bluuebunny/crossref_metadata_2025_split huggingface dataset:
Alcohol Use Disorder Is Associated with Higher Risks of Adverse Brain Outcomes
Authors: Zhang Pengyue , Edenberg Howard , Nurnberger John , Lai Dongbing , Cheng Feixiong , Liu Yunlong 
Published: May 2022

AbstractAlcohol use disorder (AUD) is on the ascendancy in the US older adult population, while the association between AUD and adverse brain outcomes remains inconclusive. The objective of this work is to investigate the associations between AUD with the onset of Alzheimer’s disease and Parkinson’s disease. In a retrospective cohort design using US insurance claim data (2007-2020), 129,182 patients with AUD were matched with 129,182 controls by age, sex, race, and clinical characteristics. After adjusting for covariates, AUD was associated with a higher risk of Alzheimer’s disease (female adjusted HR=1.78, 95% CI: 1.68-1.90, P<0.001; male adjusted HR=1.80, 95% CI: 1.71-1.91, P<0.001) and a higher risk of Parkinson’s disease (female adjusted HR=1.49, 95% CI: 1.32-1.68 P<0.001; male adjusted HR=1.42, 95% CI: 1.32-1.52, P<0.001) in the overall sample. In separate analyses of Black, White, and Hispanic patients, those with AUD had higher risk of Alzheimer’s disease (adjusted HRs≥1.58; Ps≤0.001). A significantly elevated risk for Parkinson’s disease was found only in the White subpopulation (female adjusted HR=1.55, 95% CI: 1.36-1.77, P<0.001; male adjusted HR=1.45, 95% CI: 1.33-1.57, P<0.001). Alcohol use disorder is associated with Alzheimer’s disease. Alcohol use disorder is associated with Parkinson’s disease in White persons. Cognitive screening and neurological examination among older adults with severe problematic alcohol use hold the promise for early detection of Alzheimer’s disease and Parkinson’s disease.
Conceptualization of Health Literacy from a Nursing Perspective
Authors: Wilandika Angga , Pandin Moses Glorino Rumambo 
Published: May 2022

ABSTRACTHealth as an inseparable part of human beings needs to be maintained to achieve a complete human health degree. The role of health literacy in attaining optimum health is significant. When associated with nursing, health literacy must be interpreted as a part of the role and function of nursing. However, to understand health literacy, it is necessary to study it from the aspect of scientific formation itself and a nursing perspective. This review proposes an alternative conceptualization of health literacy from a nursing perspective. This review used an integrative search through four databases: ScienceDirect, ProQuest, SAGE Journal, and Google Scholar. Search using various combinations of keywords with the help of Boolean operators, including: health literacy, nursing perspective, nursing, and conceptualization combined as MESH terms. The inclusion criteria are peer-reviewed articles in English that discuss health literacy and nursing perspective. Articles published within the last six years (2017-2022). Research such as literature reviews, dissertations, editorials, commentaries, and other expert opinions are excluded. Ten articles were considered in this literature review. We describe the conceptualization of health literacy from the nurse’s point of view, the predictors that influence it, the dimensions surrounding health literacy, the implication of health literacy, and how nurses will participate in supporting this health literacy. In the end, this conceptualization will be used as an illustration material to integrate the concept of health literacy into various problems that become nursing tasks.
A Genomic Risk Score Identifies Individuals at High Risk for Intracerebral Hemorrhage
Authors: Myserlis Evangelos Pavlos , Georgakis Marios K. , Demel Stacie L. , Sekar Padmini , Chung Jaeyoon , Malik Rainer , Hyacinth Hyacinth I. , Comeau Mary E. , Falcone Guido , Langefeld Carl D. , Rosand Jonathan , Woo Daniel , Anderson Christopher D. 
Published: May 2022

ABSTRACTBackgroundIntracerebral hemorrhage (ICH), the most fatal form of stroke, has an estimated heritability of 29%. Applying a meta-scoring approach, we developed a genomic risk score for ICH and determined its predictive power in comparison to standard clinical risk factors.MethodsUsing a meta-analytic approach, we combined genome-wide association data from individuals of European ancestry for ICH and ICH-related traits in a meta-genomic risk score (metaGRS) consisting of 2.6 million variants. We tested associations with ICH and the predictive performance of the metaGRS in addition to clinical risk factors in a held-out validation dataset (842 cases and 796 controls). Furthermore, we tested associations with risk of incident ICH in the population-based UK Biobank cohort (486,784 individuals, 1,526 events, median follow-up 11.3 years).ResultsOne SD increment in the metaGRS was significantly associated with 45% higher odds for ICH (OR 1.45; 95%CI: 1.30-1.63) in age- and sex-adjusted models and 31% higher odds for ICH (OR: 1.31, 95%CI: 1.16-1.48) in models further adjusted for clinical risk factors. The metaGRS identified individuals with almost 5-fold higher odds for ICH in the top score percentile (OR: 4.83, 95%CI: 1.56-21.2). Predictive models for ICH incorporating the metaGRS in addition to clinical predictors showed superior performance compared with clinical risk factors alone (c-index: 0.695 vs. 0.686). The metaGRS showed similar associations for both lobar and non-lobar ICH, which were independent of the known APOE risk locus for lobar ICH. In the UK Biobank, the metaGRS was associated with higher risk of incident ICH (HR: 1.15, 95%CI: 1.09-1.21). The associations were significant within both a relatively high-risk population of users of antithrombotic medications, as well as among a relatively low-risk population with a good control of vascular risk factors and no use of anticoagulants.ConclusionsWe developed and validated a genomic risk score that predicts lifetime risk of ICH beyond established clinical risk factors among individuals of European ancestry. Whether implementation of the score in risk prognostication models for high-risk populations, such as patients under antithrombotic treatment, could improve clinical decision making should be explored in future studies.
Reporting Rates for VAERS Death Reports Following COVID-19 Vaccination, December 14, 2020-November 17, 2021
Authors: Day Brendan , Menschik David , Thompson Deborah , Jankosky Christopher , Su John , Moro Pedro , Zinderman Craig , Welsh Kerry , Nair Narayan 
Published: May 2022

AbstractBackgroundDespite widely available safety information for the COVID-19 vaccines, vaccine hesitancy remains a challenge. In some cases, vaccine hesitancy may be related to concerns about the number of reports of death to the Vaccine Adverse Event Reporting System (VAERS).ObjectiveTo provide information and context about reports of death to VAERS following COVID-19 vaccination.DesignDescriptive study; reporting rates for VAERS death reports.SettingUnited States; December 14, 2020, to November 17, 2021.ParticipantsCOVID-19 vaccine recipients.MeasurementsReporting rates for death events per million persons vaccinated; adverse event counts; data mining signals of disproportionate reporting.Results9,201 death events were reported for COVID-19 vaccine recipients aged five years and older (or age unknown). Reporting rates for death events increased with increasing age, and males generally had higher reporting rates than females. For death events within seven days and 42 days of vaccination, respectively, observed reporting rates were lower than the expected all-cause death rates. Reporting rates for Ad26.COV2.S vaccine were generally higher than for mRNA COVID-19 vaccines, but still lower than the expected all-cause death rates. Reported adverse events were non-specific or reflected the known leading causes of death.LimitationsVAERS data are subject to several limitations such as reporting bias (underreporting and stimulated reporting), missing or inaccurate information, and lack of a control group. Reported diagnoses, including deaths, are not causally verified diagnoses.ConclusionReporting rates for death events were lower than the expected all-cause mortality rates. Trends in reporting rates reflected known trends in background mortality rates. These findings do not suggest an association between vaccination and overall increased mortality.Funding SourceNo external sources of funding were used.
Temporal Characterization of Longitudinal Sequelae Including Acute Pain, Physiologic Status, and Toxicity Kinetics in Head and Neck Cancer Patients Receiving Radiotherapy: A Prospective Electronic Health Record Embedded Registry Study
Authors: Salama Vivian , Youssef Sara , Xu Tianlin , Chen Jaime , Rigert Jillian , Wahid Kareem , Reyes-Gibby Cielito C. , Lee Anna , Hutcheson Katherine A. , Gunn Brandon , Rosenthal David I. , Mohammed Abdallah S. R. , van Dijk Lisanne V , Lin Ruitao , Fuller Clifton D. , Moreno Amy C. 
Published: May 2022

AbstractBackgroundPain is a common, debilitating symptom experienced by patients with oral cavity and oropharyngeal cancer (OC/OPC) treated with radiotherapy (RT). Managing acute pain (AP) over 6 - 7 weeks of RT remains a significant challenge, warranting further investigation. Using a modern prospective registry, the objective of this study was to characterize longitudinal AP profiles and temporal changes in vital signs (VS), radiation toxicities, and analgesic prescribing patterns during RT.MethodsA total of 351 patients with OC (n=120) and OPC (n=228) treated with curative RT from 2013-2021 were included. Baseline cohort characteristics, weekly patient-reported pain descriptors, physician-graded toxicities (CTCAE v5), and analgesic orders during RT were extracted. Temporal changes in AP scores and VS were analyzed using linear mixed effect models. AP trajectories were reduced to single metric area under the curve calculations (AUCpain). Correlations were assessed using Spearman correlation coefficients.ResultsMedian age was 60 years, and 70% and 42% received chemotherapy and surgery, respectively. A significant increase in pain, mucositis, dermatitis, and overall treatment toxicity severity were observed by the end of RT. AUCpain was significantly different based on gender, primary tumor site, surgery, drug use history and pre-RT pain. There was a temporal mean weight loss of 7.1% bodyweight (95%CI, 10-8.2; P<0.001), a mean arterial pressure (MAP) decline of 6.8 mmHg (95%CI, −8.8 to −4.7; P<0.001), and increased pulse rate of 11 beats/min (95%CI, 7.6-13.8; P<0.001). AP and pulse rate were positively associated over time (P<0.001) while weight and MAP were negatively associated over time (P<0.001). A temporal increase in analgesics use, mainly opioids, was detected.ConclusionThis study characterizes longitudinal treatment-related toxicity kinetics using a prospective OC/OPC registry and demonstrates an ongoing need for optimized, timely pain control. Pain AUC metrics preserve temporal information and may be useful for developing algorithmic pain prediction and management models.
Deep learning identified genetic variants associated with COVID-19 related mortality
Authors: Li Zihuan , Dai Wei , Wang Shiying , Yao Yisha , Zhang Heping 
Published: May 2022

AbstractAnalysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data. We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (OR=1.594, p=5.47×10−9) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050 and rs12540488. We also discover a super variant (OR=1.353, p=2.87×10−8) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G and rs180899355.
Retinal transcriptome and cellular landscape in relation to the progression of diabetic retinopathy
Authors: Wang Jiang-Hui , Wong Raymond C.B. , Liu Guei-Sheung 
Published: May 2022

AbstractImportancePrevious studies identify putative genes associated with diabetic retinopathy only focusing on specific clinical stage, thus resulting genes are not necessarily reflective of disease progression.ObjectiveTo identify genes associated with the severity level of diabetic retinopathy using likelihood-ration test (LRT) and ordinal logistic regression (OLR) model, as well as to profile immune and retinal cell landscape in progressive diabetic retinopathy using a machine learning deconvolution approach.Design, Setting, and ParticipantsThis study used published transcriptomic dataset (GSE160306) from macular regions of donors with different degrees of diabetic retinopathy (10 healthy controls, 10 cases of diabetes, 9 cases of nonproliferative diabetic retinopathy and 10 cases of proliferative diabetic retinopathy or combined with diabetic macular edema). Transcriptomic dataset was released on April 19, 2021; data were analyzed on 28th March 2022.Main Outcomes and MeasuresIdentification of severity-associated genes with LRT and OLR model and proportional changes of immune and retinal cells in progressive diabetic retinopathy.ResultsBy controlling for gender and age using LRT and OLR, 50 genes were identified to be significantly increased in expression with the severity of diabetic retinopathy. Functional enrichment analyses suggested these severity-associated genes are related to inflammation and immune responses. CCND1 and FCGR2B are further identified as key regulators to interact with many other severity-associated genes and are crucial to inflammation. Deconvolution analyses demonstrated that the proportions of memory B cells, M2 macrophages and Müller glia were significantly increased with the progression of diabetic retinopathy.Conclusions and RelevanceThese findings demonstrate the deep analyses of transcriptomic data can advance our understanding of progressive ocular diseases, such as DR, by applying LRT and OLR model as well as bulk gene expression deconvolution.Key PointsQuestionDo genes change in expression or immune cells and retinal cells change in proportions in the human retina with the severity of diabetic retinopathy?FindingsIn this in-depth retinal transcriptomic analysis of 39 participants, consisting of 10 heathy controls, 29 cases of diabetic retinopathy at different clinical stages, severity-associated genes were identified, and the estimated proportions of immune cell and retinal cells were profiled, respectively.MeaningThese findings demonstrate that a group of genes are significantly increased in expression, and the proportions of memory B cells, M2 macrophages and Müller glia were significantly increased with the severity of diabetic retinopathy.
Validation of a transcriptome-based assay for classifying cancers of unknown primary origin
Authors: Michuda Jackson , Breschi Alessandra , Kapilivsky Joshuah , Manghnani Kabir , McCarter Calvin , Hockenberry Adam J , Mineo Brittany , Igartua Catherine , Dudley Joel T , Stumpe Martin C , Beaubier Nike , Shirazi Maryam , Jones Ryan , Morency Elizabeth , Blackwell Kim , Guinney Justin , Beauchamp Kyle A , Taxter Timothy 
Published: May 2022

AbstractCancers assume a variety of distinct histologies and may originate from a myriad of sites including solid organs, hematopoietic cells, and connective tissue. Clinical decision making based on consensus guidelines such as NCCN is often predicated on a specific histologic and anatomic diagnosis, supported by clinical features and pathologist interpretation of morphology and immunohistochemical (IHC) staining patterns. However, in patients with nonspecific morphologic and IHC findings—in addition to ambiguous clinical presentations such as recurrence versus new primary—a definitive diagnosis may not be possible, resulting in the patient being categorized as having a cancer of unknown primary (CUP). Therapeutic options and clinical outcomes are poor for CUP patients, with a median survival of 8-11 months. Here we describe and validate the Tempus Tumor Origin (Tempus TO) assay, an RNA-seq-based machine learning classifier capable of discriminating between 68 clinically relevant cancer subtypes. We show that the Tempus TO model is 91% accurate when assessed on retrospectively and prospectively held out cohorts of containing 9,210 samples with known diagnoses. When evaluated on a cohort of CUPs, the model recapitulated established associations between genomic alterations and cancer subtype. Combining diagnostic prediction tests (e.g., Tempus TO) with sequencing-based variant reporting (e.g., Tempus xT) may expand therapeutic options for patients with cancers of unknown primary or uncertain histology.
COVID-19 vaccine effectiveness during a prison outbreak when the Omicron was the dominant circulating variant— Zambia, December 2021
Authors: Simwanza John , Hines Jonas Z. , Sinyange Danny , Sinyange Nyambe , Mulenga Chilufya , Hanyinza Sarah , Sakubita Patrick , Langa Nelia , Nowa Haggai , Gardner Priscilla , Saasa Ngonda , Chipeta Gabriel , Simpungwe James , Malambo Warren , Hamainza Busiku , Kapata Nathan , Kapina Muzala , Musonda Kunda , Liwewe Mazyanga , Mwale Consity , Fwoloshi Sombo , Mulenga Lloyd B. , Agolory Simon , Mukonka Victor , Chilengi Roma 
Published: May 2022

AbstractDuring a COVID-19 outbreak in a prison in Zambia from 14th to 19th December 2021, a case control study was done to measure vaccine effectiveness (VE) against infection and symptomatic infection, when the Omicron variant was the dominant circulating variant. Among 382 participants, 74.1% were fully vaccinated and the median time since full vaccination was 54 days. There were no hospitalizations or deaths. COVID-19 VE against any SARS-CoV-2 infection was 64.8% and VE against symptomatic SARS-CoV-2 infection was 72.9%. COVID-19 vaccination helped protect incarcerated persons against SARS-CoV-2 infection during an outbreak while Omicron was the dominant variant in Zambia.
PixelPrint: Three-dimensional printing of realistic patient-specific lung phantoms for validation of computed tomography post-processing and inference algorithms
Authors: Shapira Nadav , Donovan Kevin , Mei Kai , Geagan Michael , Roshkovan Leonid , Gang Grace J. , Abed Mohammed , Linna Nathaniel , Cranston Coulter , O’Leary Cathal , Dhanaliwala Ali , Kontos Despina , Litt Harold I. , Stayman J. Webster , Shinohara Russell T. , Noël Peter B. 
Published: May 2022

ABSTRACTBackgroundRadiomics and other modern clinical decision-support algorithms are emerging as the next frontier for diagnostic and prognostic medical imaging. However, heterogeneities in image characteristics due to variations in imaging systems and protocols hamper the advancement of reproducible feature extraction pipelines. There is a growing need for realistic patient-based phantoms that accurately mimic human anatomy and disease manifestations to provide consistent ground-truth targets when comparing different feature extraction or image cohort normalization techniques.Materials and MethodsPixelPrint was developed for 3D-printing lifelike lung phantoms for computed tomography (CT) by directly translating clinical images into printer instructions that control the density on a voxel-by-voxel basis. CT datasets of three COVID-19 pneumonia patients served as input for 3D-printing lung phantoms. Five radiologists rated patient and phantom images for imaging characteristics and diagnostic confidence in a blinded reader study. Linear mixed models were utilized to evaluate effect sizes of evaluating phantom as opposed to patient images. Finally, PixelPrint’s reproducibility was evaluated by producing four phantoms from the same clinical images.ResultsEstimated mean differences between patient and phantom images were small (0.03-0.29, using a 1-5 scale). Effect size assessment with respect to rating variabilities revealed that the effect of having a phantom in the image is within one-third of the inter- and intra-reader variabilities. PixelPrint’s production reproducibility tests showed high correspondence among four phantoms produced using the same patient images, with higher similarity scores between high-dose scans of the different phantoms than those measured between clinical-dose scans of a single phantom.ConclusionsWe demonstrated PixelPrint’s ability to produce lifelike 3D-printed CT lung phantoms reliably. These can provide ground-truth targets for validating the generalizability of inference-based decision-support algorithms between different health centers and imaging protocols, as well as for optimizing scan protocols with realistic patient-based phantoms.
How to improve access to TB care for the nomads? Review of barriers and enablers for Sahel nomadic populations
Authors: Traore Hugues Asken , Chaverondier Roxane , Combary Adjima , Diallo Adama , Ouedraogo Salifou , Kane El hadj , Koita Mohamedou , Mourtala Assao , Adamou Sina , Sarr Marie , Toure Nafissatou , Ba Tacko Aly , Abdelhadi Oumar , Abdelrahim Abderramane , Konaté Bakary , Ballayira Yaya , Camara Fatima , Roij Madelon , Merle Corinne Simone 
Published: May 2022

AbstractTuberculosis (TB) control in nomadic populations represents a major public health problem in sub–Saharan Africa.Barriers and enablers of TB care for nomads were identified through a literature review and survey conducted among the National TB Programs (NTPs) of six Sahelian countries: Burkina Faso, Chad, Niger, Mali, Mauritania, and Senegal. A conceptual framework was developed. Data retrieved from twenty-eight peer-reviewed papers or collected through the survey were regrouped in 5 categories: health system related factors, socioeconomic factors, cultural, political and environmental factors.The large distance between nomadic camps and health care facilities and the absence of TB-specific programmatic interventions for nomads were the main barriers identified. The establishment of a multi-ministerial national committee in charge of nomadic populations, the mapping of nomadic transhumance roads, the identification of gaps in health service provision and community engagement for defining fit for purpose solutions are key elements to improve TB control in nomadic population.Some countries in the region successfully implemented interventions to overcome the barriers to TB care. These interventions should be more widely shared to inform other countries for the development of appropriate strategies for which community engagement is essential.