bluuebunny/crossref_metadata_2025_split huggingface dataset:
Disparities in Access to Hepatitis C Treatment Among Arizona Medicaid Beneficiaries With Chronic Hepatitis C
Authors: Jiang Xinyi , Song Hyun Jin , Chang Ching-Yuan , Wilson Debbie , Guo Jingchuan , Lo-Ciganic Wei-Hsuan , Park Haesuk 
Published: December 2022

Background:
High costs of direct-acting antivirals (DAAs) have led to their restricted access for patients with hepatitis C virus (HCV).

Objective:
The aim was to assess how HCV treatment access and predictors of HCV treatment changed in the post-DAA period compared with pre-DAA period.

Methods:
A retrospective cohort study using Arizona Medicaid data was conducted for patients with HCV to compare treatment initiation rates between pre-DAA (January 2008–October 2013) and post-DAA (November 2013–December 2018) periods. Multivariable logistic regression was used, controlling for demographic and clinical variables.

Results:
Twenty-four thousand and ninety and 28,756 patients during the pre-DAA and post-DAA periods were identified. Overall, 12.6% were treated in the post-DAA period compared with 7.8% in the pre-DAA period (P<0.001). The relative increase in the HCV treatment initiation rate from the pre-DAA to the post-DAA period was significant greater for Black beneficiaries compared with White beneficiaries (P=0.002). Hispanic beneficiaries were less likely to be treated in the post-DAA period [adjusted odds ratios (aOR): 0.88; CI: 0.79–0.98] compared with White beneficiaries. Those with mental illness (aOR: 0.71; 95% CI: 0.63–0.80) and substance use disorders (aOR: 0.63; 95% CI: 0.58–0.68) were less likely to be treated in the post-DAA period.

Conclusions:
Although treatment initiation increased and disparities for Black beneficiaries compared with White beneficiaries attenuated in the post-DAA period, only 13% of Arizona Medicaid patients with HCV received DAA treatment. Disparities in DAA access remained among Hispanic patients and those with mental illness and substance use disorders.
Update on combined heart and liver transplantation: evolving patient selection, improving outcomes, and outstanding questions
Authors: Tracy Kaitlyn M. , Matsuoka Lea K. , Alexopoulos Sophoclis P. 
Published: December 2022

Purpose of review
Combined heart and liver transplantation (CHLT) is an uncommon but increasingly performed procedure with rising need as the population who has undergone Fontan palliation for single ventricle physiology grows. This article reviews the current literature to summarize what is known about patient selection and outcomes and highlights the questions that remain.

Recent findings
Congenital heart disease (CHD) with Fontan-associated liver disease (FALD) has surpassed noncongenital heart disease as the most common indication for CHLT. In patients with failing Fontan physiology, accurate assessment of recoverability of liver injury remains challenging and requires multifaceted evaluation to determine who would benefit from isolated versus dual organ transplantation. Patient survival has improved over time without significant differences between those with and without a diagnosis of CHD. En bloc surgical technique and best use of intraoperative mechanical circulatory support are topics of interest as the field continues to evolve.

Summary
A more refined understanding of appropriate patient selection and indication-specific outcomes will develop as we gain more experience with this complex operation and perform prospective, randomized studies.
Creating a Safe Space for Simulation
Authors: Preiksaitis Carl M. , Lee Moon O. , Schertzer Kimberly 
Published: December 2022

Summary Statement
Use of the term “confederate” is often used in research literature to describe an individual allied with the research team. Confederate is used in simulation research to describe participants allied with the simulation facilitator. Confederate can also refer to the Confederate States of America and has connotations of racial injustice and slavery. Use of this term in simulation may adversely affect psychological safety of learners. Use of the term within the literature is a potential driver of use during simulation sessions. We completed a rapid review of the health care simulation literature to determine the frequency of the term confederate. From 2000 to 2021, 2635 uses of confederate were identified in 765 articles. There seems to be an increased trend in use of this word. We argue that alternative terms exist and should be used to maximize psychological safety of learners.
Multivariate Analysis for the Influence of Ejection Fraction Value on Propofol Anesthesia Induction Requirement and its Pharmacodynamic Properties in Cardiopulmonary Bypass Surgery (Observational Study based on the Clinical Outcomes)
Authors: Permeisari Dias 
Published: December 2022

BackgroundThe majority of propofol utilization as an induction anesthetic in cardiac surgery, particularly in cardiopulmonary bypass surgery led to several risks to the patient. The most common risk is dropped mean arterial pressure, even with the high risk of cardiac arrest.ObjectiveDetermining the influences of ejection fraction value on the amount of propofol requirement as an induction agent based on the patient’s primary outcome (BIS spectral index) and the secondary outcomes (mean arterial pressure and heart rate)DesignProspective study, analytical observational with multivariate linear regression analysis, and multicenter studySetting2 hospitals, including 1 teaching hospital and 1 private hospitalPatientsall patients who underwent cardiopulmonary bypass surgery and are eligible for the inclusion criteriaMeasurementsDoses of Propofol as an anesthesia induction, mean arterial pressure (MAP) prior to surgery, heart rate (HR) prior to surgery, BIS Spectral Index prior to surgery, MAP after induction, HR after induction, and BIS Spectral Index after inductionResultsThese data were analyzed using MATLAB R2022a software to obtain R2(determining the effect size or influences) and p-value for each condition of ejection fraction value and the clinical responses. The data of this observational study is divided into six groups : 1. the effect size of ejection fraction value < 50% on BIS index obtained R20.9231 and p-value 0.88, 2. the effect size of ejection fraction value ≥ 50% on BIS index obtained R20.7794 and p-value 0.01, 3. the effect size of ejection fraction value < 50% on mean arterial pressure obtained R20.00024 and p-value 0.97, 4. The effect size of ejection fraction value ≥ 50% on mean arterial pressure obtained R20.0786 and p-value 0.005, 5. The effect size of ejection fraction value < 50% on heart rate obtained R20.3992 and p-value 0.06, 6. The effect size of ejection fraction value ≥ 50% on heart rate obtained R20.1757 and p-value 7.0776e-04.ConclusionsPropofol extremely impacts BIS index value compared to the patient’s mean arterial pressure or heart rate at the induction doses of propofol in general anesthesia for patients with a reduced ejection fraction
A Transformer-Based Model Trained on Large Scale Claims Data for Prediction of Severe COVID-19 Disease Progression
Authors: Lentzen Manuel , Linden Thomas , Veeranki Sai , Madan Sumit , Kramer Diether , Leodolter Werner , Fröhlich Holger 
Published: December 2022

AbstractIn situations like the COVID-19 pandemic, healthcare systems are under enormous pressure as they can rapidly collapse under the burden of the crisis. Machine learning (ML) based risk models could lift the burden by identifying patients with high risk of severe disease progression. Electronic Health Records (EHRs) provide crucial sources of information to develop these models because they rely on routinely collected healthcare data. However, EHR data is challenging for training ML models because it contains irregularly timestamped diagnosis, prescription, and procedure codes. For such data, transformer-based models are promising. We extended the previously published Med-BERT model by including age, sex, medications, quantitative clinical measures, and state information. After pre-training on approximately 988 million EHRs from 3.5 million patients, we developed models to predict Acute Respiratory Manifestations (ARM) risk using the medical history of 80,211 COVID-19 patients. Compared to XGBoost and Random Forests, our transformer-based models more accurately forecast the risk of developing ARM after COVID-19 infection. We used Integrated Gradients and Bayesian networks to understand the link between the essential features of our model. Finally, we evaluated adapting our model to Austrian in-patient data. Our study highlights the promise of predictive transformer-based models for precision medicine.
Continuous Positive Airway Pressure (CPAP) in Covid 19 Acute Respiratory Distress Syndrome (ARDS): A Systematic Review
Authors: Hoole Anbesan 
Published: December 2022

AbstractIntroductionAcute Respiratory Distress Syndrome (ARDS) is a feared consequence of Covid 19 Pneumonia. Traditional guidance was for ARDS to be treated with Intubation and Mechanical Ventilation (IMV), when failing simple oxygen. However globally numbers of patients with Covid 19 ARDS (CARDS) quickly overwhelmed IMV capacity, with Continuous Positive Airway Pressure (CPAP) has been used as a bridge or alternative to IMV. However, the evidence base remains limited in quality despite widespread adoption in guidelines.MethodsPubmed (15.6.2022), Embase (30.7.2022) and Google Scholar (4.8.2022) were searched to identify studies with the primary outcome of IMV free survival in patients with CARDS receiving CPAP, ideally with simple oxygen as a comparator. Secondary outcomes were overall survival with CPAP, length of stay and adverse events. All studies were assessed by the relevant Critical Appraisal Skills Programme Tool (CASP).Results13 studies were identified, out of which only 1 was a Randomised Control Trial (RCT) with simple oxygen as a comparator. There were 11 Cohort studies and one Systematic review.DiscussionThere is much heterogeneity in CPAP success rates (50 – 70%), which may be linked to variation in candidate selection, resource setting, application protocols and combined use with other respiratory support modalities (Non Invasive Ventilation – NIV, and High Flow Nasal Oxygen – HFNO). Adverse events and economic data such as length of stay are under reported.ConclusionCPAP is an effective respiratory support in CARDS particularly in resource poor settings. However further research is needed to refine optimum candidate selection, application protocols and any added benefit from combination with NIV or HFNO.No funding was received for this study. This review was not registered.
Tools for categorization of diagnostic codes in hospital data: Operationalizing CCSR into a patient data repository
Authors: Malecki Sarah , Loffler Anne , Tamming Daniel , Fralick Michael , Sohail Shahmir , Shi Jiamin , Roberts Surain , Colacci Michael , Razak Fahad , Verma Amol 
Published: December 2022

AbstractBackgroundThe Clinical Classification Software refined version (CCSR) is a tool to aggregateInternational Classification of Diseases, 10th Revision, Clinical Modification/Procedure Coding System(ICD-10-CM/PCS) diagnosis codes into clinically meaningful categories. ICD-10-CM/PCS codes are primarily used in the United States and the tool has not been optimized for use with other country-specific ICD-10 coding systems.MethodWe developed an automated procedure for mapping Canadian ICD-10 codes (ICD-10-CA) to CCSR categories using discharge diagnosis data from adult medical hospitalizations at 7 hospitals between Apr 1 2010 and Dec 31 2020, and manually validated the results.ResultsThere were 383,972 Canadian hospital admissions with 5,186 distinct ICD-10 discharge diagnosis codes. Only 46.6% of ICD-10-CA codes could be mapped directly to CCSR categories. Our algorithm improved mapping of hospital codes to CCSR categories to 98.2%. Validation of the algorithm demonstrated a high degree of accuracy with strong interrater agreement (observed proportionate agreement of 0.98). The algorithm was critical for mapping the majority of diagnosis codes associated with heart failure (96.6%), neurocognitive disorders (96.0%), skin and subcutaneous tissue infections (97.2%), and epilepsy (92.5%).ConclusionOur algorithm for operationalizing CCSR into a patient data repository (https://github.com/GEMINI-Medicine/gemini-ccsr) has been validated for use with Canadian ICD-10 codes and may be useful to clinicians and researchers from diverse geographic locations.
Time-varying and tissue-dependent effects of adiposity on leptin levels: a Mendelian randomization study
Authors: Richardson Tom G , Leyden Genevieve M , Davey Smith George 
Published: December 2022

AbstractBackgroundFindings from Mendelian randomization (MR) studies are conventionally interpreted as lifelong effects, which typically do not provide insight into the molecular mechanisms underlying the effect of an exposure on an outcome. In this study, we apply two recently developed MR approaches (known as ‘lifecourse’ and ‘tissue-partitioned’ MR) to investigate lifestage specific effects and tissues of action in the relationship between adiposity and circulating leptin levels.MethodGenetic instruments for childhood and adult adiposity were used to estimate lifestage specific effects on leptin levels measured during early life (mean age:10 years) in the Avon Longitudinal Study of Parents and Children (ALSPAC) and in adulthood (mean age:55 years) using summary-level data from the deCODE Health study. This was followed by partitioning body mass index (BMI) instruments into those whose effects are putatively mediated by gene expression in either subcutaneous adipose or brain tissues, followed by using MR to simultaneously estimate their separate effects on childhood and adult leptin levels.ResultsThere was strong evidence that childhood adiposity has a direct effect on leptin levels at age 10 years in the lifecourse (Beta=1.10, 95% CI=0.90 to 1.30, P=6×10−28), whereas evidence of an indirect effect was found on adulthood leptin along the causal pathway involving adulthood body size (Beta=0.74, 95% CI=0.62 to 0.86, P=1×10−33). Tissue-partitioned MR analyses provided evidence to suggest that BMI exerts its effect on leptin levels during both childhood and adulthood via brain-tissue mediated pathways (Beta=0.79, 95% CI=0.22 to 1.36, P=6×10−3& Beta=0.51, 95% CI=0.32 to 0.69, P=1×10−7respectively).ConclusionsOur findings demonstrate the use of lifecourse MR to disentangle direct and indirect effects of early life exposures on time-varying complex outcomes. Furthermore, by integrating tissue-specific data, we highlight the aetiological importance of appetite regulation in the effect of adiposity on leptin levels, as well as raising implications for the gene-environment equivalence assumption in MR.FundingThis work was supported by the Integrative Epidemiology Unit which receives funding from the UK Medical Research Council and the University of Bristol (MC_UU_00011/1).
Temporal landscape of mitochondrial proteostasis governed by the UPRmt
Authors: Uoselis Louise , Lindblom Runa , Skulsuppaisarn Marvin , Khuu Grace , Nguyen Thanh N. , Rudler Danielle L. , Filipovska Aleksandra , Schittenhelm Ralf B. , Lazarou Michael 
Published: December 2022

ABSTRACTBreakdown of mitochondrial proteostasis activates quality control pathways including the mitochondrial unfolded protein response (UPRmt) and PINK1/Parkin mitophagy. However, beyond the upregulation of chaperones and proteases, we have a limited understanding of how the UPRmtremodels and restores damaged mito-proteomes. Here, we have developed a functional proteomics framework, termed MitoPQ (MitochondrialProteostasisQuantification), to dissect the UPRmt’s role in maintaining proteostasis during stress. We discover essential roles for the UPRmtin both protecting and repairing proteostasis, with oxidative phosphorylation metabolism being a central target of the UPRmt. Transcriptome analyses together with MitoPQ reveal that UPRmttranscription factors drive independent signaling arms that act in concert to maintain proteostasis. Unidirectional interplay between the UPRmtand PINK1/Parkin mitophagy was found to promote oxidative phosphorylation recovery when the UPRmtfailed. Collectively, this study defines the network of proteostasis mediated by the UPRmtand highlights the value of functional proteomics in decoding stressed proteomes.
Robust and High-Throughput Analytical Flow Proteomics Analysis of Cynomolgus Monkey and Human Matrices with Zeno SWATH Data Independent Acquisition
Authors: Sun Weiwen , Lin Yuan , Huang Yue , Chan Josolyn , Terrillon Sonia , Rosenbaum Anton I. , Contrepois Kévin 
Published: December 2022

ABSTRACTModern mass spectrometers routinely allow deep proteome coverage in a single experiment. These methods are typically operated at nano and micro flow regimes, but they often lack throughput and chromatographic robustness, which is critical for large-scale studies. In this context, we have developed, optimized and benchmarked LC-MS methods combining the robustness and throughput of analytical flow chromatography with the added sensitivity provided by the Zeno trap across a wide range of cynomolgus monkey and human matrices of interest for toxicological studies and clinical biomarker discovery. SWATH data independent acquisition (DIA) experiments with Zeno trap activated (Zeno SWATH DIA) provided a clear advantage over conventional SWATH DIA in all sample types tested with improved sensitivity, quantitative robustness and signal linearity as well as increased protein coverage by up to 9-fold. Using a 10-min gradient chromatography, up to 3,300 proteins were identified in tissues at 2 µg peptide load. Importantly, the performance gains with Zeno SWATH translated into better biological pathway representation and improved the ability to identify dysregulated proteins and pathways associated with two metabolic diseases in human plasma. Finally, we demonstrate that this method is highly stable over time with the acquisition of reliable data over the injection of 1,000+ samples (14.2 days of uninterrupted acquisition) without the need for human intervention or normalization. Altogether, Zeno SWATH DIA methodology allows fast, sensitive and robust proteomic workflows using analytical flow and is amenable to large-scale studies. This work provides detailed method performance assessment on a variety of relevant biological matrices and serves as a valuable resource for the proteomics community.
Analysis of RNA polyadenylation in healthy and osteoarthritic human articular cartilage
Authors: Winstanley-Zarach Phaedra , Rot Gregor , Kuba Shweta , Smagul Aibek , Peffers Mandy J , Tew Simon R 
Published: December 2022

ABSTRACTAn important transcript structural element is its 3’ polyadenylated (polyA) tail, which defines the 3’ boundary of the transcript’s genetic information and is necessary for transcript stability. The position of the polyA tail can vary, with multiple alternatively polyadenylated (APA) transcripts existing for a single gene. This can lead to different length transcripts which can vary in their 3’ regulatory domains and even by inclusion or exclusion of protein-coding introns. The distribution of polyA tail location on articular chondrocyte transcripts has not been examined before and this study aimed to be the first to define polyadenylation events in human chondrocytes using age-matched healthy and osteoarthritic knee articular cartilage samples. Total RNA was isolated from frozen tissue samples and analysed using the QuantSeqReverse 3’ RNA Sequencing approach, where each read runs 3’ to 5’ from within the polyA tail into the transcript and will contains a distinct polyA site. Initial analysis of differential expression of overall transcript abundance identified by the reads showed significant disruption to transcript levels when healthy samples were compared to osteoarthritic ones. As we expected, differentially regulated genes were enriched with functionalities that were strongly associated with joint pathology. As part of this analysis, we also identified a substantial number of differentially expressed long non-coding RNAs that had not been linked to osteoarthritis before. Subsequent examination of polyA site data allowed us to deifne the extent of site usage across all the samples. This included identification of chondrocyte genes that exhibited the greatest amount polyA site variation. When comparing healthy and osteoarthritic samples, we found that differential use of polyadenylation sites was modest. However, of the small number of genes affected, there was clear potential for the change in polyadenylation site usage elicited by pathology to have functional relevance. We examined two genes, OSMR and KMT2A, in more detail, defining how APA affects transcript turnover and then, in the case of OSMR, identifying that APA is sensitive to inflammatory cytokine stimulation. Overall, we have characterised the polyadenylation landscape of human knee articular chondrocytes but can conclude that osteoarthritis does not elicit a widespread change in their polyadenylation site usage. This finding differentiates knee osteoarthritis from pathologies such as cancer where APA is more commonly observed.
Vector-valued dopamine improves learning of continuous outputs in the striatum
Authors: Wärnberg Emil , Kumar Arvind 
Published: December 2022

AbstractIt is well established that midbrain dopaminergic neurons support reinforcement learning (RL) in the basal ganglia by transmitting a reward prediction error (RPE) to the striatum. In particular, different computational models and experiments have shown that a striatumwide RPE signal can support RL over a small discrete set of actions (e.g. no/no-go, choose left/right). However, there is accumulating evidence that the basal ganglia functions not as a selector between predefined actions, but rather as a dynamical system with graded, continuous outputs. To reconcile this view with RL, there is a need to explain how dopamine could support learning of dynamic outputs, rather than discrete action values.Inspired by the recent observations that besides RPE, the firing rates of midbrain dopaminergic neurons correlate with motor and cognitive variables, we propose a model in which dopamine signal in the striatum carries a vector-valued error feedback signal (a loss gradient) instead of a homogeneous scalar error (a loss). Using a recurrent network model of the basal ganglia, we show that such a vector-valued feedback signal results in an increased capacity to learn a multidimensional series of real-valued outputs. The corticostriatal plasticity rule we employed is based on Random Feedback Learning Online learning and is a fully local, “three-factor” product of the presynaptic firing rate, a post-synaptic factor and the unique dopamine concentration perceived by each striatal neuron. Crucially, we demonstrate that under this plasticity rule, the improvement in learning does not require precise nigrostriatal synapses, but is compatible with random placement of varicosities and diffuse volume transmission of dopamine.