bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anterior Cartilage Rasping During Otoplasty Performed With an Adson Brown Cartilage Forceps
Authors: Rauso Raffaele , Lo Faro Carmelo , Rugge Luigi , Califano Luigi , Tartaro Gianpaolo 
Published: August 2020

Abstract
Protruding ears are a common occurrence and can affect the aesthetics and psychosocial aspects of patients. Hundreds of procedures have been described over the years to correct the 2 main deformities related to protruding ears: conchal hypertrophy and anti-helical fold absence.
For the rasping technique, the rasp is inserted posteriorly, from the side where the skin is excised;
The ending part of the forceps looks like a small rasp, it worked very well and the surgery was completed without problems
The authors think this tip could be a useful “tool” for all the surgeons used to perform cartilage rasping “in case of necessity” when rasp is not available.
Assesing Intraoperative Virtual Navigation on My Craniofacial Surgery Fellowship for Orbital Fractures Repair: Is it Useful?
Authors: García-Cano Eugenio , Malagón-Hidalgo Héctor Omar , Gónzalez-Magaña Fernando , Monroy-Cedillo Jose Luis. 
Published: August 2020

Abstract
Orbital fractures pose specific challenge in its surgical management. One of the greatest challenges is to obtain satisfactory restoration of normal orbital volume and globe projection following traumatic injury, due to the inability of the surgeon to gain adequate visibility and to verify proper implant position and placement during the operation. Surgical navigation is a very helpful tool when dealing with the reconstruction of such orbital fractures. During the training of the craniofacial fellowship learning to recognize the orbital floor boundaries is essential for the correct implant placement for reconstruction, their identification is a critical step, which may be assisted by intraoperative virtual navigation. Six patients were surgically treated for orbital floor fracture with intraoperative virtual navigation. The clinical evaluation showed no complications such as enophtalmos, exophtalmos or dystopia in all the patients 2 months post operatively and a correct implant/graft position.
During surgery, navigation provides exact determination of transverse, cranio-caudal and postero-anterior dimensions within the orbit and precise control of the position of implants/bone grafts.
This tool aids consistently on the craniofacial surgery fellow's formation, as it facilitates the identification of the bony floor boundaries and verifies the correct placement of the implants/bone grafts. It is routinely use could help to avoid implants/bone grafts misplacement not only for craniofacial surgeon's fellow, but for all the orbital surgeons.
Review and update in the diagnosis of peripheral nerve sheath tumors
Authors: Meyer Anders 
Published: August 2020

Purpose of review
Although tumors with nerve sheath differentiation are vast, the main clinically significant problems faced by the pathologist are the separation of malignant peripheral nerve sheath tumors (MPNSTs) from histologic mimics, the diagnosis of neurofibromatous neoplasms with atypical features, and the separation of cutaneous neurofibromatous neoplasms from melanoma. This review briefly discusses a variety of common nerve sheath tumors and summarizes recent advances on these diagnostic fronts.

Recent findings
Much of recent work has focused on abnormalities in polycomb repressive complex 2, and the ways in which these abnormalities may be exploited in the diagnosis of MPNSTs. Progress has been made in the diagnostic and clinical understanding of atypical neurofibromatous neoplasms and low-grade MPNSTs. A number of reports have explored the diagnostic distinction between cutaneous neurofibroma and melanoma.

Summary
New discoveries show promise in the diagnosis of peripheral nerve sheath tumors, but challenges – old and new – remain.
Cognitive and behavioural impairment in amyotrophic lateral sclerosis
Authors: Pender Niall , Pinto-Grau Marta , Hardiman Orla 
Published: August 2020

Purpose of review
The current review provides an up to date overview of the nature and progression of the cognitive and behavioural impairment in amyotrophic lateral sclerosis (ALS). Understanding these symptoms has implications for the management of the disease and the design of clinical trials, in addition to the support of patient and caregiver regarding mental capacity and end of life decision-making.

Recent findings
Cognitive and behavioural change in ALS are best characterized as the consequence of extensive network dysfunction. 35–45% of ALS patients present with mild–moderate cognitive impairment and comorbid dementia occurs in approximately 14% of patients, the majority of these meeting diagnostic criteria for frontotemporal dementia (FTD). Cognitive change in ALS manifests most commonly as executive dysfunction and language impairment. Behavioural change in the form of apathy, disinhibition, loss of sympathy and empathy, stereotyped behaviours and dietary changes occur.

Summary
Cognitive and behavioural impairment is an important feature of ALS, and reflects broad network dysfunction of frontostriatal and frontotemporal systems. Cognition and behaviour should be assessed early in the diagnostic process, and data driven approaches should be developed to enable reliable quantitative outcome assessment suitable for clinical trials.
3D Printed Snorkel Mask Adapter for Failed N95 Fit Tests and PPE Shortages
Authors: Dalla Shiv , Shinde Rohit , Ayres Jack , Waller Stephen , Nachtigal Jay 
Published: August 2020

ABSTRACTIntroductionThe shortage of personal protective equipment (PPE) across the country has been widely discussed throughout the COVID-19 pandemic. Unfortunately, recent reports indicate that PPE shortages persist amidst continually increasing caseloads nationwide. Additionally, there have been reports of poor-fitting masks, a problem which is magnified by shortages. The lack of adequate access to conventional N95 masks pushed for some to pursue 3D printing and locally distributing their own manufactured masks as substitutes when PPE, including N95 masks, were not readily available. The design presented, the snorkel mask adapter, is one such design born from the local maker community in partnership with local physicians and hospitals. This article discusses the design, manufacturing, and validation of the snorkel mask adapter and its immediate use in the COVID-19 pandemic as well as future use as stopgap PPE.MethodsThe design presented is an adapter which can be used with a commercially available snorkel mask in order to serve as a full face respirator in either the case of a PPE shortage or more pertinently for those who are unable to pass fit testing with the available N95 respirators at their respective facilities. Mask components were 3D printed, assembled, and then fit tested by qualitative fit testing (QLFT) at The University of Kansas Health System (TUKHS) in Kansas City, KS as a proof of concept.ResultsAt TUKHS, the mask was fit tested on 22 individuals who required an N95 mask but were not able to pass qualitative fit testing with the masks available to them at the time. Of the 22 tested, all 22 of them were able to pass QLFT with the snorkel mask, adapter, and viral/bacterial filter combination.ConclusionThe results of the fit testing at TUKHS is promising for this N95 alternative. More extensive testing can and should be done, including quantitative fit testing. Persistently increasing caseloads and PPE shortages necessitates an urgent dissemination of these preliminary results. The authors do not advocate for this design as a replacement of traditional N95 masks or other PPE but do endorse this design as a stopgap measure, proven to be effective in situations of dire PPE shortage or for individuals who have failed fit testing with conventional PPE.
Genetically-predicted vitamin D status, ambient UVB during the pandemic and COVID-19 risk in UK Biobank: Mendelian Randomisation study
Authors: Li Xue , Geffen Jos van , Weele Michiel van , Zhang Xiaomeng , He Yazhou , Meng Xiangrui , Timofeeva Maria , Campbell Harry , Dunlop Malcolm , Zgaga Lina , Theodoratou Evropi 
Published: August 2020

AbstractA growing body of evidence shows that poor vitamin D status has been associated with an increased susceptibility to viral and bacterial respiratory infections. In this study, we aimed to examine the association between vitamin D and COVID-19 risk and outcomes, and to explore potential causal effects. We used logistic regression to identify associations between different vitamin D variables (25-hydroxyvitamin D concentration (25-OHD), ambient UVB and genetically-predicted 25-OHD concentrations) and COVID-19 (risk of infection, hospitalisation and death) in 495,780 participants from UK Biobank. We subsequently performed a Mendelian Randomisation (MR) study to test if there was any causal effect. In total, 1,746 COVID-19 cases and 399 COVID-19 deaths occurred between March and June 2020. We found significant inverse associations between COVID-19 infection and 25-OHD in univariable models, but these associations were non-significant after adjustment for confounders. Ambient UVB was strongly and inversely associated with hospitalization and death. Although the main MR analysis showed that genetically-predicted vitamin D levels were not causally associated with COVID-19 risk, MR sensitivity analysis using weighted mode method indicated a potential causal effect (OR=0.72, 95% CI:0.53-0.98; P=0.041). In conclusion, our study found suggestive evidence of association between vitamin D and the risk or severity of COVID-19 but further studies are needed.
Whether Early Steroid dose is associated with lower mortality in COVID-19 critically ill Patients- An exploratory chart review
Authors: Goyal Abhishek , Saigal Saurabh , Joshi Ankur , Brahmam Dodda , Niwariya Yogesh , Khurana Alkesh , Singh Pooja , Kama Sunaina Tejpal , Sharma Jaiprakash , Khadanga Sagar , Pavan G Sai , Mitra Arun 
Published: August 2020

AbstractIntroductionSteroids have shown its usefulness in critically ill COVID19 patients. However time of starting steroid and dose tailored to severity remains a matter of inquiry due to still emerging evidences and wide-ranging concerns of benefits and harms. We did a retrospective record analysis in an apex teaching hospital ICU setting to explore optimal doses and duration of steroid therapy which can decrease mortality.Methodology114 adults with COVID19-ARDS admitted to ICU between 20thMarch-15thAugust2020 were included in chart review. We did preliminary exploratory analysis(rooted in steroid therapy matrix categorized by dose and duration) to understand the effect of several covariates on survival. This was followed by univariate and multivariate Cox proportion hazard regression analysis and model diagnostics.ResultsExploratory analysis and visualization indicated age, optimal steroid, severity (measured in P/F) of disease and infection status as potential covariates for survival. Univariate cox regression analysis showed significant positive association of age>60 years{2.6 (1.5-4.7)} and protective effect of optimum steroid{0.38(0.2-0.72)} on death (hazard) in critically ill patients. Multivariate cox regression analysis after adjusting effect of age showed protective effect of optimum steroid on hazard defined as death {0.46(0.23-0.87),LR=17.04,(p=2e- 04)}.The concordance was 0.70 and model diagnostics fulfilled the assumption criteria for proportional hazard model.ConclusionOptimal dose steroid as per defined ‘optimum’ (<24 hours and doses tailored to P/F at presentation) criteria can offer protective effect from mortality which persists after adjusting for age. This protective effect was not found to be negatively influenced by the risk of infection.No funding was taken for this paper.
Development of Diagnostic Score for Acute Pericarditis in Patients Admitted for Chest Pain
Authors: Meireles André Costa , Oliveira João Vitor Miranda Porto , de Sá Barreto Pontes Bruna , Souza Alexandre Costa , Gomes Laila Caroline Oliveira Souza Barbo , Silva Thomaz Emanoel Azevedo , de Melo Milton Henrique Vitoria , Bagano Gabriela Oliveira , Rabelo Márcia Maria Noya , Correia Luis Claudio Lemos 
Published: August 2020

ABSTRACTBackgroundDespite the presence of clinical, laboratory and electrocardiographic characteristics suggestive of acute pericarditis, there is no multivariate diagnostic score developed for this condition.ObjectiveTo develop a clinical score for diagnosis of pericarditis as the cause of acute chest pain, using data from admission.MethodsIn a diagnostic case-control study, we compared consecutive 45 patients of the Chest Pain Registry diagnosed of pericarditis (confirmed by magnetic resonance imaging or the presence of pleural effusion in echocardiography) versus 90 patients with an alternative confirmed diagnosis, randomly selected from our registry. Six clinical characteristics, 16 chest pain characteristics and 4 additional tests were candidates as predictors. Logistic regression was used to derivate a model composed by independent predictors of pericarditis.ResultsAmong 17 variables associated with pericarditis, 5 remained independent predictors: age; pain aggravation with thorax movement; positive troponin; diffuse ST-segment elevation and C-reactive protein. Each independent predictor was attributed points proportional to its regression coefficient. The final score presented discriminatory capacity represented by C-statistic of 0.97 (95% CI = 0.93 – 1.0). The best cutoff point was defined as > 6 points, with sensitivity of 96% (95% CI = 85 – 100), specificity of 87% (95% CI = 78 – 93), positive likelihood ratio of 7.2 (95% CI = 4.2 – 12) and negative likelihood ratio of 0.05 (95% CI = 0.01 – 0.2).ConclusionThe proposed multivariate score seems to be accurate for the diagnosis of pericarditis and require further validation in an independent sample.
Evaluation of emotional arousal level and depression severity using the centripetal force derived from voice
Authors: Shinohara Shuji , Toda Hiroyuki , Nakamura Mitsuteru , Omiya Yasuhiro , Higuchi Masakazu , Takano Takeshi , Saito Taku , Tanichi Masaaki , Boku Shuken , Mitsuyoshi Shunji , So Mirai , Yoshino Aihide , Tokuno Shinich 
Published: August 2020

AbstractIn this research, we propose a new voice feature called centripetal force (CF) to investigate the relationship between emotional arousal level and depression severity. First, CFs were calculated from various speech recordings in the interactive emotional dyadic motion capture database, and the correlation with the arousal level of each voice was examined. The resulting correlation coefficient was 0.52. We collected a total of 178 datasets comprising 10 speech phrases and the Hamilton Rating Scale for Depression (HAM-D) score of outpatients with major depression at the Ginza Taimei Clinic (GTC) and the National Defense Medical College (NDMC) Hospital. The correlation coefficients between CF and HAM-D scores were –0.33 and –0.43 at the GTC and NDMC, respectively. Next, the dataset was divided into the no depression group (HAM-D< 8) and the depression group (HAM-D ≥8) according to the HAM-D score. There was a significant difference in the mean CF values between the two groups in both the GTC and NDMC data (p = 0.0089 and p = 0.0016, respectively). The AUC when discriminating both groups by CF was 0.76 in GTC data and 0.72 in NDMC data. Indirectly, using CF established a relationship between emotional arousal level and depression severity.
Transmission dynamics of COVID-19 in household and community settings in the United Kingdom
Authors: Bernal Jamie Lopez , Panagiotopoulos Nikolaos , Byers Chloe , Garcia Vilaplana Tatiana , Boddington Nicki , Zhang Xu-Sheng , Charlett Andre , Elgohari Suzanne , Coughlan Laura , Whillock Rosie , Logan Sophie , Bolt Hikaru , Sinnathamby Mary , Letley Louise , MacDonald Pauline , Vivancos Roberto , Edeghere Oboaghe , Anderson Charlotte , Paranthaman Karthik , Cottrell Simon , McMenamin Jim , Zambon Maria , Dabrera Gavin , Ramsay Mary , Saliba Vanessa 
Published: August 2020

AbstractBackgroundHouseholds appear to be the highest risk setting for transmission of COVID-19. Large household transmission studies were reported in the early stages of the pandemic in Asia with secondary attack rates ranging from 5–30% but few large scale household transmission studies have been conducted outside of Asia.MethodsA prospective case ascertained study design based on the World Health Organization FFX protocol was undertaken in the UK following the detection of the first case in late January 2020. Household contacts of cases were followed using enhanced surveillance forms to establish whether they developed symptoms of COVID-19, became confirmed cases and their outcomes. Household secondary attack rates and serial intervals were estimated. Individual and household basic reproduction numbers were also estimated. The incubation period was estimated using known point source exposures that resulted in secondary cases.ResultsA total of 233 households with two or more people were included with a total of 472 contacts. The overall household SAR was 37% (95% CI 31–43%) with a mean serial interval of 4.67 days, an R0of 1.85 and a household reproduction number of 2.33. We find lower secondary attack rates in larger households. SARs were highest when the primary case was a child. We estimate a mean incubation period of around 4.5 days.ConclusionsHigh rates of household transmission of COVID-19 were found in the UK emphasising the need for preventative measures in this setting. Careful monitoring of schools reopening is needed to monitor transmission from children.
Machine learning based clinical decision support system for early COVID-19 mortality prediction
Authors: Karthikeyan Akshaya , Garg Akshit , Vinod P. K. , Priyakumar U. Deva 
Published: August 2020

ABSTRACTThe coronavirus disease 2019 (COVID-19) is an acute respiratory disease that has been classified as a pandemic by World Health Organization (WHO). The sudden spike in the number of infections and high mortality rates have put immense pressure on the public medical systems. Hence, it’s crucial to identify the key factors of mortality that yield high accuracy and consistency to optimize patient treatment strategy. This study uses machine learning methods to identify a powerful combination of five features that help predict mortality with 96% accuracy: neutrophils, lymphocytes, lactate dehydrogenase (LDH), high-sensitivity C-reactive protein (hs-CRP) and age. Various machine learning algorithms have been compared to achieve a consistent high accuracy across the days that span the disease. Robust testing with three cases confirm the strong predictive performance of the proposed model. The model predicts with an accuracy of 90% as early as 16 days before the outcome. This study would help accelerate the decision making process in healthcare systems for focused medical treatments early and accurately.
Ensemble Forecasts of Coronavirus Disease 2019 (COVID-19) in the U.S.
Authors: Ray Evan L , Wattanachit Nutcha , Niemi Jarad , Kanji Abdul Hannan , House Katie , Cramer Estee Y , Bracher Johannes , Zheng Andrew , Yamana Teresa K , Xiong Xinyue , Woody Spencer , Wang Yuanjia , Wang Lily , Walraven Robert L , Tomar Vishal , Sherratt Katharine , Sheldon Daniel , Reiner Robert C , Prakash B. Aditya , Osthus Dave , Li Michael Lingzhi , Lee Elizabeth C , Koyluoglu Ugur , Keskinocak Pinar , Gu Youyang , Gu Quanquan , George Glover E. , España Guido , Corsetti Sabrina , Chhatwal Jagpreet , Cavany Sean , Biegel Hannah , Ben-Nun Michal , Walker Jo , Slayton Rachel , Lopez Velma , Biggerstaff Matthew , Johansson Michael A , Reich Nicholas G 
Published: August 2020

AbstractBackgroundThe COVID-19 pandemic has driven demand for forecasts to guide policy and planning. Previous research has suggested that combining forecasts from multiple models into a single “ensemble” forecast can increase the robustness of forecasts. Here we evaluate the real-time application of an open, collaborative ensemble to forecast deaths attributable to COVID-19 in the U.S.MethodsBeginning on April 13, 2020, we collected and combined one- to four-week ahead forecasts of cumulative deaths for U.S. jurisdictions in standardized, probabilistic formats to generate real-time, publicly available ensemble forecasts. We evaluated the point prediction accuracy and calibration of these forecasts compared to reported deaths.ResultsAnalysis of 2,512 ensemble forecasts made April 27 to July 20 with outcomes observed in the weeks ending May 23 through July 25, 2020 revealed precise short-term forecasts, with accuracy deteriorating at longer prediction horizons of up to four weeks. At all prediction horizons, the prediction intervals were well calibrated with 92-96% of observations falling within the rounded 95% prediction intervals.ConclusionsThis analysis demonstrates that real-time, publicly available ensemble forecasts issued in April-July 2020 provided robust short-term predictions of reported COVID-19 deaths in the United States. With the ongoing need for forecasts of impacts and resource needs for the COVID-19 response, the results underscore the importance of combining multiple probabilistic models and assessing forecast skill at different prediction horizons. Careful development, assessment, and communication of ensemble forecasts can provide reliable insight to public health decision makers.
Long-term anabolic androgenic steroid use is associated with deviant brain aging
Authors: Bjørnebekk Astrid , Kaufmann Tobias , Hauger Lisa E. , Westlye Lars T. 
Published: August 2020

AbstractBackgroundHigh-dose long-term use of anabolic-androgenic steroids (AAS) may bring a range of health consequences, including brain and cognitive abnormalities. We performed age prediction based on brain scans to test whether prolonged AAS use is associated with accentuated brain aging.MethodsT1-weighted brain MRI data were obtained from male weightlifters with a history of prolonged (n = 133) or no (n = 105) AAS use. We trained machine learning models on combinations of regional brain volumes, cortical thickness and surface area in an independent training set of 1838 healthy males aged 18–92 years and predicted brain age for each participant in our study. We used linear models to compare the gap between chronological age and predicted brain age (the brain age gap, BAG) between the two groups, and, in a subsample with longitudinal data (mean interval 3.5 years), tested for group differences in the change rate of BAG. Moreover, we tested for associations between apparent brain aging and AAS use duration, administration pattern and dependence.ResultsAAS users had higher BAG compared to weightlifting controls with strongest effects for frontal and insular regions. Higher BAG was associated with current AAS use, dependency, and longer history of AAS use. Group differences in BAG could not be explained by substance use, general cognitive abilities or depression. Longitudinal data revealed no group difference in the rate of BAG change.ConclusionsThe findings suggest that long-term high dose AAS use may have adverse effects on brain aging, potentially linked to current and exaggerated use of AAS.