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1.
Ann Palliat Med ; 11(2): 544-550, 2022 Feb.
Article in English | MEDLINE | ID: covidwho-1727123

ABSTRACT

BACKGROUND: Under the current epidemic of the coronavirus disease of 2019 (COVID-19), there is a need to distinguish the differences between the laboratory examinations of COVID-19-infected patients, tumor patients with fever, and those with normal fever patients. We aimed to investigate the temperature of tumor patients with different tumor burdens, stages, and cancer types. METHODS: We recruited 3 groups of patients to this study: fever patients with malignant tumors, ordinary fever patients, and confirmed cases of COVID-19, with 31, 55, and 28 cases in each group, respectively. RESULTS: The levels of leukocytes and neutrophils were the highest among non-tumor patients, and the count of COVID-19 was the lowest, with a P value of 0.000. Among the leukocytosis group, non-tumor patients had the highest proportion (43.6%), while that of COVID-19 was only 3.6% (P=0.000). Similarly, there were significant differences in the grading of neutrophils, where most of the infected patients were in the normal group and the P value was 0.000. The lymphocyte count of the tumor group was significantly reduced, with an average of (0.97±0.66) ×109/L (P=0.004). In the lymphocyte grades, most of the infected patients were the normal group (71.4%), while tumor patients in the lymphocytopenia group accounted for 63.1% (P=0.006). There were also significant differences in the neutrophil to lymphocyte ratio (NLR) (P=0.006). There was a significant difference in temperature between different tumor burden groups (P=0.014). CONCLUSIONS: The normal fever group had the highest count of leukocyte and neutrophils, whereas the infected group had the lowest relative count. The NLR was the lowest in the infected group. The NLR was higher in the bigger tumor load group.


Subject(s)
COVID-19 , Neoplasms , Humans , Lymphocytes , Neoplasms/complications , Prognosis , Retrospective Studies , SARS-CoV-2
2.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-315332

ABSTRACT

The COVID-2019 disease caused by the SARS-CoV-2 virus (aka 2019-nCoV) has raised significant health concerns in China and worldwide. While novel drug discovery and vaccine studies are long, repurposing old drugs against the COVID-2019 epidemic can help identify treatments, with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter Phase 3 or 4 or can be used directly in clinical settings. In this study, we presented a novel network based drug repurposing platform to identify potential drugs for the treatment of COVID-2019. We first analysed the genome sequence of SARS-CoV-2 and identified SARS as the closest disease, based on genome similarity between both causal viruses, followed by MERS and other human coronavirus diseases. Using our AutoSeed pipeline (text mining and database searches), we obtained 34 COVID-2019-related genes. Taking those genes as seeds, we automatically built a molecular network for which our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules and finally suggested 78 drugs to repurpose. Following manual filtering based on clinical knowledge, we re-prioritized 30 potential repurposable drugs against COVID-2019 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide) . We hope that this data can provide critical insights into SARS-CoV-2 biology and help design rapid clinical trials of treatments against COVID-2019.

3.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-312180

ABSTRACT

Background: The aim of the study was to establish and validate nomograms to predict the mortality risk of patients with COVID-19 using routine clinical indicators. Method: This retrospective study included a development cohort enrolled 2119 hospitalized COVID-19 patients and a validation cohort included 1504 COVID-19 patients. The demographics, clinical manifestations, vital signs and laboratory test results of the patients at admission and outcome of in-hospital death were recorded. The independent factors associated with death were identified by a forward stepwise multivariate logistic regression analysis and used to construct two prognostic nomograms. The models were then tested in an external dataset. Results: Nomogram 1 is a full model included nine factors identified in the multivariate logistic regression and nomogram 2 is built by selecting four factors from nine to perform as a reduced model. Nomogram 1 and nomogram 2 established showed better performance in discrimination and calibration than the MuLBSTA score in training. In validation, Nomogram 1 performed better than nomogram 2 for calibration. Conclusion: Nomograms we established performed better than the MuLBSTA score. We recommend the application of nomogram 1 in general hospital which provide robust prognostic performance but more cumbersome;nomogram 2 in mobile cabin hospitals which depend on less laboratory examinations and more convenient. Both nomograms can help clinicians in identifying patients at risk of death with routine clinical indicators at admission, which may reduce the overall mortality of COVID-19.

6.
Front Cell Infect Microbiol ; 11: 768993, 2021.
Article in English | MEDLINE | ID: covidwho-1556329

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) shows a high degree of homology with SARS-CoV. They share genes, protein sequences, clinical manifestations, and cellular entry patterns. Thus, SARS research may serve helpful in gaining a better understanding of the current coronavirus disease 2019 (COVID-19) pandemic. Serum antibodies from convalescent patients with SARS collected in 2018 were used to target the recombinant SARS-CoV-2 spike protein via a chemiluminescence microsphere immunoassay. Antibodies of convalescent patients with SARS exhibited serous immune cross-reactivity with the SARS-CoV-2 spike protein. The serous antibodies, excluding S22 of convalescent patients with SARS, did not competitively inhibit the binding of SARS-CoV-2 spike protein to ACE2. T cellular immunity research was conducted in vitro using peripheral blood mononuclear cells (PBMCs) stimulated by pooled peptide epitopes 15 years post-infection. Interferon gamma was detected and the PBMC transcriptomic profile was obtained. The heatmap of the transcriptomic profile showed that mRNAs and circRNAs of the SARS group clustered together after being stimulated by the peptide epitope pool. Differentially expressed mRNAs were most significantly enriched in immunity and signal transduction (P < 0.01). SARS elicits cytokine and chemokine responses, partially consistent with previously published data about COVID-19. Overall, our results indicate that antibodies from convalescent patients with SARS persisted for 15 years and displayed immune cross-reactivity with the SARS-CoV-2 spike protein. The immune status of patients with SARS 15 years post-infection may provide a better understanding of the future immune status of patients with COVID-19.


Subject(s)
COVID-19 , Leukocytes, Mononuclear , Antibodies, Viral , Humans , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Transcriptome
8.
New Media & Society ; : 1, 2021.
Article in English | Academic Search Complete | ID: covidwho-1507065

ABSTRACT

The coronavirus pandemic has been accompanied by the spread of misinformation on social media. The Plandemic conspiracy theory holds that the pandemic outbreak was planned to create a new social order. This study examines the evolution of this popular conspiracy theory from a dynamic network perspective. Guided by the analytical framework of network evolution, the current study explores drivers of tie changes in the Plandemic communication network among serial participants over a 4-month period. Results show that tie changes are explained by degree-based and closure-based structural features (i.e. tendencies toward transitive closure and shared popularity and tendencies against in-degree activity and transitive reciprocated triplet) and nodal attributes (i.e. bot probability and political preference). However, a participant’s level of anger expression does not predict the evolution of the observed network. [ABSTRACT FROM AUTHOR] Copyright of New Media & Society is the property of Sage Publications, Ltd. 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 abstract 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 abstract. (Copyright applies to all Abstracts.)

9.
Front Med (Lausanne) ; 8: 706380, 2021.
Article in English | MEDLINE | ID: covidwho-1502327

ABSTRACT

This study aimed to establish and validate the nomograms to predict the mortality risk of patients with coronavirus disease 2019 (COVID-19) using routine clinical indicators. This retrospective study included a development cohort enrolled 2,119 hospitalized patients with COVID-19 and a validation cohort included 1,504 patients with COVID-19. The demographics, clinical manifestations, vital signs, and laboratory tests of the patients at admission and outcome of in-hospital death were recorded. The independent factors associated with death were identified by a forward stepwise multivariate logistic regression analysis and used to construct the two prognostic nomograms. The nomogram 1 was a full model to include nine factors identified in the multivariate logistic regression and nomogram 2 was built by selecting four factors from nine to perform as a reduced model. The nomogram 1 and nomogram 2 showed better performance in discrimination and calibration than the Multilobular infiltration, hypo-Lymphocytosis, Bacterial coinfection, Smoking history, hyper-Tension and Age (MuLBSTA) score in training. In validation, nomogram 1 performed better than nomogram 2 for calibration. We recommend the application of nomogram 1 in general hospitals which provide robust prognostic performance though more cumbersome; nomogram 2 in the out-patient, emergency department, and mobile cabin hospitals, which depend on less laboratory examinations to make the assessment more convenient. Both the nomograms can help the clinicians to identify the patients at risk of death with routine clinical indicators at admission, which may reduce the overall mortality of COVID-19.

10.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-291157

ABSTRACT

Background: SARS-COV-2 is a new virus responsible for the outbreak of respiratory illness known as Corona Virus Disease 2019 (COVID-19). Mycoplasma is an uncommon co-infected pathogen with SARS-COV-2 and has not been reported yet. Besides, Computed Tomography (CT), used as an accessory examination, may play a more significant role this time. Case presentation: A 49-year-old female presented with cough, expectoration and chest congestion followed by elevated CRP and ESR. CT images showed ground-glass opacities in bilateral lower lobes and patchy and striate shadow in right upper lobe. IgM antibody of Mycoplasma pneumoniae was positive and RT-PCR outcome of sputum was positive for the SARS-COV-2 nucleic acid. Her diagnosis of COVID-19 was made on the basis of laboratory results, chest CT images, clinical manifestations and epidemiologic characteristics. She was treated with combination therapy for 17 days following which she showed marked recovery. Conclusion: Co-infection of SARS-COV-2 and Mycoplasma in COVID-19 patients appears to be uncommon. Computed tomography is an acceptive way to make primary diagnosis and treatment for patients as soon as possible. Combination therapy of antiviral, anti-inflammatory, traditional Chinese medical herbal and supportive care may be a reference for further progress.

11.
BMC Infect Dis ; 21(1): 1012, 2021 Sep 27.
Article in English | MEDLINE | ID: covidwho-1440914

ABSTRACT

BACKGROUND: The receptor of severe respiratory syndrome coronavirus 2 (SARS-CoV-2), angiotensin-converting enzyme 2, is more abundant in kidney than in lung tissue, suggesting that kidney might be another important target organ for SARS-CoV-2. However, our understanding of kidney injury caused by Coronavirus Disease 2019 (COVID-19) is limited. This study aimed to explore the association between kidney injury and disease progression in patients with COVID-19. METHODS: A retrospective cohort study was designed by including 2630 patients with confirmed COVID-19 from Huoshenshan Hospital (Wuhan, China) from 1 February to 13 April 2020. Kidney function indexes and other clinical information were extracted from the electronic medical record system. Associations between kidney function indexes and disease progression were analyzed using Cox proportional-hazards regression and generalized linear mixed model. RESULTS: We found that estimated glomerular filtration rate (eGFR) and creatinine clearance (Ccr) decreased in 22.0% and 24.0% of patients with COVID-19, respectively. Proteinuria was detected in 15.0% patients and hematuria was detected in 8.1% of patients. Hematuria (HR 2.38, 95% CI 1.50-3.78), proteinuria (HR 2.16, 95% CI 1.33-3.51), elevated baseline serum creatinine (HR 2.84, 95% CI 1.92-4.21) and blood urea nitrogen (HR 3.54, 95% CI 2.36-5.31), and decrease baseline eGFR (HR 1.58, 95% CI 1.07-2.34) were found to be independent risk factors for disease progression after adjusted confounders. Generalized linear mixed model analysis showed that the dynamic trajectories of uric acid was significantly related to disease progression. CONCLUSION: There was a high proportion of early kidney function injury in COVID-19 patients on admission. Early kidney injury could help clinicians to identify patients with poor prognosis at an early stage.


Subject(s)
Acute Kidney Injury , COVID-19 , Cohort Studies , Disease Progression , Humans , Kidney , Retrospective Studies , Risk Factors , SARS-CoV-2
12.
Diabetes Res Clin Pract ; 180: 109041, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1401412

ABSTRACT

AIMS: We aimed to investigate the role of Fasting Plasma Glucose (FPG) and glucose fluctuation in the prognosis of COVID-19 patients stratified by pre-existing diabetes. METHODS: The associations of FPG and glucose fluctuation indexes with prognosis of COVID-19 in 2,642 patients were investigated by multivariate Cox regression analysis. The primary outcome was in-hospital mortality; the secondary outcome was disease progression. The longitudinal changes of FPG over time were analyzed by the latent growth curve model in COVID-19 patients stratified by diabetes and severity of COVID-19. RESULTS: We found FPG as an independent prognostic factor of overall survival after adjustment for age, sex, diabetes and severity of COVID-19 at admission (HR: 1.15, 95% CI: 1.06-1.25, P = 1.02 × 10-3). Multivariate logistic regression analysis indicated that the standard deviation of blood glucose (SDBG) and largest amplitude of glycemic excursions (LAGE) were also independent risk factors of COVID-19 progression (P = 0.03 and 0.04, respectively). The growth trajectory of FPG over the first 3 days of hospitalization was steeper in patients with critical COVID-19 in comparison to moderate patients. CONCLUSIONS: Hyperglycemia and glucose fluctuation were adverse prognostic factors of COVID-19 regardless of pre-existing diabetes. This stresses the importance of glycemic control in addition to other therapeutic management.


Subject(s)
COVID-19 , Diabetes Mellitus , Blood Glucose , Diabetes Mellitus/epidemiology , Fasting , Glucose , Humans , Prognosis , Retrospective Studies , Risk Factors , SARS-CoV-2
13.
Security and Communication Networks ; 2021, 2021.
Article in English | ProQuest Central | ID: covidwho-1378088

ABSTRACT

Loneliness and isolation are on the rise worldwide, threatening human well-being and the wellness of different age groups and backgrounds. Notably, global social distancing measures during the COVID-19 crisis have exacerbated this problem, resulting in various psychological and physiological ailments. Within both the categories of social and medical robots, companion robots are capable of engaging emotionally with users and providing continuous monitoring and assessment of their health. In this study, we propose a framework for modeling the emotion space of companion robots to facilitate their emotion generation and transition based on Plutchik’s wheel of emotions and reversible quantum circuit schemes. Superposition encodings allow fewer computing resources for the generation and storage of emotional states, and by using unitary operations, they facilitate easier emotion transition and recovery over different intervals. Further, an encryption strategy is designed based on the emotion communication architecture to secure the emotion-related data in human-robot interaction. It is hoped that such an integrative framework and research agenda exploring the role of companion robots will be useful to care for users’ social health by mitigating their negative emotions, especially during difficult times.

14.
Water Res ; 204: 117606, 2021 Oct 01.
Article in English | MEDLINE | ID: covidwho-1373297

ABSTRACT

The epidemic of COVID-19 has aroused people's particular attention to biosafety. A growing number of disinfection products have been consumed during this period. However, the flaw of disinfection has not received enough attention, especially in water treatment processes. While cutting down the quantity of microorganisms, disinfection processes exert a considerable selection effect on bacteria and thus reshape the microbial community structure to a great extent, causing the problem of disinfection-residual-bacteria (DRB). These systematic and profound changes could lead to the shift in regrowth potential, bio fouling potential, as well as antibiotic resistance level and might cause a series of potential risks. In this review, we collected and summarized the data from the literature in recent 10 years about the microbial community structure shifting of natural water or wastewater in full-scale treatment plants caused by disinfection. Based on these data, typical DRB with the most reporting frequency after disinfection by chlorine-containing disinfectants, ozone disinfection, and ultraviolet disinfection were identified and summarized, which were the bacteria with a relative abundance of over 5% in the residual bacteria community and the bacteria with an increasing rate of relative abundance over 100% after disinfection. Furthermore, the phylogenic relationship and potential risks of these typical DRB were also analyzed. Twelve out of fifteen typical DRB genera contain pathogenic strains, and many were reported of great secretion ability. Pseudomonas and Acinetobacter possess multiple disinfection resistance and could be considered as model bacteria in future studies of disinfection. We also discussed the growth, secretion, and antibiotic resistance characteristics of DRB, as well as possible control strategies. The DRB phenomenon is not limited to water treatment but also exists in the air and solid disinfection processes, which need more attention and more profound research, especially in the period of COVID-19.


Subject(s)
COVID-19 , Microbiota , Bacteria , Disinfection , Humans , SARS-CoV-2
15.
Preprint in English | medRxiv | ID: ppmedrxiv-21260221

ABSTRACT

Genomic regions have been associated with COVID-19 susceptibility and outcomes, including the chr12q24.13 locus encoding antiviral proteins OAS1-3. Here, we report genetic, functional, and clinical insights into genetic associations within this locus. In Europeans, the risk of hospitalized vs. non-hospitalized COVID-19 was associated with a single 19Kb-haplotype comprised of 76 OAS1 variants included in a 95% credible set within a large genomic fragment introgressed from Neandertals. The risk haplotype was also associated with impaired spontaneous but not treatment-induced SARS-CoV-2 clearance in a clinical trial with pegIFN-{lambda}1. We demonstrate that two exonic variants, rs10774671 and rs1131454, affect splicing and nonsense-mediated decay of OAS1. We suggest that genetically-regulated loss of OAS1 expression contributes to impaired spontaneous clearance of SARS-CoV-2 and elevated risk of hospitalization for COVID-19. Our results provide the rationale for further clinical studies using interferons to compensate for impaired spontaneous SARS-CoV-2 clearance, particularly in carriers of the OAS1 risk haplotypes.

16.
Front Med (Lausanne) ; 8: 655604, 2021.
Article in English | MEDLINE | ID: covidwho-1282393

ABSTRACT

Objectives: Diabetes is a risk factor for poor COVID-19 prognosis. The analysis of related prognostic factors in diabetic patients with COVID-19 would be helpful for further treatment of such patients. Methods: This retrospective study involved 3623 patients with COVID-19 (325 with diabetes). Clinical characteristics and laboratory tests were collected and compared between the diabetic group and the non-diabetic group. Binary logistic regression analysis was applied to explore risk factors associated in diabetic patients with COVID-19. A prediction model was built based on these risk factors. Results: The risk factors for higher mortality in diabetic patients with COVID-19 were dyspnea, lung disease, cardiovascular diseases, neutrophil, PLT count, and CKMB. Similarly, dyspnea, cardiovascular diseases, neutrophil, PLT count, and CKMB were risk factors related to the severity of diabetes with COVID-19. Based on these factors, a risk score was built to predict the severity of disease in diabetic patients with COVID-19. Patients with a score of 7 or higher had an odds ratio of 7.616. Conclusions: Dyspnea is a critical clinical manifestation that is closely related to the severity of disease in diabetic patients with COVID-19. Attention should also be paid to the neutrophil, PLT count and CKMB levels after admission.

17.
Int J Biol Sci ; 17(8): 2124-2134, 2021.
Article in English | MEDLINE | ID: covidwho-1271048

ABSTRACT

The efficacy of tocilizumab on the prognosis of severe/critical COVID-19 patients is still controversial so far. We aimed to delineate the inflammation characteristics of severe/critical COVID-19 patients and determine the impact of tocilizumab on hospital mortality. Here, we performed a retrospective cohort study which enrolled 727 severe or critical inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Huoshenshan Hospital (Wuhan, China), among which 50 patients received tocilizumab. This study confirmed that most recovered patients manifested relatively normal inflammation levels at admission, whereas most of the deceased cases presented visibly severe inflammation at admission and even progressed into extremely aggravated inflammation before their deaths, proved by some extremely high concentrations of interleukin-6, procalcitonin, C-reactive protein and neutrophil count. Moreover, based on the Cox proportional-hazards models before or after propensity score matching, we demonstrated that tocilizumab treatment could lessen mortality by gradually alleviating excessive inflammation and meanwhile continuously enhancing the levels of lymphocytes within 14 days for severe/critical COVID-19 patients, indicating potential effectiveness for treating COVID-19.


Subject(s)
Anti-Inflammatory Agents/therapeutic use , Antibodies, Monoclonal, Humanized/therapeutic use , COVID-19/drug therapy , Inflammation/drug therapy , SARS-CoV-2 , Aged , Aged, 80 and over , C-Reactive Protein/analysis , COVID-19/blood , COVID-19/mortality , COVID-19/physiopathology , Comorbidity , Female , Humans , Inflammation/blood , Interleukin-6/blood , Length of Stay/statistics & numerical data , Leukocyte Count , Male , Middle Aged , Neutrophils , Procalcitonin/blood , Propensity Score , Proportional Hazards Models , Retrospective Studies
18.
Transpl Immunol ; 67: 101395, 2021 08.
Article in English | MEDLINE | ID: covidwho-1199110

ABSTRACT

Since its emergence in December 2019 many end-stage renal disease (ESRD) patients have been infected with coronavirus disease 2019 (COVID-19). Herein, we describe the case of an ESRD patient who received a kidney transplant after recovering from COVID-19. We described the clinical course of COVID-19 and kidney transplant management, including the patient's symptoms, laboratory results, computed tomography, and antibody profiles. He recovered well, without complications. Chest computed tomography, PCR, and IgG results indicated no recurrence of COVID-19 during the subsequent two weeks. Therefore, kidney transplantation is feasible in an ESRD patient who has recovered from COVID-19, under a normal immunosuppressive regimen.


Subject(s)
COVID-19/therapy , Immunocompromised Host , Kidney Failure, Chronic/surgery , Kidney Transplantation , Transplant Recipients , Adult , Antiviral Agents/therapeutic use , Glomerulonephritis/surgery , Humans , Immunosuppressive Agents/adverse effects , Immunosuppressive Agents/therapeutic use , Male , SARS-CoV-2
19.
BMC Pulm Med ; 21(1): 120, 2021 Apr 14.
Article in English | MEDLINE | ID: covidwho-1183526

ABSTRACT

BACKGROUND: During outbreak of Coronavirus Disease 2019 (COVID-19), healthcare providers are facing critical clinical decisions based on the prognosis of patients. Decision support tools of risk stratification are needed to predict outcomes in patients with different clinical types of COVID-19. METHODS: This retrospective cohort study recruited 2425 patients with moderate or severe COVID-19. A logistic regression model was used to select and estimate the factors independently associated with outcomes. Simplified risk stratification score systems were constructed to predict outcomes in moderate and severe patients with COVID-19, and their performances were evaluated by discrimination and calibration. RESULTS: We constructed two risk stratification score systems, named as STPCAL (including significant factors in the prediction model: number of clinical symptoms, the maximum body temperature during hospitalization, platelet count, C-reactive protein, albumin and lactate dehydrogenase) and TRPNCLP (including maximum body temperature during hospitalization, history of respiratory diseases, platelet count, neutrophil-to-lymphocyte ratio, creatinine, lactate dehydrogenase, and prothrombin time), to predict hospitalization duration for moderate patients and disease progression for severe patients, respectively. According to STPCAL score, moderate patients were classified into three risk categories for a longer hospital duration: low (Score 0-1, median = 8 days, with less than 20.0% probabilities), intermediate (Score 2-6, median = 13 days, with 30.0-78.9% probabilities), high (Score 7-9, median = 19 days, with more than 86.5% probabilities). Severe patients were stratified into three risk categories for disease progression: low risk (Score 0-5, with less than 12.7% probabilities), intermediate risk (Score 6-11, with 18.6-69.1% probabilities), and high risk (Score 12-16, with more than 77.9% probabilities) by TRPNCLP score. The two risk scores performed well with good discrimination and calibration. CONCLUSIONS: Two easy-to-use risk stratification score systems were built to predict the outcomes in COVID-19 patients with different clinical types. Identifying high risk patients with longer stay or poor prognosis could assist healthcare providers in triaging patients when allocating limited healthcare during COVID-19 outbreak.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , COVID-19/therapy , Clinical Decision Rules , Disease Progression , Hospitalization/statistics & numerical data , Severity of Illness Index , Adolescent , Adult , Aged , Aged, 80 and over , Clinical Decision-Making/methods , Female , Humans , Logistic Models , Male , Middle Aged , Prognosis , Retrospective Studies , Risk Assessment , Risk Factors , Sensitivity and Specificity , Triage/methods , Young Adult
20.
Chin Med J (Engl) ; 134(8): 944-953, 2021 Apr 01.
Article in English | MEDLINE | ID: covidwho-1165520

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly spread throughout the world. In this study, we aimed to identify the risk factors for severe COVID-19 to improve treatment guidelines. METHODS: A multicenter, cross-sectional study was conducted on 313 patients hospitalized with COVID-19. Patients were classified into two groups based on disease severity (nonsevere and severe) according to initial clinical presentation. Laboratory test results and epidemiological and clinical characteristics were analyzed using descriptive statistics. Univariate and multivariate logistic regression models were used to detect potential risk factors associated with severe COVID-19. RESULTS: A total of 289 patients (197 nonsevere and 92 severe cases) with a median age of 45.0 (33.0, 61.0) years were included in this study, and 53.3% (154/289) were male. Fever (192/286, 67.1%) and cough (170/289, 58.8%) were commonly observed, followed by sore throat (49/289, 17.0%). Multivariate logistic regression analysis suggested that patients who were aged ≥ 65 years (OR: 2.725, 95% confidence interval [CI]: 1.317-5.636; P = 0.007), were male (OR: 1.878, 95% CI: 1.002-3.520, P = 0.049), had comorbid diabetes (OR: 3.314, 95% CI: 1.126-9.758, P = 0.030), cough (OR: 3.427, 95% CI: 1.752-6.706, P < 0.001), and/or diarrhea (OR: 2.629, 95% CI: 1.109-6.231, P = 0.028) on admission had a higher risk of severe disease. Moreover, stratification analysis indicated that male patients with diabetes were more likely to have severe COVID-19 (71.4% vs. 28.6%, χ2 = 8.183, P = 0.004). CONCLUSIONS: The clinical characteristics of those with severe and nonsevere COVID-19 were significantly different. The elderly, male patients with COVID-19, diabetes, and presenting with cough and/or diarrhea on admission may require close monitoring to prevent deterioration.


Subject(s)
COVID-19/diagnosis , Adult , COVID-19/pathology , China/epidemiology , Comorbidity , Cough , Cross-Sectional Studies , Diarrhea , Female , Humans , Male , Middle Aged , Retrospective Studies , Risk Factors
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