bluuebunny/crossref_metadata_2025_split huggingface dataset:
Post-Traumatic Stress, Depression, and Quality of Life in Women with Peripartum Cardiomyopathy
Authors: Donnenwirth Jo Ann , Hess Rosanna , Ross Ratchneewan 
Published: April 2020

Abstract

Purpose:
Peripartum cardiomyopathy, a traumatic life-threatening type of heart failure, occurs in the last trimester of pregnancy or shortly after childbirth. Little is known about psychological or emotional conditions women experience with peripartum cardiomyopathy. The purpose of this study was to examine relationships among post-traumatic stress, depression, and quality of life in women with peripartum cardiomyopathy.

Design and Methods:
This cross-sectional, correlational survey study included 28 participants recruited via public notice on Facebook. Participants completed the Horowitz Impact of Events Scale, the Center for Epidemiology Scale–Depression 20, and the Ferrans & Powers Quality of Life Index©–Cardiac Version-IV.

Results:
Post-traumatic stress correlated significantly and positively with depression (r = .809, p < .001). Post-traumatic stress and depression correlated significantly and inversely with quality of life (r = -.455, p = .015), (r = -.544, p = .003), respectively. All participants measured positive for depression. Participants with lower education scored higher on post-traumatic stress and depression, whereas those unemployed or disabled registered a lower quality of life.

Clinical Implications:
Nurses, midwives, and physicians caring for women with cardiomyopathies must be vigilant for evidence of post-traumatic stress, depression, and poor quality of life. Targeted antenatal and postnatal support could be vital to emotional and psychological recovery.
Caring for Critically Ill Adults With Coronavirus Disease 2019 in a PICU: Recommendations by Dual Trained Intensivists*
Authors: Remy Kenneth E. , Verhoef Philip A. , Malone Jay R. , Ruppe Michael D. , Kaselitz Timothy B. , Lodeserto Frank , Hirshberg Eliotte L. , Slonim Anthony , Dezfulian Cameron 
Published: April 2020

Objective:
In the midst of the severe acute respiratory syndrome coronavirus 2 pandemic, which causes coronavirus disease 2019, there is a recognized need to expand critical care services and beds beyond the traditional boundaries. There is considerable concern that widespread infection will result in a surge of critically ill patients that will overwhelm our present adult ICU capacity. In this setting, one proposal to add “surge capacity” has been the use of PICU beds and physicians to care for these critically ill adults.

Design:
Narrative review/perspective.

Setting:
Not applicable.

Patients:
Not applicable.

Interventions:
None.

Measurements and Main Results:
The virus’s high infectivity and prolonged asymptomatic shedding have resulted in an exponential growth in the number of cases in the United States within the past weeks with many (up to 6%) developing acute respiratory distress syndrome mandating critical care services. Coronavirus disease 2019 critical illness appears to be primarily occurring in adults. Although pediatric intensivists are well versed in the care of acute respiratory distress syndrome from viral pneumonia, the care of differing aged adult populations presents some unique challenges. In this statement, a team of adult and pediatric-trained critical care physicians provides guidance on common “adult” issues that may be encountered in the care of these patients and how they can best be managed in a PICU.

Conclusions:
This concise scientific statement includes references to the most recent and relevant guidelines and clinical trials that shape management decisions. The intention is to assist PICUs and intensivists in rapidly preparing for care of adult coronavirus disease 2019 patients should the need arise.
Body Mass Index and Lymphedema Morbidity: Comparison of Obese versus Normal-Weight Patients
Authors: Greene Arin K. , Zurakowski David , Goss Jeremy A. 
Published: April 2020

Background:
Obesity is a risk factor for the development of secondary lymphedema after axillary lymphadenectomy and radiation therapy. The purpose of this study was to determine whether obesity influences the morbidity of lymphedema in patients who have the condition.

Methods:
Two cohorts of patients were compared: group 1, normal weight (body mass index ≤25 kg/m2); and group 2, obese (body mass index ≥30 kg/m2). Inclusion criteria were patients aged 21 years or older with lymphedema confirmed by lymphoscintigraphy. Covariates included age, sex, lymphedema type (primary or secondary), location, comorbidities, lymph node dissection, radiation therapy, lymphoscintigram result, and disease duration. Outcome variables were infection, hospitalization, and degree of limb overgrowth. The cohorts were compared using the Mann-Whitney U test, Fisher’s exact test, and multivariable logistic regression.

Results:
Sixty-seven patients were included: group 1, n = 33; and group 2, n = 34. Disease duration did not differ between groups (p = 0.72). Group 2 was more likely to have an infection (59 percent), hospitalization (47 percent), and moderate or severe overgrowth (79 percent), compared to group 1 (18, 6, and 40 percent, respectively; p < 0.001). Multivariable logistic regression showed that obesity was an independent risk factor for infection (OR, 7.9; 95 percent CI, 2.5 to 26.3; p < 0.001), hospitalization (OR, 30.0; 95 percent CI, 3.6 to 150.8; p < 0.001), and moderate to severe limb overgrowth (OR, 6.7; 95 percent CI, 2.1 to 23.0; p = 0.003).

Conclusions:
Obesity negatively affects patients with established lymphedema. Obese individuals are more likely to have infections, hospitalizations, and larger extremities compared to subjects with a normal body mass index. Patients with lymphedema should be counseled about the negative effects of obesity on their condition.

CLINICAL QUESTION/LEVEL OF EVIDENCE:
Risk, II.
The Preimplantation Psychosocial Evaluation and Prediction of Clinical Outcomes During Mechanical Circulatory Support: What Information Is Most Prognostic?
Authors: Dew Mary Amanda , Hollenberger Jennifer C. , Obregon Laura L. , Hickey Gavin W. , Sciortino Christopher M. , Lockard Kathleen L. , Kunz Nicole M. , Mathier Michael A. , Ramani Ravi N. , Kilic Arman , McNamara Dennis M. , Simon Marc A. , Keebler Mary E. , Kormos Robert L. 
Published: April 2020

Background.Psychosocial evaluations are required for long-term mechanical circulatory support (MCS) candidates, no matter whether MCS will be destination therapy (DT) or a bridge to heart transplantation. Although guidelines specify psychosocial contraindications to MCS, there is no comprehensive examination of which psychosocial evaluation domains are most prognostic for clinical outcomes. We evaluated whether overall psychosocial risk, determined across all psychosocial domains, predicted outcomes, and which specific domains appeared responsible for any effects.Methods.A single-site retrospective analysis was performed for adults receiving MCS between April 2004 and December 2017. Using an established rating system, we coded psychosocial evaluations to identify patients at low, moderate, or high overall risk. We similarly determined risk within each of 10 individual psychosocial domains. Multivariable analyses evaluated whether psychosocial risk predicted clinical decisions about MCS use (DT versus bridge), and postimplantation mortality, transplantation, rehospitalization, MCS pump exchange, and standardly defined adverse medical events (AEs).Results.In 241 MCS recipients, greater overall psychosocial risk increased the likelihood of a DT decision (odds ratio, 1.76;P= 0.017); and postimplantation pump exchange and occurrence of AEs (hazard ratios [HRs] ≥ 1.25;P≤ 0.042). The individual AEs most strongly predicted were cardiac arrhythmias and device malfunctions (HRs ≥ 1.39;P≤ 0.032). The specific psychosocial domains predicting at least 1 study outcome were mental health problem severity, poorer medical adherence, and substance use (odds ratios and HRs ≥ 1.32;P≤ 0.010).Conclusions.The psychosocial evaluation predicts not only clinical decisions about MCS use (DT versus bridge) but important postimplantation outcomes. Strategies to address psychosocial risk factors before or soon after implantation may help to reduce postimplantation clinical risks.
Evaluation of WHO listed COVID-19 qPCR primers and probe in silico with 375 SERS-CoV-2 full genome sequences
Authors: Toms Derek , Li Julang , Cai Hugh Y. 
Published: April 2020

AbstractQuantitative reverse-transcription PCR (qRT-PCR) assays remains the gold standard for detection of the SARS-CoV-2 virus because of its sensitivity and specificity. However, successful design of qRT-PCR assays requires accurate viral genome sequences. With mutations accumulating as the virus is transmitted globally, we sought to compare current assays recommended by the World Health Organization with available SARS-CoV-2 genomic sequences in silico. While most sequences were conserved, there were notable mismatches, particularly in assays developed using early sequences when compared to more recent isolates. We recommend that any assay being evaluated for diagnostic tests be compared with prevalent sequence data from the region of proposed testing and that continued publicly accessible sequence information continue to be provided by the research community.
Resident physician exposure to novel coronavirus (2019-nCoV, SARS-CoV-2) within New York City during exponential phase of COVID-19 pandemic: Report of the New York City Residency Program Directors COVID-19 Research Group
Authors: Breazzano Mark P. , Shen Junchao , Abdelhakim Aliaa H. , Glass Lora R. Dagi , Horowitz Jason D. , Xie Sharon X , Moraes C. Gustavo de , Chen-Plotkin Alice , Chen Royce W. S. 
Published: April 2020

ABSTRACTBackgroundFrom March 2-April 12, 2020, New York City (NYC) experienced exponential growth of the COVID-19 pandemic due to novel coronavirus (SARS-CoV-2). Little is known regarding how physicians have been affected. We aimed to characterize COVID-19 impact on NYC resident physicians.MethodsIRB-exempt and expedited cross-sectional analysis through survey to NYC residency program directors (PDs) April 3–12, 2020, encompassing events from March 2–April 12, 2020.FindingsFrom an estimated 340 residency programs around NYC, recruitment yielded 91 responses, representing 24 specialties and 2,306 residents. 45.1% of programs reported at least one resident with confirmed COVID-19: 101 resident physicians were confirmed COVID-19-positive, with additional 163 residents presumed positive for COVID-19 based on symptoms but awaiting or unable to obtain testing. 56.5% of programs had a resident waiting for, or unable to obtain, COVID-19 testing. Two COVID-19-positive residents were hospitalized, with one in intensive care. Among specialties with >100 residents represented, negative binomial regression indicated that infection risk differed by specialty (p=0.039). Although most programs (80%) reported quarantining a resident, with 16.8% of residents experiencing quarantine, 14.9% of COVID-19-positive residents were not quarantined. 90 programs, encompassing 99.2% of the resident physicians, reported reuse or extended mask use, and 43 programs, encompassing 60.4% of residents, felt that personal protective equipment (PPE) was suboptimal. 65 programs (74.7%) have redeployed residents elsewhere to support COVID-19 efforts.InterpretationMany resident physicians around NYC have been affected by COVID-19 through direct infection, quarantine, or redeployment. Lack of access to testing and concern regarding suboptimal PPE are common among residency programs. Infection risk may differ by specialty.FundingAHA, MPB, RWSC, CGM, LRDG, JDH are supported by NEI Core Grant P30EY019007 and an unrestricted grant from RPB. ACP and JS are supported by the Parker Family Chair. SXX is supported by the University of Pennsylvania.
Infection Density and Epidemic Size of COVID-19 in China outside the Hubei province
Authors: Liu Yukun , Qin Jing , Fan Yan , Zhou Yong , Follmann Dean A. , Huang Chiung-Yu 
Published: April 2020

AbstractThe novel coronavirus (COVID-19) has spread to almost all countries in the world, claiming more than 160,000 lives and sickening more than 2,400,000 people by April 21, 2020. There has been research showing that on average, each infected person spreads the infection to more than two persons. Therefore the majority of the population is at risk of infection if no intervention measures were undertaken. The true size of the COVID-19 epidemic remains unknown, as a significant proportion of infected individuals only exhibit mild symptoms or are even asymptomatic. A timely assessment of the evolving epidemic size is crucial for resource allocation and triage decisions. In this article, we modify the back-calculation algorithm to obtain a lower bound estimate of the number of COVID-19 infected persons in China outside the Hubei province. We estimate the infection density among infected and show that the drastic control measures enforced throughout China following the lockdown of Wuhan City effectively slowed down the spread of the disease in two weeks. Our findings from China are expected to provide guidelines and enlightenment for surveillance and control activities of COVID-19 in other countries around the world.
COVID-19 spreading: a recursive model
Authors: Ilyin Sergey O. 
Published: April 2020

AbstractThis communication describes a recursive mathematical model of the spreading COVID-19 infection, which allows estimating the effectiveness of quarantine measures. This model takes into account the contagiousness of infected people during the incubation period of the disease and the conditionally non-contagiousness of sick people due to their isolation. The model was used to analyze the situation in eight countries and to find the viral transmissibility, which made it possible to give a brief prediction of the COVID-19 spreading.
SARS-CoV-2 Detection Using an Isothermal Amplification Reaction and a Rapid, Inexpensive Protocol for Sample Inactivation and Purification
Authors: Rabe Brian A , Cepko Constance 
Published: April 2020

AbstractAs the current SARS-CoV-2 pandemic spreads, the need for more diagnostic capabilities is great. In order to address this need, we have developed a highly sensitive RT-LAMP assay compatible with current reagents, that utilizes a colorimetric readout in as little as 30 minutes. In addition to this, we have developed an inexpensive pipeline to further increase sensitivity without requiring highly specialized equipment. A rapid inactivation protocol capable of inactivating virions, as well as endogenous nucleases, was also developed to increase sensitivity and sample stability. This protocol, combined with our RT-LAMP assay, has a sensitivity of at least 50 viral RNA copies per microliter in a sample. To further increase the sensitivity, a purification protocol compatible with this inactivation method was developed. The inactivation and purification protocol, combined with our RT-LAMP assay, brings the sensitivity to at least 1 viral RNA copy per microliter in a sample. We hope that this inactivation and purification pipeline, which costs approximately $0.07 per sample and which uses readily available reagents, will increase the availability of SARS-CoV-2 testing, as well as expand the settings in which this testing can be performed.
A simple mathematical model for Coronavirus (COVID-19)
Authors: Melliani Said , Allaoui Abdelati El , Chadli Lalla Saadia 
Published: April 2020

AbstractA novel coronavirus (COVID-19) was identified in Wuhan, China in the end of 2019, it causing an outbreak of viral pneumonia. It caused to the death rate of 4.63% among 571, 678 confirmed cases around the world to the March 28th, 2020. In this brief currentstudy, we will present a simple mathematical model where we show how the probability of successfully getting infected when coming into contact with an infected individual and the per-capita contact rate affect the healthy and infected population with time. The proposed model is used to offer predictions about the behavior of COVID-19 for a shorter period of time.
Variation in COVID-19 Outbreaks at U.S. State and County Levels
Authors: Messner Wolfgang , Payson Sarah E. 
Published: April 2020

BackgroundThe COVID-19 pandemic poses an unprecedented threat to the health and economic prosperity of the world’s population. Yet, some countries or regions within a country appear to be affected in different ways.ObjectivesThis research aims to understand whether the outbreak varies significantly between U.S. states and counties.MethodsA statistical model is estimated using publicly available outbreak data in the U.S., and regional differences are statistically analyzed.ResultsThere is significant variance in outbreak data between U.S. states and counties. At the state level, the outbreak rate follows a normal distribution with an average relative growth rate of 0.197 (doubling time 3.518 days). But there is a low degree of reliability between state-wide and county-specific data reported (ICC = 0.169, p < 0.001), with a bias of 0.070 (standard deviation 0.062) as shown with a Bland-Altman plot.ConclusionsThe results emphasize the need for policy makers to look at the pandemic from the smallest population subdivision possible, so that countermeasures can be implemented, and critical resources provided effectively. Further research is needed to understand the reasons for these regional differences.
Clinical course and risk factors for mortality of COVID-19 patients with pre-existing cirrhosis: A multicenter cohort study
Authors: Qi Xiaolong , Liu Yanna , Fallowfield Jonathan A. , Wang Jitao , Wang Jianwen , Li Xinyu , Shi Jindong , Pan Hongqiu , Zou Shengqiang , Zhang Hongguang , Chen Zhenhuai , Li Fujian , Luo Yan , Mei Mei , Liu Huiling , Wang Zhengyan , Li Jinlin , Yang Hua , Xiang Huihua , Li Xiaodan , Liu Tao , Zheng Ming-Hua , Liu Chuan , Huang Yifei , Xu Dan , Li Xiaoguo , Kang Ning , He Qing , Gu Ye , Zhang Guo , Shao Chuxiao , Liu Dengxiang , Zhang Lin , Li Xun , Kawada Norifumi , Jiang Zicheng , Wang Fengmei , Xiong Bin , Takehara Tetsuo , Rockey Don C. ,   for the COVID-Cirrhosis-CHESS Group
Published: April 2020

SummaryBackgroundPatients with pre-existing cirrhosis are considered at increased risk of severe coronavirus disease 2019 (COVID-19) but the clinical course in these patients has not yet been reported. This study aimed to provide a detailed report of the clinical characteristics and outcomes among COVID-19 patients with pre-existing cirrhosis.MethodsIn this retrospective, multicenter cohort study, we consecutively included all adult inpatients with laboratory-confirmed COVID-19 and pre-existing cirrhosis that had been discharged or had died by 24 March 2020 from 16 designated hospitals in China.Demographic, clinical, laboratory and radiographic findings on admission, treatment, complications during hospitalization and clinical outcomes were collected and compared between survivors and non-survivors.FindingsTwenty-one patients were included consecutively in this study, of whom 16 were cured and 5 died in hospital. Seventeen patients had compensated cirrhosis and hepatitis B virus infection was the most common etiology. Lymphocyte and platelet counts were lower, and direct bilirubin levels were higher in patients who died than those who survived (p= 0·040, 0·032, and 0·006, respectively). Acute respiratory distress syndrome and secondary infection were both the most frequently observed complications. Only one patient developed acute on chronic liver failure. Of the 5 non-survivors, all patients developed acute respiratory distress syndrome and 2 patients progressed to multiple organ dysfunction syndrome.InterpretationLower lymphocyte and platelet counts, and higher direct bilirubin level might represent poor prognostic indicators in SARS-CoV-2-infected patients with pre-existing cirrhosis.
The incubation period of COVID-19 – A rapid systematic review and meta-analysis of observational research
Authors: McAloon Conor G. , Collins Áine B. , Hunt Kevin , Barber Ann , Byrne Andrew W. , Butler Francis , Casey Miriam , Griffin John , Lane Elizabeth , McEvoy David , Wall Patrick , Green Martin J. , O’Grady Luke , More Simon J. 
Published: April 2020

ABSTRACTBackgroundReliable estimates of the incubation period are important for decision making around the control of infectious diseases. Knowledge of the incubation period distribution can be used directly to inform decision-making or as inputs into mathematical models.ObjectivesThe aim of this study was to conduct a rapid systematic review and meta-analysis of estimates of the incubation periods of COVID-19.DesignRapid systematic review and meta-analysis of observational researchData sourcesPublications on the electronic databases PubMed, Google Scholar, MedRxiv and BioRxiv were searched. The search was not limited to peer-reviewed published data, but also included pre-print articles.Study appraisal and synthesis methodsStudies were selected for meta-analysis if they reported either the parameters and confidence intervals of the distributions fit to the data, or sufficient information to facilitate calculation of those values. The majority of studies suitable for inclusion in the final analysis modelled incubation period as a lognormal distribution. We conducted a random effects meta-analysis of the parameters of this distribution.ResultsThe incubation period distribution may be modelled with a lognormal distribution with pooled mu and sigma parameters of 1.63 (1.51, 1.75) and 0.50 (0.45, 0.55) respectively. The corresponding mean was 5.8 (5.01, 6.69 days). It should be noted that uncertainty increases towards the tail of the distribution: the pooled parameter estimates resulted in a median incubation period of 5.1 (4.5, 5.8) days, whereas the 95thpercentile was 11.6 (9.5, 14.2) days.Conclusions and implicationsThe choice of which parameter values are adopted will depend on how the information is used, the associated risks and the perceived consequences of decisions to be taken. These recommendations will need to be revisited once further relevant information becomes available. Finally, we present an RShiny app that facilitates updating these estimates as new data become available.ARTICLE SUMMARYStrengths and limitations of this studyThis study provides a pooled estimate of the distribution of incubation periods which may be used in subsequent modelling studies or to inform decision-makingThis estimate will need to be revisited as subsequent data become available. We present an RShiny app to allow the meta-analysis to be updated with new estimates