bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between Stage 1 Hypertension Defined by the 2017 ACC/AHA Hypertension Guideline and Cardiovascular Risk: A Large Cohort Study from the UK
Authors: Li Fu-Rong , Wu Xian-Bo 
Published: April 2020

ABSTRACTImportanceThe 2017 American College of Cardiology (ACC)/American Heart Association (AHA) hypertension (HTN) guideline lowered the threshold for HTN from 140/90 mmHg to 130/80 mmHg for systolic/diastolic blood pressure (SBP/DBP), resulting in a newly defined stage 1 HTN with an SBP/DBP reading of 130–139/80–89 mmHg. Few studies have assessed the impact of the redefined HTN on cardiovascular outcomes among UK population.ObjectiveTo examine the effects of the revised ACC/AHA stage 1 HTN blood pressure parameters on the prevalence of HTN and related cardiovascular disease (CVD) risk in a large UK population.DesignAdult men and women from a national cohort study in the UK.SettingThe UK Biobank Study.ParticipantsA total of 470,625 adults (mean age 56 years) with available data on blood pressure (BP) and without history of CVDs at baseline.Main outcome measuresPrevalence of HTN and incident composite CVD outcomes.MethodsProspective CVD events were analysed for survival in relation to BP measures using Cox proportional hazards regression models, adjusting for potential confounders. The associations are described by hazard ratios (HRs) and 95% confidence intervals (CIs).ResultsBy adopting the 2017 ACC/AHA HTN guideline, an additional 24.7% of the participants were classified as having ACC/AHA stage 1 HTN, which resulted in a prevalence of HTN of 75.1% at baseline. During a mean follow-up period of 8.1 years, ACC/AHA stage 1 HTN (130–139/80–89 mmHg) was associated with a significantly increased risk of CVD (HR 1.20; 95% CI 1.10–1.30) compared to the risk associated with a normal BP (<120/80 mmHg). The excess risk of CVD associated with ACC/AHA stage 1 HTN was mainly driven by myocardial infarction (HR 1.19; 95% CI 1.05-1.36) and haemorrhagic stroke (HR 1.40; 95% CI 1.08-1.81), rather than ischaemic stroke (HR 1.02; 95% CI 0.87-1.19) and CVD death (HR 1.07; 95% CI 0.90-1.26).ConclusionsThe adoption of the 2017 ACC/AHA guideline would lead to a dramatic increase in the prevalence of HTN in the UK Biobank cohort study. Evidence from the present national cohort study may support lowering the threshold for HTN from 140/90 mmHg to 130/80 mmHg in the UK.
Hypertension Subtype Defined by the 2017 ACC/AHA Blood Pressure Guidelines and Risk of Cardiovascular Disease: A Large Prospective Cohort Study
Authors: Li Fu-Rong , Wu Xian-Bo 
Published: April 2020

AbstractBackgroundThe 2017 American College of Cardiology/American Heart Association (ACC/ AHA) blood pressure (BP) guideline lowered the hypertension threshold from a systolic blood pressure/diastolic blood pressure level of ≥140/90 mm Hg to ≥130/80 mm Hg. The significance of hypertension subtype under the new definition has not been fully explored.ObjectiveTo examine the associations of isolated systolic hypertension (ISH) and isolated diastolic hypertension (IDH) by the 2017 ACC/AHA guidelines with risk of cardiovascular disease (CVD) among the UK population.DesignProspective population-based cohort studySettingUK BiobankParticipants and MethodsWe included 470,625 participants who were free of CVD at baseline and had available data on BP measures. Of these, 13,157 CVD events were recorded (median follow-up 8.1 years), including 6,865 nonfatal myocardial infarctions (MI), 3,415 nonfatal ischemic strokes (ISs), 1,118 nonfatal hemorrhagic strokes (HSs), and 2,971 CVD deaths. Participants were categorized into 5 groups: normal BP, normal high BP, ISH, IDH and systolic and diastolic hypertension (SDH). The associations of each type of hypertension for the risk of CVD were estimated using a Cox proportional hazards regression model with adjustment for potential confounding factors.ResultsAccording to the hypertension threshold of ≥130/80 mm Hg by ACC/AHA guideline, both ISH (HR 1.35, 95% CI 1.24-1.46) and IDH (HR 1.22, 95% CI 1.11-1.36) were significantly associated with higher risk of overall CVD risk, compared with those with normal BP. ISH was predictive of most CVD risk, except for IS; while the excess CVD risk associated with IDH appeared to be driven mainly by MI. We found heterogeneity by sex and age regarding the effects of IDH on overall CVD risk, with the associations stronger in women and younger adults (age < 60 years) and null in men and older adults (age ≥60 years).ConclusionsISH and IDH by the ACC/AHA BP guideline were both associated with increased risk of CVD, highlighting the justification to lower the criteria of hypertension definition in the UK. Further research is needed to identify participants with IDH who are at especially greater risk for developing CVD.
Systematic review of COVID-19 autopsies: accelerated hyaluronan concentration as the primary driver of morbidity and mortality in high-risk COVID-19 patients: with therapeutic introduction of an oral hyaluronan inhibitor in the prevention of “Induced Hyaluronan Storm” Syndrome
Authors: Mong Michael A. , Awkal Jacob A. , Marik Paul E. 
Published: April 2020

AbstractTo date, the fundamental drivers of the morbidity and mortality in COVID-19 remain uncertain. Clinicians worldwide appear to be at a loss to know how to prevent and treat the severe respiratory distress in these patients effectively. Consequently, the fundamental mechanisms leading to death in high-risk patients need to be discovered and addressed with urgency. The post-mortem autopsy remains an essential part of both discovering the cause of death in a particular individual, but also in advancing the science and treatment of disease, especially in the case of novel pathogens such as SARS-CoV-2[2]. The goal of an autopsy is to discover the cause of death (COD) using a macro/microscopic investigation. Because lung weight is often affected by the cause of death and the last breath occurs very near if not at death, the evaluation of the lungs is one of the starting points of any COD investigation[3]. A comprehensive search was performed to systematically review all reported autopsy findings in COVID-19 patients with respect to lung weights and histologic findings. We then compared these findings with the results of a targeted literature review of hyaluronan in relationship to acute respiratory distress syndrome (ARDS). In total, data from 38 autopsies were identified. From this group, 36 autopsies of COVID-19 patients were selected for detailed review and statistical analysis. The average lung weight of those who were determined to have died as a result of SARS-CoV-2 was 1683g approximately 3.2 times the normal lung weight. Hyaline membranes were consistently identified on histologic sections. A review of the literature reveals that markedly elevated lung weights and hyaline membranes and have been associated with the pathophysiology of ARDS since 1967. However, the key role key of hyaluronan in driving the morbidity and mortality of the condition has heretofore not been fully recognized. We propose that the induced hyaluronan storm syndrome or IHS, is a model that addresses the heretofore perplexing respiratory failure that is the proximal cause of death. An aggressive research effort should be undertaken to discover why the majority of individuals who are exposed to the virus are minimally symptomatic, while a minority of high-risk individuals rapidly progress to respiratory failure and death.“You may take notes for 20 years, from morning to night at the bedside of the sick, upon the diseases of the viscera, and all will be to you only a confusion of symptoms…a train of incoherent phenomena. Open a few bodies and this obscurity will disappear.” - Marie-François-Xavier Bichat (1771–1802), “The Father of Histology”[1].
Flow cytometric analysis and purification of airway epithelial cell subsets
Authors: Bonser Luke R. , Koh Kyung Duk , Johansson Kristina , Choksi Semil P. , Cheng Dan , Liu Leqian , Sun Dingyuan I. , Zlock Lorna T. , Eckalbar Walter L. , Finkbeiner Walter E. , Erle David J. 
Published: April 2020

AbstractThe human airway epithelium is essential in homeostasis, and epithelial dysfunction contributes to chronic airway disease. Development of flow cytometric methods to characterize subsets of airway epithelial cells will enable further dissection of airway epithelial biology. Leveraging single cell RNA-sequencing (scRNA-seq) data in combination with known cell type-specific markers, we developed panels of antibodies to characterize and isolate the major airway epithelial subsets (basal, ciliated, and secretory cells) from human bronchial epithelial cell cultures. We also identified molecularly distinct subpopulations of secretory cells and demonstrated cell subset-specific expression of low abundance transcripts and micro-RNAs that are challenging to analyze with current scRNA-seq methods. These new tools will be valuable for analyzing and separating airway epithelial subsets and interrogating airway epithelial biology.
Audiometric profiles and patterns of benefit. A data-driven analysis of subjective hearing difficulties and handicaps
Authors: Sanchez-Lopez Raul , Dau Torsten , Whitmer William M. 
Published: April 2020

ObjectiveHearing rehabilitation attempts to compensate for auditory dysfunction, reduce hearing difficulties and minimize participation restrictions that can lead to social isolation. However, there is no systematic approach to assess the quality of the intervention at an individual level that might help to evaluate the need of further hearing rehabilitation in the hearing care clinic.DesignA data-driven analysis on subjective data reflecting hearing disabilities and handicap was chosen to explore “benefit patterns” as a result of rehabilitation in different audiometric groups. The method was based on: 1) Dimensionality reduction; 2) Stratification; 3) Archetypal analysis; 4) Clustering; and 5) Item importance estimation.Study sample572 hearing-aid users completed questionnaires of hearing difficulties (speech, spatial and qualities hearing scale; SSQ) and hearing handicap (HHQ).ResultsThe data-driven approach revealed four benefit profiles that were different for each audiometric group. The groups with low degree of high-frequency hearing loss (HLHF) showed a priority for rehabilitating hearing handicaps, whereas the groups with HLHF > 50 dB HL showed a priority for improvements in speech understanding.ConclusionsThe patterns of benefit and the stratification approach might guide the clinical intervention strategy and improve the efficacy and quality of service in the hearing care clinic.
Rapid identification of SARS-CoV-2-infected patients at the emergency department using routine testing
Authors: Kurstjens Steef , van der Horst Armando , Herpers Robert , Geerits Mick W.L. , Kluiters-de Hingh Yvette C.M. , Göttgens Eva-Leonne , Blaauw Martinus J.T. , Thelen Marc H.M. , Elisen Marc G.L.M. , Kusters Ron 
Published: April 2020

ABSTRACTBackgroundThe novel coronavirus disease 19 (COVID-19), caused by SARS-CoV-2, spreads rapidly across the world. The exponential increase in the number of cases has resulted in overcrowding of emergency departments (ED). Detection of SARS-CoV-2 is based on an RT-PCR of nasopharyngeal swab material. However, RT-PCR testing is time-consuming and many hospitals deal with a shortage of testing materials. Therefore, we aimed to develop an algorithm to rapidly evaluate an individual’s risk of SARS-CoV-2 infection at the ED.MethodsIn this multicenter retrospective study, routine laboratory parameters (C-reactive protein, lactate dehydrogenase, ferritin, absolute neutrophil and lymphocyte counts), demographic data and the chest X-ray/CT result from 967 patients entering the ED with respiratory symptoms were collected. Using these parameters, an easy-to-use point-based algorithm, called the corona-score, was developed to discriminate between patients that tested positive for SARS-CoV-2 by RT-PCR and those testing negative. Computational sampling was used to optimize the corona-score. Validation of the model was performed using data from 592 patients.ResultsThe corona-score model yielded an area under the receiver operating characteristic curve of 0.91 in the validation population. Patients testing negative for SARS-CoV-2 showed a median corona-score of 3 versus 11 (scale 0-14) in patients testing positive for SARS-CoV-2 (p<0.001). Using cut-off values of 4 and 11 the model has a sensitivity and specificity of 96% and 95%, respectively.ConclusionThe corona-score effectively predicts SARS-CoV-2 RT-PCR outcome based on routine parameters. This algorithm provides the means for medical professionals to rapidly evaluate SARS-CoV-2 infection status of patients presenting at the ED with respiratory symptoms.
A simulation of a COVID-19 epidemic based on a deterministic SEIR model
Authors: Carcione José M. , Santos Juan E. , Bagaini Claudio , Ba Jing 
Published: April 2020

AbstractAn epidemic disease caused by a new coronavirus has spread in Northern Italy with a strong contagion rate. We implement an SEIR model to compute the infected population and number of casualties of this epidemic. The example may ideally regard the situation in the Italian Region of Lombardy, where the epidemic started on February 24, but by no means attempts to perform a rigorous case study in view of the lack of suitable data and uncertainty of the different parameters, namely, the variation of the degree of home isolation and social distancing as a function of time, the number of initially exposed individuals and infected people, the incubation and infectious periods and the fatality rate.First, we perform an analysis of the results of the model, by varying the parameters and initial conditions (in order the epidemic to start, there should be at least one exposed or one infectious human). Then, we consider the Lombardy case and calibrate the model with the number of dead individuals to date (April 28, 2020) and constraint the parameters on the basis of values reported in the literature. The peak occurs at day 37 (March 31) approximately, when there is a rapid decrease, with a reproduction ratio R0 = 3 initially, 1.36 at day 22 and 0.78 after day 35, indicating different degrees of lockdown. The predicted death toll is almost 15325 casualties, with 2.64 million infected individuals at the end of the epidemic. The incubation period providing a better fit of the dead individuals is 4.25 days and the infectious period is 4 days, with a fatality rate of 0.00144/day [values based on the reported (official) number of casualties]. The infection fatality rate (IFR) is 0.57 %, and 2.36 % if twice the reported number of casualties is assumed. However, these rates depend on the initially exposed individuals. If approximately nine times more individuals are exposed, there are three times more infected people at the end of the epidemic and IFR = 0.47 %. If we relax these constraints and use a wider range of lower and upper bounds for the incubation and infectious periods, we observe that a higher incubation period (13 versus 4.25 days) gives the same IFR (0.6 % versus 0.57 %), but nine times more exposed individuals in the first case. Other choices of the set of parameters also provide a good fit of the data, but some of the results may not be realistic. Therefore, an accurate determination of the fatality rate and characteristics of the epidemic is subject to the knowledge of precise bounds of the parameters.Besides the specific example, the analysis proposed in this work shows how isolation measures, social distancing and knowledge of the diffusion conditions help us to understand the dynamics of the epidemic. Hence, the importance to quantify the process to verify the effectiveness of the lockdown.
COVID-19 in Iran, a comprehensive investigation from exposure to treatment outcomes
Authors: Ashraf Mohammad Ali , Shokouhi Nasim , Shirali Elham , Davari-tanha Fateme , Memar Omeed , Kamalipour Alireza , Azarnoush Ayein , Mabadi Avin , Ossareh Adele , Sanginabadi Milad , Azad Talat Mokhtari , Aghaghazvini Leila , Ghaderkhani Sara , Poordast Tahereh , Pourdast Alieh , Nazemi Pershang 
Published: April 2020

AbstractPurposeThere is a growing need for information regarding the recent coronavirus disease of 2019 (Covid-19). We present a comprehensive report of Covid-19 patients in Iran.MethodsOne hundred hospitalized patients with Covid-19 were studied. Data on potential source of exposure, demographic, clinical, and paraclinical features, therapy outcome, and post-discharge follow-up were analyzed.ResultsThe median age of the patients was 58 years, and the majority of the patients (72.7%) were above 50 years of age. Fever was present in 45.2% of the patients on admission. The most common clinical symptoms were shortness of breath (74%) and cough (68%). Most patients had elevated C-reactive protein (92.3%), elevated erythrocyte sedimentation rate (82.9%), lymphocytopenia (74.2 %) on admission. Lower lobes of the lung were most commonly involved, and ground-glass opacity (81.8%) was the most frequent finding in CT scans. The administration of hydroxychloroquine improved the clinical outcome of the patients. Lopinavir/ritonavir was efficacious at younger ages. Of the 70 discharged patients, 40% had symptom relapse, (8.6%) were readmitted to the hospital, and 3 patients (4.3%) died.ConclusionThis report demonstrates a heterogeneous nature of clinical manifestations in patients affected with Covid-19. The most common presenting symptoms are non-specific, so attention should be made on broader testing, especially in age groups with the greatest risk and younger individuals who can serve as carriers of the disease. Hydroxychloroquine and lopinavir/ritonavir (in younger age group) can be potential treatment options. Finally, patients discharged from the hospital should be followed up because of potential symptom relapse.
Eye movement evaluation in Multiple Sclerosis and Parkinson’s Disease using a Standardized Oculomotor and Neuro-ophthalmic Disorder Assessment (SONDA)
Authors: Grillini Alessandro , Renken Remco J. , Vrijling Anne C. L. , Heutink Joost , Cornelissen Frans W. 
Published: April 2020

AbstractEvaluating the state of the oculomotor system of a patient is one of the fundamental tests done in neuro-ophthalmology. However, up to date, very few quantitative standardized tests of eye movements quality exist, limiting this assessment to confrontational tests reliant on subjective interpretation. Furthermore, quantitative tests relying on eye movement properties such as pursuit gain and saccade dynamics are often insufficient to capture the complexity of the underlying disorders and are often (too) long and tiring. In this study, we present SONDA (Standardised Oculomotor and Neurological Disorder Assessment): this test is based on analyzing eye tracking recorded during a short and intuitive continuous tracking task. We tested patients affected by Multiple Sclerosis (MS) and Parkinson’s Disease (PD) and find that: (1) the saccadic dynamics of the main sequence alone are not sufficient to separate patients from healthy controls; (2) the combination of spatio-temporal and statistical properties of saccades and saccadic dynamics enables an identification of oculomotor abnormalities in both MS and PD patients. We conclude that SONDA constitutes a powerful screening tool that allows an in-depth evaluation of (deviant) oculomotor behavior in a few minutes of non-invasive testing.
Automated Contouring and Planning for Hippocampal-Avoidant Whole-Brain Radiotherapy
Authors: Feng Christine H. , Cornell Mariel , Moore Kevin L. , Karunamuni Roshan , Seibert Tyler M. 
Published: April 2020

AbstractPurposeDesign and evaluate a workflow using commercially available artificial intelligence tools for automated hippocampal segmentation and treatment planning to efficiently generate clinically acceptable hippocampal-avoidant whole brain (HA-WBRT) radiotherapy plans.Methods and MaterialsWe retrospectively identified 100 consecutive adult patients treated for brain metastases outside the hippocampal region. Each patient’s T1 post-contrast brain MRI was processed using FDA-approved software that provides segmentations of brain structures in 5-7 minutes. Automated hippocampal segmentations were reviewed for accuracy and edited manually if necessary, then converted to files compatible with a commercial treatment planning system, where hippocampal avoidance regions and planning target volumes (PTV) were generated. Other organs-at-risk (OARs) were previously contoured per clinical routine. A RapidPlan knowledge-based planning routine was applied for a prescription of 30 Gy in 10 fractions using volumetric modulated arc therapy (VMAT) delivery. Plans were evaluated based on NRG CC001 dose-volume objectives.ResultsOf the 100 cases, 99 (99%) had acceptable automated hippocampi segmentations without manual intervention. Knowledge-based planning was applied to all cases; the median processing time was 9 minutes 59 seconds (range 6:53 – 13:31). All plans met per-protocol dose-volume objectives for PTV per the NRG CC001 protocol. For comparison, only 66.0% of plans on NRG CC001 met PTV goals per protocol, with 26.3% within acceptable variation. In this study, 43 plans (43%) met OAR constraints, and the remaining 57 (57%) were within acceptable variation, compared to 42.9% and 48.6% on NRG CC001, respectively. No plans in this study had unacceptable dose to OARs, compared to 0.8% of manually generated plans from NRG CC001.ConclusionAn automated pipeline harnessing the efficiency of commercially available artificial intelligence tools can generate clinically acceptable VMAT HA-WBRT plans with minimal manual intervention. This process could improve clinical efficiency for a treatment established to improve patient outcomes over standard WBRT.
An Interactive Tool to Forecast US Hospital Needs in the Coronavirus 2019 Pandemic
Authors: Locey Kenneth J. , Webb Thomas A. , Khan Jawad , Antony Anuja K. , Hota Bala 
Published: April 2020

ABSTRACTHospital enterprises have been continually faced with anticipating the spread of COVID- 19 and the effects it is having on visits, admissions, bed needs, and crucial supplies. While many studies have focused on understanding the basic epidemiology of the disease, few open source tools have been made available to aid hospitals in their planning. We developed a web-based application (available at: http://covid19forecast.rush.edu/) for US states and territories that allows users to choose from a suite of models already employed in characterizing the spread of COVID-19. Users can obtain forecasts for hospital visits and admissions as well as anticipated needs for ICU and non-ICU beds, ventilators, and personal protective equipment supplies. Users can also customize a large set of inputs, view the variability in forecasts over time, and download forecast data. We describe our web application and its models in detail and provide recommendations and caveats for its use. Our application is primarily designed for hospital leaders, healthcare workers, and government official who may lack specialized knowledge in epidemiology and modeling. However, specialists can also use our open source code as a platform for modification and deeper study. As the dynamics of COVID-19 change, our application will also change to meet emerging needs of the healthcare community.