bluuebunny/crossref_metadata_2025_split huggingface dataset:
Substance Use and Pre-Hospital Crash Injury Severity Among U.S. Older Adults: A Five-Year National Cross-sectional Study
Authors: Adeyemi Oluwaseun , Bukur Marko , Berry Cherisse , DiMaggio Charles , Grudzen Corita , Adenikinju Abidemi , Cuthel Allison , Minois Jean-Baptiste Bouillon , Akinsola Omotola , Moore Alison , Chodosh Joshua 
Published: June 2022

BackgroundAlcohol and drug use (substance use) is a risk factor for crash involvement.ObjectivesTo assess the association between substance use and crash injury severity among older adults and how the relationship differs by rurality/urbanicity.MethodsWe pooled 2017 – 2021 cross-sectional data from the United States National Emergency Medical Service (EMS) Information System. We measured injury severity (low acuity, emergent, critical, and fatal) predicted by substance use, defined as self-reported or officer-reported alcohol and/or drug use. We controlled for age, sex, race/ethnicity, road user type, anatomical injured region, location (scene) of the injury, rurality/urbanicity, time of the day, and EMS response time. We performed a partial proportional ordinal logistic regression and reported the odds of worse injury outcomes (emergent, critical, and fatal injuries) compared to low acuity injuries, and the predicted probabilities by rurality/urbanicity.ResultsOur sample consisted of 253,933 older adults (65 years and older) road users. Approximately 67%, 25%, 6%, and 1% sustained low acuity, emergent, critical, and fatal injuries, respectively. Substance use was reported in approximately 3% of the population, and this proportion did not significantly differ by rurality/urbanicity. After controlling for patient, crash, and injury characteristics, substance use was associated with 35% increased odds of worse injury severity. Compared to urban areas, the predicted probabilities of emergent, critical, and fatal injuries were higher in rural and suburban areas.ConclusionSubstance use is associated with worse older adult crash injury severity and the injury severity is higher in rural and suburban areas compared to urban areas.
Polygenic Health Index, General Health, Pleiotropy, Embryo Selection and Disease Risk
Authors: Widen Erik , Lello Louis , Raben Timothy G. , Tellier Laurent C. A. M. , Hsu Stephen D. H. 
Published: June 2022

AbstractWe construct a polygenic health index as a weighted sum of polygenic risk scores for 20 major disease conditions, including, e.g., coronary artery disease, type 1 and 2 diabetes, schizophrenia, etc. Individual weights are determined by population-level estimates of impact on life expectancy. We validate this index in odds ratios and selection experiments using unrelated individuals and siblings (pairs and trios) from the UK Biobank. Individuals with higher index scores have decreased disease risk across almost all 20 diseases (no significant risk increases), and longer calculated life expectancy. When estimated Disability Adjusted Life Years (DALYs) are used as the performance metric, the gain from selection among 10 individuals (highest index score vs average) is found to be roughly 4 DALYs. We find no statistical evidence for antagonistic trade-offs in risk reduction across these diseases. Correlations between genetic disease risks are found to be mostly positive and generally mild. These results have important implications for public health and also for fundamental issues such as pleiotropy and genetic architecture of human disease conditions.
Experiences of mental health and wellbeing support for NHS staff during the COVID-19 pandemic: a reflexive thematic analysis
Authors: Clarkson Corinne , Scott Hannah R. , Hegarty Siobhan , Souliou Emilia , Bhundia Rupa , Gnanapragasam Sam , Docherty Mary Jane , Raine Rosalind , Stevelink Sharon A. M. , Greenberg Neil , Hotopf Matthew , Wessely Simon , Madan Ira , Rafferty Anne Marie , Lamb Danielle 
Published: June 2022

AbstractStaff in the National Health Service (NHS) have been placed under considerable strain during the COVID-19 pandemic; whilst NHS Trusts provide a variety of health and wellbeing support services, there has been little research investigating staff perceptions of these services. Moreover, the research that does exist typically includes only clinical staff, despite a large proportion of patient-facing NHS workers being in non-clinical roles. We interviewed forty-eight clinical and non-clinical healthcare workers from eighteen NHS Trusts in England about their experiences of workplace health and wellbeing support during the pandemic. Reflexive thematic analysis identified that perceived stigma around help-seeking, and staffing shortages due to wider socio-political contexts such as austerity, were barriers to using support services. Visible, caring leadership at all levels (CEO to line managers), peer support, easily accessible services, and clear communication about support offers were enablers. Our evidence suggests Trusts should have active strategies to improve help-seeking. This could involve providing all staff with regular reminders about support options, in a variety of formats (e.g. email, posters, mentioned in meetings), and easily remembered single points of access, delivered by a mix of in-house and externally-provided services, to cater for those more and less concerned about stigma and confidentiality. In addition, managers at all levels should be trained and supported to feel confident to speak about mental health with staff, with formal peer support facilitated by building in time for this during working hours. As others have pointed out, this will require long-term strategic planning to address workforce shortages.
Detecting CTP Truncation Artifacts in Acute Stroke Imaging from the Arterial Input and the Vascular Output Functions
Authors: de la Rosa Ezequiel , Sima Diana M. , Kirschke Jan S. , Menze Bjoern , Robben David 
Published: June 2022

AbstractBackgroundCurrent guidelines for CT perfusion (CTP) in acute stroke suggest acquiring scans with a minimal duration of 60-70 s. But even then, CTP analysis can be affected by truncation artifacts. Conversely, shorter acquisitions are still widely used in clinical practice and are usually sufficient to reliably estimate lesion volumes. We aim to devise an automatic method that detects scans affected by truncation artifacts.MethodsShorter scan durations are simulated from the ISLES’18 dataset by consecutively removing the last CTP time-point until reaching a 10 s duration. For each truncated series, perfusion lesion volumes are quantified and used to label the series as unreliable if the lesion volumes considerably deviate from the original untruncated ones. Afterwards, nine features from the arterial input function (AIF) and the vascular output function (VOF) are derived and used to fit machine-learning models with the goal of detecting unreliably truncated scans. Methods are compared against a baseline classifier solely based on the scan duration, which is the current clinical standard. The ROC-AUC, precision-recall AUC and the F1-score are measured in a 5-fold cross-validation setting.ResultsMachine learning models obtained high performance, with a ROC-AUC of 0.964 and precision-recall AUC of 0.958 for the best performing classifier. The highest detection rate is obtained with support vector machines (F1-score = 0.913). The most important feature is the AIFcoverage, measured as the time difference between the scan duration and the AIF peak. In comparison, the baseline classifier yielded a lower performance of 0.940 ROC-AUC and 0.933 precision-recall AUC. At the 60-second cutoff, the baseline classifier obtained a low detection of unreliably truncated scans (F1-Score = 0.638).ConclusionsMachine learning models fed with discriminant AIF and VOF features accurately detected unreliable stroke lesion measurements due to insufficient acquisition duration. Unlike the 60s scan duration criterion, the devised models are robust to variable contrast injection and CTP acquisition protocols and could hence be used for quality assurance in CTP post-processing software.
Meta-Analysis of Genome-Wide Association Studies of Hoarding Symptoms in 27 537 Individuals
Authors: Strom Nora I. , Smit Dirk J.A. , Silzer Talisa , Iyegbe Conrad , Burton Christie L. , Pool René , Lemire Mathieu , Crowley James J. , Hottenga Jouke-Jan , Ivanov Volen Z. , Larsson Henrik , Lichtenstein Paul , Magnusson Patrik , Rück Christian , Schachar Russell , Wu Hei Man , Meier Sandra M. , Crosbie Jennifer , Arnold Paul D. , Mattheisen Manuel , Boomsma Dorret I. , Mataix-Cols David , Cath Danielle 
Published: June 2022

AbstractHoarding Disorder (HD) is a mental disorder characterized by persistent difficulties discarding or parting with possessions, often resulting in cluttered living spaces, distress, and impairment. Its etiology is largely unknown, but twin studies suggest that it is moderately heritable. In this study, we pooled phenotypic and genomic data from seven international cohorts (N = 27 537 individuals) and conducted a genome wide association study (GWAS) meta-analysis of parent- or self-reported hoarding symptoms (HS). We followed up the results with gene-based and gene-set analyses, as well as leave-one-out HS polygenic risk score (PRS) analyses. To examine a possible genetic association between hoarding symptoms and other phenotypes we conducted cross-trait PRS analyses. Though we did not report any genome-wide significant SNPs, we found a significant contribution of common genetic factors to HS, as indicated by substantial SNP-based twin-heritability estimates ranging between 26% and 48% and a SNP-heritability of 11% for one sub-cohort. Cross-trait PRS analyses showed that the genetic risk for schizophrenia and autism spectrum disorder were significantly associated with hoarding symptoms. We also found suggestive evidence for an association with educational attainment. There were no significant associations with other phenotypes previously linked to HD, such as obsessive-compulsive disorder, depression, anxiety, or attention-deficit hyperactivity disorder. To conclude, we found that HS are heritable, confirming and extending previous twin studies but we had limited power to detect any genome-wide significant loci. Much larger samples will be needed to further extend these findings and reach a “gene discovery zone”. To move the field forward, future research should not only include genetic analyses of quantitative hoarding traits in larger samples, but also in samples of individuals meeting strict diagnostic criteria for HD, and more ethnically diverse samples.
Trends in Clinical Validation and Usage of Food and Drug Administration (FDA)-Cleared Artificial Intelligence (AI) Algorithms for Medical Imaging
Authors: Khunte Mihir , Chae Allison , Wang Richard , Jain Rishubh , Sun Yujuan , Sollee John R. , Jiao Zhicheng , Bai Harrison X. 
Published: June 2022

AbstractObjectiveThe objective of this study is to examine the current landscape of FDA-approved AI medical imaging devices and identify trends in clinical validation strategy.Materials and MethodsWe conducted a retrospective study that analyzed data extracted from the American College of Radiology (ACR) Data Science Institute AI Central database as of November 2021 to identify trends in FDA clearance of AI products related to medical imaging. Product and clinical validation information of each device was gathered from their respective public 510(k) summary or de novo request submission, depending on their type of authorization.ResultsOverall, the database included a total of 151 AI algorithms that were cleared by the FDA between 2008 and November 2021. Out of the 151 FDA summaries reviewed, 97 (64.2%) reported the use of clinical data to validate their device. Of these 151 summaries, 81 (53.6%) reported the total number of patient cases used during validation, with the average number of cases being 799 (SD: 1363) and the range of cases spanning from 15 to 9122. A total of 51 (33.8%) AI devices characterized their clinical data as multicenter, 3 (2.0%) as single-center, and the remaining 97 (64.2%) did not specify. The ground truth used for clinical validation was specified in 78 (51.6%) FDA summaries.Discussion and ConclusionA wide breadth of AI algorithms have been developed for medical imaging. Most of the devices’ FDA summaries mention their use of clinical data and patient cases for device validation, emphasizing their utility in real clinical practice.
Antimicrobial Prescribing Practices at Dermatology Outpatient Departments in Tertiary Care Hospitals: A multi-centered, Cross Sectional Study
Authors: Sultana Nagina , Ferdoush Jannatul , Johora Fatema , Towfiq Hossain Sharif Mohammad , Hossain Arifa 
Published: June 2022

AbstractBackgroundThe purpose of this study is to evaluate antimicrobial prescribing behaviors in the dermatology outpatient department.MethodsThis multi-centered, cross-sectional study was conducted at dermatology outpatient department of three tertiary care hospitals in Chittagong division, Bangladesh during the period October, 2021 to April, 2022.ResultsDuring the study period, 463 prescriptions were obtained. Over half of the participants were female (57%) and between the ages of 21 to 40 years. The majority of patients were diagnosed with eczema (19%), acne (17%), and scabies (15%). Most commonly prescribed antimicrobials was Azithromycin (22%), followed by Permethrin (16%) and Erythromycin (7%). In most cases, antimicrobials were recommended for more than two weeks (60%). Nearly half of the antimicrobials (53 %) were recommended as combination of systemic and topical route.ConclusionCurrent study found that dermatologists frequently recommended broad-spectrum antimicrobials for extended periods of time, which may lead to antimicrobial resistance. There is a need for continuing medical education on the appropriate use of antimicrobials, which will result in the effective management of skin diseases.
Evaluating multiple next-generation sequencing derived tumor features to accurately predict DNA mismatch repair status
Authors: Walker Romy , Georgeson Peter , Mahmood Khalid , Joo Jihoon E. , Makalic Enes , Clendenning Mark , Como Julia , Preston Susan , Joseland Sharelle , Pope Bernard J. , Hutchinson Ryan , Kasem Kais , Walsh Michael D. , Macrae Finlay A. , Win Aung K. , Hopper John L. , Mouradov Dmitri , Gibbs Peter , Sieber Oliver M. , O’Sullivan Dylan E. , Brenner Darren R. , Gallinger Steven , Jenkins Mark A. , Rosty Christophe , Winship Ingrid M. , Buchanan Daniel D. 
Published: June 2022

AbstractIdentifying tumor DNA mismatch repair deficiency (dMMR) is important for precision medicine. We assessed tumor features, individually and in combination, in whole-exome sequenced (WES) colorectal cancers (CRCs) and in panel sequenced CRCs, endometrial cancers (ECs) and sebaceous skin tumors (SSTs) for their accuracy in detecting dMMR. CRCs (n=300) with WES, where MMR status was determined by immunohistochemistry, were assessed for microsatellite instability (MSMuTect, MANTIS, MSIseq, MSISensor), COSMIC tumor mutational signatures (TMS) and somatic mutation counts. A 10-fold cross-validation approach (100 repeats) evaluated the dMMR prediction accuracy for 1) individual features, 2) Lasso statistical model and 3) an additive feature combination approach. Panel sequenced tumors (29 CRCs, 22 ECs, 20 SSTs) were assessed for the top performing dMMR predicting features/models using these three approaches. For WES CRCs, 10 features provided >80% dMMR prediction accuracy, with MSMuTect, MSIseq, and MANTIS achieving ≥99% accuracy. The Lasso model achieved 98.3%. The additive feature approach with ≥3/6 of MSMuTect, MANTIS, MSIseq, MSISensor, INDEL count or TMS ID2+ID7 achieved 99.7% accuracy. For the panel sequenced tumors, the additive feature combination approach of ≥3/6 achieved accuracies of 100%, 95.5% and 100%, for CRCs, ECs, and SSTs, respectively. The microsatellite instability calling tools performed well in WES CRCs, however, an approach combining tumor features may improve dMMR prediction in both WES and panel sequenced data across tissue types.
Attitudes of the US general public towards Monkeypox
Authors: Malik Amyn A. , Winters Maike S. , Omer Saad B. 
Published: June 2022

AbstractWhile the Monkeypox outbreak is growing, little is known about the general public’s levels of knowledge, their trusted sources of information and attitudes towards a Monkeypox vaccine. In our representative survey of the US general public, we find that almost half the respondents (47%) feel that their knowledge level about Monkeypox is poor or very poor. The most trusted sources of information about the outbreak are healthcare professional and officials, but also known doctors and researchers with a large online following. Being vaccinated against COVID-19 was a strong predictor of willingness to receive a Monkeypox if recommended (adjusted Odds Ratio 32.1, 95% Confidence Interval 16.7-61.7). Our findings point to the urgent need for clear communication.
Digital reconstruction of infraslow activity in human intracranial ictal recordings using a deconvolution-based inverse filter
Authors: Lee Somin , Henry Julia , Tryba Andrew K. , Esengul Yasar , Warnke Peter , Wu Shasha , van Drongelen Wim 
Published: June 2022

ABSTRACTInfraslow activity (ISA) is a biomarker that has recently become of interest in the characterization of seizure recordings. Recent data from a small number of studies have suggested that the epileptogenic zone may be identified by the presence of ISA. Investigation of low frequency activity in clinical seizure recordings, however, has been hampered by technical limitations. EEG systems necessarily include a high-pass filter early in the measurement chain to remove large artifactual drifts that can saturate recording elements such as the amplifier. This filter unfortunately attenuates legitimately seizure-related low frequencies, making ISA difficult to study in clinical EEG recordings. In this study, we present a deconvolution-based digital inverse filter that allows recovery of attenuated low frequency activity in intracranial recordings of temporal lobe epilepsy patients. First, we show that the unit impulse response (UIR) of an EEG system can be characterized by differentiation of the system’s step response. As proof of method, we present several examples that show that the low frequency component of a high-pass filtered signal can be restored by deconvolution with the UIR. We then demonstrate that this method can be applied to biologically relevant signals including clinical EEG recordings obtained from seizure patients. Finally, we discuss how this method can be applied to study ISA to identify and assess the seizure onset zone.
Host microRNAs are differentially expressed in EBV+ Post-transplant Lymphoproliferative Disorder solid-organ transplant recipients
Authors: Sen Ayantika , Enriquez Jeanna , Rao Mahil , Glass Marla , Balachandran Yarl , Syed Sharjeel , Twist Clare J. , Weinberg Kenneth , Boyd Scott D. , Bernstein Daniel , Trickey Amber , Gratzinger Dita , Tan Brent , Lapasaran Mary Gay , Robien Mark A. , Brown Merideth , Armstrong Brian , Desai Dev , Mazariegos George , Chin Clifford , Fishbein Thomas , Venick Robert S. , Tekin Akin , Zimmermann Heiner , Trappe Ralf U. , Anagnostopoulos Ioannis , Esquivel Carlos.O. , Martinez Olivia M. , Krams Sheri M. 
Published: June 2022

AbstractPost-transplant lymphoproliferative disorder (PTLD) is a serious complication of solid organ transplantation (SOT). Predisposing factors include primary Epstein-Barr virus (EBV) infection, reactivation of EBV in recipient B cells, and decreased T cell immunity due to immunosuppression. Previously, we demonstrated that EBV infection markedly reshapes the microRNA (miR) landscape in EBV+ B cell lines leading to increased IL-10 production. To establish the miRNAome of PTLD tumors we analyzed formalin-fixed, paraffin-embedded shavings of tumor tissues obtained from EBV+ PTLD SOT recipients by microarray analysis and quantitative PCR. The miRNAome of EBV+ PTLD tumors were distinctly different from EBV-PTLD tumors with reduced expression of miRs-17, 19 and 106a, and 194 among EBV+ PTLD tumors. miRs-17, 19, 106a, 155, and 194 were quantitated in the plasma and extracellular vesicles (EVs) from EBV+ PTLD+ SOT recipients and matched transplant controls. The plasma and EV levels of miRs-17, 19, 106a and 194 trended lower in the EBV+ PTLD+ group compared to matched controls, with miR-17 (plasma), miR-19 (EVs) and 106a (plasma and EVs) being significantly reduced. Importantly, the cell free miRs were contained primarily within the EVs. Further studies on the diagnostic, mechanistic, and therapeutic potential of these miRs in PTLD are warranted.
Kinetics of neutralising antibodies against Omicron variant in Vietnamese healthcare workers after primary immunisation with ChAdOx1-S and booster with BNT162b2
Authors: Van Vinh Chau Nguyen , Nguyet Lam Anh , Dung Nguyen Thanh , Quang Vo Minh , Truong Nguyen Thanh , Toan Le Mau , Hung Le Manh , Huy Man Dinh Nguyen , Khoa Dao Bach , Phong Nguyen Thanh , Ngoc Nghiem My , Thao Huynh Phuong , Bich Ty Dinh Thi , Thanh Pham Ba , Han Ny Nguyen Thi , Thanh Le Kim , Thuy Cao Thu , Anh Nguyen To , Thu Hong Nguyen Thi , Truc Nhu Le Nguyen , Yen Lam Minh , Thwaites Guy , Thanh Tran Tan , Tan Le Van ,   OUCRU COVID-19 Research Group
Published: June 2022

AbstractWe studied the development and persistence of neutralising antibodies against SARS-CoV-2 ancestral strain, and Delta and Omicron (BA.1 and BA.2) variants in Vietnamese healthcare workers (HCWs) up to 15 weeks after booster vaccination. We included 47 HCWs with different pre-existing immune statuses (group 1 (G1): n=21, and group 2 (G2): n=26 without and with prior breakthrough Delta variant infection, respectively). The study participants had completed primary immunisation with ChAdOx1-S and booster vaccination with BNT162b2. Neutralising antibodies were measured using a surrogate virus neutralisation assay. Of the 21 study participants in G1, neutralising antibodies against ancestral strain, Delta variant, BA.1 and BA.2 were (almost) abolished at month 8 after the second dose, but all had detectable neutralising antibodies to the study viruses at week two post booster dose. Of the 26 study participants in G2, neutralising antibody levels to BA.1 and BA.2 were significantly higher than those to the corresponding viruses measured at week 2 post breakthrough infection and before the booster dose. At week 15 post booster vaccination, neutralising antibodies to BA.1 and BA.2 dropped significantly, with more profound changes observed in those without breakthrough Delta variant infection. Booster vaccination enhanced neutralising activities against ancestral strain and Delta variant, as compared to those induced by primary vaccination. These responses were maintained at high levels for at least 15 weeks. Our findings emphasise the importance of the first booster dose in producing cross-neutralising antibodies against Omicron variant. A second booster dose might be needed to maintain long-term protection against Omicron variant.