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1.
IEEE J Biomed Health Inform ; 26(6): 2458-2468, 2022 Jun.
Article in English | MEDLINE | ID: covidwho-1878966

ABSTRACT

Despite efforts made to model and predict COVID-19 transmission, large predictive uncertainty remains. Failure to understand the dynamics of the nonlinear pandemic prediction model is an important reason. To this end, local and multiple global sensitivity analysis approaches are synthetically applied to analyze the sensitivities of parameters and initial state variables and community size (N) in susceptible-infected-recovered (SIR) and its variant susceptible-exposed-infected-recovered (SEIR) models and basic reproduction number (R0), aiming to provide prior information for parameter estimation and suggestions for COVID-19 prevention and control measures. We found that N influences both the maximum number of actively infected cases and the date on which the maximum number of actively infected cases is reached. The high effect of N on maximum actively infected cases and peak date suggests the necessity of isolating the infected cases in a small community. The protection rate and average quarantined time are most sensitive to the infected populations, with a summation of their first-order sensitivity indices greater than 0.585, and their interactions are also substantial, being 0.389 and 0.334, respectively. The high sensitivities and interaction between the protection rate and average quarantined time suggest that protection and isolation measures should always be implemented in conjunction and started as early as possible. These findings provide insights into the predictability of the pandemic models by estimating influential parameters and suggest how to effectively prevent and control epidemic transmission.


Subject(s)
COVID-19 , Pandemics , Basic Reproduction Number , COVID-19/epidemiology , Humans , Quarantine , SARS-CoV-2
2.
Interact Cardiovasc Thorac Surg ; 35(1)2022 06 15.
Article in English | MEDLINE | ID: covidwho-1873917

ABSTRACT

Lung transplants are still limited by the shortage of suitable donor lungs, especially during the coronavirus disease 2019 pandemic. A heterotopic lung transplant (HLTx), as a flexible surgical procedure, can maximize the potential of donor lungs in an emergency, but its widespread use is hindered by difficulties in anastomosis and paucity of outcome data. We performed a retrospective review of 4 patients, each of whom received an HLTxs over 1 year, including 1 left-to-right single HLTx, 2 right-to-left single HLTxs and 1 lobar HLTx (right upper lobe-to-left). The median recipient age was 58.5 years (46-68); 3 patients were male. The postoperative hospital stay was 33 days (30-42). One recipient lived for 10 years and died of bronchiolitis obliterans syndrome; the others were alive with no major morbidity at 12 to 31 months after the operation with a 1-year survival of 100%. The follow-up chest images showed that transplanted lungs could be inflated well and adapted morphologically to fill the thoracic cavity in the short and long term. This study demonstrates that an HLTx is a feasible alternative to a conventional lung transplant in emergency cases and could be considered in selected patients at advanced medical centres.


Subject(s)
Bronchiolitis Obliterans , COVID-19 , Lung Transplantation , Tissue and Organ Procurement , Aged , Female , Humans , Lung , Lung Transplantation/adverse effects , Lung Transplantation/methods , Male , Middle Aged , Retrospective Studies
3.
Zool Res ; 43(3): 457-468, 2022 May 18.
Article in English | MEDLINE | ID: covidwho-1836354

ABSTRACT

COVID-19 is an immune-mediated inflammatory disease caused by SARS-CoV-2 infection, the combination of anti-inflammatory and antiviral therapy is predicted to provide clinical benefits. We recently demonstrated that mast cells (MCs) are an essential mediator of SARS-CoV-2-initiated hyperinflammation. We also showed that spike protein-induced MC degranulation initiates alveolar epithelial inflammation for barrier disruption and suggested an off-label use of antihistamines as MC stabilizers to block degranulation and consequently suppress inflammation and prevent lung injury. In this study, we emphasized the essential role of MCs in SARS-CoV-2-induced lung lesions in vivo, and demonstrated the benefits of co-administration of antihistamines and antiviral drug remdesivir in SARS-CoV-2-infected mice. Specifically, SARS-CoV-2 spike protein-induced MC degranulation resulted in alveolar-capillary injury, while pretreatment of pulmonary microvascular endothelial cells with antihistamines prevented adhesion junction disruption; predictably, the combination of antiviral drug remdesivir with the antihistamine loratadine, a histamine receptor 1 (HR1) antagonist, dampened viral replication and inflammation, thereby greatly reducing lung injury. Our findings emphasize the crucial role of MCs in SARS-CoV-2-induced inflammation and lung injury and provide a feasible combination antiviral and anti-inflammatory therapy for COVID-19 treatment.


Subject(s)
COVID-19 , Lung Injury , Rodent Diseases , Adenosine Monophosphate/analogs & derivatives , Alanine/analogs & derivatives , Animals , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , COVID-19/drug therapy , COVID-19/veterinary , Endothelial Cells , Histamine Antagonists/therapeutic use , Inflammation/drug therapy , Inflammation/etiology , Inflammation/veterinary , Lung Injury/drug therapy , Lung Injury/veterinary , Mice , Rodent Diseases/drug therapy , SARS-CoV-2 , Spike Glycoprotein, Coronavirus
4.
Front Mol Biosci ; 7: 569414, 2020.
Article in English | MEDLINE | ID: covidwho-1793002

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19) was first detected in patients with pneumonia in December 2019 in China and it spread rapidly to the rest of the world becoming a global pandemic. Several observational studies have reported that cancer is a risk factor for COVID-19. On the other hand, ACE2, a receptor for the SARS-CoV-2 virus, was found to be aberrantly expressed in many tumors. However, the characterization of aberrant ACE2 expression in malignant tumors has not been elucidated. Here, we conducted a systematic analysis of the ACE2 expression profile across 31 types of tumors. METHODS: Distribution of ACE2 expression was analyzed using the GTEx, CCLE, TCGA pan-cancer databases. We evaluated the effect of ACE2 on clinical prognosis using the Kaplan-Meier survival plot and COX regression analysis. Correlation between ACE2 and immune infiltration levels was investigated in various cancer types. Additionally, the correlation between ACE2 and immune neoantigen, TMB, microsatellite instability, Mismatch Repair Genes (MMRs), HLA gene members, and DNA Methyltransferase (DNMT) was investigated. The frequency of ACE2 gene mutation in various tumors was analyzed. Functional enrichment analysis was conducted in various cancer types using the GSEA method. RESULTS: In normal tissues, ACE2 was highly expressed in almost all 31 organs tested. In cancer cell lines, the expression level of ACE2 was low to medium. Although aberrant expression was observed in most cancer types, high expression of ACE2 was not linked to OS, DFS, RFS, and DFI in most tumors in TCGA pan-cancer data. We found that ACE2 expression was significantly correlated with the infiltrating levels of macrophages and dendritic cells, CD4+ T cells, CD8+ T cells, and B cells in multiple tumors. A positive correlation between ACE2 expression and immune neoantigen, TMB, and microsatellite instability was found in multiple cancers. GSEA analysis which was carried out to determine the effect of ACE2 on tumors indicated that several cancer-associated pathways and immune-related pathways were hyperactivated in the high ACE2 expression group of most tumors. CONCLUSION: These findings suggest that ACE2 is not correlated with prognosis in most cancer types. However, elevated ACE2 is significantly correlated with immune infiltrating levels, including those of CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and DCs in multiple cancers, especially in lung and breast cancer patients. These findings suggest that ACE2 may affect the tumor environment in cancer patients with COVID-19.

6.
IEEE Transactions on Automation Science & Engineering ; 19(2):586-602, 2022.
Article in English | Academic Search Complete | ID: covidwho-1788780

ABSTRACT

During the COVID-19 pandemic, communities faced two conflicting objectives: 1) minimizing infections among vulnerable populations with higher risk for severe illness and 2) enabling reopening to revive American livelihoods. The U.S. pandemic strategy myopically considered one objective at a time, with lockdowns that addressed the former, but was detrimental to the latter, and phased reopening that pursued the latter, but lost control over the former. How could we prioritize interventions to simultaneously minimize cases of severe illness and fatalities while reopening? A team of researchers anchored by the Center on Stochastic Modeling, Optimization, & Statistics (COSMOS), The University of Texas at Arlington, has formulated a computationally efficient optimization framework, referred to as COSMOS COVID-19 Linear Programming (CC19LP), to study the delicate balance between the expected fatality rate due to cases of severe illness and the level of normalcy in the community. The key to the CC19LP framework is a focus on “key contacts” that separate individuals at higher risk from the rest of the population. CC19LP minimizes expected fatalities by optimizing the use of available interventions, namely, COVID-19 testing, personal protective equipment (PPE), COVID-19 vaccines, and social precautions, such as distancing, handwashing, and face coverings. A C3.ai award-winning online CC19LP tool is accessible from the COSMOS COVID-19 project site (https://cosmos.uta.edu/projects/covid-19/) and has been tested for all 3142 U.S. county areas. Results are demonstrated for several metropolitan counties with a deeper investigation for Miami-Dade County in Florida. Note to Practitioners—In this article, a computationally fast optimization framework is presented to study the delicate balance between reopening U.S. communities and controlling severe cases of COVID-19 that lead to hospitalizations and fatalities. This framework can provide guidance to decision-makers on optimal intervention strategies for protecting high-risk individuals while reopening communities. This optimization framework demonstrates a practical approach to conduct decision-making in an uncertain environment and can be useful for the prioritization of resources and interventions in the case of future epidemics or pandemics. Resources on understanding and implementing the framework are publicly available, including an award-winning online optimization tool that automatically accesses county-level data from Census, Centers for Disease Control and Prevention (CDC), and Johns Hopkins COVID-19 repositories. [ FROM AUTHOR] Copyright of IEEE Transactions on Automation Science & Engineering is the property of IEEE and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

7.
Cardiol Plus ; 6(1): 30-40, 2021 01 01.
Article in English | MEDLINE | ID: covidwho-1776423

ABSTRACT

Coronavirus disease 2019 (COVID-19) has spread, at an unprecedented speed and scale, into a global pandemic, infecting more than 29 million cases worldwide across 215 countries and territories and killing more than 930,000 individuals. There is evidence that preexisting cardiac disease can render individuals vulnerable. A large number of patients with COVID-19 present with preexisting cardiovascular disease or develop new-onset cardiac dysfunction during the course of the illness. Therefore, particular attention should be given to cardiovascular protection during COVID-19 treatment. This review highlights recent advances in our understanding of the interaction between COVID-19 and the cardiovascular system, with special attention to the virological, pathological, and immunological characteristics of COVID-19, acute myocardial injury, myocarditis, arrhythmias, coronary artery disease, heart function, and the possible mechanisms.

8.
Front Microbiol ; 13: 816778, 2022.
Article in English | MEDLINE | ID: covidwho-1775711

ABSTRACT

Background: Although effective vaccines have been developed against coronavirus disease 2019 (COVID-19), the level of neutralizing antibodies (NAbs) induced after vaccination in the real world is still unknown. The aim of this work was to evaluate the level and persistence of NAbs induced by two inactivated COVID-19 vaccines in China. Methods: Serum samples were collected from 1,335 people aged 18 years and over who were vaccinated with an inactivated COVID-19 vaccine at Peking University People's Hospital from January 19 to June 23, 2021, for the detection of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies. Results: The positive rate for NAbs against SARS-CoV-2 was 79-91% from the first month to the second month after the second vaccine dose. The gradual decline in positivity rate for NAb response was observed from 78% at 3 months post-vaccination to 0% at 12 months post-vaccination. When there was a 21-day interval between the two doses of vaccine, the NAb positivity rate was 0% 6 months after the second dose. NAb levels were significantly higher when the interval between two doses were 3-8 weeks than when it was 0-3 weeks (χ2 = 14.04, p < 0.001). There was a linear correlation between NAbs and IgG antibodies in 1,335 vaccinated patients. NAb levels decreased in 31 patients (81.6%) and increased in 7 patients (18.4%) over time in the series of 38 patients after the second vaccination. The NAb positivity rate was significantly higher in 18- to 40-year-old subjects than in 41- to 60-year-old subjects (t = -1.959, p < 0.01; t = 0.839, p < 0.01). Conclusion: The NAb positivity rate was the highest at the first and second month after the second dose of vaccine, and gradually decreased over time. With a 21-day interval between two doses of vaccine, neutralizing antibody levels persisted for only 6 months after the second dose of vaccine. Therefore, a third vaccine dose is recommended. Our results suggest that in cases in which NAbs cannot be detected, IgM/IgG antibodies can be detected instead. The level of NAbs produced after vaccination was affected by age but not by sex. Our results suggest that an interval of 21 to 56 days between shots is suitable for vaccination.

10.
Journal of Safety Science and Resilience ; 2022.
Article in English | ScienceDirect | ID: covidwho-1757577

ABSTRACT

Since the rapid spread of the COVID-19 worldwide, the pandemic has led to a huge impact on global sporting events. As a major international event, the 2022 Beijing Winter Olympics has commonalities with the 2008 Beijing Olympics, the 2014 Sochi Winter Olympics, and the 2020 Tokyo Olympics in terms of international public opinion context and epidemiological background. In this study, over 1 million pieces of UGC(User Generated Contents) in Chinese and English languages were obtained from social media platforms such as Twitter, YouTube, as well as traditional mass media in various countries to compare the differences between the two languages in international public opinion. Using sentiment analysis, this study explores the evolution of international public opinion topics and sentiment differences among the above four Olympic Games. The analysis results show that:1) regardless of traditional mass media or online social media, there is a more obvious tendency of general politicization in the topics of the 2008 Beijing Olympics and 2022 Beijing Winter Olympics, and extreme emotional remarks of the 2022 Beijing Winter Olympics are more frequent;2) in the topic of political opinion involving China, international Chinese public opinion presents more negative sentiment than those in English;3) Among the topics involving COVID-19, the negative level of public opinion in Chinese and English is opposite for the 2020 Tokyo Olympics and the 2022 Beijing Winter Olympics;4) International public opinion on the topic of sports events is significantly more positive in Chinese than in English;5) YouTube's Chinese opinion environment is better than English.

11.
Annals of Translational Medicine ; 10(2), 2022.
Article in English | EuropePMC | ID: covidwho-1733252

ABSTRACT

Background A novel colorectal cancer center (CCC) was developed in the Shanghai Tenth People’s hospital of Tongji University during the COVID-19 epidemic. In this study, we aimed to evaluate the CCC model in terms of three aspects. Methods This retrospective study used data from the Shanghai Tenth People’s hospital patient databases. The research hypothesis was that the CCC reduces preoperative waiting time (PWT), length of hospital stay (LOS), and costs of hospitalization, without reducing the quality of surgery. Thus, we compared the time, cost, and quality between March 1 to December 31, 2019, and March 1 to December 31, 2020. Descriptive and inferential analyses of patient demographic characteristics, time, postoperative outcomes, and inpatient costs were conducted. Results A total of 965 hospitalizations for colorectal cancer (CRC) were identified—415 in 2019 and 550 in 2020. In the CCC, PWT declined by 26.2 hours (P<0.01). Patients in the CCC express group only needed to wait for 24.5 hours before undergoing surgery, with a shorter LOS than the normal group (P<0.01). None of the patients had any symptoms of COVID-19 or were high-risk COVID-19 contacts, and the incidence of immediate postoperative complications was low. The mean total inpatient cost (TIC) for all patients with CRC was 78,309.824 Chinese Yuan in 2020, which was slightly lower than that in 2019. Conclusions This study found that the centralized management model for CRC care could help patients save the PWT, LOS and costs of hospitalization during the COVID-19 epidemic.

12.
Front Med ; 16(2): 263-275, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1729392

ABSTRACT

Emerging evidence indicates that the gut microbiome contributes to the host immune response to infectious diseases. Here, to explore the role of the gut microbiome in the host immune responses in COVID-19, we conducted shotgun metagenomic sequencing and immune profiling of 14 severe/critical and 24 mild/moderate COVID-19 cases as well as 31 healthy control samples. We found that the diversity of the gut microbiome was reduced in severe/critical COVID-19 cases compared to mild/moderate ones. We identified the abundance of some gut microbes altered post-SARS-CoV-2 infection and related to disease severity, such as Enterococcus faecium, Coprococcus comes, Roseburia intestinalis, Akkermansia muciniphila, Bacteroides cellulosilyticus and Blautia obeum. We further analyzed the correlation between the abundance of gut microbes and host responses, and obtained a correlation map between clinical features of COVID-19 and 16 severity-related gut microbe, including Coprococcus comes that was positively correlated with CD3+/CD4+/CD8+ lymphocyte counts. In addition, an integrative analysis of gut microbiome and the transcriptome of peripheral blood mononuclear cells (PBMCs) showed that genes related to viral transcription and apoptosis were up-regulated in Coprococcus comes low samples. Moreover, a number of metabolic pathways in gut microbes were also found to be differentially enriched in severe/critical or mild/moderate COVID-19 cases, including the superpathways of polyamine biosynthesis II and sulfur oxidation that were suppressed in severe/critical COVID-19. Together, our study highlighted a potential regulatory role of severity related gut microbes in the immune response of host.


Subject(s)
COVID-19 , Gastrointestinal Microbiome , Clostridiales , Humans , Immunity , Leukocytes, Mononuclear , SARS-CoV-2
14.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-325323

ABSTRACT

In semantic segmentation, we aim to train a pixel-level classifier to assign category labels to all pixels in an image, where labeled training images and unlabeled test images are from the same distribution and share the same label set. However, in an open world, the unlabeled test images probably contain unknown categories and have different distributions from the labeled images. Hence, in this paper, we consider a new, more realistic, and more challenging problem setting where the pixel-level classifier has to be trained with labeled images and unlabeled open-world images -- we name it open world semantic segmentation (OSS). In OSS, the trained classifier is expected to identify unknown-class pixels and classify known-class pixels well. To solve OSS, we first investigate which distribution that unknown-class pixels obey. Then, motivated by the goodness-of-fit test, we use statistical measurements to show how a pixel fits the distribution of an unknown class and select highly-fitted pixels to form the unknown region in each image. Eventually, we propose an end-to-end learning framework, known-region-aware domain alignment (KRADA), to distinguish unknown classes while aligning distributions of known classes in labeled and unlabeled open-world images. The effectiveness of KRADA has been verified on two synthetic tasks and one COVID-19 segmentation task.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-325159

ABSTRACT

At least three months have been passed since the outbreak of the severe acute respiratory disease, COVID-19 in Wuhan city, China in December 2019, caused by the infection of a novel coronavirus, SARS-CoV-2. 1,2 . Due to its rapid spread throughout China and abroad, knowledge sharing for both its epidemiology and clinic manifestations is urgently need. Here we analyzed the clinical, molecular and immunological data from 326 confirmed cases of SARS-CoV-2 infection in Shanghai. Genomic sequences assembled from 112 quality samples together with uploaded sequences in Global Initiative on Sharing All Influenza Data (GISAID) showed a stable evolution and suggested two major lineages with differential exposure history during the earliest outbreak in Wuhan. Nevertheless, they exhibited similar virulence and clinical outcomes. Lymphocytopenia, especially the reduced CD4+ and CD8+ T cell counts upon admission, was predictive of disease progression. High level of IL-6 and IL-8 during treatment was observed in severe and critical patients and correlated with decreased lymphocyte count. The determinants of disease severity seemed to stem mostly from host factors such age, lymphocytopenia and its associated cytokine storm whereas viral genetic variation did not significantly affect the outcomes. This comprehensive analysis on the molecular, immunological and clinical data provides a panorama of the key determinants related to the disease outcomes which should be helpful for improving the current combat against this extremely aggressive pandemic.Authors Xiaonan Zhang, Yun Tan, Yun Ling, Gang Lu, Feng Liu, and Zhigang Yi contributed equally to this work.

16.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324295

ABSTRACT

Objective: To clarify the outcomes of elderly patients with COVID-19. Methods: : All 265 confirmed adult patients with COVID-19 were included in this retrospective study, 43 (16.2%) of whom were 65 years and older. Electronic medical records of the subjects were reviewed to obtain information on clinical characteristics and outcomes. The allocations of medical resource were also recorded. Results: : Only one death case occurred in the elderly. The mortality of elderly patients was no higher than that of young patients (2.3% vs. 0%, P = 0.126). The cure rate was 95.3% in elderly patients and 99.5% in young patients ( P = 0.067), and the duration of hospitalization is 27 days in elderly patients and 18 days in young patients ( P = 0.001). The elderly suffered from more comorbidities (67.4% vs. 24.8%, P < 0.001), most of which is hypertension. Significantly more severe cases occurred in elderly patients compared with young patients (37.2% vs. 16.7%, P = 0.004). The elderly were more likely to present with complications including acute respiratory distress syndrome, acute myocardial injury, septic shock and acute kidney injury (all P < 0.05), respectively. No medical staffs were infected during the treatment of COVID-19. Conclusion: The cure rate and the mortality of the elderly seemed to be no worse than that of the young, though the elderly were with longer hospitalization. Elderly patients with COVID-19 could be treatable if handled properly. More severe cases and complications in elderly patients should prompt for more complex treatment and special considerations.

17.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324294

ABSTRACT

Objective: To clarify the clinical features of cured patients with coronavirus disease (COVID-19) and the relevance of IgM and IgG testing. Methods: : A total of 187 cured COVID-19 patients with antibody test were followed up every two weeks at Guangzhou Eighth People's hospital. Assessment for general condition, symptoms, epidemiological contact history, polymerase chain reaction (PCR) assay, and antibody tests were performed and recorded. Information from Guangzhou CDC was also screened. Results: : There were 154 (82.4%) patients with positive results for IgG and 35 (18.7%) patients with positive results for IgM. PCR assay was positive in 10 (5.3%) patients. Neither IgG nor IgM results showed a relationship with PCR test results (all P > 0.05). No re-infection was found in the cured patients. Among people who were in close contact with the cured patients, no one was diagnosed with COVID-19 as reported both by the cured patients and the Guangzhou CDC. Factors associated with appearance of IgG comprised hospitalization days (OR: 1.07, 95%CI: 1.02-1.13, P = 0.004) and antibiotics treatment (OR: 2.78, 95%CI: 1.10-7.01, P = 0.031) . Conclusion: In our study, neither re-infection nor human-to-human transmission was found in cured patients with COVID-19. Additionally, neither IgG nor IgM can be used to replace the PCR test in cured patients.

18.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-324184

ABSTRACT

Objective: To explore discrepancy in CT manifestations of coronavirus disease 2019 (COVID-19) in patients outside Wuhan between cases with a history of exposure to Wuhan and with the second-generation infection. Methods: : Twenty-two patients with confirmed COVID-19 from two hospitals in Nanchong outside Wuhan were enrolled. All patients underwent initial and follow-up computed tomography after admission, and were divided into two groups. Group A and B were composed of 15 patients with a history of exposure to Wuhan and 7 with the second-generation infection in Nanchong, respectively. Initial CT features including extent score and density score between groups were statistically compared. Results: : All patients in group A had abnormal CT findings while 3 of 7 patients in group B had. Patients with abnormal CT findings were more frequent in group A than in group B ( P < 0.05). On initial CT, pure ground glass opacity (GGO), and GGO with consolidation and/or other abnormalities were found in 20% (3/15) and 80% (12/15) patients in group A, respectively, while 1 (14.3%), 2 (28.6%) and 4 (57.1%) had pure GGO, GGO with focal consolidation, and normal CT appearances in Group B, respectively. Patients with extent and density scores of ≥5 were more frequent in group A than in group B ( P s < 0.01). Additionally, 3 of 4 (75%) patients with normal initial CT findings had focal pure GGO lesions on follow-up CT. Conclusion: The COVID-19 in patients with a history of exposure to Wuhan can be severer than with the second-generation infection on CT.

19.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-316997

ABSTRACT

Objective: To clarify the clinical and medical expense characteristics of COVID-19. Methods: : In this retrospective, single-center study, 55 cured cases with confirmed COVID-19 were analyzed for demographic, epidemiological, clinical, and radiological features and medical expense data. Results: : The average age of the 54 successfully treated patients with COVID-19 was 53.2 years old (SD 19.0), including 27 men and 27 women. Off this, 31 (57.4%) patients had chronic diseases. Patients commonly had clinical manifestations of fever (45 [83.3%] patients), cough (29[54.7%] patients), expectoration (28 [51.9%] patients), fatigue (24[44.4%] patients) and diarrhea (8[14.8%] patients) on admission. There was a 10-day interval from the onset of signs and symptoms to hospital admission. About 80% of them got recovery after a two-week treatment. The mean interval from the onset of signs and symptoms to hospital discharge was 20.5 (IQR 16-29) days. The median total medical expense of the treated patient, in general, was 2579.6 (IQR 1366.1-4837.6) U.S. dollars. Still, the median medical expense was 8904.1 (IQR 6660.1- 27143.8) U.S. dollars in patients with more than five comorbid illnesses during the treatment. Conclusion: There is a 3-week interval from the onset of signs and symptoms to cure, and most hospitalized patients get recovery within two weeks. The total medical expense of cases with more than five comorbid conditions during the treatment is higher. Quite a few COVID-19 cases with other serious diseases are likely to account for most of the total medical expenses.

20.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315643

ABSTRACT

Background: The novel coronavirus disease (COVID-19) is leading to high morbidity and mortality. This study aimed to test whether blood urea nitrogen-to-creatinine ratios (BCR) is a predictor of poor prognosis in patients with COVID-19. Method: From 9,165 generally healthy subjects, we calculated ranges of “normal” BCR values. 416 COVID-19 patients were randomly assigned to training cohort and validation cohort contained 337, 79 patients, respectively. The prognostic ability of abnormal BCR range was assessed using a Logistic regression. Development a nomogram for predicting in-hospital mortality incorporated age, sex and BCR. The model discrimination was assessed using the calibration curves and concordance index in training and validation cohort. The predictive accuracy and clinical values of the nomogram was measured by decision curve analysis (DCA) and clinical impact curve analysis (CICA). Results: : Among 337 COVID-19 patients, 13.4% and 11.3% were classified into higher and lower than normal range group, respectively. The BCR was identified as an independent risks factor for death in COVID-19 patients (P<0.0001), with area under the curve (AUC) 0.768;95%CI: 0.717-0.819). Kaplan-Meier curves for all-cause mortality outcomes showed that patients with above normal range of BCR had worse prognosis (p<0.0001). Logistic regression analysis revealed that BCR above the normal range was independently associated with death in COVID-19 patients (Odds ratio 7.54;95%CI: 1.55-36.66;P=0.012). ROC curves showed that the nomogram had good discrimination in the training cohort (AUC 0.838;95%CI 0.795–0.880) and the validation cohort (AUC 0.929;95%CI 0.869-0.989). Using maximum Youden index, the cutoff values of 59.8 points, the sensitivity and specificity were 75.4% and 81%. The calibration curves showed good agreement between nomogram prediction and actual observation. DCA and CICA indicated the clinical usefulness of the prediction nomogram. Conclusion: BCR was a useful prognostic factor for COVID-19 patients. Development of an individualized prediction nomogram BCR-based, which can effectively predict the risk of mortality, and then, help clinicians to improve individual treatment, make clinical decisions timely and early.

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