Corpus overview


Overview

MeSH Disease

Human Phenotype

Pneumonia (5)

Cough (2)

Fever (1)

Myalgia (1)

Fatigue (1)


Transmission

Seroprevalence
    displaying 1 - 10 records in total 35
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    Previous and active tuberculosis MESHD in COVID-19 patients increases risk of death MESHD and prolongs recovery

    Authors: Karla Therese L. Sy; Nel Jason Ladiao Haw; Jhanna Uy

    doi:10.1101/2020.07.22.20154575 Date: 2020-07-26 Source: medRxiv

    Background: There is a growing literature on the association of SARS-CoV-2 and other chronic conditions, such as noncommunicable diseases MESHD. However, little is known about the impact of coinfection MESHD with tuberculosis MESHD. We aimed to compare the risk of death MESHD and recovery, as well as time-to- death MESHD and time-to-recovery TRANS, in COVID-19 patients with and without TB. Methods: We created a 4:1 propensity score matched sample of COVID-19 patients without and with tuberculosis MESHD, using COVID-19 surveillance data in the Philippines. We conducted a longitudinal cohort analysis of matched COVID-19 patients as of May 17, 2020, following them until June 15, 2020. The primary analysis estimated the risk ratios of death MESHD and recovery in patients with and without tuberculosis MESHD. Kaplan-Meier curves described time-to- death MESHD and time-to-recovery TRANS stratified by tuberculosis MESHD status, and differences in survival were assessed using the Wilcoxon test. Results: The risk of death MESHD in COVID-19 patients with tuberculosis MESHD was 2.17 times higher than in those without (95% CI: 1.40-3.37). The risk of recovery in COVID-19 patients with tuberculosis MESHD was 25% lower than in those without (RR=0.75, 95% CI 0.63-0.91). Similarly, time-to- death MESHD was significantly shorter (p=0.0031) and time-to-recovery TRANS significantly longer in patients with tuberculosis MESHD (p=0.0046). Conclusions: Our findings show that coinfection MESHD with tuberculosis MESHD increased morbidity and mortality in COVID-19 patients. Our findings highlight the need to prioritize routine and testing services for tuberculosis MESHD, although health systems are disrupted by the heavy burden of the SARS-CoV-2 pandemic.

    Effect of Ribavirin on Recovery Time TRANS in COVID-19 Patients: A Real-world Retrospective Cohort Study

    Authors: Yuanlong Hu; Xue Zhu; Ning Shen; Xinhua Jia; Xingcai Zhang; Jian Han; Miao Yue; Chengmin Yuan; Zhanjun Qiu; Huijie Ma; Hui Li; Yingying Liu; Wei Zhang

    doi:10.21203/rs.3.rs-47356/v1 Date: 2020-07-22 Source: ResearchSquare

    Background: Up to now, there is still no specific drug against COVID-19. However, Ribavirin may bring clinical benefits to COVID-19 patients.Methods: This study was designed as a real-world retrospective cohort study based on electronic medical record (EMR), and linear regression model was used to evaluate the effect of Ribavirin on recovery time TRANS.Results: 342 patients were enrolled in this study. Both unadjusted and unadjusted models showed that interferon or Lopinavir-Ritonavir combined with Ribavirin could shorten the recovery time TRANS of patients, which was evident in all subgroups considered except the severe subgroup and after fine adjustments.Conclusion: This study shows that interferon or Lopinavir-Ritonavir combined with Ribavirin can shorten the recovery time TRANS of patients with non-severe COVID-19.

    Time between Symptom Onset TRANS, Hospitalisation and Recovery or Death MESHD: a Statistical Analysis of Different Time-Delay Distributions in Belgian COVID-19 Patients

    Authors: Christel Faes; Steven Abrams; Dominique Van Beckhoven; Geert Meyfroidt; Erika Vlieghe; Niel Hens

    doi:10.1101/2020.07.18.20156307 Date: 2020-07-21 Source: medRxiv

    Background There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. Different age-groups TRANS are also impacted differently. However, it remains unclear whether the time from symptom onset TRANS to diagnosis and hospitalization or the length of stay in the hospital is different for different age groups TRANS, gender TRANS, residence place or whether it is time dependent. Methods Sciensano, the Belgian Scientific Institute of Public Health, collected information on hospitalized patients with COVID-19 hospital admissions from 114 participating hospitals in Belgium. Between March 14, 2020 and June 12, 2020, a total of 14,618 COVID-19 patients were registered. The time of symptom onset TRANS, time of COVID-19 diagnosis, time of hospitalization, time of recovery TRANS or death MESHD, and length of stay in intensive care are recorded. The distributions of these different event times for different age groups TRANS are estimated accounting for interval censoring and right truncation in the observed data. Results The truncated and interval-censored Weibull regression model is the best model for the time between symptom onset TRANS and diagnosis/hospitalization best, whereas the length of stay in hospital is best described by a truncated and interval-censored lognormal regression model. Conclusions The time between symptom onset TRANS and hospitalization and between symptom onset TRANS and diagnosis are very similar, with median length between symptom onset TRANS and hospitalization ranging between 3 and 10.4 days, depending on the age TRANS of the patient and whether or not the patient lives in a nursing home. Patients coming from a nursing home facility have a slightly prolonged time between symptom onset TRANS and hospitalization (i.e., 2 days). The longest delay time is observed in the age group TRANS 20-60 years old. The time from symptom onset TRANS to diagnosis follows the same trend, but on average is one day longer as compared to the time to hospitalization. The median length of stay in hospital varies between 3 and 10.4 days, with the length of stay increasing with age TRANS. However, a difference is observed between patients that recover and patients that die. While the hospital length of stay for patients that recover increases with age TRANS, we observe the longest time between hospitalization and death MESHD in the age group TRANS 20-60. And, while the hospital length of stay for patients that recover is shorter for patients living in a nursing home, the time from hospitalization to death MESHD is longer for these patients. But, over the course of the first wave, the length of stay has decreased, with a decrease in median length of stay of around 2 days.

    A New Mathematical Approach for the Estimation of epidemic Model Parameters with Demonstration on COVID-19 Pandemic in Libya

    Authors: Mohamed E Saleh; Zeinab Elmehdi Saleh

    doi:10.1101/2020.07.19.20157115 Date: 2020-07-21 Source: medRxiv

    Background: The SEIR model or a variation of it is commonly used to study epidemic spread and make predictions on how it evolves. It is used to guide officials in their response to an epidemic. This research demonstrates an effective and simple approach that estimates the parameters of any variations of the SEIR model. This new technique will be demonstrated on the spread of COVID-19 in Libya. Methods: A five compartmental epidemic model is used to model the COVID-19 pandemic in Libya. Two sets of data are needed to evaluate the model parameters, the cumulative number of symptomatic cases and the total number of active cases. This data along with the assumption that the cumulative number of symptomatic cases grows exponentially, to determine most of the model parameters. Results: Libya epidemic start-date was estimated as t_o=-18.5 days, corresponding to May 5th. We mathematically demonstrated that the number of active cases follows two competing exponential distributions: a positive exponential function, measuring how many new cases are added, and a negative exponential function, measuring how many cases recovered. From this distribution we showed that the average recovery time TRANS is 48 days, and the incubation period TRANS is 15.2 days. Finally, the productive number was estimated as R0 TRANS = 7.6. Conclusions: With only the cumulative number of cases and the total number of active cases of COVID19, several important SEIR model parameters can be measured effectively. This approach can be applied for any infectious disease MESHD epidemic anywhere in the world.

    Longitudinal symptom dynamics of COVID-19 infection MESHD in primary care

    Authors: Barak Mizrahi; Smadar Shilo; Hagai Rossman; Nir Kalkstein; Karni Marcus; Yael Barer; Ayya Keshet; Na'ama Shamir-Stein; Varda Shalev; Anat Ekka Zohar; Gabriel Chodick; Eran Segal

    doi:10.1101/2020.07.13.20151795 Date: 2020-07-14 Source: medRxiv

    Objective : Data regarding the clinical characteristics of COVID-19 infection MESHD is rapidly accumulating. However, most studies thus far are based on hospitalized patients and lack longitudinal follow up. As the majority of COVID-19 cases are not hospitalized, prospective studies of symptoms in the population presenting to primary care are needed. Here, we assess the longitudinal dynamic of clinical symptoms in non-hospitalized individuals prior to and throughout the diagnosis of SARS-CoV-2 infection MESHD. Design Data on symptoms were extracted from electronic health records (EHR) consisting of both results of PCR tests and symptoms recorded by primary care physicians, and linked longitudinal self reported symptoms. Setting The second largest Health Maintenance Organization in Israel , Maccabi Health Services Participants From 1/3/2020 to 07/06/2020, information on symptoms from either surveys or primary care visits was available for 206,377 individuals, including 2,471 who tested positive for COVID-19. Main Outcomes Longitudinal prevalence SERO of clinical symptoms in COVID-19 infection MESHD diagnosed by PCR testing for SARS-CoV-2 from nasopharyngeal swabs. Results: In adults TRANS, the most prevalent symptoms recorded in EHR were cough MESHD cough HP (11.6%), fever MESHD fever HP (10.3%), and myalgia MESHD myalgia HP (7.7%) and the most prevalent self-reported symptoms were cough MESHD cough HP (21%), fatigue MESHD fatigue HP (19%) and rhinorrhea HP and/or nasal congestion (17%). In children TRANS, the most prevalent symptoms recorded in the EHR were fever MESHD fever HP (7%), cough MESHD cough HP (5.5%) and abdominal pain MESHD abdominal pain HP (2.4%) . Emotional disturbances were documented in 15.9% of the positive adults TRANS and 4.2% of the children TRANS. Loss of taste and smell, either self-reported or documented by a physician, 3 weeks prior to testing, were the most discriminative symptoms in adults TRANS (OR =11.18 and OR=5.47 respectively). Additional symptoms included self reported headache MESHD headache HP (OR = 2.03) and fatigue MESHD fatigue HP (OR = 1.73) and a documentation of syncope MESHD syncope HP, rhinorrhea HP (OR = 2.09 for both ) and fever MESHD fever HP (OR= 1.62 ) by a physician. Mean time to recovery TRANS was 23.5 +- 9.9 days. Children TRANS had a significantly shorter disease MESHD duration (21.7 +- 8.8 days, p-value=0.01). Several symptoms, including fatigue MESHD fatigue HP, myalgia MESHD myalgia HP, runny nose and shortness of breath were reported weeks after recovery. Conclusions As the COVID-19 pandemic progresses rapidly worldwide, obtaining accurate information on symptoms and their progression is of essence. Our study shed light on the full clinical spectrum of symptoms experienced by infected individuals in primary care, and may alert physicians for the possibility of COVID-19 infection MESHD.

    Auxora Versus Standard of Care For The Treatment of Severe or Critical COVID-19 Pneumonia MESHD Pneumonia HP: Results From A Randomized Controlled Trial

    Authors: Joseph Miller; Charles Bruen; Michael Schnaus; Jeffrey Zhang; Sadia Ali; April Lind; Zachary Stoecker; Kenneth Stauderman; Sudarshan Hebbar

    doi:10.21203/rs.3.rs-42600/v2 Date: 2020-07-14 Source: ResearchSquare

    BACKGROUND: Calcium release-activated calcium (CRAC) channel inhibitors stabilize the pulmonary endothelium and block proinflammatory cytokine release, potentially mitigating respiratory complications observed in patients with COVID-19. This study aimed to investigate the safety and efficacy of Auxora, a novel, intravenously administered CRAC channel inhibitor, in adults TRANS with severe or critical COVID-19 pneumonia METHODS: A randomized, controlled, open-label study of Auxora was conducted in adults TRANS with severe or critical COVID-19 pneumonia MESHD pneumonia HP. Patients were randomized 2:1 to receive three doses of once-daily Auxora versus standard of care (SOC) alone. The primary objective was to assess safety and tolerability of Auxora. Following FDA guidance, study enrollment was halted early to allow for transition to a randomized, blinded, placebo-controlled study. RESULTS: In total, 17 patients with severe and three with critical COVID-19 pneumonia MESHD pneumonia HP were randomized to Auxora and nine with severe and one with critical COVID-19 pneumonia MESHD pneumonia HP to SOC. Similar proportions of patients receiving Auxora and SOC experienced ≥1 adverse event (75% versus 80%, respectively). Fewer patients receiving Auxora experienced serious adverse events versus SOC (30% versus 50%, respectively). Two patients (10%) receiving Auxora and two (20%) receiving SOC died in the 30 days after randomization. Among patients with severe COVID-19 pneumonia MESHD pneumonia HP, median time to recovery TRANS with Auxora was five days versus 12 days with SOC; recovery rate ratio was 1.87 (95%CI, 0.72, 4.89). Invasive mechanical ventilation was needed in 18% of patients with severe COVID-19 pneumonia MESHD pneumonia HP receiving Auxora versus 50% receiving SOC (absolute risk reduction=32%; 95%CI, -0.07, 0.71). Outcomes measured by an 8-point ordinal scale were significantly improved for patients receiving Auxora, especially for patients with a baseline PaO2/FiO2=101-200. CONCLUSIONS: Auxora demonstrated a favorable safety profile in patients with severe or critical COVID-19 pneumonia MESHD pneumonia HP and improved outcomes in patients with severe COVID-19 pneumonia MESHD pneumonia HP. These results, however, are limited by the open-label study design and small patient population resulting from early cessation of enrollment in response to regulatory guidance. The impact of Auxora on respiratory complications in patients with severe COVID-19 pneumonia MESHD pneumonia HP will be further assessed in a planned randomized, blinded, placebo-controlled study. Trial registration: ClinicalTrials.gov, NCT04345614. Submitted 7April2020 - https://clinicaltrials.gov/ct2/show/NCT04345614

    Hospitalization dynamics during the first COVID-19 pandemic wave: SIR modelling compared to Belgium, France, Italy, Switzerland and New York City data

    Authors: Gregory Kozyreff

    id:2007.01411v1 Date: 2020-07-02 Source: arXiv

    Using the classical Susceptible-Infected-Recovered epidemiological model, an analytical formula is derived for the number of beds occupied by Covid-19 patients. The analytical curve is fitted to data in Belgium, France, New York City and Switzerland, with a correlation coefficient exceeding 98.8%, suggesting that finer models are unnecessary with such macroscopic data. The fitting is used to extract estimates of the doubling time in the ascending phase of the epidemic, the mean recovery time TRANS and, for those who require medical intervention, the mean hospitalization time. Large variations can be observed among different outbreaks.

    Characteristics and Recovery Prognosis Factors Among COVID-2019 Infected Cases: A Tunisian Nationwide Analysis

    Authors: Chahida Harizi

    doi:10.21203/rs.3.rs-38903/v1 Date: 2020-06-29 Source: ResearchSquare

    Background: The outbreak of coronavirus disease MESHD (COVID-19) continues to constitute a public health of international concern. Few data are available on the duration and prognosis factors for recovery. We aimed to study the recovery time TRANS among a Tunisian cohort of COVID-19 confirmed patients and identify its prognosis factors.Methods: A retrospective and national study was conducted from March 2 to May 8, 2020, recruiting all patients who were diagnosed with COVID-19, by RT-PCR methods, in Tunisia.  Data were collected via phone call interview. Kaplan-Meir Methods and Cox proportional hazards regression models were, respectively, used to study the recovery time TRANS and estimate its prognosis factors.Results: 1030 patients with COVID-19 ( aged TRANS 43.2 ± 18.2 years, 526 female TRANS (51.1%)) were enrolled. Among them 174 (16.9%) were healthcare professionals. Out of 173 patients (17.8%) admitted to the hospital, 47 were admitted in an intensive care unit. Among those who didn’t require specialized care, 55.5% were self-isolated at home, while the rest were in specialized centers. Almost ¾ of the patients were symptomatic. A total of 634 (61.6 %) patients have recovered and 45 (4.4 %) patients died. The median duration of illness was estimated to be 31 days (95% CI: [29 - 32]). Older age TRANS (HR=0.66, CI:[ 0.46-0.96], P=0.031) and symptoms (HR=0.61, CI:[ 0.43-0.81], P=0.021) were independently associated with a delay in recovery time TRANS. Being a healthcare professional (HR=1.52, CI :[1.10-2.08], P=0.011) and patients in home isolation compared to isolation centers (HR=2.99, CI :[1.85-4.83], P<10¯³) were independently associated with faster recovery time TRANS. Conclusion: the duration of illness was estimated to be one month. However, this long estimated duration of illness may not equate to infectiousness. A particular attention must to be paid to elderly TRANS and symptomatic patients with closer monitoring.

    Mathematical modeling explains differential SARS CoV-2 kinetics in lung and nasal passages in remdesivir treated rhesus macaques

    Authors: Ashish Goyal; Elizabeth R Duke; Erwing Fabian Cardozo-Ojeda; Joshua T Schiffer

    doi:10.1101/2020.06.21.163550 Date: 2020-06-22 Source: bioRxiv

    Remdesivir was recently demonstrated to decrease recovery time TRANS in hospitalized patients with SARS-CoV-2 infection MESHD. In rhesus macaques, early initiation of remdesivir therapy prevented pneumonia MESHD pneumonia HP and lowered viral loads in the lung, but viral loads increased in the nasal passages five days after therapy. We developed mathematical models to explain these results. We identified that 1) drug potency is slightly higher in nasal passages than in lungs, 2) viral load decrease in lungs relative to nasal passages during therapy because of infection MESHD-dependent generation of refractory cells in the lung, 3) incomplete drug potency in the lung that decreases viral loads even slightly may allow substantially less lung damage, and 4) increases in nasal viral load may occur due to a slight blunting of peak viral load and subsequent decrease of the intensity of the innate immune response, as well as a lack of refractory cells. We also hypothesize that direct inoculation of the trachea in rhesus macaques may not recapitulate natural infection MESHD as lung damage occurs more abruptly in this model than in human infection MESHD. We demonstrate with sensitivity SERO analysis that a drug with higher potency could completely suppress viral replication and lower viral loads abruptly in the nasal passages as well as the lung. One Sentence SummaryWe developed a mathematical model to explain why remdesivir has a greater antiviral effect on SARS CoV-2 in lung versus nasal passages in rhesus macaques.

    Statistical Issues and Lessons Learned from COVID-19 Clinical Trials with Lopinavir-Ritonavir and Remdesivir

    Authors: Guosheng Yin; Chenyang Zhang; Huaqing Jin

    doi:10.1101/2020.06.17.20133702 Date: 2020-06-19 Source: medRxiv

    Background: Since the outbreak of the novel coronavirus disease MESHD 2019 (COVID-19) in December 2019, it has rapidly spread in more than 200 countries or territories with over 8 million confirmed cases TRANS and 440,000 deaths MESHD by June 17, 2020. Recently, three randomized clinical trials on COVID-19 treatments were completed, one for lopinavir-ritonavir and two for remdesivir. One trial reported that remdesivir was superior to placebo in shortening the time to recovery TRANS, while the other two showed no benefit of the treatment under investigation. However, several statistical issues in the original design and analysis of the three trials are identified, which might shed doubts on their findings and the conclusions should be evaluated with cautions. Objective: From statistical perspectives, we identify several issues in the design and analysis of three COVID-19 trials and reanalyze the data from the cumulative incidence curves in the three trials using more appropriate statistical methods. Methods: The lopinavir-ritonavir trial enrolled 39 additional patients due to insignificant results after the sample size reached the planned number, which led to inflation of the type I error rate. The remdesivir trial of Wang et al. failed to reach the planned sample size due to a lack of eligible patients, while the bootstrap method was used to predict the quantity of clinical interest conditionally and unconditionally if the trial had continued to reach the originally planned sample size. Moreover, we used a terminal (or cure) rate model and a model-free metric known as the restricted mean survival time or the restricted mean time to improvement (RMTI) in this context to analyze the reconstructed data due to the existence of death MESHD as competing risk and a terminal event. The remdesivir trial of Beigel et al. reported the median recovery time TRANS of the remdesivir and placebo groups and the rate ratio for recovery, while both quantities depend on a particular time point representing local information. We reanalyzed the data to report other percentiles of the time to recovery TRANS and adopted the bootstrap method and permutation test to construct the confidence intervals as well as the P values. The restricted mean time to recovery TRANS (RMTR) was also computed as a global and robust measure for efficacy. Results: For the lopinavir-ritonavir trial, with the increase of sample size from 160 to 199, the type I error rate was inflated from 0.05 to 0.071. The difference of terminal rates was -8.74% (95% CI [-21.04, 3.55]; P=.16) and the hazards ratio (HR) adjusted for terminal rates was 1.05 (95% CI [0.78, 1.42]; P=.74), indicating no significant difference. The difference of RMTIs between the two groups evaluated at day 28 was -1.67 days (95% CI [-3.62, 0.28]; P=.09) in favor of lopinavir-ritonavir but not statistically significant. For the remdesivir trial of Wang et al., the difference of terminal rates was -0.89% (95% CI [-2.84, 1.06]; P=.19) and the HR adjusted for terminal rates was 0.92 (95% CI [0.63, 1.35]; P=.67). The difference of RMTIs at day 28 was -0.89 day (95% CI [-2.84, 1.06]; P=.37). The planned sample size was 453, yet only 236 patients were enrolled. The conditional prediction shows that the HR estimates would reach statistical significance if the target sample size had been maintained, and both conditional and unconditional prediction delivered significant HR results if the trial had continued to double the target sample size. For the remdesivir trial of Beigel et al., the difference of RMTRs between the remdesivir and placebo groups up to day 30 was -2.7 days (95% CI [-4.0, -1.2]; P

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MeSH Disease
Human Phenotype
Transmission
Seroprevalence


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