93 to 1.81) nor ARB (OR = 0.94, 95% CI 0.57 to 1.55) was associated with increased risk of severe COVID‐19. Thiazide use did not modify this relationship. Beta blockers, calcium channel blockers, and anticoagulant medications were not associated with COVID‐19 severity. In conclusion, cardiovascular‐related comorbidities were associated with severe COVID‐19 outcomes, especially among patients under age 65. We found no substantial increased risk of severe COVID‐19 among patients taking antihypertensive medications. Our findings support recommendations against discontinuing use of renin–angiotensin system (RAS) inhibitors to prevent severe COVID‐19