bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reducing Wait Time in a High-volume Pediatric Neuro-oncology Clinic by Optimizing Process Flow: A Quality Improvement Project
Authors: Vinitsky Anna , David Barbara , Michalik Layna , Ramirez Nicole , Risinger Adam , Burlison Jonathan D. , Zanders Jacky , Mans Bridget , Heady Katie , Holdiness Joni , Qaddoumi Ibrahim , Robinson Giles W. , Moreira Daniel , Upadhyaya Santhosh A. , Gajjar Amar 
Published: June 2022

Introduction:
Hospital wait time (WT) influences healthcare quality and patient satisfaction. Long WTs are distressful for patients and considered substandard healthcare delivery. Pediatric hematology/oncology patients with complex medical conditions frequently need multiple appointments in a day, making their scheduling very challenging. Here, we report a quality improvement (QI) project aimed to decrease the percentage of patients waiting >30 minutes before room placement in the neuro-oncology clinic.

Methods:
We measured WT from when the patient reported to the clinic (or, for those arriving early, from scheduled appointment) to when the patient got an exam room. We collected data by random sampling and collected baseline data over the initial 4 weeks; generated process mapping and Pareto charts to identify reasons for delayed patient placement in rooms; and used iterative Plan-Do-Study-Act (PDSA) cycles to test interventions. We used Run charts and Shewhart charts for data analysis.

Results:
Our baseline data analyses showed provider and room availability as critical reasons for delayed room placement (38.4% and 30%, respectively). We also completed related PDSA improvement cycles. The median percent of patients waiting >30 minutes decreased from 21% to 13%. The median average waiting time decreased from 21 to 11 minutes.

Conclusion:
Using structured QI methodology, we decreased the percent of patients waiting >30 minutes before room placement and overall WTs. We developed a strategy for continuous improvement and future interventions. Furthermore, our results suggest that QI projects, which account for the complexity of hospital systems, can improve patient flow throughout the hospital.
Improving Knowledge of Active Safety and QI Projects Amongst Practitioners in a Pediatric ICU
Authors: Flaherty Brian F. , Hummel Kevin , Vijayarajah Senthuran , White Benjamin R. , Outsen Shad , Larsen Gitte Y. 
Published: June 2022

Introduction:
The success of quality improvement (QI) projects depends on many factors, with communication and knowledge of project-specific practice change being fundamental. This project aimed to improve the knowledge of active safety and QI projects.

Methods:
Two interventions were trialed to improve knowledge: paired email and meeting announcements followed by a daily huddle to review ongoing projects. Knowledge, measured as the ability to recall a project and its practice change, was the primary outcome. The frequency and duration of the Huddle were process and balancing measures, respectively.

Results:
Seven days after a meeting/email announcement, 3 of 13 (23%) faculty and fellows recalled the announced practice change. Investigators then tested the effects of the Huddle by assessing practitioners’ knowledge of safety and QI project-related practice changes on the first and last day of a service week. The average percentage of items recalled increased from the beginning to end of a service week by 33% [46% to 79%, 95% confidence interval (CI) 12–53] for faculty and 27% (51% to 77%, 95% CI 13–40) for fellows. The Huddle occurred in four of seven (interquartile range 2–5) days/wk with a mean duration of 4.5 (SD 2) minutes. Follow-up assessment 2 years after Huddle implementation demonstrate sustained increase in item recall [faculty +36% (95% CI +13% to 40%); fellows +35% (95% CI +23% to 47%)].

Conclusions:
A daily huddle to discuss safety and QI project-related practice change is an effective and time-efficient communication method to increase knowledge of active projects.
Improving Blood Product Transfusion Premedication Plan Documentation: A Single-institution Quality Improvement Effort
Authors: Sitthi-amorn Jitsuda , Denton Emily , Harper Erin , Carias Delia , Hashmi Saman , Bami Sakshi , Ast Allison , Landry Taylor , Pettit Kenneth L. , Gorantla Shilpa , Vinitsky Anna , Zheng Yan , Johnson Liza-Marie 
Published: June 2022

Introduction:
Premedication with acetaminophen and/or diphenhydramine to prevent febrile nonhemolytic transfusion reactions and minor allergic transfusion reactions is a common practice based on historical recommendations. However, recent small randomized-controlled trials showed no benefit of premedication. This inconsistency leads to practice variability, which results in the inefficiency of our institution’s blood product ordering process. This project aimed to improve the number of transfusion encounters with premedication plan documentation from a baseline of 19% to 80% in 12 months.

Methods:
A multidisciplinary quality improvement (QI) team used QI tools to design interventions to improve the efficiency of the ordering process for blood products. Measures were tracked monthly and analyzed using statistical process control.

Results:
From September 2018 to January 2021, 5,351 blood product transfusion visits were scheduled. At baseline, 34% of patients received premedication, and 19% had premedication plans documented. Interventions included a passive computerized provider order entry alert, clinical care pathway development, and clinician education. Postimplementation, the average number of encounters with a premedication plan increased from 19% to 87%, whereas encounters receiving premedication decreased from 34% to 25%. There was no change in the average number of transfusion reactions (1.8 per 100 transfusions).

Conclusions:
Using QI methods, our team successfully standardized the blood product premedication plan documentation despite unclear best practices regarding blood product transfusion premedication. The team added premedication plan documentation training to new employee orientation for sustainability.
A Safety Analysis of Programmed Death 1 Pathway Inhibitors in Patients With Solid Tumor Malignancies and Preexisting Autoimmune Disease
Authors: Higgins Jordyn Paige , Trinh Anh Viet , Watson Marley L. , Beardslee Tyler , Goyal Subir , Kudchadkar Ragini , Pakkala Suchita , Waltuck Jonathan , Momary Kathryn , Byers Kristina F. 
Published: June 2022

Objective
The aim of this study was to characterize the safety of programmed death 1 inhibitors in patients with preexisting autoimmune disease.

Methods
A medical records review study was conducted on adults with solid tumor malignancies who received ≥1 dose of pembrolizumab or nivolumab at Emory Healthcare from September 4, 2014 until December 31, 2019. All autoimmune patients were included (n = 77), whereas the nonautoimmune patients were randomized and the first 156 patients were included in a 2:1 ratio to autoimmune patients. The primary objective was the comparison of incidence of immune-related adverse events (irAEs) between patients with preexisting autoimmune disease and those without. Secondary objectives included irAE characterization, irAE treatment, and survival analyses.

Results
Preexisting autoimmune disease was controlled in all of the autoimmune patients before immunotherapy initiation. The rate of irAE was 32.7% in the nonautoimmune group and 42.9% in the autoimmune group (odds ratio, 0.65; 95% confidence interval, 0.37–1.14; p = 0.130). In the patient population diagnosed with a rheumatologic autoimmune disease, 23.81% of irAEs were considered to be a flare of their preexisting autoimmune disease. Less patients in the autoimmune group experienced a grade ≥3 irAE (21.21% vs 37.25%, p = 0.379) and received systemic corticosteroids (54.55% vs 67.35%, p = 0.241) for the treatment of the irAE.

Conclusions
These results suggest that pembrolizumab and nivolumab can be safely administered in patients with controlled preexisting autoimmune diseases without a significant increase in irAE compared with patients without autoimmune diseases. Inclusion of patients with preexisting autoimmune diseases in prospective clinical trials is warranted.
Immune Checkpoint Inhibitor–Associated Myositis
Authors: Saygin Didem , Ghosh Nilasha , Reid Pankti 
Published: June 2022

Abstract
Research on the relationship between inflammatory myopathy and malignancy has grown considerably within the last century. Now, the burgeoning field of inflammatory myopathy has yet another player in the mix: immune checkpoint inhibitor–associated myositis (ICI myositis). Immune checkpoint inhibitor–associated myositis is indicated by clinical diagnosis of inflammatory myopathy after initiation of immune checkpoint inhibitor for cancer management. Current literature reflects low prevalence but high mortality associated with ICI myositis, especially when involving myasthenia gravis and myocarditis. Immune checkpoint inhibitor–associated myositis tends to have muscle pain along with weakness, infrequent presentation with dermatitis, or interstitial lung disease and is typically seronegative with scattered, endomysial inflammatory infiltrates on biopsy. The differential diagnosis of ICI myositis includes myasthenia gravis and other neurological immune-related adverse events. Therapeutic approach involves high doses of corticosteroids with a choice of steroid-sparing immunomodulating agent(s) that is primarily driven by expert opinion due to lack of robust research to support one agent over another. There is wide variation in the inclusion criteria for ICI myositis used in previous studies. We review previously used inclusion criteria and suggest an expertise-based classification criterion to provide a standardized definition and allow comparability between studies. There is a critical need for prospective translational and clinical studies that elucidate the pathophysiology of ICI myositis in order to improve evaluation and management of these patients.
Predictors of Remission and Low Disease Activity in Rheumatoid Arthritis Patients
Authors: Gamboa-Cárdenas Rocío-V. , Ugarte-Gil Manuel-F. , Pimentel-Quiroz Víctor , Reátegui -Sokolova Cristina , Rodríguez-Bellido Zoila , Zevallos-Miranda Francisco , Medina-Chinchón Mariela , Alfaro-Lozano José , Noriega-Zapata Erika , Cucho-Venegas J. Mariano , Perich-Campos Risto , Pastor-Asurza César , Alarcón Graciela S. 
Published: June 2022

Background
Clinical remission is the goal in rheumatoid arthritis (RA) management; however, this can be difficult to achieve in several parts of the world. Our objective was to determine predictors of remission and remission/low disease activity (LDA) in RA.

Methods
A longitudinal real-setting RA cohort was followed up (January 2016–2020). Predictors examined were sex, age at diagnosis, disease duration, socioeconomic status, tobacco use, rheumatoid factor titer, comorbidities (Charlson index), Simple Disease Activity Index (SDAI) score, disability (Multidimensional Disease Health Assessment Questionnaire), health-related quality of life (Short Form-36 questionnaire), glucocorticoid dose, biological/target synthetic disease-modifying antirheumatic drugs, and conventional DMARD (c-DMARD) use. Univariable and multivariable generalized estimating equation models were done to determine predictors of remission (at a given visit) and sustained remission (2 consecutives visits), using the SDAI definition (0 or <3.3). Similarly, remission/LDA (SDAI <11) predictors were examined.

Results
Five hundred thirty RA patients included the following: 160 patients (30.2%) achieved remission in at least 1 visit, and 126 patients (23.77%) achieved sustained remission. On the multivariable analysis glucocorticoid dose (odds ratio [OR], 1.060; 95% confidence interval [CI], 1.027–1.094; p = 0.004) and current (OR, 2.293; 95% CI, 1.811–2.903; p < 0.001) or past (OR, 1.383; 95% CI, 1.127–1.698; p = 0.002) use of c-DMARDs predicted remission/LDA in at least 1 visit, whereas the SDAI (OR, 0.951; 95% CI, 0.942–0.959; p < 0.001), Multidimensional Disease Health Assessment Questionnaire (OR, 0.648; 95% CI, 0.549–0.764; p < 0.001), and age at diagnosis (OR, 0.994; 95% CI, 0.990–0.998; p = 0.004) were negative predictors. As to sustained remission/LDA, current (OR, 2.012; 95% CI, 1.458–2.776: p < 0.001) or past (OR, 1.517; 95% CI, 1.155–1.993; p = 0.003) use of c-DMARDs, having a better Short Form-36 questionnaire physical component summary (OR, 1.022; 95% CI, 1.014–1.029; p < 0.001), and older age at diagnosis (OR, 1.013; 95% CI, 1.003–1.022; p = 0.008) predicted it, whereas SDAI (OR, 0.949; 95% CI, 0.933–0.965; p < 0.001) and medium low/low socioeconomic status (OR, 0.674; 95% CI, 0.500–0.909; p = 0.010) were negative predictors.

Conclusion
During follow-up of this real-world RA cohort, c-DMARD use predicted remission and remission/LDA. In contrast, disease activity was a negative predictor.
Potential Pitfall in the Interpretation of Ganglioneuronal Uptake of 18F-PSMA-1007 PET/CT Scans Performed With a High Spatial Resolution Digital PET Scanner
Authors: Kisiel Nadya , Thomas Paul 
Published: June 2022

Abstract
A 69-year-old man with biochemical recurrence of prostate cancer after radical prostatectomy 5 years previously and subsequent salvage radiotherapy to the prostate bed and pelvic nodes underwent PET/CT on a Siemens mCT Flow PET and a second PET/CT 10 months later on a Siemens Vision 600 Digital PET. In addition to a suspicious left hilar lymph node, the new high-resolution PET showed increased visualization and avidity of physiologic uptake in paraspinal and presacral sympathetic ganglia. Caution should be undertaken when interpreting PET/CTs performed on high-resolution digital scanners to avoid mistaking ganglia uptake for metastatic disease.
Virtual Reality Training in Disaster Medicine
Authors: Brown Natasha , Margus Colton , Hart Alexander , Sarin Ritu , Hertelendy Attila , Ciottone Gregory 
Published: June 2022

Summary Statement
Disaster medicine (DM) training aims to recreate stressful, mass casualty scenarios faced by medical professionals in the field with high fidelity. Virtual (VR) and augmented reality (AR) are well suited to disaster training as it can provide a safe, socially distant simulation with a high degree of realism. The purpose of this literature review was to summarize the current use of VR or AR for simulation training of healthcare providers in DM education. A systematic review of peer-reviewed articles was performed from January 1, 2000, to November 21, 2020, on PubMed, Embase, and OVID. Exclusion criteria included non-English articles, computer-generated models without human participants, or articles not relating to DM, VR or AR. Thirty-two articles were included. Triage accuracy was evaluated in 17 studies. Participants reported improved confidence and positive satisfaction after the simulations. The studies suggest VR or AR can be considered for disaster training in addition to other, more traditional simulation methods. More research is needed to create a standardized educational model to incorporate VR and AR into DM training and to understand the relationship between disaster simulation and improved patient care.
Development and validation of a Bayesian belief network predicting the probability of blood transfusion after pediatric injury
Authors: Sullivan Travis M. , Milestone Zachary P. , Tempel Peyton E. , Gao Sarah , Burd Randall S. 
Published: June 2022

BACKGROUND
Early recognition and intervention of hemorrhage are associated with decreased morbidity in children. Triage models have been developed to aid in the recognition of hemorrhagic shock after injury but require complete data and have limited accuracy. To address these limitations, we developed a Bayesian belief network, a machine learning model that represents the joint probability distribution for a set of observed or unobserved independent variables, to predict blood transfusion after injury in children and adolescents.

METHODS
We abstracted patient, injury, and resuscitation characteristics of injured children and adolescents (age 1 to 18 years) from the 2017 to 2019 Trauma Quality Improvement Project database. We trained a Bayesian belief network to predict blood transfusion within 4 hours after arrival to the hospital following injury using data from 2017 and recalibrated the model using data from 2018. We validated our model on a subset of patients from the 2019 Trauma Quality Improvement Project. We evaluated model performance using the area under the receiver operating characteristic curve and calibration curves and compared performance with pediatric age-adjusted shock index (SIPA) and reverse shock index with Glasgow Coma Scale (rSIG) using sensitivity, specificity, accuracy, and Matthew's correlation coefficient (MCC).

RESULTS
The final model included 14 predictor variables and had excellent discrimination and calibration. The model achieved an area under the receiver operating characteristic curve of 0.92 using emergency department data. When used as a binary predictor at an optimal threshold probability, the model had similar sensitivity, specificity, accuracy, and MCC compared with SIPA when only age, systolic blood pressure, and heart rate were observed. With the addition of the Glasgow Coma Scale score, the model has a higher accuracy and MCC than SIPA and rSIG.

CONCLUSION
A Bayesian belief network predicted blood transfusion after injury in children and adolescents better than SIPA and rSIG. This probabilistic model may allow clinicians to stratify hemorrhagic control interventions based upon risk.

LEVEL OF EVIDENCE
Prognostic and Epidemiologic; Level III.
Mutation accumulation opposes polymorphism: supergenes and the curious case of balanced lethals
Authors: Berdan Emma L. , Blanckaert Alexandre , Butlin Roger K. , Flatt Thomas , Slotte Tanja , Wielstra Ben 
Published: June 2022

Supergenes offer spectacular examples of long-term balancing selection in nature, but their origin and maintenance remain a mystery. Reduced recombination between arrangements, a critical aspect of many supergenes, protects adaptive multi-trait phenotypes but can lead to mutation accumulation. Mutation accumulation can stabilize the system through the emergence of associative overdominance (AOD), destabilize the system, or lead to new evolutionary outcomes. One outcome is the formation of maladaptive balanced lethal systems, where only heterozygotes remain viable and reproduce. We investigated the conditions under which these different outcomes occur, assuming a scenario of introgression after divergence. We found that AOD aided the invasion of a new supergene arrangement and the establishment of a polymorphism. However, this polymorphism was easily destabilized by further mutation accumulation, which was often asymmetric, disrupting the quasi-equilibrium state. Mechanisms that accelerated degeneration tended to amplify asymmetric mutation accumulation between the supergene arrangements and vice-versa. As the evolution of balanced lethal systems requires symmetric degeneration of both arrangements, this leaves only restricted conditions for their evolution, namely small population sizes and low rates of gene conversion. The dichotomy between the persistence of polymorphism and degeneration of supergene arrangements likely underlies the rarity of balanced lethal systems in nature.
This article is part of the theme issue ‘Genomic architecture of supergenes: causes and evolutionary consequences’.
Protein-based Virtual Screening Tools applied for RNA-Ligand Docking identify new Binders of the preQ1-Riboswitch
Authors: Kallert Elisabeth , Fischer Tim R. , Schneider Simon , Grimm Maike , Helm Mark , Kersten Christian 
Published: June 2022

AbstractTargeting RNA with small molecules is an emerging field. While several ligands for different RNA targets are reported, structure-based virtual screenings against RNAs are still rare. Here, we elucidated the general capabilities of protein-based docking programmes to reproduce native binding modes of small molecule RNA ligands and to discriminate known binders from decoys by the scoring function. The programmes were found to perform similar compared to the RNA-based docking tool rDOCK and the faced challenges during docking, namely protomer and tautomer selection, target dynamics and explicit solvent, do not largely differ from challenges in conventional protein-ligand docking. A prospective virtual screening with the Bacillus subtilis preQ1-riboswitch aptamer domain performed with FRED, HYBRID and FlexX, followed by microscale thermophoresis assays identified 6 active compounds out of 23 tested virtual screening hits with potencies between 29.5 nM and 11.0 μM. The hits were selected not solely based on their docking score, but for resembling key interactions of the native ligand. Therefore, this study demonstrates the general feasibility to perform structure-based virtual screenings against RNA targets, while at the same time it highlights pitfalls and their potential solutions when executing RNA-ligand docking.
Gene expression studies of WT1 mutant Wilms tumor cell lines in the frame work of published kidney development data reveals their early stem cell origin
Authors: Royer-Pokora Brigitte , Wruck Wasco , Beier Manfred 
Published: June 2022

AbstractIn order to get a better insight into the timing of WT1 mutant Wilms tumor development, we compared the gene expression profiles of nine established WT1 mutant Wilms tumor cell lines with published data from different kidney cell types during development. Publications describing genes expressed in nephrogenic precursor cells, ureteric bud cells, more mature nephrogenic epithelial cells and interstitial cell types were used. These studies uncovered that the WT1 mutant Wilms tumor cells lines express genes from the earliest nephrogenic progenitor cells, as well as from more differentiated nephron cells with the highest expression from the stromal/interstitial compartment. The expression of genes from all cell compartments points to an early developmental origin of the tumor in a common stem cell. Although variability of the expression of specific genes was evident between the cell lines the overall expression pattern was very similar. This is likely dependent on their different genetic backgrounds with distinct WT1 mutations and the absence/presence of mutant CTNNB1.
Paragraph - Antibody Paratope prediction using Graph Neural Networks with minimal feature vectors
Authors: Chinery Lewis , Wahome Newton , Moal Iain , Deane Charlotte M. 
Published: June 2022

1AbstractSummaryThe development of new vaccines and antibody therapeutics typically takes several years and requires over $1bn in investment. Accurate knowledge of the paratope (antibody binding site) can speed up and reduce the cost of this process by improving our understanding of antibody-antigen binding. We present Paragraph, a structure-based paratope prediction tool that outperforms current state-of-the-art tools using simpler feature vectors and no antigen information.AvailabilitySource code is freely available at www.github.com/oxpigContactdeane@stats.ox.ac.ukSupplementary informationSupplementary data are available at bioRxiv online.