bluuebunny/crossref_metadata_2025_split huggingface dataset:
Obesity and Smoking as Risk Factors for Invasive Mechanical Ventilation in COVID-19 Respiratory Failure: a Retrospective, Observational Cohort Study
Authors: Monteiro Ana C. , Suri Rajat , Emeruwa Iheanacho O. , Stretch Robert J. , Cortes-Lopez Roxana Y. , Sherman Alexander , Lindsay Catherine C. , Fulcher Jennifer A. , Goodman-Meza David , Sapru Anil , Buhr Russell G. , Chang Steven , Wang Tisha , Qadir Nida 
Published: August 2020

AbstractPurposeTo describe the trajectory of respiratory failure in COVID-19 and explore factors associated with risk of invasive mechanical ventilation (IMV).Materials and MethodsA retrospective, observational cohort study of 112 inpatient adults diagnosed with COVID-19 between March 12 and April 16, 2020. Data were manually extracted from electronic medical records. Multivariable and Univariable regression were used to evaluate association between baseline characteristics, initial serum markers and the outcome of IMV.ResultsOur cohort had median age of 61 (IQR 45-74) and was 66% male. In-hospital mortality was 6% (7/112). ICU mortality was 12.8% (6/47), and 18% (5/28) for those requiring IMV. Obesity (OR 5.82, CI 1.74-19.48), former (OR 8.06, CI 1.51-43.06) and current smoking status (OR 10.33, CI 1.43-74.67) were associated with IMV after adjusting for age, sex, and high prevalence comorbidities by multivariable analysis. Initial absolute lymphocyte count (OR 0.33, CI 0.11-0.96), procalcitonin (OR 1.27, CI 1.02-1.57), IL-6 (OR 1.17, CI 1.03-1.33), ferritin (OR 1.05, CI 1.005-1.11), LDH (OR 1.57, 95% CI 1.13-2.17) and CRP (OR 1.13, CI 1.06-1.21), were associated with IMV by univariate analysis.ConclusionsObesity, smoking history, and elevated inflammatory markers were associated with increased need for IMV in patients with COVID-19.
Clinical characteristics and Outcomes of 500 patients with COVID Pneumonia – Results from a Single center (Southend University Hospital)
Authors: Koduri Gouri , Gokaraju Sriya , Darda Maria , Warrier Vinod , Duta Irina , Hayes Fiona , Sayed Iman El , Ahmed Yasser 
Published: August 2020

AbstractObjectivesTo characterise the clinical features of hospitalised COVID-19 patients in a single centre during the first epidemic wave and explore potential predictive variables associated with outcomes such as mortality and the need for mechanical ventilation, using baseline clinical parameters.MethodologyWe conducted a retrospective review of electronic records for demographic, clinical and laboratory data, imaging and outcomes for 500 hospitalised patients between February 20thand May 7th2020 from Southend University Hospital, Essex, UK. Multivariate logistic regression models were used to identify risk factors relevant to outcome.ResultsThe mean age of the cohort admitted to hospital with Covid-19, was 69.4 and 290 (58%) were over 70. The majority were Caucasians, 437 (87%) with ≤2 comorbidities 280(56%). Most common were hypertension 186(37%), Cardiovascular disease 178(36%) and Diabetes 128 (26%), represented in a larger proportion on the mortality group. Mean CFS was 4 with Non - Survivors had significantly higher CFS 5 vs 3 in survivors, p<0.001. In addition, Mean CRP was significantly higher 150 vs 90, p<0.001 in Non-Survivors. We observed the baseline predictors for mortality were age, CFS and CRP.ConclusionsIn this single centre study, older and frailer patients with more comorbidities and a higher baseline CRP and creatinine were risk factors for worse outcomes. Integrated frailty and age-based risk stratification are essential, in addition to monitoring SFR (Sp02/Fi02) and inflammatory markers throughout the disease course to allow for early intervention to improve patient outcomes.
Extracting novel antimicrobial emergence events from scientific literature and medical reports
Authors: Mendelsohn Emma , Ross Noam , White Allison M. , Whiting Karissa , Basaraba Cale , Madubuonwu Brooke Watson , Johnson Erica , Dualeh Mushtaq , Matson Zach , Dattaray Sonia , Ezeokoli Nchedochukwu , Lieberman Melanie Kirshenbaum , Kotcher Jacob , Maher Samantha , Zambrana-Torrelio Carlos , Daszak Peter 
Published: August 2020

AbstractDespite considerable global surveillance of antimicrobial resistance (AMR), data on the global emergence of new resistance genotypes in bacteria has not been systematically compiled. We conducted a study of English-language scientific literature (2006-2017) and disease surveillance reports (1994-2017) to identify global events of novel AMR emergence (first clinical reports of unique drug-bacteria resistance combinations). We screened 24,966 abstracts and reports, ultimately identifying 1,773 novel AMR emergence events from 294 articles. Events were reported in 66 countries, with most events in the United States (152), India (129), and China (128). The most common bacteria demonstrating new resistance were Klebsiella pneumoniae (352) and Escherichia coli (218). Resistance was most common against antibiotic drugs imipenem (89 events), ciprofloxacin (85) and ceftazidime (82). We provide an open-access database of emergence events with standardized fields for bacterial species, drugs, location, and date, and we discuss guidelines and caveats for data analysis. This database may be broadly useful for understanding rates and patterns of AMR evolution, identifying global drivers and correlates, and targeting surveillance and interventions.
The cost-effectiveness of common strategies for the prevention of transmission of SARS-CoV-2: a flexible policy online platform
Authors: Zafari Zafar , Goldman Lee , Kovrizhkin Katia , Muennig Peter 
Published: August 2020

AbstractBackgroundThe added value of interventions to prevent the transmission of SARS-CoV-2 among university affiliates is uncertain but needed as universities attempt to remain open.MethodsWe use a decision-analytic simulation to examine the cost-effectiveness of common interventions to reduce SARS-CoV-2 transmission. We use Columbia University for reference values but our approach centers around an online model that allows users to tailor the model and interventions to their local conditions and existing strategies. All interventions are compared relative to implementing the Centers for Disease Control and Prevention (CDC) guidelines alone. Results. At prevalence rate of actively infectious cases of COVID-19 in the community surrounding the university of 0.1%, using a symptom-checking mobile application is cost-saving relative to CDC guidelines alone and the university can expect to remain open. At a prevalence of 1%, standardizing masks will be cost-saving. At a prevalence rate of 2%, thermal imaging cameras cost $965,070 (95% credible interval [CrI] = $198,821, $2.15 million)/quality-adjusted life year (QALY) gained. One-time testing on entry costs $1.08 million (95% CrI = $170,703, $3.33 million)/QALY gained. Weekly testing costs $820,119 (95% CrI = $452,673, $1.68 million)/QALY gained. Upgrades to ventilation systems or installation of far-ultraviolet C lighting systems will be cost-effective at a willingness-to-pay threshold of $200,000/QALY gained only if aerosols account for 86-90% of all on-campus transmission of SARS-CoV-2.ConclusionsThe value of interventions to prevent transmission of SARS-CoV-2 vary greatly with the prevalence rate of actively infectious cases of COVID-19 in the community surrounding the university.Key PointsUniversities are struggling to remain open in the face of COVID-19 infections among affiliates. There are a number of modalities to reduce the transmission of SARS-CoV-2, but it is unclear which are worthwhile investments for any given university.
Socio-demographic and Clinical Characteristics of Adults with SARS-CoV-2 Infection in Two Hospitals in Bogota, Colombia
Authors: Moscoso D Alejandro , Sanchez Alejandra , Aya Adriana , Gomez Carolina , Rodriguez Yazmin , Garzon Javier , Lobelo Felipe 
Published: August 2020

ABSTRACTThis study is a retrospective cohort of 122 adult patients with SARS-CoV-2 diagnosed and managed at two medium-sized, tertiary private Hospitals. The analysis includes demographic and socio-economic information, symptoms, comorbidities, laboratory test results, therapeutic management, clinical outcomes and complications.
Identification on Admission of COVID-19 Patients at Risk of Subsequent Rapid Clinical Deterioration
Authors: Beals J. , Barnes J. , Durand D. , Rimar J. , Donohue T. , Hoq M. , Belk K. , Amin A. , Rothman M.J. 
Published: August 2020

AbstractIntroductionRecent localized surges in COVID-19 cases have resulted in the hospitals serving those areas being overwhelmed. In such cases, the ability to rapidly and objectively determine a patient’s acuity and predict near-term care needs is a major challenge. At issue is the clinician’s ability to correctly identify patients at risk for subsequent rapid clinical deterioration. Data-driven tools that can support such determinations in real-time may be a valuable adjunct to clinician judgement during COVID-19 surges.ObjectiveTo assess the effectiveness of the Rothman Index (RI) predictive model in distinguishing the risk of subsequent deterioration or elevated care needs among hospitalized COVID-19 patients at the time of hospital admission.MethodsWe evaluated the initial RI score on admission to predict COVID-19 patient risk for 216 COVID-19 patients discharged from March 21stto June 7th, 2020 at Sinai LifeBridge Hospital and 1,453 COVID-19 patients discharged from any of Yale New Haven Health System’s Yale New Haven, Bridgeport, and Greenwich hospitals from April 1stto April 28th, 2020. In-hospital mortality as a function of age and RI on admission for COVID-19 and non-COVID-19 patients were compared. AUC values using each COVID-19 patient’s initial RI on admission to predict in-hospital mortality, mechanical ventilation, and ICU utilization were computed, as were precision and recall for mortality prediction at specific RI thresholds.ResultsThe RI computed at the time of admission provides a high degree of objective discrimination to differentiate the COVID-19 population into high and low risk populations at the outset of hospitalization. The high risk segment based on initial RI constitutes 20-30% of the COVID-19 positive population with mortality rates from 40-50%. The low risk segment based on initial RI constitutes 40%-55% of the population with mortality rates ranging from 1%-8%. Of note is that COVID-19 patients who present with heightened but generally unremarkable acuity can be identified early as having considerably elevated risk for subsequent physiological deterioration.ConclusionCOVID-19 patients exhibit elevated mortality rates compared to non-COVID-19 medical service patients and may be subject to rapid deterioration following hospital admission. A lack of predictive indicators for identifying patients at high risk of subsequent deterioration or death can pose a challenge to clinicians. The RI has excellent performance characteristics when stratifying risk among COVID-19 patients at the time of admission. The RI can assist clinicians in real-time with a high degree of objective discrimination by segmenting the COVID-19 population into high and low risk populations. This supports rapid and optimal patient bed assignment and resource allocation.
Comparison of RNA extraction methods for the detection of SARS-CoV-2 by RT-PCR
Authors: Eichhoff Ossia M. , Bellini Elisa , Lienhard Reto , Stark Wendelin J. , Bechtold Philippe , Grass Robert N. , Bosshard Philipp P. , Levesque Mitchell P. 
Published: August 2020

AbstractObjectivesThe SARS-CoV-2 pandemic outbreak has stressed health care systems as well as medical supply chains, but diagnostic testing is an essential public health measure to control viral spread. Here we test the suitability of different RNA extraction methods for integration into a diagnostic workflow for coronavirus testing.MethodsWe applied six RNA extraction methods on the same 24 SARS-CoV-2 positive patient samples and quantified their results by subsequent reverse-transcriptase PCR (RT-PCR) of three viral genes. These methods included a) column-based extraction, b) phenol-chloroform extraction, as well as c) extraction using magnetic beads (i.e., one commercial kit as well as three different magnetic beads in combination with home-brewed buffers and solutions).ResultsWe achieved diagnostic-quality RT-PCR results with all methods, and there was no significant difference between the tested methods, except for one magnetic bead protocol with home-brewed buffers, in which the number of positive tested genes was significantly lower.ConclusionsFive of the six RNA extraction methods are interchangeable in a diagnostic workflow. Since some methods are more scalable than others, and have comparable results on RT-PCR quantitation, they may be more amenable to high-throughput sample processing pipelines.Graphical abstract
Quality of life and anxiety in patients with non-muscle invasive bladder cancer: a prospective study
Authors: Vaioulis Alexandros , Konstantinos Bonotis , Perivoliotis Konstantinos , Yiannis Kiouvrekis , Stavros Gravas , Vasilios Tzortzis , Anastasios Karatzas 
Published: August 2020

AbstractIntroductionWe evaluated anxiety and quality of life (QoL) in patients who were operated for non-muscle invasive bladder cancer (NMIBC)MethodsThe present study is a prospective analysis of patients with histopathologically confirmed NMIBCs after they were submitted to transurethral resection of the tumour (TURBT). Eligible were all adult patients with a single or multiple NMIBCs. All included patients followed therapy with either BCG or Epirubicin instillations. The SF-36 questionnaire Physical and Mental health aspects were used for QoL assessment. Similarly, the STAI-Y was introduced for the state (STAI-Y1) and trait anxiety (STAI-Y2) evaluation.ResultsIn total, 117 eligible patients were included. Regarding SF-36 Physical a 6 months decrease was followed by an improvement at 12 months. Similarly, an increase of the SF-36 Mental health score was identified. In contrast to STAI-Y2, a long-term reduction of the state anxiety was identified. Preoperative SF-36 Physical was inversely correlated with age, while absence of alcohol was associated with lower mental health. Overall, patient characteristics, habits and the administered treatment did not affect the postoperative QoL and anxiety.ConclusionsPatient QoL and anxiety improved during follow up. Although certain characteristics were related to QoL and anxiety, further larger scale studies are required.
Clinical characteristics of COVID-19 and the model for predicting the occurrence of critically ill patients: a retrospective cohort study
Authors: Ouyang Jing , Shan Xuefeng , Wang Xin , Zhang Xue , Chen Yaling , Qi Miaomiao , Xia Chao , Gu Dongqing , Chen Yaokai , Zhang Ben 
Published: August 2020

AbstractBackgroundThe present study aim to comprehensively report the epidemiological and clinical characteristics of the COVID-19 patients and to develop a multi-feature fusion model for predicting the critical ill probability.MethodsIt was a retrospective cohort study that incorporating the laboratory-confirmed COVID-19 patients in the Chongqing Public Health Medical Center. The prediction model was constructed with least absolute shrinkage and selection operator (LASSO) logistic regression method and the model was further tested in the validation cohort. The performance was evaluated by the receiver operating curve (ROC), calibration curve and decision curve analysis (DCA).ResultsA total of 217 patients were included in the study. During the treatment, 34 patients were admitted to intensive care unit (ICU) and no developed death. A model incorporating the demographic and clinical characteristics, imaging features and laboratory findings were constructed to predict the critical ill probability and it was proved to have good calibration, discrimination ability and clinic use.ConclusionsThe prevalence of critical ill was relatively high and the model may help the clinicians to identify the patients with high risk for developing the critical ill, thus to conduct timely and targeted treatment to reduce the mortality rate.
Deep Learning for Automated Recognition of Covid-19 from Chest X-ray Images
Authors: Duong Linh T. , Nguyen Phuong T. , Iovino Ludovico , Flammini Michele 
Published: August 2020

AbstractBackgroundThe pandemic caused by coronavirus in recent months is having a devastating global effect, which puts the world under the most ever unprecedented emergency. Currently, since there are not effective antiviral treatments for Covid-19 yet, it is crucial to early detect and monitor the progression of the disease, thus helping to reduce mortality. While a corresponding vaccine is being developed, and different measures are being used to combat the virus, medical imaging techniques have also been investigated to assist doctors in diagnosing this disease.ObjectiveThis paper presents a practical solution for the detection of Covid-19 from chest X-ray (CXR) images, exploiting cutting-edge Machine Learning techniques.MethodsWe employ EfficientNet and MixNet, two recently developed families of deep neural networks, as the main classification engine. Furthermore, we also apply different transfer learning strategies, aiming at making the training process more accurate and efficient. The proposed approach has been validated by means of two real datasets, the former consists of 13,511 training images and 1,489 testing images, the latter has 14,324 and 3,581 images for training and testing, respectively.ResultsThe results are promising: by all the experimental configurations considered in the evaluation, our approach always yields an accuracy larger than 95.0%, with the maximum accuracy obtained being 96.64%.ConclusionsAs a comparison with various existing studies, we can thus conclude that our performance improvement is significant.
Mass screening of asymptomatic persons for SARS-CoV-2 using saliva
Authors: Yokota Isao , Shane Peter Y , Okada Kazufumi , Unoki Yoko , Yang Yichi , Inao Tasuku , Sakamaki Kentaro , Iwasaki Sumio , Hayasaka Kasumi , Sugita Junichi , Nishida Mutsumi , Fujisawa Shinichi , Teshima Takanori 
Published: August 2020

AbstractBackgroundCOVID-19 has rapidly evolved to become a global pandemic due largely to the transmission of its causative virus through asymptomatic carriers. Detection of SARS-CoV-2 in asymptomatic people is an urgent priority for the prevention and containment of disease outbreaks in communities. However, few data are available in asymptomatic persons regarding the accuracy of PCR testing. Additionally, although self-collected saliva has significant logistical advantages in mass screening, its utility as an alternative specimen in asymptomatic persons is yet to be determined.MethodsWe conducted a mass-screening study to compare the utility of nucleic acid amplification, such as reverse transcriptase polymerase chain reaction (RT-PCR) testing, using NPS and saliva samples from each individual in two cohorts of asymptomatic persons: the contact tracing cohort and the airport quarantine cohort.ResultsIn this mass-screening study including 1,924 individuals, the sensitivity of nucleic acid amplification testing with nasopharyngeal and saliva specimens were 86% (90%CI:77-93%) and 92% (90%CI:83-97%), respectively, with specificities greater than 99.9%. The true concordance probability between the nasopharyngeal and saliva tests was estimated at 0.998 (90%CI:0.996-0.999) on the estimated airport prevalence, 0.3%. In positive individuals, viral load was highly correlated between NPS and saliva.ConclusionBoth nasopharyngeal and saliva specimens had high sensitivity and specificity. Self-collected saliva is a valuable specimen to detect SARS-CoV-2 in mass screening of asymptomatic persons.
Health care seeking behaviors in Puerperal sepsis in rural Sindh, Pakistan: a qualitative study
Authors: Ariff Shabina , Khan Ubaidullah , Turab Ali , Kureishy Sumra , Raza Farrukh , Tabassum Farhana , Mir Fatima , LeFevre Amnesty , Bartlett Linda A. , Habib Atif , Soofi Sajid Bashir , Bhutta Zulfiqar A 
Published: August 2020

AbstractBackgroundPuerperal sepsis (PS) is one of the major causes of maternal death, contributing to 26 000 deaths per year in developing countries. Early recognition and treatment are essential to managing PS, but numerous social, cultural and technical barriers prevent or delay access to care and necessary medical attention. Through this qualitative study, we identified barriers to care seeking for puerperal sepsis among recently delivered women in Matiari, Pakistan.MethodsWe conducted 20 in-depth interviews among recently delivered women with and without sepsis and their family members. Key informant interviews were conducted with 14 healthcare providers and traditional birth attendants. The themes used for content analysis were knowledge of danger signs, factors affecting care seeking and local treatment practices for postpartum sepsis.ResultsRecently delivered women, their family members and traditional birth attendants were unaware of the word PS or the local translated term for PS. However, they were familiar with most of the individual symptoms associated with PS. Healthcare providers were aware of the condition and the associated symptoms. The healthcare providers understanding of the seriousness of PS was directly proportional their age and clinical experience. The most common barriers to care seeking was the division of labor within the household, obtaining permission from the primary decision maker, access to transportation, lack of financial resources and support from family members.DiscussionIn rural Pakistan, limited knowledge of PS, division of labor within the household, obtaining permission from primary decision maker and access to transportation and financial resources were identified as barriers to seeking care among recently delivered women.ConclusionTo improve maternal care seeking behaviors for PS, interventions focusing on increasing knowledge of PS, addressing gender inequality, implementing an affordable community transport service and enhancing TBA’s knowledge and skills to manage PS need to be implemented.
Evaluation of gait initiation parameters using inertial sensors in Huntington’s Disease: Insights into anticipatory postural adjustments and cognitive interference
Authors: Desai Radhika , Fritz Nora E. , Muratori Lisa , Hausdorff Jeffrey M. , Busse Monica , Quinn Lori 
Published: August 2020

AbstractBackground and PurposeUnderstanding the contribution of anticipatory postural adjustments (APA) on walking ability in individuals with Huntington’s disease (HD) may provide insight into motor planning and the functional consequences of HD-specific cortical-basal ganglia pathway dysfunctions. The purpose of this study was to evaluate inertial measurement unit (IMU)-derived measures of APAs and first step parameters, and their contribution to gait speed, in individuals with and without manifest HD during a single-task and cognitive load condition.Methods33 individuals with manifest HD and 15 age-matched healthy controls wore three Opal APDM IMUs during a 14-meter walk during a single task and cognitive load condition. APA acceleration amplitudes, APA durations, first step range of motion (ROMs), and first step duration were compared, along with their relationship to gait speed.ResultsIndividuals with HD had significantly greater APA acceleration amplitudes, smaller first step ROMs and longer first step durations compared to healthy controls. No difference in APA durations were present between groups across conditions. Linear model results and significant correlations between mediolateral APA acceleration amplitudes and APA durations were found.ConclusionsLarger acceleration amplitudes, smaller first step ROMs of greater duration, accompanied by the preservation of APA durations reveal a discrepancy in movement scaling in HD. Additionally, the mediolateral component of the APA is likely a rate-limiting factor that drives a compensatory response in gait initiation. Additional research is needed to explore the neural correlates of HD-related movement scaling.