bluuebunny/crossref_metadata_2025 huggingface dataset:
Actin is associated with tissue injury in trauma patients and produces a hypercoagulable profile in vitro
Authors: Coleman Julia R. , Moore Ernest E. , Freeman Kalev , Grubinger Nicholas D. , Hennig Grant W. , Cohen Mitchell J. , Samuels Jason M. , Hansen Kirk
Published: April 2020

BACKGROUND

While tissue injury provokes fibrinolysis shutdown in trauma, the mechanism remains elusive. Cellular death causes release of structural proteins, including actin and myosin, which may interact with clot formation and structure. We hypothesized that tissue injury is associated with high circulating actin and that actin produces a hypercoagulable profile with decreased fibrinolysis in vitro.

METHODS

Blood was collected from trauma activation patients at a single Level I trauma center for thrombelastography and proteomics. Proteomic analyses were performed through targeted liquid chromatography coupled with mass spectrometry using isotope-labeled standards for quantification of actin and its endogenous inhibitor gelsolin. Based on the results, we added physiologic concentrations of cytoskeletal G-actin to whole blood from healthy volunteers and analyzed changes in thrombelastography, as well as to plasma and examined clot architecture using confocal microscopy of fluorescently labeled fibrinogen.

RESULTS

Overall, 108 trauma patients were included: majority (71%) men, median age of 32.7 years, 66% blunt mechanism, median New Injury Severity Score (NISS) of 41. Compared with patients without severe tissue injury (NISS < 15, n = 10), patients with severe tissue injury (NISS > 15, n = 98) had higher levels of circulating actin (0.0428 vs. 0.0301, p = 0.02). Further, there was a trend toward lower gelsolin levels in patients with fibrinolysis shutdown (0.1844 vs. 0.2052, p = 0.17) and tissue plasminogen activator resistance (0.1676 vs. 0.2188, p = 0.06).

Ten healthy volunteers were included in the in vitro experiments (50% male; median age, 31.3 years). Actin significantly increased angle (40.0° to 52.9°, p = 0.002) and decreased fibrinolysis (percent clot lysis 30 minutes after reaching maximum amplitude, 4.0% to 1.6%; p = 0.002), provoking fibrinolytic shutdown in three patients. The addition of actin to control plasma decreased fiber resolvability of fibrin clots, monitored by microscopy, and decreased plasmin-mediated fibrinolysis.

CONCLUSION

Actin increases clot propagation and provokes fibrinolysis shutdown in vitro, through a mechanism of plasmin inhibition. High circulating levels of actin are present in trauma patients with severe tissue injury, suggesting actin contributes to fibrinolysis shutdown in the setting of tissue injury.
Barriers to improving health care value in emergency general surgery: A nationwide analysis
Authors: Hanna Kamil , Haddadin Zaid , Sakran Joseph , Zeeshan Muhammad , Asmar Samer , Kulvatunyou Narong , Tang Andrew , Northcutt Ashley , Joseph Bellal
Published: April 2020

INTRODUCTION

There is a growing need to improve the quality of care while decreasing health care costs in emergency general surgery (EGS). Health care value includes costs and quality and is a targeted metric by improvement programs. The aim of our study was to evaluate the trend of health care value in EGS over time and to identify barriers to high-value surgical care.

METHODS

The (2012–2015) National Readmission Database was queried for patients 18 years or older who underwent an EGS procedure (according to the American Association for the Surgery of Trauma definition). Health care value (V = quality metrics/cost) was calculated from the rates of freedom from readmission, major complications, reoperation, and failure to rescue (FTR) indexed over inflation-adjusted hospital costs. Outcomes were the trends in the quality metrics: 6-month readmission, major complications, reoperation, FTR, hospital costs, and health care value over the study period. Multivariable linear regression was performed to determine the predictors of lower health care value.

RESULTS

We identified 887,013 patients who underwent EGS. Mean ± SD age was 51 ± 20 years, and 53% were male. The rates of 6-month readmission, major complications, reoperation, and FTR increased significantly over the study period. The median hospital costs also increased over the study period (2012, US $9,600 to 2015, US $13,000; p < 0.01). However, the health care value has decreased over the study period (2012, 0.35; 2013, 0.30; 2014, 0.28; 2015, 0.25; p < 0.01). Predictors of decreased health care value in EGS are age 65 years or older (β = −0.568 [−0.689 to −0.418], more than three comorbidities (β = −0.292 [−0.359 to −0.21]), readmission to a different hospital (β = −0.755 [−0.914 to −0.558]), admission to low volume centers (β = −0.927 [−1.126 to −0.682]), lack of rehabilitation (β = −0.004 [−0.005 to −0.003]), and admission on a weekend (β = −0.318 [−0.366 to −0.254]).

CONCLUSION

Health care value in EGS appears to be declining over time. Some of the factors leading to decreased health care value in EGS are potentially modifiable. Health care value could potentially be improved by reducing fragmentation of care and promoting regionalization.

LEVEL OF EVIDENCE

Economic, level IV.
Effect of Shoes Reducing Varus Instability of the Knee on Gait Parameters, Knee Pain, and Health-Related Quality of Life in Females With Medial Knee Osteoarthritis
Authors: Nakano Hideki , Murata Shin , Kai Yoshihiro , Abiko Teppei , Matsuo Dai , Kawaguchi Michio , Matsumoto Takeshi , Yoshiura Yuji , Sumi Michihiro
Published: April 2020

Observations:

The effects of shoes reducing varus instability of the knee on gait parameters, knee pain, and health-related quality of life (HRQOL) in patients with medial knee osteoarthritis were investigated.

Methods:

Twelve patients with medial knee osteoarthritis wore shoes reducing varus instability of the knee.

Results and Conclusions:

Gait velocity, stride length, step length, knee pain, and Japanese Knee Osteoarthritis Measure scores significantly improved in the postintervention period compared with the pre- and postcontrol periods. Therefore, shoes reducing varus instability of the knee can effectively improve gait parameters, knee pain, and HRQOL in patients with medial knee osteoarthritis.
Measuring outcomes that matter most to people with multiple sclerosis: the role of patient-reported outcomes
Authors: Brichetto Giampaolo , Zaratin Paola
Published: April 2020

Purpose of review

Patient-reported outcome (PRO) represents a unique opportunity to measure the impact of health research, and care on outcomes that matter most to people with multiple sclerosis (PwMS).

Recent findings

How to incorporate PROs in MS clinical trials and, practice remains a matter of debate. The variety of measures available for use in MS has some benefits, but the lack of a set of standard measures has significant disadvantages. To help meeting the challenge, different PROs standard sets have been developed (PROMIS) for use across a broad range of chronic health conditions, and SymptoMScreen, specifically for MS. However, many of them were not co-created with PwMS and lacking understanding about what matters to patients. The newly proposed MS care unit model together with emerging initiatives such as iConquerMS and PROMOPROMS, are shaping new meaningful PROs. However, the uptake of PROMs in all settings can be effective only by a commonly held strategic agenda shared by all relevant stakeholders.

The newly born PRO Initiative for MS (PROMS) aims to develop a strategic agenda shared by all relevant stakeholders to help meeting the challenge of developing PRO measures that correspond to the needs of all stakeholders.
Hallucinations: diagnosis, neurobiology and clinical management
Authors: Tang Siu Wa , Tang Wayne Hans
Published: April 2020

Hallucinations are important diagnostic symptoms in schizophrenia, but also occur in other medical and neuropsychiatric conditions. Not all patients with hallucinations are psychotic. There has been a surge of interest in the topic of hallucinations, as new research data have begun to reveal their neurobiology. Hallucinogenic molecules may also serve as new scaffolds for the development of new psychotropic drugs. We searched and reviewed recent literature, focusing on the refinement of clinical management, which was inspired by new data regarding the neurobiology of hallucination subtypes. We concluded that the successful management of hallucinations depends on accurate differential diagnosis to identify subtypes, which would then determine the most appropriate treatment.
A personal account of reducing and stopping antidepressant treatment
Authors: Baldwin David S.
Published: April 2020

Having responded well to an antidepressant I was determined to continue treatment for 6 months, to increase the probability of a full and lasting recovery. My productivity at work and confidence in social situations increased and it seemed easier to talk about emotional matters. Side effects became gradually less bothersome, though at times I was somewhat apathetic. Escitalopram may have helped to reduce long-standing back pain and niggly acoustic problems. Some symptoms appeared whilst I reduced the antidepressant dosage steadily: these were mild and resolved swiftly, but a few were quite puzzling. I hope this experience will enhance my understanding of the concerns of patients as they approach the end of a course of medication, and contribute to discussions of how to assess and manage symptoms that occur on and after stopping antidepressant treatment.
A response regulator protein with antar domain, AvnR, in Acinetobacter baumannii ATCC 17978 impacts its virulence and amino acid metabolism
Authors: De Silva P. Malaka , Patidar Rakesh , Graham Christopher I. , Brassinga Ann Karen C. , kumar Ayush
Published: April 2020

Acinetobacter baumannii, a Gram-negative coccobacillus, is notorious for its involvement in opportunistic infections around the world. Its resistance to antibiotics makes treatment of infections challenging. In this study, we describe a novel response regulator protein, AvnR (A1S_2006) that regulates virulence-related traits in

A. baumannii

ATCC17978. Sequence analysis suggests that AvnR is a CheY-like response regulator and contains the RNA-binding ANTAR (AmiR and NasR transcription anti-termination regulators) domain. We show that AvnR plays a role in regulating biofilm formation (on glass and plastic surfaces), surface motility, adhesion to A549 cells as well as in nitrogen metabolism in

A. baumannii

. RNA-Seq analysis revealed that avnR deletion results in altered expression of more than 150 genes (116 upregulated and 42 downregulated). RNA-Seq data suggest that altered biofilm formation and surface motility observed in the avnR deletion mutant is likely mediated by previously unknown pathways. Of note, was the altered expression of genes predicted to be involved in amino acid transport and metabolism in avnR deletion mutant. Biolog phenotypic array showed that deletion of avnR hampered

A. baumannii

ATCC17978’s ability to metabolize various nitrogen sources, particularly that of glutamic acid, serine, histidine, aspartic acid, isoleucine and arginine. Taken together our data show that AvnR, the first ANTAR protein described in A. baumannii, affects virulence phenotypes as well as its ability to metabolize nitrogen sources.
From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT Scans
Authors: Li Zhang , Zhong Zheng , Li Yang , Zhang Tianyu , Gao Liangxin , Jin Dakai , Sun Yue , Ye Xianghua , Yu Li , Hu Zheyu , Xiao Jing , Huang Lingyun , Tang Yuling
Published: April 2020

Background

Thick-section CT scanners are more affordable for the developing countries. Considering the widely spread COVID-19, it is of great benefit to develop an automated and accurate system for quantification of COVID-19 associated lung abnormalities using thick-section chest CT images.

Purpose

To develop a fully automated AI system to quantitatively assess the disease severity and disease progression using thick-section chest CT images.

Materials and Methods

In this retrospective study, a deep learning based system was developed to automatically segment and quantify the COVID-19 infected lung regions on thick-section chest CT images. 531 thick-section CT scans from 204 patients diagnosed with COVID-19 were collected from one appointed COVID-19 hospital from 23 January 2020 to 12 February 2020. The lung abnormalities were first segmented by a deep learning model. To assess the disease severity (non-severe or severe) and the progression, two imaging bio-markers were automatically computed, i.e., the portion of infection (POI) and the average infection HU (iHU). The performance of lung abnormality segmentation was examined using Dice coefficient, while the assessment of disease severity and the disease progression were evaluated using the area under the receiver operating characteristic curve (AUC) and the Cohen’s kappa statistic, respectively.

Results

Dice coefficient between the segmentation of the AI system and the manual delineations of two experienced radiologists for the COVID-19 infected lung abnormalities were 0.74±0.28 and 0.76±0.29, respectively, which were close to the inter-observer agreement, i.e., 0.79±0.25. The computed two imaging bio-markers can distinguish between the severe and non-severe stages with an AUC of 0.9680 (p-value< 0.001). Very good agreement (κ = 0.8220) between the AI system and the radiologists were achieved on evaluating the changes of infection volumes.

Conclusions

A deep learning based AI system built on the thick-section CT imaging can accurately quantify the COVID-19 associated lung abnormalities, assess the disease severity and its progressions.

Key Results

A deep learning based AI system was able to accurately segment the infected lung regions by COVID-19 using the thick-section CT scans (Dice coefficient ≥ 0.74).

The computed imaging bio-markers were able to distinguish between the non-severe and severe COVID-19 stages (area under the receiver operating characteristic curve 0.968).

The infection volume changes computed by the AI system was able to assess the COVID-19 progression (Cohen’s kappa 0.8220).

Summary Statement

A deep learning based AI system built on the thick-section CT imaging can accurately quantify the COVID-19 infected lung regions, assess patients disease severity and their disease progressions.
Clinical Characteristics of 20,662 Patients with COVID-19 in mainland China: A Systemic Review and Meta-analysis
Authors: Tang Chong , Zhang Keshi , Wang Wenlong , Pei Zheng , Liu Zheng , Yuan Ping , Guan Zhenpeng , Gu Jin
Published: April 2020

Coronavirus disease 2019 (COVID-19) is a global pandemic and has been widely reported; however, a comprehensive systemic review and meta-analysis has not been conducted. We systematically investigated the clinical characteristics of COVID-19 in mainland China to guide diagnosis and treatment. We searched the PubMed, Embase, Scopus, Web of Science, Cochrane Library, bioRxiv, medRxiv, and SSRN databases for studies related to COVID-19 published or preprinted in English or Chinese from January 1 to March 15, 2020. Clinical studies on COVID-19 performed in mainland China were included. We collected primary outcomes including signs and symptoms, chest CT imaging, laboratory tests, and treatments. Study selection, data extraction, and risk of bias assessment were performed by two independent reviewers. Qualitative and quantitative synthesis was conducted, and random-effects models were applied to pooled estimates. This study is registered with PROSPERO (number CRD42020171606). Of the 3624 records identified, 147 studies (20,662 patients) were analyzed. The mean age of patients with COVID-19 was 49.40 years, 53.45% were male, and 38.52% had at least one comorbidity. Fever and cough were the most common symptoms, followed by fatigue, expectoration, and shortness of breath. Most patients with COVID-19 had abnormal chest CT findings with ground glass opacity (70.70%) or consolidation (29.91%). Laboratory findings shown lymphopenia, increased lactate dehydrogenase, increased infection-related indicators, and fibrinolytic hyperactivity. Antiviral therapy, antibiotic therapy, and corticosteroids were administered to 89.75%, 79.13%, and 35.64% of patients, respectively. Most clinical characteristics of COVID-19 are non-specific. Patients with suspected should be evaluated by virological assays and clinically treated.
ARIMA modelling of predicting COVID-19 infections
Authors: Anne W.Regis , Jeeva S.Carolin
Published: April 2020

The World Health Organization (WHO) Director-General, Dr. Tedros Adhanom Ghebreyesus on March 11, 2020 declared the novel coronavirus (COVID-19) outbreak a global pandemic [4] the reason being the number of cases outside China increased 13-fold and the number of countries with cases increased threefold. In this paper a time series model to predict short-term prediction of the transmission of the exponentially growing COVID-19 time series is modelled and studied. Auto Regressive Integrated Moving Average (ARIMA) model prediction is performed on the number of cumulative cases over a time period and is validated over Akaike information criterion (AIC) statistics.
The involvement of male partners in care: socio determinants of health among women in Prevention of Mother to Child Transmission in Malawi
Authors: Triulzi Isotta , Keiser Olivia , Somerville Claire , Salimu Sangwani , Ciccacci Fausto , Palla Ilaria , Sagno Jean Baptiste , Gondwe Jane , Marazzi Cristina , Orlando Stefano , Palombi Leonardo , Turchetti Giuseppe
Published: April 2020

Introduction

Male partners are rarely present during PMTCT (Prevention-Mother-To-Child-Transmission) services in Sub-Saharan Africa (SSA). The involvement of men is increasingly recognised as an important element of women’s access to care. The study aims to identify the socio-demographic characteristics, HIV-Knowledge, Attitude and Practice (KAP) among women accompanied and not accompanied by the male partners to the facilities.

Method

We included pregnant women enrolled in PMTCT programme between August 2018 and November 2019 in the Southern Region of Malawi. Eligible women were aged 18 years or older, lived with a male partner, enrolled for the first time in four DREAM facilities. We provided a KAP survey to women and their partners attending the facilities. Our primary outcome was to assess and analyse the proportion of women who were accompanied by their partner at least once. We applied descriptive statistics, and logistic regressions to study the association between being accompanied and explanatory variables.

Results

We enrolled 128 HIV-positive women : 82 (64.1%) were accompanied by their male partners and 46 (35.9%) were alone. Women with high level of knowledge on HIV/AIDS are more likely to be accompanied by the male partners (53.7% vs 34.8%,p=0.040). Level of attitude and practice were not different between women accompanied or not. Patients owning a mean of transport were more likely to go alone to facility (OR 4.16, 95% CI 1.02-16.94). Women who travelled more than 90 minutes to get to the facilities (OR 0.10, 95% CI 0.02-0.49) with high HIV-knowledge (OR 0.38, 95% CI 0.16-0.91) are more likely to be accompanied.

Conclusion

Our study showed a good male partner involvement compared to other studies performed in SSA. To our knowledge this is the first study outlining the relationship between male partner involvement in care with socio determinant of health. This is crucial to design and implement effective interventions.
Decline in global transmission rates of COVID-19 through May 6 2020
Authors: Romero-Severson Ethan , Hengartner Nick , Meadors Grant David , Ke Ruian
Published: April 2020

Abstract

We analyzed COVID-19 data through May 6th, 2020 using a partially observed Markov process. Our method uses a hybrid deterministic and stochastic formalism that allows for time variable transmission rates and detection probabilities. The model was fit using iterated particle filtering to case count and death count time series from 55 countries. We found evidence for a shrinking epidemic in 30 of the 55 examined countries. Of those 30 countries, 27 have significant evidence for subcritical transmission rates, although the decline in new cases is relatively slow compared to the initial growth rates. Generally, the transmission rates in Europe were lower than in the Americas and Asia. This suggests that global scale social distancing efforts to slow the spread of COVID-19 are effective although they need to be strengthened in many regions and maintained in others to avoid further resurgence of COVID-19. The slow decline also suggests alternative strategies to control the virus are needed before social distancing efforts are partially relaxed.
Estimating the Cumulative Incidence of COVID-19 in the United States Using Four Complementary Approaches
Authors: Lu Fred S. , Nguyen Andre T. , Link Nicholas B. , Davis Jessica T. , Chinazzi Matteo , Xiong Xinyue , Vespignani Alessandro , Lipsitch Marc , Santillana Mauricio
Published: April 2020

Effectively designing and evaluating public health responses to the ongoing COVID-19 pandemic requires accurate estimation of the prevalence of COVID-19 across the United States (US). Equipment shortages and varying testing capabilities have however hindered the usefulness of the official reported positive COVID-19 case counts. We introduce four complementary approaches to estimate the cumulative incidence of symptomatic COVID-19 in each state in the US as well as Puerto Rico and the District of Columbia, using a combination of excess influenza-like illness reports, COVID-19 test statistics, COVID-19 mortality reports, and a spatially structured epidemic model. Instead of relying on the estimate from a single data source or method that may be biased, we provide multiple estimates, each relying on different assumptions and data sources. Across our four approaches emerges the consistent conclusion that on April 4, 2020, the estimated case count was 5 to 50 times higher than the official positive test counts across the different states. Nationally, our estimates of COVID-19 symptomatic cases as of April 4 have a likely range of 2.2 to 4.9 million, with possibly as many as 8.1 million cases, up to 26 times greater than the cumulative confirmed cases of about 311,000. Extending our method to May 16, 2020, we estimate that cumulative symptomatic incidence ranges from 6.0 to 10.3 million, as opposed to 1.5 million positive test counts. The proposed combination of approaches may prove useful in assessing the burden of COVID-19 during resurgences in the US and other countries with comparable surveillance systems.
An empirical estimate of the infection fatality rate of COVID-19 from the first Italian outbreak
Authors: Rinaldi Gianluca , Paradisi Matteo
Published: April 2020

Background

The coronavirus 2019 (COVID-19) pandemic has been spreading globally for months, yet the infection fatality ratio of the disease is still uncertain. This is partly because of inconsistencies in testing and death reporting standards across countries. We provide estimates which don’t rely on official cases and deaths data but only on population level statistics.

Methods

We collected demographic and death records data from the Italian Institute of Statistics. We focus on the area in Italy that experienced the initial outbreak of COVID-19 and estimated a Bayesian model fitting age-stratified mortality data from 2020 and previous years. We also assessed the sensitivity of our results to alternative assumptions on the proportion of population infected. Based on our estimates we finally studied the heterogeneity in overall lethality across countries.

Findings

We estimate an overall infection fatality rate of 1.31% (95% credible interval [CrI] 0.94 – 1.89), as well as large differences by age, with a low infection fatality rate of 0.05% for under 60 year old (CrI 0 – 0.17) and a substantially higher 4.16% (CrI 3.05 – 5.80) for people above 60 years of age. In our sensitivity analysis, we found that even under extreme assumptions, our method delivered useful information. For instance, even if only 10% of the population were infected, the infection fatality rate would not rise above 0.2% for people under 60. Finally, using data on demographics we show large expected heterogeneity in overall IFR across countries.

Interpretation

Our empirical estimates show a sharp difference in fatality rates between young and old people and rule out overall fatality ratios below 0.5% in populations with more than 30% over 60 years old.
Is there evidence that BCG vaccination has non-specific protective effects for COVID 19 infections or is it an illusion created by lack of testing?
Authors: Shivendu Shivendu , Chakraborty Saurav , Onuchowska Agnieszka , Patidar Ankit , Srivastava Arpit
Published: April 2020

The goal of this paper is to showcase that the COVID-19 disease pattern is evolving and to study the relationship between mandatory BCG policy and caseload/million or death/per million. We analyze seven recent publications on the impact of BCG vaccinations on the development of COVID19 illness and extend presented findings using the latest data from April 10, 2020. We analyze data from 98 countries and we extend existing models by adding the dimension of COVID-19-related testing conducted by the analyzed countries. Similarly to prior studies, we find that COVID-19 attributable case and death incidences across countries share a relationship with a country’s BCG vaccination inclusion in the national immunization program when testing is not taken into consideration. However, this relationship vanishes when we add the dimension of testing. We observe that case and death incidences conditional on testing do not get affected by the countries’ BCG vaccination inclusion in the national immunization program. Therefore, we show that there is no statistical evidence to support the assertion that inclusion of BCG vaccination in national immunization program (NIP) has any impact of COVID 19 infections (cases) or mortality.
Repositioned chloroquine and hydroxychloroquine as antiviral prophylaxis for COVID-19: A protocol for rapid systematic review of randomized controlled trials
Authors: Chang Raymond , Sun Wei-Zen
Published: April 2020

Since the SARS-CoV-2 outbreak rapidly evolved into a pandemic, there is an urgent need for rapid development, identification and confirmation of efficacious antiviral prophylaxis. In this setting, the existing drugs chloroquine (CQ) and hydroxychloroquine (HCQ) which has suggestive evidence of efficacy against SARS-CoV-2 infection and COVID-19 disease has become prime candidates to be repositioned as therapeutic and preventative agents, and a growing number of clinical trials have been registered to study their preventative potential for at-risk populations using a range of dosing schemes and outcome measures. This rapid systematic review protocol aims to provide streamlined and timely synthesis on methodologies and results of randomized controlled trials assessing the efficacy of CQ and HCQ in hopes that this will constructively inform further research as well as public health policy.
Clinical Characteristics of Hospitalized Covid-19 Patients in New York City
Authors: Paranjpe Ishan , Russak Adam J , De Freitas Jessica K , Lala Anuradha , Miotto Riccardo , Vaid Akhil , Johnson Kipp W. , Danieletto Matteo , Golden Eddye , Meyer Dara , Singh Manbir , Somani Sulaiman , Manna Sayan , Nangia Udit , Kapoor Arjun , O’Hagan Ross , O’Reilly Paul F , Huckins Laura M , Glowe Patricia , Kia Arash , Timsina Prem , Freeman Robert M , Levin Matthew A , Jhang Jeffrey , Firpo Adolfo , Kovatch Patricia , Finkelstein Joseph , Aberg Judith A , Bagiella Emilia , Horowitz Carol R , Murphy Barbara , Fayad Zahi A , Narula Jagat , Nestler Eric J , Fuster Valentin , Cordon-Cardo Carlos , Charney Dennis S , Reich David L , Just Allan C , Bottinger Erwin P , Charney Alexander W , Glicksberg Benjamin S , Nadkarni Girish N
Published: April 2020

Background

The coronavirus 2019 (Covid-19) pandemic is a global public health crisis, with over 1.6 million cases and 95,000 deaths worldwide. Data are needed regarding the clinical course of hospitalized patients, particularly in the United States.

Methods

Demographic, clinical, and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed Covid-19 between February 27 and April 2, 2020 were identified through institutional electronic health records. We conducted a descriptive study of patients who had in-hospital mortality or were discharged alive.

Results

A total of 2,199 patients with Covid-19 were hospitalized during the study period. As of April 2nd, 1,121 (51%) patients remained hospitalized, and 1,078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 ug/ml, C-reactive protein was 162 mg/L, and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 ug/ml, C-reactive protein was 79 mg/L, and procalcitonin was 0.09 ng/mL.

Conclusions

This is the largest and most diverse case series of hospitalized patients with Covid-19 in the United States to date. Requirement of intensive care and mortality were high. Patients who died typically had pre-existing conditions and severe perturbations in inflammatory markers.
Improving Precision and Power in Randomized Trials for COVID-19 Treatments Using Covariate Adjustment, for Binary, Ordinal, and Time-to-Event Outcomes
Authors: Benkeser David , Díaz Iván , Luedtke Alex , Segal Jodi , Scharfstein Daniel , Rosenblum Michael
Published: April 2020

Summary

Time is of the essence in evaluating potential drugs and biologics for the treatment and prevention of COVID-19. There are currently over 400 clinical trials (phase 2 and 3) of treatments for COVID-19 registered on clinicaltrials.gov. Covariate adjustment is a statistical analysis method with potential to improve precision and reduce the required sample size for a substantial number of these trials. Though covariate adjustment is recommended by the U.S. Food and Drug Administration and the European Medicines Agency, it is underutilized, especially for the types of outcomes (binary, ordinal and time-to-event) that are common in COVID-19 trials. To demonstrate the potential value added by covariate adjustment in this context, we simulated two-arm, randomized trials comparing a hypothetical COVID-19 treatment versus standard of care, where the primary outcome is binary, ordinal, or time-to-event. Our simulated distributions are derived from two sources: longitudinal data on over 500 patients hospitalized at Weill Cornell Medicine New York Presbyterian Hospital, and a Centers for Disease Control and Prevention (CDC) preliminary description of 2449 cases. We found substantial precision gains from using covariate adjustment-equivalent to 9-21% reductions in the required sample size to achieve a desired power-for a variety of estimands (targets of inference) when the trial sample size was at least 200. We provide an R package and practical recommendations for implementing covariate adjustment. The estimators that we consider are robust to model misspecification.
Analysis of SteraMist ionized hydrogen peroxide technology in the sterilization of N95 respirators and other PPE: a quality improvement study
Authors: Cramer Avilash K. , Plana Deborah , Yang Helen , Carmack Mary M. , Tian Enze , Sinha Michael S. , Krikorian David , Turner David , Mo Jinhan , Li Ju , Gupta Rajiv , Manning Heather , Bourgeois Florence T. , Yu Sherry H. , Sorger Peter K. , LeBoeuf Nicole R.
Published: April 2020

Objective

The COVID-19 pandemic has led to widespread shortages of personal protective equipment (PPE) for healthcare workers, including filtering facepiece respirators (FFRs) such as N95 masks. These masks are normally intended for single use, but their sterilization and subsequent reuse could substantially mitigate a world-wide shortage.

Design

Quality assurance.

Setting

A sealed environment chamber installed in the animal facility of an academic medical center.

Interventions

One to five sterilization cycles using ionized hydrogen peroxide (iHP), generated by SteraMist® equipment (TOMI; Frederick, MD).

Main outcome measures

Personal protective equipment, including five N95 mask models from three manufacturers, were evaluated for efficacy of sterilization following iHP treatment (measured with bacterial spores in standard biological indicator assemblies). Additionally, N95 masks were assessed for their ability to efficiently filter particles down to 0.3µm and for their ability to form an airtight seal using a quantitative fit test. Filtration efficiency was measured using ambient particulate matter at a university lab and an aerosolized NaCl challenge at a National Institute for Occupational Safety and Health (NIOSH) pre-certification laboratory.

Results

The data demonstrate that N95 masks sterilized using SteraMist iHP technology retain function up to five cycles, the maximum number tested to date. Some but not all PPE could also be sterilized using an iHP environmental chamber, but pre-treatment with a handheld iHP generator was required for semi-enclosed surfaces such as respirator hoses.

Conclusions

A typical iHP environment chamber with a volume of ~80 m3 can treat ~7000 masks per day, as well as other items of PPE, making this an effective approach for a busy medical center.
Clinical characteristics of imported and second-generation COVID-19 cases outside Wuhan, China: A multicenter retrospective study
Authors: Shi Puyu , Ren Guoxia , Yang Jun , Li Zhiqiang , Deng Shujiao , Li Miao , Wang Shasha , Xu Xiaofeng , Chen Fuping , Li Yuanjun , Li Chunyan , Yang Xiaohua , xie Zhaofeng , Wu Zhengxia , chen Mingwei
Published: April 2020

Background

The mortality of COVID-19 differs between countries and regions. By now, reports on COVID-19 are largely focused on first-generation cases. This study aimed to clarify the clinical characteristics of imported and second-generation cases.

Methods

This retrospective, multicenter cohort study included 134 confirmed COVID-19 cases from 9 cities outside Wuhan. Epidemiological, clinical and outcome data were extracted from medical records and were compared between severe and non-severe cases. We further profiled the dynamic laboratory findings of some patients.

Results

34.3% of the 134 patients were severe cases, and 11.2% had complications. As of March 7, 2020, 91.8% patients were discharged and one patient (0.7%) died. The median age was 46 years. The median interval from symptom onset to hospital admission was 4.5 (IQR 3-7) days. The median lymphocyte count was 1.1×109/L. Age, lymphocyte count, CRP, ESR, DBIL, LDH, HBDH showed difference between severe and no-severe cases (all P<0.05). Baseline lymphocyte count was higher in the survived patients than in the non-survivor case, and it increased as the condition improved, but declined sharply when death occurred. The IL-6 level displayed a downtrend in survivors, but rose very high in the death case. Pulmonary fibrosis was found on later chest CT images in 51.5% of the pneumonia cases.

Conclusion

Imported and second-generation cases outside Wuhan had a better prognosis than initial cases in Wuhan. Lymphocyte count and IL-6 level could be used for evaluating prognosis. Pulmonary fibrosis as the sequelae of COVID-19 should be taken into account.

Imported and second-generation cases manifested less complications, lower fatality, and higher discharge rate than initial cases, which may be related to the shorter interval from symptom onset to hospital admission, younger age, and higher lymphocyte count of the imported and second-generation patients. Lymphocyte count and IL-6 level could be used as indicators for evaluating prognosis. Pulmonary fibrosis was found in later chest CT images in more than half of the pneumonia cases and should be taken into account.
Spatial analysis of COVID-19 spread in Iran: Insights into geographical and structural transmission determinants at a province level
Authors: Ramírez-Aldana Ricardo , Gomez-Verjan Juan Carlos , Bello-Chavolla Omar Yaxmehen
Published: April 2020

The Islamic Republic of Iran reported its first COVID-19 cases by 19thFebruary 2020, since then it has become one of the most affected countries, with more than 73,000 cases and 4,585 deaths at the date. Spatial modeling could be used to approach an understanding of structural and sociodemographic factors that have impacted COVID-19 spread at a province-level in Iran. In the present paper, we developed a spatial statistical approach to describe how COVID-19 cases are spatially distributed and to identify significant spatial clusters of cases and how the socioeconomic features of Iranian provinces might predict the number of cases. We identified a cluster of provinces with significantly higher rates of COVID-19 cases around Tehran, which indicated that the spread of COVID-19 within Iran was spatially correlated. Urbanized, highly connected provinces with older population structures and higher average temperatures were the most susceptible to present a higher number of COVID-19 cases. Interestingly, literacy is a protective factor that might be directly related to health literacy and compliance with public health measures. These features indicate that policies related to social distancing, protecting older adults, and vulnerable populations, as well as promoting health literacy, might be targeted to reduce SARS-CoV2 spread in Iran. Our approach could be applied to model COVID-19 outbreaks in other countries with similar characteristics or in case of an upturn in COVID-19 within Iran.
A study on control of novel corona-virus (2019- nCoV) disease process by using PID controller
Authors: rad Habibolah Arasteh , Badi Arshia
Published: April 2020

Background

In this paper, the SEIR dynamic model will be used to model the epidemic of coronvirus (2019-nCoV)disease. The SEIR model has been used to model infectious diseases in Malaysia.Then, the spread and control of the disease is simulated applying a PID controller. The results of this study show that the implementation of strict restrictions such as quarantine, social distancing and closure of gathering centers is effective in controlling the disease. Using the results and analyzing them, it was found that early and strict implementation of strict restrictions such as quarantine, social distance and closure of centers with a high percentage of community is very important to control this disease and prevent irreparable economic losses and depreciation of medical staff.

Objective

Modeling the prevalence and control of corona-virus (2019-nCoV)and the impact of government actions using control engineering methods.

Method

In this study, the SEIR dynamic model was used and the common data on the prevalence of the virus in Wuhan, China and Malaysia were used. As an example, the use of control target schemes is simulated in this paper.

Results

The findings of this study use control methods and forecasting in control engineering to provide a clear picture of macro-decisions for different governments in the field of infectious diseases.

Conclusion

Management and control schemes such as travel restrictions, quarantine, social distance and closure of offices, higher education institutions must be implemented immediately to prevent major economic and social losses. The implementation of these restrictions should not be delayed during the outbreak of corona-virus(2019-nCoV) infectious diseases.
The importance of timing of a population level intervention on COVID-19 mortality
Authors: Johnston Jasper S. , Johnston Eloïse S. , Johnston Sebastian L.
Published: April 2020

COVID-19 poses an immense and immediate threat to global public health. Population level interventions (PLIs) impact this threat, with estimable large effects on reducing mortality. Many countries worldwide have currently zero/low mortality and many have yet to implement such PLIs. The importance of timing of PLI implementation on mortality outcomes is poorly understood. We extracted cumulative daily country-specific COVID-19 mortality for France, Germany, Italy, Spain and the UK to examine country-specific mortality trends and found that all five countries experienced COVID-19 mortality epidemics initially of exponential nature. We estimated the magnitude of effect on mortality of the nationwide PLI implemented on day 18 of Italy’s mortality epidemic and assessed the importance of timing of PLI implementation by computing the effect of implementation of a PLI of this magnitude at various times on subsequent mortality. The nationwide PLI in Italy saved an estimated 6,170 lives by day 30 of the Italian epidemic. Implementing a PLI with this effect magnitude in a country of 60 million people on the day of the first death, and on days 7, 10, 14 and 17 thereafter, compared to implementation on day 18, resulted in substantially greater numbers of lives saved. Implementation on day 1 resulted in an additional 3,477 lives saved, 6,955 intensive care unit admissions and 52,162 hospital admissions prevented, beyond that achieved by implementation on day 18. PLI implementation earlier than day 18 substantially enhances benefit. Intervention on the day of the first mortality event in a country achieves the greatest benefit.
Measure what matters: counts of hospitalized patients are a better metric for health system capacity planning for a reopening
Authors: Kashyap Sehj , Gombar Saurabh , Yadlowsky Steve , Callahan Alison , Fries Jason , Pinsky Benjamin A , Shah Nigam H
Published: April 2020

Responding to the COVID-19 pandemic requires accurate forecasting of health system capacity requirements using readily available inputs. We examined whether testing and hospitalization data could help quantify the anticipated burden on the health system given shelter-in-place (SIP) order.

We find a marked slowdown in the hospitalization rate within ten days of SIP even as cases continued to rise. We also find a shift towards younger patients in the age distribution of those testing positive for COVID-19 over the four weeks of SIP. The impact of this shift is a divergence between increasing positive case confirmations and slowing new hospitalizations, both of which affects the demand on health systems.

Without using local hospitalization rates and the age distribution of positive patients, current models are likely to overestimate the resource burden of COVID-19. It is imperative that health systems start using these data to quantify effects of SIP and aid reopening planning.
Weight Sensitivity of Temporal SNR Metrics in multi-echo fMRI
Authors: Liu Thomas T. , Li Bochao , Chen Conan , Fernandez Brice , Yang Baolian , Banerjee Suchandrima
Published: April 2020

Purpose

In multi-echo fMRI (ME-fMRI), various weighting schemes have been proposed for the combination of the data across echoes. Here we introduce a framework that facilitates a deeper understanding of the weight dependence of temporal SNR measures in ME-fMRI.

Theory and Methods

We examine two metrics that have been used to characterize ME-fMRI performance: temporal SNR (tSNR) and multi-echo temporal (metSNR). Both metrics can be described using the generalized Rayleigh quotient (GRQ) and are predicted to be relatively insensitive to the weights when there is a high degree of similarity between a metric-specific matrix in the GRQ numerator and a metricindependent covariance matrix in the GRQ denominator. The application of the GRQ framework to experimental data is demonstrated using a resting-state fMRI dataset acquired with a multi-echo multi-band EPI sequence.

Results

In the example dataset, similarities between the covariance matrix and the metSNR and tSNR numerator matrices are highest in grey matter (GM) and cerebrospinal fluid (CSF) voxels, respectively. For representative GM and CSF voxels that exhibit high matrix similarity values, the metSNR and tSNR values, respectively, are both within 4% of their optimal values across a range of weighting schemes. However, there is a fundamental tradeoff, with a high degree of weight sensitivity in the tSNR and metSNR metrics for the representative GM and CSF voxels, respectively. Geometric insight into the observed weight dependencies is provided through a graphical interpretation of the GRQ.

Conclusion

A GRQ framework can provide insight into the factors that determine the weight sensitivity of tSNR and metSNR measures in ME-fMRI.
A flexible target-specific anti-infection therapeutic platform that can be applied to different microbial species
Authors: Mitsunaga Makoto , Ito Kimihiro , Nishimura Takashi , Miyata Hironori , Mizunoe Yoshimitsu , Kobayashi Hisataka , Iwase Tadayuki
Published: April 2020

The emergence of new microbial pathogens, including drug-resistant strains, complicates treatment, thereby threatening global health. We demonstrated a photoimmuno-antimicrobial strategy (PIAS) that eliminated antibody-targets using a photo-activated anti-pathogen antibody generating mechanical stress that damaged the target’s binding sites. PIAS is effective against many pathogens, including methicillin-resistantStaphylococcus aureus(MRSA), the fungal pathogenCandida albicans, and viral particles irrespective of their species or drug-resistance status. Animal experiments demonstrated that PIAS saved mice from fatal infections; microbiome and histochemical analyses indicated no apparent effect on normal host microflora and tissues in PIAS-treated mice. Resistance to PIAS was not observed during the eight years of this study. As a new type of anti-infection therapy, PIAS may contribute to advances in anti-infection strategies.
RiboDiPA: A Novel tool for differential pattern analysis in Ribo-seq data
Authors: Li Keren , Hope Matthew , Wang Xiaozhong A. , Wang Ji-Ping
Published: April 2020

Abstract

Ribosome profiling (also known as Ribo-seq) has become an important technique to investigate changes in translation across a wide variety of contexts. Ribo-seq data not only provides the abundance of ribosomes bound to transcripts, but also positional information across transcripts that could be indicative of differences in translation dynamics between conditions. While many computational tools exist for the analysis of Ribo-seq data, including those that assess differences in translational efficiency between conditions, no tool currently exists for rigorous test of the pattern differences in ribosome footprint. In this paper we propose a novel approach together with an R package, RiboDiPA, forDifferentialPPatternAnalysis of Ribo-seq data. RiboDiPA allows for quick identification of genes with statistically significant differences in ribosome occupancy patterns for model organisms ranging from yeast to mammals. We show that differential pattern analysis reveals information that is distinct and complimentary to the existing methods that focus on translational efficiency analysis. Using both simulated Ribo-seq footprint data and two benchmark data sets, we illustrate that RiboDiPA can not only uncover meaningful global translational differences between conditions, but also the detailed differential ribosome binding patterns to a single codon resolution.