bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distinguishing between COVID-19 and the common cold in a primary care setting - comparison of patients with positive and negative SARS-CoV-2 PCR results
Authors: Just Johannes , Puth Marie-Therese , Regenold Felix , Weckbecker Klaus , Bleckwenn Markus 
Published: May 2020

AbstractBackgroundCombating the COVID-19 pandemic is a major challenge for health systems, citizens and policy makers worldwide. Early detection of affected patients within the large and heterogeneous group of patients with common cold symptoms is an important element of this effort, but often hindered by limited testing resources and the lack of pathognomonic symptoms in COVID-19. Therefore, we aimed to identify predictive risk factors for a positive SARS-CoV-2 PCR (CovPCR) result in a primary care setting.MethodWe performed a multi-center cross-sectional cohort study on predictive clinical characteristics for a positive CovPCR over a period of 4 weeks in primary care patients in Germany.FindingsIn total, 374 patients in 14 primary care centers received CovPCR and were included in this analysis. The median age was 44.0 (IQR: 31.0-59.0) and a fraction of 10.7% (n=40) tested positive for COVID-19. Patients who reported anosmia had a higher odds ratio (OR: 4.54; 95%-CI: 1.51-13.67) for a positive test result while patients with a sore throat had a lower OR (OR: 0.33; 95%-CI: 0.11-0.97). Patients who had a first grade contact with an infected persons and showed symptoms themselves also had an increased OR for positive testing (OR: 5.16; 95% CI: 1.72-15.51). This correlation was also present when they themselves were still asymptomatic (OR: 12.55; 95% CI: 3.97-39.67).ConclusionsSeveral anamnestic criteria may be helpful to assess pre-test probability of COVID-19 in patients with common cold symptoms
Level of clinical competence in junior medical residents and its correlation with antibiotic prescription errors: a cross-sectional study
Authors: Joshua Martínez D. , Octavio Sierra-Martínez , Arturo Galindo-Fraga , Andrés Trejo Mejía Juan , Melchor Sánchez-Mendiola , Eric Ochoa-Hein , Mirella Vázquez-Rivera , Carlos Gutiérrez-Cirlos , Jesús Naveja , Adrián Martínez-González 
Published: May 2020

AbstractBackgroundA large portion of prescribing errors can be attributed to medication knowledge deficiency. They are preventable and most often occur in the stage of ordering. Antimicrobials are the drug class most commonly related to prescribing errors.ObjectivesThe study main objective was to describe the relationship between clinical competence and antibiotic prescription errors. Secondary objectives were to measure clinical competence of junior medical residents with an Objective Structured Clinical Examination (OSCE), to describe the frequency and severity of antibiotic prescription errors and to find items and attributes of clinical competence that are correlated with the antibiotic prescription error ratio.MethodsA cross-sectional study was designed to assess the clinical competence of junior medical residents, from National Institute of Pediatrics and “Manuel Gea Gonzalez” General Hospital in Mexico City, through an infectious disease OSCE and measure the frequency and severity of antibiotic prescription errors. Statistical analysis included generalizability theory and internal consistency Cronbach’s alpha, a partial correlation controlling sex and time of degree, simple linear regression and item’s exploratory factorial analysis.ResultsThe mean OSCE score was 0.692 ± 0.073. The inter-item Cronbach’s alpha was 0.927 and inter-station Cronbach’s alpha was 0.774. The G coefficient in generalizability theory analysis was 0.84. The antibiotic prescription error ratio was 45.1% ± 7%. The severity of antibiotic prescription errors was: category C (errors that do not cause patient harm) = 56 cases, 15.5%; category D (monitoring required to confirm that errors resulted in no harm to the patient or intervention required to preclude harm) = 51 cases, 14.1%; category E (errors that may contribute to or result in temporary harm to the patient and require intervention) = 235, 65.2%; category F (errors that may contribute to or resulted in temporary harm to the patient and require initial or prolonged hospitalization) = 18 cases, 5%. The correlation between clinical competence and antibiotic prescription errors was established with Pearson correlation (r=-0.33, p<0.05, CI95% -0.57 to -0.07), and partial correlation controlling effect of gender and time since graduation (r=-0.39, p<0.01, CI95% -0.625 to -0.118).ConclusionsWe found a negative correlation between clinical competence and antibiotic prescription error ratio in graduated physicians who have been accepted in a medical specialty. The therapeutic plan, which is a component of clinical competence score, and the prescription skills had a negative correlation with antibiotic prescription errors. The most frequent mistakes in antibiotic prescriptions errors would need a second intervention.
Estimation of the basic reproduction number, average incubation time, asymptomatic infection rate, and case fatality rate for COVID-19: Meta-analysis and sensitivity analysis
Authors: He Wenqing , Yi Grace Y. , Zhu Yayuan 
Published: May 2020

AbstractThe coronavirus disease 2019 (COVID-19) has been found to be caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensive knowledge of COVID-19 remains incomplete and many important features are still unknown. This manuscripts conduct a meta-analysis and a sensitivity study to answer the questions: What is the basic reproduction number? How long is the incubation time of the disease on average? What portion of infections are asymptomatic? And ultimately, what is the case fatality rate? Our studies estimate the basic reproduction number to be 3.15 with the 95% interval (2.41, 3.90), the average incubation time to be 5.08 days with the 95% confidence interval (4.77, 5.39) (in day), the asymptomatic infection rate to be 46% with the 95% confidence interval (18.48%, 73.60%), and the case fatality rate to be 2.72% with 95% confidence interval (1.29%, 4.16%) where asymptomatic infections are accounted for.
Global prediction of unreported SARS-CoV2 infection from observed COVID-19 cases
Authors: Chow Carson C. , Chang Joshua C. , Gerkin Richard C. , Vattikuti Shashaank 
Published: May 2020

SummaryEstimation of infectiousness and fatality of the SARS-CoV-2 virus in the COVID-19 global pandemic is complicated by ascertainment bias resulting from incomplete and non-representative samples of infected individuals. We developed a strategy for overcoming this bias to obtain more plausible estimates of the true values of key epidemiological variables. We fit mechanistic Bayesian latent-variable SIR models to confirmed COVID-19 cases, deaths, and recoveries, for all regions (countries and US states) independently. Bayesian averaging over models, we find that the raw infection incidence rate underestimates the true rate by a factor, the case ascertainment ratio CARt that depends upon region and time. At the regional onset of COVID-19, the predicted global median was 13 infections unreported for each case confirmed (CARt = 0.07 C.I. (0.02, 0.4)). As the infection spread, the median CARt rose to 9 unreported cases for every one diagnosed as of April 15, 2020 (CARt = 0.1 C.I. (0.02, 0.5)). We also estimate that the median global initial reproduction number R0 is 3.3 (C.I (1.5, 8.3)) and the total infection fatality rate near the onset is 0.17% (C.I. (0.05%, 0.9%)). However the time-dependent reproduction number Rt and infection fatality rate as of April 15 were 1.2 (C.I. (0.6, 2.5)) and 0.8% (C.I. (0.2%,4%)), respectively. We find that there is great variability between country- and state-level values. Our estimates are consistent with recent serological estimates of cumulative infections for the state of New York, but inconsistent with claims that very large fractions of the population have already been infected in most other regions. For most regions, our estimates imply a great deal of uncertainty about the current state and trajectory of the epidemic.
Battling the COVID-19 Pandemic: Is Bangladesh Prepared?
Authors: Khan Md Hasinur Rahaman , Howlader Tamanna , Islam Md. Mazharul 
Published: May 2020

AbstractFollowing detection of the first few COVID-19 cases in early March, Bangladesh has stepped up its efforts to strengthen capacity of the healthcare system to avert a crisis in the event of a surge in the number of cases. This paper sheds light on the preparedness of the healthcare system by examining the spatial distribution of isolation beds across districts and divisions, forecasting the number of ICU units that may be required in the short term and analyzing the availability of frontline healthcare workers to combat the pandemic. As of May 2, COVID-19 cases have been found in 61 of the 64 districts in Bangladesh with Dhaka District being the epicenter. Seventy-one percent of the cases have been identified in 6 neighboring districts, namely, Dhaka, Narayanganj, Gazipur, Narsingdi, Munsiganj and Kishoreganj, which appear to form a spatial cluster. However, if one takes into account the population at risk, the prevalence appears to be highest in Dhaka, followed by Narayanganj, Gazipur, Kishorganj, Narsingdi and Munshiganj. These regions may therefore be flagged as the COVID-19 hotspots in Bangladesh. Among the eight divisions, prevalence is highest in Dhaka Division followed by Mymensingh. The number of cases per million exceeds the number of available isolation beds per million in the major hotspots indicating that there is a risk of the healthcare system becoming overwhelmed should the number of cases rise. This is especially true for Dhaka Division, where the ratio of COVID-19 patients to doctors appears to be alarmingly high. My-mensingh Division also has a disproportionately small number of doctors relative to the number of COVID-19 patients. Using second order polynomial regression, the analysis predicts that even if all ICU beds are allocated to COVID-19 patients, Bangladesh may run out of ICU beds soon after May 15, 2020. We conclude that in spite of a significant increase in hospital capacity during 2005-15 and a 57 % rise in the number of doctors during the same period, the healthcare system in Bangladesh and Dhaka Division in particular, may not be fully prepared to handle the COVID-19 crisis. Thus, further steps need to be taken to flatten the curve and improve healthcare capacity.
Functional Impacts of Aminoglycoside Treatment on Speech Perception and Extended High-Frequency Hearing Loss in Cystic Fibrosis
Authors: Blankenship Chelsea M. , Hunter Lisa L. , Feeney M. Patrick , Cox Madison , Bittinger Lindsey , Garinis Angie , Lin Li , McPhail Gary , Clancy John P. 
Published: May 2020

AbstractPurposeThe purpose of this study is to better understand the prevalence of ototoxicity-related hearing loss and its functional impact on communication in a pediatric and young adult cohort with cystic fibrosis (CF) and individuals without CF (controls).MethodObservational, cross-sectional investigation of hearing function in children, teens, and young adults with CF (n = 57, mean = 15.0 yr.) who received intravenous aminoglycoside antibiotics and age- and gender-matched controls (n = 61, mean = 14.6 yr.). Participants completed standard and extended high frequency audiometry, middle ear measures, speech perception tests, and a hearing and balance questionnaire.ResultsIndividuals with CF were 3 to 4 times more likely to report issues with hearing, balance, and tinnitus and performed significantly poorer on speech perception tasks compared to controls. A higher prevalence of hearing loss was observed in individuals with CF (57%) compared to controls (37%). CF and control groups had similar proportions of slight and mild hearing losses, however individuals with CF were 7.6 times more likely to have moderate and greater degrees of hearing loss. Older participants displayed higher average EHF thresholds, with no effect of age on average SF thresholds. Although middle ear dysfunction has not previously been reported to be more prevalent in CF, this study showed that 16% had conductive or mixed hearing loss and higher rates of previous otitis media and pressure equalization (PE) tube surgeries compared to controls.ConclusionsIndividuals with CF have a higher prevalence of conductive, mixed and sensorineural hearing loss, poorer speech-in-noise performance and higher rates of multiple symptoms associated with otologic disorders (tinnitus, hearing difficulty, dizziness, imbalance and otitis media) compared to controls. Accordingly, children with CF should be asked about these symptoms, receive baseline hearing assessment(s) prior to treatment with potentially ototoxic medications, and at regular intervals thereafter in order to provide otologic and audiologic treatment for hearing and ear-related problems to improve communication functioning.
Clinical characteristics of 106 patients with neurological diseases and co-morbid coronavirus disease 2019: a retrospective study
Authors: Yin Rong , Yang ZhiQi , Wei YaXuan , Li YuanMing , Chen Hui , Liu Zhao , Zhao Bo , Ma DanDan , Dan MeiLing , Zhang YingJie , Liu Xuan , Leng HuiCeng , Xiang DaWei 
Published: May 2020

AbstractObjectivesTo describe the clinical characteristics of patients with coronavirus disease 2019 (COVID-19) with co-morbid neurological symptoms.DesignRetrospective case series.SettingHuoshenshan Hospital in Wuhan, China.ParticipantsFrom 4 February to 14 April 2020, 106 patients with neurological diseases were enrolled from all patients in the hospital with confirmed COVID-19 and divided into a severe group and a non-severe group according to their COVID-19 diagnosis.Main outcome measuresClinical characteristics, laboratory results, imaging findings, and treatment methods were all retrieved through an electronic medical records system and recorded in spreadsheets.ResultsThe mean (standard deviation, SD) age of patients was 72.7 (11.8) years, and 64 patients were male (60.4%). Among patients with co-morbid neurological diseases, 81 had a previous cerebral infarction (76.4%), 20 had dementia (18.9%), 10 had acute cerebral infarction (9.4%), 5 had sequelae of cerebral haemorrhage (4.7%), 4 had intracranial mass lesions (3.8%), 3 had epilepsy (2.8%), 2 had Parkinson’s disease (1.9%), and 1 had myelopathy (0.9%). Fever (n = 62, 58.5%) was the most common symptom. The most common neurological symptoms were myalgia (n = 26, 24.5%), followed by extremity paralysis (n = 20, 18.9%), impaired consciousness (n = 17, 16%), and positive focal neurological signs (n = 42, 39.6%). Eight patients (7.5%) died. There were more patients with altered mental status in the severe group than in the non-severe group (6 [10.2%] vs. 0, P = 0.033). The inflammatory response in the severe group was more significant than that in the non-severe group. There were more patients taking anticoagulant drugs (25 [42.4%] vs. 4 [8.5%], P < 0.001) and sedative drugs (22 [37.3%] vs. 9 [19.1%], P = 0.041) in the severe group than in the non-severe group. Amid all 93 patients with cerebrovascular diseases, only 32 (34.4%) were taking aspirin, 13 (14%) taking clopidogrel, and 33 (35.5%) taking statins.ConclusionsPatients with COVID-19 with co-morbid neurological diseases had an advanced age, a high rate of severe illness, and a high mortality rate. Among the neurological symptoms, altered mental status was more common in patients with severe COVID-19 with co-morbid neurological diseases.
AN INTERACTIVE COVID-19 MOBILITY IMPACT AND SOCIAL DISTANCING ANALYSIS PLATFORM
Authors: Zhang Lei , Ghader Sepehr , Pack Michael L. , Xiong Chenfeng , Darzi Aref , Yang Mofeng , Sun QianQian , Kabiri AliAkbar , Hu Songhua 
Published: May 2020

ABSTRACTThe research team has utilized privacy-protected mobile device location data, integrated with COVID-19 case data and census population data, to produce a COVID-19 impact analysis platform that can inform users about the effects of COVID-19 spread and government orders on mobility and social distancing. The platform is being updated daily, to continuously inform decision-makers about the impacts of COVID-19 on their communities using an interactive analytical tool. The research team has processed anonymized mobile device location data to identify trips and produced a set of variables including social distancing index, percentage of people staying at home, visits to work and non-work locations, out-of-town trips, and trip distance. The results are aggregated to county and state levels to protect privacy and scaled to the entire population of each county and state. The research team are making their data and findings, which are updated daily and go back to January 1, 2020, for benchmarking, available to the public in order to help public officials make informed decisions. This paper presents a summary of the platform and describes the methodology used to process data and produce the platform metrics.
Diagnostic value of self-report compared with Beck Depression Inventory (BDI-II) in screening of depression
Authors: zarghami Mehran , Taghizadeh Fatemeh , mousazadeh Mahmood 
Published: May 2020

AbstractBackgroundDepression is a common cause of mortality and morbidity worldwide. To detect depression, we compared Beck Depression Inventory scoring as a valid tool with participants self-reporting depression.MethodologyThis cross-sectional study aimed to explore the diagnostic values of self-reporting in patients’ with depression comparing to Beck Depression Inventory scoring in Mazandaran Persian cohort study, with a total of 1300 samples. The sample size was determined to include 155 participants through the census method. In order to increase the test power, 310 healthy participants were included in the study through random selection. In order to evaluate the diagnostic value of self-reporting, BDI-II was completed by blind interviewing to the case group as well as to another group who reported that they were not depressed, as control.ResultsSensitivity, specificity, accuracy, false positive, false negative, positive and negative predictive values of self-reporting was calculated 58.4%, 79.1%,73.4%, 20.8%, 41.6%, 51.8%, and 83.2% for the total population respectively, as well as, sensitivity, specificity, accuracy, positive and negative predictive values of self-report in males were 83.3%, 77.2%, 77.1%, 43.8% and 95.6% and 53.7%, 78.1%, 71.2%, 49.2%, and 81.1% for females, respectively.ConclusionThe positive predictive value and sensitivity of self-reporting are insufficient in total population and females, and therefore self-reporting cannot detect depressed patients, but regarding to its average positive predictive value, perhaps, it can be used to identify non-depressant individuals.
Early transmission dynamics and control of COVID-19 in a southern hemisphere setting: Lima-Peru, February 29th-March 30th, 2020
Authors: Munayco César V. , Tariq Amna , Soto-Cabezas Gabriela G , Reyes Mary F. , Valle Andree , Rojas-Mezarina Leonardo , Cabezas César , Loayza Manuel ,   Peru COVID-19 working group, Chowell Gerardo 
Published: May 2020

AbstractThe COVID-19 pandemic that emerged in Wuhan China rapidly spread around the world. The daily incidence trend has been rapidly rising in Latin America since March 2020 with the great majority of the cases reported in Brazil (28320) followed by Peru (11475) as of April 15th, 2020. Although Peru implemented social distancing measures soon after the confirmation of its first case on March 6th, 2020, the daily number of new COVID-19 cases continues to increase. We assessed the early COVID-19 transmission dynamics and the effect of social distancing interventions in Lima, Peru.We estimate the transmission potential of COVID-19, R, during the early phase of the outbreak, from the daily series of imported and autochthonous cases by the date of symptoms onset as of March 30th, 2020. We also assessed the effect of social distancing interventions in Lima by generating short-term forecasts grounded on the early transmission dynamics before interventions were put in place.Prior to the implementation of the social distancing measures in Lima, we estimated the reproduction number at 2.3 (95% CI: 2.0, 2.5). Our analysis indicates that school closures and other social distancing interventions have helped stem the spread of the virus, with the nearly exponential growth trend shifting to an approximately linear growth trend after the national emergency declaration.The COVID-19 epidemic in Lima followed an early exponential growth trend, which slowed down and turned into an almost linear growth trend after broad scale social distancing interventions were put in place by the government.Peru COVID-19 working group
Single-cell Transcriptome Analysis Indicates New Potential Regulation Mechanism of ACE2 and NPs signaling among heart failure patients infected with SARS-CoV-2
Authors: Xu Dachun , Ma Mengqiu , Xu Yanhua , Su Yang , Ong Sang-Bing , Hu Xingdong , Chai Min , Zhao Maojun , Li Hong , Xu Xiaojiang 
Published: May 2020

AbstractThe coronavirus disease 2019 (COVID-19) has resulted in high morbidity and mortality worldwide since December 2019. Recent studies showed that patients with previous heart disease, especially heart failure (HF), whose plasma Natriuretic Peptides (NPs) concentrations are higher, were more susceptible to SARS-CoV-2 infection. In this study, we retrospectively analyzed single-center case series of 91 patients with COVID-19 in China. 46 (50.5%) patients exhibited cardiac dysfunction as indicated by elevated Natriuretic Peptides B (BNP) levels. Moreover, the results indicate that patients with cardiac dysfunction had higher mortality than those without cardiac dysfunction. Nonetheless, it remains unclear as to how the virus infects the heart, especially in HF patients and why a higher level of BNP in the heart dampen inflammation. Angiotensin-converting enzyme 2 (ACE2), the critical host cellular receptor of SARS-CoV-2, expresses in different organs. Still, its cellular distribution in the human heart, especially in patients with HF remains unclear. Thus, we investigated ACE2 gene expression pattern in single-cell RNA sequence (scRNA-seq) data of hearts from normal adults versus patients with HF. Our results indicate that ACE2 is predominantly enriched in cardiomyocytes (CMs), endothelial cells, fibroblasts and smooth muscle cells in normal heart. Not only ACE2+ CMs, but also expression of ACE2 are significantly boosted in CMs of patients with HF. Also, genes related to virus entry, virus replication and suppression of IFN-γ signaling besides ACE2 were up-regulated in HF patient, mainly in CMs, indicating the higher susceptibility to SARS-CoV-2 infection. Interestingly, NPs are significantly up-regulated in ACE2-postive (ACE2+) ventricular myocytes and share the upstream transcription factor. ACE2 and NPs can form a negative feedback loop with protective effects. But it maybe turns into a positive feedback loop by virus and ineffective NPs, which lead to severe prognosis. In summary, the increased expression of ACE2, NPs during HF predisposes to SARS-CoV-2 infection. Modulating the levels of ACE2, NPs therefore may potentially be a novel therapeutic target to prevent the SARS-CoV-2 infection.