Taming the Wilde: Collaborating with Expertise for Faster, Better, Smarter Collection Analysis

The importance of collection assessment and evaluation has been a hot topic due to increasing budget restrictions and the need to prove worth to stakeholders through evidence‐based evaluations. More robust collection analyses, like comparisons of holdings usage to ILL requests, and gap analyses, are increasingly embraced by the library community. Less thought, however, has been given to how to best conduct these analyses to ensure that the cleanest data is used and that the data tells the right story. The data to do these types of analyses often reside in complex systems and web‐environments, which may not be fully understood by the collection managers or subject librarians. The University of Houston Libraries embarked on a largescale gap analysis of the collection by subject area. The key component to success was quickly, accurately, and properly mining the data sources such as Sierra and the electronic resource management system. Our collection team contends that collaboration with expertise in the Resource Discovery Systems Department allowed the team to more quickly develop complete and accurate datasets, and helped to shape the analysis conducted. This paper discusses the challenges of defining project scope, the process of forming methodology, and the challenges of collecting the data. It will also review how experts were able to contribute to each step of this process. Finally it will outline some initial findings of the analysis, and how this research was accomplished in a realistic time frame

The CTSA University of Texas Health Science Center (UTHSC) Northeast—Tyler and Rio Grande Valley Success Story: How Rural, Underserved Academic Communities Rapidly Built a Robust Engine for Collaborative COVID-19 Clinical Research

In 2018, The University of Texas Health Science Center– Tyler and University of Texas Rio Grande Valley were invited to develop clinical research units for an existing Clinical and Translational Science Award (CTSA) consortium with the objective to equip medically underserved, economically disadvantaged communities and subsequently to deploy COVID-19 clinical trials in response to a public health emergency

Structural analysis of pathogenic mutations in the DYRK1A gene in patients with developmental disorders.

Haploinsufficiency in DYRK1A is associated with a recognizable developmental syndrome, though the mechanism of action of pathogenic missense mutations is currently unclear. Here we present 19 de novo mutations in this gene, including five missense mutations, identified by the Deciphering Developmental Disorder study. Protein structural analysis reveals that the missense mutations are either close to the ATP or peptide binding-sites within the kinase domain, or are important for protein stability, suggesting they lead to a loss of the protein's function mechanism. Furthermore, there is some correlation between the magnitude of the change and the severity of the resultant phenotype. A comparison of the distribution of the pathogenic mutations along the length of DYRK1A with that of natural variants, as found in the ExAC database, confirms that mutations in the N-terminal end of the kinase domain are more disruptive of protein function. In particular, pathogenic mutations occur in significantly closer proximity to the ATP and the substrate peptide than the natural variants. Overall, we suggest that de novo dominant mutations in DYRK1A account for nearly 0.5% of severe developmental disorders due to substantially reduced kinase function

Error Metrics for Large-Scale Digitization

The paper summarizes the methodology utilized in an ongoing project that is exploring quality issues in the large-scale digitization of books by third-party vendors – such as Google and the Internet Archive – that are preserved in the HathiTrust Digital Library. The paper describes the research foundation for the project and the model of digitization error that frames the data gathering effort. The heart of the paper is an overview of the metrics and methodologies developed in the project to apply the error model to statistically valid random samples of digital book-surrogates that represent the full range of source volumes digitized by Google and other third party vendors. Proportional and systematic sampling of page-images within each 1,000-volume sample produced a study set of 356,217 page images. Using custom-built web-enabled database systems, teams of trained coders have recorded perceived error in page-images on a severity scale of 0-5 for up to eleven possible errors. The paper concludes with a summary of ongoing research and the potential for future research derived from the present effort.National Science FoundationInstitute for Museum and Library Serviceshttp://deepblue.lib.umich.edu/bitstream/2027.42/99520/1/C8 Conway-Bronicki Digitization Error Metrics 2012.pd

Analyzing monograph usage of approval and firm orders for collection development

The poster describes a collection assessment project that compares the use of monographs purchased on an approval plan with those acquired via subject librarians’ selections. The goal is to reveal the usage trends between the two different selection processes. The analysis is based on LC classifications and subject groupings. We hypothesize that the usage patterns vary among subjects. The findings will inform collection managers in their effort to establish an effective and sustainable collection strategy.Librarie

Report on Open Access Publishing for the Research and Scholarship Committee of the Faculty Senate with Recommendations

Report with recommendations submitted to the Research and Scholarship Committee of the UH Faculty SenateIn this report, we discuss the need for the University of Houston to take an active role in managing open access (OA) publishing for the faculty and librarians.Biology and Biochemistry, Department ofLibrarie

The impact of medical interventions on admission characteristics in children with congenital heart disease and cardiomyopathy

Introduction: Children with congenital heart disease and cardiomyopathy are a unique patient population. Different therapies continue to be introduced with large practice variability and questionable outcomes. The purpose of this study is to determine the impact of various medications on intensive care unit length of stay, total length of stay, billed charges, and mortality for admissions with congenital heart disease and cardiomyopathy. Materials and methods: We identified admissions of paediatric patients with cardiomyopathy using the Pediatric Health Information System database. The admissions were then separated into two groups: those with and without inpatient mortality. Univariate analyses were conducted between the groups and the significant variables were entered as independent variables into the regression analyses. Results: A total of 10,376 admissions were included these analyses. Of these, 904 (8.7%) experienced mortality. Comparing patients who experienced mortality with those who did not, there was increased rate of acute kidney injury with an odds ratio (OR) of 5.0 [95% confidence interval (CI) 4.3 to 5.8, p \u3c 0.01], cardiac arrest with an OR 7.5 (95% CI 6.3 to 9.0, p \u3c 0.01), and heart transplant with an OR 0.3 (95% CI 0.2 to 0.4, p \u3c 0.01). The medical interventions with benefit for all endpoints after multivariate regression analyses in this cohort are methylprednisolone, captopril, enalapril, furosemide, and amlodipine. Conclusions: Diuretics, steroids, angiotensin-converting enzyme inhibitors, calcium channel blockers, and beta blockers all appear to offer beneficial effects in paediatric cardiomyopathy admission outcomes. Specific agents within each group have varying effects

Alpha-blockade during congenital heart surgery admissions: Analysis from national database

INTRODUCTION: The effects of alpha-blockade on haemodynamics during and following congenital heart surgery are well documented, but data on patient outcomes, mortality, and hospital charges are limited. The purpose of this study was to characterise the use of alpha-blockade during congenital heart surgery admissions and to determine its association with common clinical outcomes. MATERIALS AND METHODS: A cross-sectional study was conducted using the Pediatric Health Information System database. De-identified data for patients under 18 years of age with a cardiac diagnosis who underwent congenital heart surgery were obtained from 2004 to 2015. Patients were subdivided on the basis of receiving alpha-blockade with either phenoxybenzamine or phentolamine during admission or not. Continuous and categorical variables were analysed using Mann−Whitney U-tests and Fisher exact tests, respectively. Characteristics between subgroups were compared using univariate analysis. Regression analyses were conducted to determine the impact of alpha-blockade on ICU length of stay, hospital length of stay, billed charges, and mortality. RESULTS: Of the 81,313 admissions, 4309 (5.3%) utilised alpha-blockade. Phentolamine was utilised in 4290 admissions. In univariate analysis, ICU length of stay, total length of stay, inpatient mortality, and billed charges were all significantly higher in the alpha-blockade admissions. However, regression analyses demonstrated that other factors were behind these increased. Alpha-blockade was significantly, independently associated with a 1.5 days reduction in ICU length of stay (p \u3c 0.01) and a 3.5 days reduction in total length of stay (p \u3c 0.01). Alpha-blockade was significantly, independently associated with a reduction in mortality (odds ratio 0.8, 95% confidence interval 0.7−0.9). Alpha-blockade was not independently associated with any significant change in billed charges. CONCLUSIONS: Alpha-blockade is used in a subset of paediatric cardiac surgeries and is independently associated with significant reductions in ICU length of stay, hospital length of stay, and mortality without significantly altering billed charges

Correlation of near-infrared spectroscopy oximetry and corresponding venous oxygen saturations in children with congenital heart disease

Invasive and non-invasive monitoring allow for early detection of hemodynamic compromise, facilitating timely intervention and avoidance of further decline. While venous oximetry is useful for assessing the adequacy of systemic oxygen delivery (DO2), it is most often intermittent, invasive, and costly. Near-infrared spectroscopy (NIRS) oximetry allows for the non-invasive estimation of the adequacy of DO2. We assessed the correlation between cerebral NIRS oximetry and superior vena cava (SVC) and jugular venous (JV) oxygen saturations and between renal NIRS oximetry and inferior vena cava (IVC) oxygen saturations. Systematic review of the literature was conducted to identify studies with data regarding near-infrared spectroscopy and venous saturation. The PubMed, EMBASE, Medline, and Cochrane databases were queried using the following terms in isolation and various combinations: congenital heart disease, near infrared spectroscopy, venous saturation, and pediatric. Pediatric studies in which simultaneous NIRS oximetry and corresponding venous oxygen saturations were simultaneously collected after cardiac surgery or catheterization were identified. Data were pooled from these studies to analyze the correlation between NIRS oximetry and the corresponding venous oxygen saturations. A total of 16 studies with 613 patients were included in the final analyses. Data were present to compare cerebral and renal NIRS oximetry with corresponding venous oxygen saturation. Cerebral NIRS and SVC and JV oxygen saturations and renal NIRS and IVC oxygen saturations demonstrated strong degrees of correlation (r-value 0.70 for each). However, cerebral NIRS and IVC oxygen saturation had a week degree of correlation (r-value of 0.38). Pooled analyses demonstrate that cerebral NIRS oximetry correlates strongly with SVC or JV oxygen saturation while renal NIRS oximetry correlates strongly with IVC oxygen saturations. A weak correlation was noted between cerebral NIRS oximetry and IVC oxygen saturations