bluuebunny/crossref_metadata_2025_split huggingface dataset:
Care Coordination Processes in Transitional Care for Patients With Heart Failure
Authors: Wei Sijia , McConnell Eleanor S. , Granger Bradi , Corazzini Kirsten N. 
Published: January 2022

Background
Transitional care components are well studied, but their coordination has not been systematically reviewed. Viewing transitional care through a social network framework can focus attention on processes leading to information and relationship transferal to ensure continuity and may lead to new strategies to improve transitional care.

Objective
The aim of this study was to examine care coordination processes in transitional care interventions for older adults with heart failure by integrating a social network analysis approach.

Methods
PubMed, Scopus, and CINAHL were searched to capture transitional care interventions (a) involving care coordination for older adults with heart failure transitioning from hospital to home and (b) published in the United States from 2010 to 2020. Study characteristics, intervention characteristics, and care coordination processes (ie, participants, interactions among participants, and their characteristics) were extracted.

Results
In 17 studies reviewed, the number of individual roles involved in care coordination varied from 3 to 32. Nurses and pharmacists were the most common interventionists. Six studies involved informal caregivers. In-person interactions were most common among individuals within settings; interactions across settings were typically assisted by technology. Despite high variability among the individuals and interactions involved, a common triadic process was found through which interventionists, patients, and primary care providers or outpatient cardiologists aimed to facilitate the transfer of information and care relationships from hospital to community.

Conclusions
High variability in transitional care is likely because the processes are highly relational. Using a network analysis may help uncover the relational structures and processes underlying transitional care to inform intervention development.
Promoting Professional Quality of Life and Resiliency in Sexual Assault Nurse Examiners
Authors: Bouchard Lindsay , Williams Deborah , Kiser Lisa , Freese Erica , Taren Douglas 
Published: January 2022

ABSTRACT

Background
Sexual assault nurse examiners (SANEs) have received specialized education and clinical training in providing forensic care for sexual assault and abuse victims. SANEs provide compassionate and competent care that promotes emotional recovery for their patients; however, caring for this population puts SANEs at risk for secondary traumatic stress, professional burnout, and compassion fatigue. The research regarding SANEs indicates that there may be multiple personal and organizational factors that affect their development of negative outcomes related to professional quality of life.

Purpose
This study explored challenges SANEs experience in their work and what resources are utilized to promote their resiliency and professional quality of life.

Methods
SANEs were recruited to complete an anonymous online survey through the International Association of Forensic Nurses community; 69 SANEs completed the survey. Eight of the SANEs also participated in follow-up focus groups.

Results
The participants reported many gratifying aspects of their work. They also described challenges related to personal, professional, organizational, and community factors. Many of the reported negative effects align with secondary traumatic stress and professional burnout. The SANEs identified multiple ways to support their resiliency in the context of this difficult work.

Implications
The nature of this work puts SANEs at risk for developing adverse symptoms related to professional quality of life. SANEs need better support and resources to cope with the demands of their work. Findings of this study will be used to design SANE Well, a support application to promote SANE wellness and resiliency.
Airway Amyloidosis
Authors: Baqir Misbah , Schwegman Alex R. , Maldonado Fabien , Johnson Tucker F. , Ryu Jay H. 
Published: January 2022

Background:
Amyloidosis can involve any compartment in the thorax. We aimed to explore the clinical and radiologic presentation, treatment, and clinical course of airway amyloidosis.

Methods:
A computer-assisted search was performed to identify patients who had biopsy-proven airway amyloidosis and were evaluated at Mayo Clinic in Rochester, MN, from January 1, 1997 through December 31, 2019. Demographic, clinical, and radiologic features along with clinical outcomes were analyzed.

Results:
We identified 43 patients who had airway amyloidosis. Median age was 60 years (range: 33 to 91 y), and 58% were female. Shortness of breath (63% of patients) and cough (44%) were the most common presenting symptoms. Most patients (82%) had localized amyloidosis with light chain being the most common amyloid type; 63% had tracheobronchial amyloidosis, and 23% had tracheal and upper airway involvement. On computed tomography of the chest, the most common findings were airway wall thickening with nodularity (60% of patients), airway calcification (53%), and airway occlusion without collapse (47%). On bronchoscopy (33 patients), the extent of amyloid involvement was most commonly submucosal (n=15) or nodular (n=8). External beam radiotherapy was the most common treatment modality. Among the 30 patients who had follow-up at our institution, the prognosis appeared to depend on the extent of the disease and whether patients had localized or systemic amyloidosis.

Conclusion:
Computed tomography of the chest, bronchoscopy, and biopsy are needed to establish the diagnosis of airway amyloidosis, and systemic amyloidosis should be ruled out. Treatment of amyloidosis requires a multidisciplinary approach.
Evaluation of a Natural Language Processing Approach to Identify Social Determinants of Health in Electronic Health Records in a Diverse Community Cohort
Authors: Rouillard Christopher J. , Nasser Mahmoud A. , Hu Haihong , Roblin Douglas W. 
Published: January 2022

Background:
Health care systems in the United States are increasingly interested in measuring and addressing social determinants of health (SDoH). Advances in electronic health record systems and Natural Language Processing (NLP) create a unique opportunity to systematically document patient SDoH from digitized free-text provider notes.

Methods:
Patient SDoH status [recorded by Your Current Life Situation (YCLS) Survey] and associated provider notes recorded between March 2017 and June 2020 were extracted (32,261 beneficiaries; 50,722 YCLS surveys; 485,425 provider notes).
NLP patterns were generated using a machine learning test statistic (Term Frequency-Inverse Document Frequency). Patterns were developed and assessed in a training, training validation, and final validation dataset (64%, 16%, and 20% of total data, respectively).
NLP models analyzed SDoH-specific categories (housing, medical care, and transportation needs) and a combined SDoH metric. Model performance was assessed using sensitivity, specificity, and Cohen κ statistic, assuming the YCLS Survey to be the gold standard.

Results:
Within the training validation dataset, NLP models showed strong sensitivity and specificity, with moderate agreement with the YCLS Survey (Housing: sensitivity=0.67, specificity=0.89, κ=0.51; Medical care: sensitivity=0.55, specificity=0.73, κ=0.20; Transportation: sensitivity=0.79, specificity=0.87, κ=0.58). Model performance in the training and training validation datasets were comparable.
In the final validation dataset, a combined SDoH prediction metric showed sensitivity=0.77, specificity=0.69, κ=0.45.

Conclusion:
This NLP algorithm demonstrated moderate performance in identification of unmet patient social needs. This novel approach may enable improved targeting of interventions, allocation of limited resources and monitoring a health care system’s addressing its patients’ SDoH needs.
An electrocardiography score predicts heart failure hospitalization or death beyond that of cardiovascular magnetic resonance imaging
Authors: Maanja Maren , Schlegel Todd T , Fröjdh Fredrika , Niklasson Louise , Wieslander Björn , Bacharova Ljuba , Schelbert Erik B , Ugander Martin 
Published: January 2022

AbstractBackgroundThe electrocardiogram (ECG) and cardiovascular magnetic resonance imaging (CMR) both provide powerful prognostic information. The aim was to determine the relative prognostic value of ECG and CMR, respectively.MethodsConsecutive patients (n=783) undergoing CMR and resting 12-lead ECG with a QRS duration <120 ms were included. CMR measures included feature tracking global longitudinal strain (GLS), extracellular volume fraction (ECV), left ventricular mass and volumes, and ischemic and non-ischemic scar size. Prognosis scores for one-year event-free survival were derived using continuous ECG or CMR measures, and multinomial logistic regression, and compared with regards to the combined outcome of survival free from hospitalization for heart failure or death.ResultsPatients (median [interquartile range] age 55 [43–64] years, 44% female) had 155 events during 5.7 [4.4–6.6] years. The ECG prognosis score included 1) the frontal plane QRS-T angle, and 2) the heart rate corrected QT duration (QTc) (log-rank 55, p<0.001). The CMR prognosis score included 1) GLS, and 2) ECV (log-rank 85, p<0.001). The combination of positive scores for both ECG and CMR yielded the highest prognostic value (log-rank 105, p<0.001). Multivariable analysis showed an association with outcomes for both the ECG prognosis score (log-rank 8.4, hazard ratio [95% confidence interval] 1.29 [1.09–1.54], p=0.004) and the CMR prognosis score (log-rank 47, hazard ratio 1.90 [1.58–2.28], p<0.001).ConclusionsAn ECG prognosis score predicted outcomes independently of, and beyond CMR. Combining the results of ECG and CMR using both prognosis scores improved the overall prognostic performance.
Genome-wide association study of nociceptive musculoskeletal pain treatment response in UK Biobank
Authors: Li Song , Poelmans Geert , van Boekel Regina L.M. , Coenen Marieke J.H. 
Published: January 2022

AbstractDrug treatment for nociceptive musculoskeletal pain (NMP) follows a three-step analgesic ladder proposed by the World Health Organization (WHO), starting from non-steroidal anti-inflammatory drugs (NSAIDs), followed by weak or strong opioids until the pain is under control. However, effective pain treatment is challenged by inter-individual differences, and unsatisfied pain treatment response (PTR) rates ranging from 34 to 79% in those suffering from NMP. To investigate the underlying genetic component of PTR, we performed a genome-wide association study (GWAS) in ∼ 23,000 participants with NMP from the UK Biobank. In our primary analysis, we compared NSAID vs. opioid users as a reflection of (non)response to NSAIDs, adjusting for age, sex, BMI, population substructure, and study-specific covariates. One genome-wide significant hit was identified in an intergenic region on chromosome 4, rs549224715 (P = 3.88×10−8), and seven signals pass the suggestively significant threshold (P < 1×10−6). All identified loci were in non-coding regions, but most variants showed potential regulatory functions. SNPs in LD (r2> 0.6) with the lead SNPs passing the nominal significant threshold (P < 0.05) were mapped to 28 target genes in FUMA. Eight of these 28 genes are involved in processes linked to neuropathic pain and musculoskeletal development. Pathway and network analyses with Ingenuity resulted in the identification of immunity-related processes and a (putative) central role of EGFR. Genetic correlation analysis including 596 traits resulted in the identification of 67 nominally significant (P < 0.05) genetic correlations, and these traits were significantly enriched for chronic pain and socioeconomic status traits (P = 3.35 × 10−12). Additionally, we conducted a subtype GWAS for inflammatory NMP and a secondary GWAS for participants with NMP disease history, but no significant hits or overlap with the primary analysis were observed. Overall, we identified one genome-wide significant association in this first GWAS focusing on pain treatment using the analgesic ladder as phenotype. However, we realize that this study lacked power and should be viewed as a first step to elucidate the genetic background of NMP treatment.
Towards an optimal monoclonal antibody with higher binding affinity to the receptor-binding domain of SARS-CoV-2 spike proteins from different variants
Authors: Neamtu Andrei , Mocci Francesca , Laaksonen Aatto , Barroso da Silva Fernando L. 
Published: January 2022

ABSTRACTA highly efficient and robust multiple scales in silico protocol, consisting of atomistic constant charge Molecular Dynamics (MD), constant-charge coarse-grain (CG) MD and constant-pH CG Monte Carlo (MC), has been used to study the binding affinities, the free energy of complexation of selected antigen-binding fragments of the monoclonal antibody (mAbs) CR3022 (originally derived from SARS-CoV-1 patients almost two decades ago) and 11 SARS-CoV-2 variants including the wild type. CR3022 binds strongly to the receptor-binding domain (RBD) of SARS-CoV-2 spike protein, but chooses a different site rather than the receptor-binding motif (RBM) of RBD, allowing its combined use with other mAbs against new emerging virus variants. Totally 235,000 mAbs structures were generated using the RosettaAntibodyDesign software, resulting in top 10 scored CR3022-RBD complexes with critical mutations and compared to the native one, all having the potential to block virus-host cell interaction. Of these 10 finalists, two candidates were further identified in the CG simulations to be clearly best against all virus variants, and surprisingly, all 10 candidates and the native CR3022 did exhibit a higher affinity for the Omicron variant with its highest number of mutations (15) of them all considered in this study. The multiscale protocol gives us a powerful rational tool to design efficient mAbs. The electrostatic interactions play a crucial role and appear to be controlling the affinity and complex building. Clearly, mAbs carrying a lower net charge show a higher affinity. Structural determinants could be identified in atomistic simulations and their roles are discussed in detail to further hint at a strategy towards designing the best RBD binder. Although the SARS-CoV-2 was specifically targeted in this work, our approach is generally suitable for many diseases and viral and bacterial pathogens, leukemia, cancer, multiple sclerosis, rheumatoid, arthritis, lupus, and more.
Human land-use impacts viral diversity and abundance in a New Zealand river
Authors: French Rebecca , Charon Justine , Lay Callum Le , Muller Chris , Holmes Edward C. 
Published: January 2022

AbstractAlthough water-borne viruses have important implications for the health of humans and other animals, little is known about the impact of human land-use on viral diversity and evolution in water systems such as rivers. We used metagenomic next-generation sequencing to compare the diversity and abundance of viruses at sampling sites along a single river in New Zealand that differed in human land use impact, ranging from pristine to urban. From this we identified 504 putative virus species, of which 97% were novel. Many of the novel viruses were highly divergent, and likely included a new subfamily within theParvoviridae. We identified at least 63 virus species that may infect vertebrates – most likely fish and water birds – from theAstroviridae, Birnaviridae, ParvoviridaeandPicornaviridae. No putative human viruses were detected. Importantly, we observed differences in the composition of viral communities at sites impacted by human land-use (farming and urban) compared to native forest sites (pristine). At the viral species level, the urban sites had higher diversity (327 virus species) than the farming (n=150) and pristine sites (n=119), and more viruses were shared between the urban and farming sites (n=76) than between the pristine and farming or urban sites (n=24). The two farming sites had a lower viral abundance across all host types, while the pristine sites had a higher abundance of viruses associated with animals, plants and fungi. We also identified viruses linked to agriculture and human impact at the river sampling sites in farming and urban areas that were not present at the native forest sites. Overall, our study shows that human land-use can impact viral communities in rivers, such that further work is needed to reduce the impact of intensive farming and urbanization on water systems.
Fully Vaccinated and Boosted Patients Requiring Hospitalization for COVID-19: an Observational Cohort Analysis
Authors: Mielke Nicholas , Johnson Steven , Bahl Amit 
Published: January 2022

ABSTRACTObjectiveReal-world data on the effectiveness of boosters against COVID-19, especially as new variants continue to emerge, is limited. It is our objective to assess demographic, clinical, and outcome variables of patients requiring hospitalization for severe SARS-CoV-2 infection comparing fully vaccinated and boosted (FV&B) and unvaccinated (UV) patients.MethodsThis multicenter observational cohort analysis compared demographic, clinical, and outcome variables in FV&B and UV adults hospitalized for COVID-19. A sub-analysis of FV&B patients requiring intensive care (ICU) care versus non-ICU care was performed to describe and analyze common symptom presentations, initial vital signs, initial laboratory workup, and pertinent medication use in these two groups.ResultsBetween August 12th, 2021 and December 6th, 2021, 4,571 patient encounters had a primary diagnosis of COVID-19 and required inpatient treatment at an acute-care hospital system in Southeastern Michigan. Of the 4,571 encounters requiring hospitalization, 65(1.4%) were FV&B and 2,935(64%) were UV. FV&B individuals were older (74 [67, 81] vs 58 [45, 70]; p <0.001) with a higher proportion of immunocompromised individuals (32.3% vs 10.4%; p<0.001). Despite a significantly higher baseline risk of in-hospital mortality in the FV&B group compared to the UV (Elixhauser 16 vs 8 (p <0.001)), there was a trend toward lower in-hospital mortality (7.7% vs 12.1%; p=0.38) among FV&B patients. Other severe outcomes followed this same trend, with 7.7% of FV&B vs 11.1% UV patients needing mechanical ventilation and 4.6% vs 10.6% of patients needing vasopressors in each group, respectively (p=0.5 and 0.17).ConclusionsFully vaccinated and boosted individuals requiring hospital-level care for breakthrough COVID-19 tended to have less severe outcomes despite appearing to be higher risk at baseline when compared to unvaccinated individuals during the same time period. Specifically, there was a trend that FV&B group had lower rates of mechanical ventilation, use of vasopressors, and in-hospital mortality. As COVID-19 continues to spread, larger expansive trials are needed to further identify risk factors for severe outcomes among the FV&B population.
A multiwell-plate Caenorhabditis elegans assay for assessing the therapeutic potential of Bacteriophages against Clinical Pathogens
Authors: Manohar Prasanth , Loh Belinda , Elangovan Namasivayam , Loganathan Archana , Nachimuthu Ramesh , Leptihn Sebastian 
Published: January 2022

AbstractIn order to establish phage therapy as a standard clinical treatment for bacterial infections, testing of every phage to ensure the suitability and safety of the biological compound is required. While some issues have been addressed over recent years, standard and easy-to-use animal models to test phages are still rare. Testing of phages in highly suitable mammalian models such as mice is subjected to strict ethical regulations, while insect larvae such as the Galleria mellonella model suffers from batch-to-batch variations and requires manual operator skills to inject bacteria, resulting in unreliable experimental outcomes. A much simpler model is the nematode Caenorhabditis elegans which feeds on bacteria, a fast growing and easy to handle organism which can be used in high-throughput screening. In this study, two clinical bacterial strains of Escherichia coli, one Klebsiella pneumoniae and one Enterobacter cloacae strain were tested on the model system together with lytic bacteriophages that we isolated previously. We developed a liquid-based assay, in which the efficiency of phage treatment was evaluated using a scoring system based on microscopy and counting of the nematodes, allowing increasing statistical significance compared to other assays such as larvae or mice. Our work demonstrates the potential to use Caenorhabditis elegans to test the virulence of strains of Klebsiella pneumoniae, Enterobacter cloacae and EHEC/ EPEC as well as the efficacy of bacteriophages to treat or prevent infections, allowing a more reliable evaluation for the clinical therapeutic potential of lytic phages.ImportanceValidating the efficacy and safety of phages prior to clinical application is crucial to see phage therapy in practice. Current animal models include mice and insect larvae, which pose ethical or technical challenges. This study examined the use of the nematode model organism, C. elegans as a quick, reliable and simple alternative for testing phages. The data shows that all the four tested bacteriophages can eliminate bacterial pathogens and protect the nematode from infections. Survival rates of the nematodes increased from <20% in the infection group to >90% in the phage treatment group. Even the nematodes with poly-microbial infections recovered during phage cocktail treatment. The use of C. elegans as a simple whole-animal infection model is a rapid and robust way to study the efficacy of phages before testing them on more complex model animals such as mice.
Feature distillation and accumulated selection for automated fraudulent publisher classification from user click data of online advertising
Authors: Sisodia Deepti , Sisodia Dilip Singh 
Published: January 2022

PurposeThe problem of choosing the utmost useful features from hundreds of features from time-series user click data arises in online advertising toward fraudulent publisher's classification. Selecting feature subsets is a key issue in such classification tasks. Practically, the use of filter approaches is common; however, they neglect the correlations amid features. Conversely, wrapper approaches could not be applied due to their complexities. Moreover, in particular, existing feature selection methods could not handle such data, which is one of the major causes of instability of feature selection.Design/methodology/approachTo overcome such issues, a majority voting-based hybrid feature selection method, namely feature distillation and accumulated selection (FDAS), is proposed to investigate the optimal subset of relevant features for analyzing the publisher's fraudulent conduct. FDAS works in two phases: (1) feature distillation, where significant features from standard filter and wrapper feature selection methods are obtained using majority voting; (2) accumulated selection, where we enumerated an accumulated evaluation of relevant feature subset to search for an optimal feature subset using effective machine learning (ML) models.FindingsEmpirical results prove enhanced classification performance with proposed features in average precision, recall, f1-score and AUC in publisher identification and classification.Originality/valueThe FDAS is evaluated on FDMA2012 user-click data and nine other benchmark datasets to gauge its generalizing characteristics, first, considering original features, second, with relevant feature subsets selected by feature selection (FS) methods, third, with optimal feature subset obtained by the proposed approach. ANOVA significance test is conducted to demonstrate significant differences between independent features.