bluuebunny/crossref_metadata_2025_split huggingface dataset:
My family sold a cow to pay for my Traditional doctor and now there’s no money to travel to the HIV clinic: barriers to antiretroviral adherence among rural-Indigenous peoples living with HIV in the Comarca Ngäbe-Buglé, Panamá
Authors: Gabster Amanda , Socha Eliana , Pascale Juan Miguel , Talavero Gonzalo Cabezas , Castrellón Alezander , Quiel Yaremis , Gantes César , Mayaud Philippe 
Published: December 2021

AbstractIntroductionThe Comarca Ngäbe-Buglé (CNB) is an administratively autonomous Indigenous region in Western Panama that is home to over 200,000 individuals of Ngäbe and Buglé ethnicities. The CNB is the most impoverished region in Panama and is relatively isolated from outside influences, with limited roads, electricity, and internet connection. Around 1.5% of all rapid HIV tests are positive, compared to a national prevalence of 0.9%; in CNB, diagnosis tends to be late where 56.3% of individuals had an initial CD4 count of <350 cells/mm3. In this region, antiretroviral treatment (ART) dropout is five times higher than the national average; there is high early mortality due to opportunistic infections. This study aims to describe some of the barriers associated with ART adherence and retention in HIV care among PLHIV the CNB. A better understanding of factors that obstruct adherence could lead to more effective HIV care and prevention in CNB.MethodsWe conducted 21 semi-structured interviews with PLHIV who reside across all three regions of the CNB and who have attended an ART clinic at least once. The interviews took place between November 2018 and December 2019.DiscussionPsychological health and social support and discrimination acted as both individual-level facilitators and barriers to adherence and retention. Notably, structural barriers included difficult access to ART care due to travel costs, ART shortages, and uncooperative Western/Traditional medical systems. Recommended interventions used in other Low- and Middle-Income settings include increasing peer and family-level support and community knowledge and understanding of HIV infection. Additionally, we suggest structural interventions, including decreasing cost and distance of travel to the ART clinic through decentralization of services and multi-month dispensing, decreasing food scarcity, and increasing collaboration between Western and Traditional providers.
Liver Volumetry from Magnetic Resonance Images with Convolutional Neural Networks
Authors: Saunders Sara L. , Clark Justin M. , Rudser Kyle , Chauhan Anil , Ryder Justin R. , Bolan Patrick J. 
Published: December 2021

AbstractMeasurements of liver volume from MR images can be valuable for both clinical and research applications. Automated methods using convolutional neural networks have been used successfully for this using a variety of different MR image types as input. In this work, we sought to determine which types of magnetic resonance images give the best performance when used to train convolutional neural networks for liver segmentation and volumetry.Abdominal MRI scans were performed at 3 Tesla on 42 adolescents with obesity. Scans included Dixon imaging (giving water, fat, and T2* images) and low-resolution T2-weighted anatomical scans. Multiple convolutional neural network models using a 3D U-Net architecture were trained with different input images. Whole-liver manual segmentations were used for reference. Segmentation performance was measured using the Dice similarity coefficient (DSC) and 95% Hausdorff distance. Liver volume accuracy was evaluated using bias, precision, and normalized root mean square error (NRMSE).The models trained using both water and fat images performed best, giving DSC = 0.94 and NRMSE = 4.2%. Models trained without the water image as input all performed worse, including in participants with elevated liver fat. Models using the T2-weighted anatomical images underperformed the Dixon-based models, but provided acceptable performance (DSC ≥ 0.92, NMRSE ≤ 6.6%) for use in longitudinal pediatric obesity interventions. The model using Dixon water and fat images as input gave the best performance, with results comparable to inter-reader variability and state-of-the-art methods.
Age-dependent normalisation functions for T-lymphocytes in healthy individuals
Authors: Schröter Juliane , Borghans José A. M. , Bitter W. Marieke , van Dongen Jacques J. M. , de Boer Rob J. 
Published: December 2021

AbstractLymphocyte numbers naturally change through age. Normalisation functions to account for this are sparse, and mostly disregard measurements from children in which these changes are most prominent. In this study, we analyse cross-sectional numbers of mainly T-lymphocytes (CD3+, CD3+CD4+ and CD3+CD8+) and their subpopulations (naive and memory) from 673 healthy Dutch individuals ranging from infancy to adulthood (0-62 years). We fitted the data by a delayed exponential function and received parameter estimates for each lymphocyte subset. Our modelling approach follows general laboratory measurement procedures in which absolute cell counts of T-lymphocyte subsets are calculated from observed percentages within a reference population that is truly counted (typically the total lymphocyte count). Consequently, we receive one set of parameter estimates per T-cell subset representing both the trajectories of their counts and percentages. We allow for an initial time delay of half a year before the total lymphocyte counts per µl of blood start to change exponentially, and we find that T-lymphocyte trajectories tend to increase during the first half a year of life. Thus, our study provides functions describing the general trajectories of T-lymphocyte counts and percentages of the Dutch population. These functions provide important references to study T-lymphocyte dynamics in disease, and allow one to quantify losses and gains in longitudinal data, such as the CD4+ T-cell decline in HIV-infected children, and/or the rate of T-cell recovery after the onset of treatment.
Multi-method investigation of factors influencing amyloid onset and impairment in three cohorts
Authors: Betthauser Tobey J. , Bilgel Murat , Koscik Rebecca L. , Jedynak Bruno M. , An Yang , Kellett Kristina A. , Moghekar Abhay , Jonaitis Erin M. , Stone Charles K. , Engelman Corinne D. , Asthana Sanjay , Christian Bradley T. , Wong Dean F. , Albert Marilyn , Resnick Susan M. , Johnson Sterling C. ,   the Alzheimer’s Disease Neuroimaging Initiative
Published: December 2021

AbstractAlzheimer’s disease biomarkers are becoming increasingly important for characterizing the longitudinal course of disease, predicting the timing of clinical and cognitive symptoms, and for recruitment and treatment monitoring in clinical trials. In this work, we develop and evaluate three methods for modeling the longitudinal course of amyloid accumulation in three cohorts using amyloid PET imaging. We then use these novel approaches to investigate factors that influence the timing of amyloid onset and the timing from amyloid onset to impairment onset in the Alzheimer’s disease continuum.Data were acquired from the Alzheimer’s Disease Neuroimaging Initiative (ADNI), the Baltimore Longitudinal Study of Aging (BLSA) and the Wisconsin Registry for Alzheimer’s Prevention (WRAP). Amyloid PET was used to assess global amyloid burden. Three methods were evaluated for modeling amyloid accumulation using 10-fold cross-validation and hold-out validation where applicable. Estimated amyloid onset age was compared across all three modeling methods and cohorts. Cox regression and accelerated failure time models were used to investigate whether sex, apolipoprotein E genotype and e4 carriage were associated with amyloid onset age in all cohorts. Cox regression was used to investigate whether apolipoprotein E (e4 carriage and e3e3, e3e4, e4e4 genotypes), sex or age of amyloid onset were associated with the time from amyloid onset to impairment onset (global Clinical Dementia Rating ≥1) in a subset of 595 ADNI participants that were not impaired prior to amyloid onset.Model prediction and estimated amyloid onset age were similar across all three amyloid modeling methods. Sex and apolipoprotein E-e4 carriage were not associated with PET-measured amyloid accumulation rates. Apolipoprotein E genotype and e4 carriage, but not sex, were associated with amyloid onset age such that e4 carriers became amyloid positive at an earlier age compared to non-carriers, and greater e4 dosage was associated with an earlier amyloid onset age. In the ADNI, e4 carriage, being female and a later amyloid onset age were all associated with a shorter time from amyloid onset to impairment onset. The risk of impairment onset due to age of amyloid onset was nonlinear and accelerated for amyloid onset age >65. These findings demonstrate the feasibility of modeling longitudinal amyloid accumulation to enable individualized estimates of amyloid onset age from amyloid PET imaging. These estimates provide a more direct way to investigate the role of amyloid and other factors that influence the timing of clinical impairment in Alzheimer’s disease.
Declines and pronounced state disparities in prescription opioid distribution in the United States
Authors: Madera Joshua D. , Ruffino Amanda E. , Feliz Adriana , McCall Kenneth L. , Davis Corey S. , Piper Brian J. 
Published: December 2021

AbstractBackgroundThe United States (US) opioid epidemic is a persistent and pervasive public health emergency that now claims the lives of over 100,000 Americans per year. There have been sustained efforts to reverse this crisis over the past decade, including a number of measures designed to decrease the use of prescription opioids for the treatment of pain. This study analyzed the changes in federal production quotas for prescription opioids and the distribution of prescription opioids for pain, and identified state-level differences between 2010 and 2019.Methods and FindingsData on opioid production quotas and distribution of ten prescription opioids (codeine, fentanyl, hydrocodone, hydromorphone, meperidine, methadone, morphine, oxycodone, oxymorphone, and tapentadol) for 2010 to 2019 were obtained from the Drug Enforcement Administration. Total opioid production quotas increased substantially from 2010 to 2013 before decreasing 41.5% from 2013 (87.6 morphine mg equivalent metric tons) to 2019 (51.3). The peak year for distribution of all ten prescription opioids was between 2010 and 2013, except for codeine (2015). The largest quantities of opioid distribution were observed in Tennessee (520.70 morphine mg equivalent or MME per person) and Delaware (251.45) in 2011 and 2019. There was a 52.0% overall decrease in opioid distribution per capita from 2010 to 2019, with the largest decrease in Florida (−61.6%) and smallest in Texas (−18.6%). The highest to lowest state ratio of total opioid distribution, corrected for population, decreased from 5.25 in 2011 to 2.78 in 2019. The mean 95th/5th ratio was relatively consistent in 2011 (4.78 +0.70) compared to 2019 (5.64+0.98). Southern states had the highest per capita distribution for eight of the ten opioids in 2019.ConclusionsThis study found a sustained decline in distribution of ten prescription opioids during the last half-decade. Distribution was non-homogeneous at the state level. Analysis of state-level differences revealed a three-fold difference in the 95th:5th percentile ratio between states which was unchanged over the past decade. Production quotas did not correspond with the distribution, particularly in the 2010-2016 period. Future research focused on identifying factors contributing to the observed regional variability in opioid distribution could prove valuable to understanding, and potentially remediating, the pronounced disparities in prescription opioid-related harm in the US.
Prevalence, Comorbidity, and Sociodemographic Correlates of Psychiatric Disorders in the All Of Us Biobank
Authors: Barr Peter B. , Bigdeli Tim B. , Meyers Jacquelyn M. 
Published: December 2021

ABSTRACTImportanceAll of Us is a landmark initiative for population-scale research into the etiology of psychiatric disorders and disparities across various sociodemographic categories.ObjectiveTo estimate the prevalence, comorbidity, and demographic covariates of psychiatric and substance use disorders in the All of Us biobank.Design, Setting, and ParticipantsWe estimated prevalence, overlap, and demographic correlates for psychiatric disorders derived from electronic health records in the All of Us biobank (release 5; N = 331,380)ExposuresSocial and demographic covariates.Main Outcome and MeasuresPsychiatric disorders derived from ICD10CM codes and grouped into phecodes across six broad domains: mood disorders, anxiety disorders, substance use disorders, stress-related disorders, schizophrenia, and personality disorders.ResultsThe prevalence of various disorders ranges from approximately 15% to less than 1%, with mood and anxiety disorders being the most common, followed by substance use disorders, stress-related disorders, schizophrenia, and personality disorders. There is substantial overlap among disorders, with a large portion of those with a disorder (~57%) having two or more registered diagnoses and tetrachoric correlations ranging from 0.43 – 0.74. The prevalence of disorders across demographic categories demonstrates that non-Hispanic whites, those of low socioeconomic status, women and those assigned female at birth, and sexual minorities are at greatest risk for most disorders.Conclusions and RelevanceAlthough the rates of disorders in All of Us are lower than rates for disorders in the general population, there is considerable variation, comorbidity, and differences across social groups. Large-scale resources like All of Us will prove to be invaluable for understanding the causes and consequences of psychiatric conditions. As we move towards an era of precision medicine, we must work to ensure it is delivered in an equitable manner.
Disruptions in Care: Consequences of the COVID-19 Pandemic in a Children’s Hospital
Authors: Diskin Catherine , Orkin Julia , Dharmaraj Blossom , Agarwal Tanvi , Parmar Arpita , Naughton Kelly Mc , Cohen Eyal , Sunderji Alia , Faraoni David , Fecteau Annie , Fischer Jason , Maynes Jason , Mahant Sanjay , Friedman Jeremy N 
Published: December 2021

AbstractBackgroundPublic health restrictions are an essential strategy to prevent the spread of COVID-19; however, unintended consequences of these interventions may have led to significant delays, deferrals and disruptions in medical care. This study explores clinical cases where the care of children was perceived to have been negatively impacted as a result of public health measures and changes in healthcare delivery and access due to the COVID-19 pandemic.MethodsThis study used a qualitative multiple case study design with descriptive thematic analysis of clinician-reported consequences of the COVID-19 pandemic on care provided at a children’s hospital. A quantitative analysis of overall hospital activity data during the study period was performed.ResultsThe COVID-19 pandemic has resulted in significant change to hospital activity at our tertiary care hospital, including an initial reduction in Emergency Department attendance by 38% and an increase in ambulatory virtual care from 4% before COVID-19, to 67% in August, 2020. Two hundred and twelve clinicians reported a total of 116 unique cases. Themes including (1) timeliness of care, (2) disruption of patient-centered care, (3) new pressures in the provision of safe and efficient care and (4) inequity in the experience of the COVID-19 pandemic emerged, each impacting patients, their families and healthcare providers.ConclusionBeing aware of the breadth of the impact of the COVID-19 pandemic across all of the identified themes is important to enable the delivery of timely, safe, high-quality, family-centred pediatric care moving forward.What’s newCOVID-19 disrupted typical paediatric care delivery.This study demonstrates the breadth of its’ impact on the delivery of timely, safe, equitable and patient and family centered care, highlighting considerations for paediatric providers as we move forward.
Health inequities in SARS-CoV-2 infection, seroprevalence, and COVID-19 vaccination: Results from the East Bay COVID-19 study
Authors: Adams Cameron , Horton Mary , Solomon Olivia , Wong Marcus , Wu Sean L. , Fuller Sophia , Shao Xiaorong , Fedrigo Indro , Quach Hong L. , Quach Diana L. , Meas Michelle , Lopez Luis , Broughton Abigail , Barcellos Anna L. , Shim Joan , Seymens Yusef , Hernandez Samantha , Montoya Magelda , Johnson Darrell M. , Beckman Kenneth B. , Busch Michael P. , Coloma Josefina , Lewnard Joseph A. , Harris Eva , Barcellos Lisa F. 
Published: December 2021

AbstractComprehensive data on transmission mitigation behaviors and both SARS-CoV-2 infection and serostatus are needed from large, community-based cohorts to identify COVID-19 risk factors and the impact of public health measures. From July 2020-March 2021, approximately 5,500 adults from the East Bay Area, California were followed over three data collection rounds to investigate the association between geographic and demographic characteristics and transmission mitigation behavior with SARS-CoV-2 prevalence. We estimated the populated-adjusted prevalence of antibodies from SARS-CoV-2 infection and COVID-19 vaccination, and self-reported COVID-19 test positivity. Population-adjusted SARS-CoV-2 seroprevalence was low, increasing from 1.03% (95% CI: 0.50-1.96) in Round 1 (July-September 2020), to 1.37% (95% CI: 0.75-2.39) in Round 2 (October-December 2020), to 2.18% (95% CI: 1.48-3.17) in Round 3 (February-March 2021). Population-adjusted seroprevalence of COVID-19 vaccination was 21.64% (95% CI: 19.20-24.34) in Round 3, with Whites having 4.35% (95% CI: 0.35-8.32) higher COVID-19 vaccine seroprevalence than non-Whites. No evidence for an association between transmission mitigation behavior and seroprevalence was observed. Despite >99% of participants reporting wearing masks, non-Whites, lower-income, and lower-educated individuals had the highest SARS-CoV-2 seroprevalence and lowest vaccination seroprevalence. Results demonstrate that more effective policies are needed to address these disparities and inequities.
Seroprevalence of SARS-CoV-2 antibodies prior to the widespread introduction of vaccine programmes in the WHO European Region, January - December 2020: a systematic review
Authors: Vaughan A , Duffell EF , Friedl GS , Lemos DS , Funk T , Nardone A , Valenciano M , Subissi L , Bergeri I , Broberg E , Penttinen P , Pebody R , Keramarou M 
Published: December 2021

ABSTRACTBackgroundSeroprevalence surveys are essential to assess the age-specific prevalence of pre-existing cross-reactive antibodies in the population with the emergence of a novel pathogen; to measure population cumulative seroincidence of infection, and to contribute to estimating infection severity. With the emergence of SARS-CoV-2, ECDC and WHO Regional Office for Europe have supported Member States in undertaking standardized population-based SARS-CoV-2 seroprevalence surveys across the WHO European Region.ObjectivesThe objective of this study was to undertake a systematic literature review of SARS-CoV-2 population seroprevalence studies undertaken in the WHO European Region to measure pre-existing and cumulative seropositivity prior to the roll out of vaccination programmes.MethodsWe systematically searched MEDLINE, ELSEVIER and the pre-print servers medRxiv and bioRxiv within the “COVID-19 Global literature on coronavirus disease” database using a predefined search strategy. We included seroepidemiology studies published before the widespread implementation of COVID-19 vaccination programmes in January 2021 among the general population and blood donors, at national and regional levels. Study risk of bias was assessed using a quality scoring system based on sample size, sampling and testing methodologies. Articles were supplemented with unpublished WHO-supported Unity-aligned seroprevalence studies and other studies reported directly to WHO Regional Office for Europe and ECDC.ResultsIn total, 111 studies from 26 countries published or conducted between 01/01/2020 and 31/12/2020 across the WHO European Region were included. A significant heterogeneity in implementation was noted across the studies, with a paucity of studies from the east of the Region. Eighty-one (73%) studies were assessed to be of low to medium risk of bias. Overall, SARS-CoV-2 seropositivity prior to widespread community circulation was very low. National seroprevalence estimates after circulation started ranged from 0% to 51.3% (median 2.2% (IQR 0.7-5.2%); n=124), while sub-national estimates ranged from 0% to 52% (median 5.8% (IQR 2.3-12%); n=101), with the highest estimates in areas following widespread local transmission.ConclusionsThe review found evidence of low national SARS-CoV-2 seroprevalence (<10%) across the WHO European Region in 2020. The low levels of SARS-CoV-2 antibody in most populations prior to the start of vaccine programmes highlights the critical importance of vaccinating priority groups at risk of severe disease while maintaining reduced levels of transmission to minimize population morbidity and mortality.
The Impact of COVID-19 on NO2 and PM2.5 Levels and Their Associations with Human Mobility Patterns in Singapore
Authors: Li Yangyang , Zhu Yihan , Tan Jia Yu Karen , Teo Hoong Chen , Law Andrea , Qu Dezhan , Luo Wei 
Published: December 2021

AbstractThe decline in NO2 and PM2.5 pollutant levels were observed during COVID-19 around the world, especially during lockdowns. Previous studies explained such observed decline with the decrease in human mobility, whilst overlooking the meteorological changes (e.g., rainfall, wind speed) that could mediate air pollution level simultaneously. This pitfall could potentially lead to over-or under-estimation of the effect of COVID-19 on air pollution. Consequently, this study aims to re-evaluate the impact of COVID-19 on NO2 and PM2.5 pollutant level in Singapore, by incorporating the effect of meteorological parameters in predicting NO2 and PM2.5 baseline in 2020 using machine learning methods. The results found that NO2 and PM2.5 declined by a maximum of 38% and 36%, respectively, during lockdown period. As two proxies for change in human mobility, taxi availability and carpark availability were found to increase and decrease by a maximum of 12.6% and 9.8%, respectively, in 2020 from 2019 during lockdown. To investigate how human mobility influenced air pollutant level, two correlation analyses were conducted: one between PM2.5 and carpark availability changes at regional scale and the other between NO2 and taxi availability changes at a spatial resolution of 0.01°. The NO2 variation was found to be more associated with the change in human mobility, with the correlation coefficients vary spatially across Singapore. A cluster of stronger correlations were found in the South and East Coast of Singapore. Contrarily, PM2.5 and carpark availability had a weak correlation, which could be due to the limit of regional analyses. Drawing to the wider context, the high association between human mobility and NO2 in the South and East Coast area can provide insights into future NO2 reduction policy in Singapore.Graphical Abstract