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1.
Diabetes Metab Syndr Obes ; 14: 4469-4482, 2021.
Article in English | MEDLINE | ID: covidwho-1526719

ABSTRACT

Purpose: To analyze the impact of hyperglycemia on the clinical outcome of COVID-19 in patients with newly diagnosed diabetes (NDD). Patients and Methods: We performed a retrospective study of 3114 cases of COVID-19 without pre-existing diabetes, 351 of which had NDD, in Hubei Province, China. The Cox regression model was used to calculate the risk of adverse clinical outcomes comparing the NDD vs non-NDD group before and after propensity score-matched (PSM) analysis. Patients with NDD were further divided into a sustained hyperglycemia group, a fluctuating group, and a remitted group based on their blood glucose levels during hospitalization as well as into hypoglycemic agent users and nonusers. Results: Compared to the non-NDD individuals, individuals with NDD had a significantly increased risk of all-cause mortality (adjusted HR after PSM, 2.65; 95% CI, 1.49-4.72; P = 0.001) and secondary outcomes involving organ damage during the 28-day follow-up period. Subgroup analyses indicated that among individuals with NDD, the individuals with remitted hyperglycemia had the lowest 28-day mortality, whereas those with sustained hyperglycemia had the highest (IRR 24.27; 95% CI, 3.21-183.36; P < 0.001). Moreover, individuals treated with hypoglycemic agents had significantly lower all-cause mortality than those not treated with hypoglycemic agents (IRR 0.08; 95% CI, 0.01-0.56; P < 0.001). Conclusion: Our study reinforces the clinical message that NDD is strongly associated with poor outcomes in COVID-19 patients. Furthermore, resolved hyperglycemia in the later phase of the disease and the use of hypoglycemic agents were associated with improved prognosis in patients with NDD.

2.
Journal of Infection and Public Health ; 2021.
Article in English | ScienceDirect | ID: covidwho-1517346

ABSTRACT

Background Coronavirus disease 2019 (COVID-19) pandemic continues to escalate intensively worldwide. Massive studies on general populations with SARS-CoV-2 infection have revealed that pre-existing comorbidities were a major risk factor for the poor prognosis of COVID-19. Notably, 49-75% of COVID-19 patients had no comorbidities, but this cohort would also progress to severe COVID-19 or even death. However, risk factors contributing to disease progression and death in patients without chronic comorbidities are largely unknown;thus, specific clinical interventions for those patients are challenging. Methods A multicenter, retrospective study based on 4,806 COVID-19 patients without chronic comorbidities was performed to identify potential risk factors contributing to COVID-19 progression and death using LASSO and a stepwise logistic regression model. Results Among 4,806 patients without pre-existing comorbidities, the proportions with severe progression and mortality were 34.29% and 2.10%, respectively. The median age was 47.00 years [interquartile range, 36.00-56.00], and 2,162 (44.99%) were men. Among 51 clinical parameters on admission, age ≥ 47, oxygen saturation < 95%, increased lactate dehydrogenase, neutrophil count, direct bilirubin, creatine phosphokinase, blood urea nitrogen levels, dyspnea, increased blood glucose and prothrombin time levels were associated with COVID-19 mortality in the entire cohort. Of the 3,647 patients diagnosed with non-severe COVID-19 on admission, 489(13.41%) progressed to severe disease. The risk factors associated with COVID-19 progression from non-severe to severe illness were increased procalcitonin levels, SpO2 < 95%, age ≥ 47, increased LDH, activated partial thromboplastin time levels, decreased high-density lipoprotein cholesterol levels, dyspnea and increased D-dimer levels. Conclusions COVID-19 patients without pre-existing chronic comorbidities have specific traits and disease patterns. COVID-19 accompanied by severe bacterial infections, as indicated by increased procalcitonin levels, was highly associated with disease progression from non-severe to severe. Aging, impaired respiratory function, coagulation dysfunction, tissue injury, and lipid metabolism dysregulation were also associated with disease progression. Once factors for multi-organ damage were elevated and glucose increased at admission, these findings indicated a higher risk for mortality. This study provides information that helps to predict COVID-19 prognosis specifically in patients without chronic comorbidities.

3.
Sci Rep ; 11(1): 20987, 2021 10 25.
Article in English | MEDLINE | ID: covidwho-1483149

ABSTRACT

Acid suppressants are widely-used classes of medications linked to increased risks of aerodigestive infections. Prior studies of these medications as potentially reversible risk factors for COVID-19 have been conflicting. We aimed to determine the impact of chronic acid suppression use on COVID-19 infection risk while simultaneously evaluating the influence of social determinants of health to validate known and discover novel risk factors. We assessed the association of chronic acid suppression with incident COVID-19 in a 1:1 case-control study of 900 patients tested across three academic medical centers in California, USA. Medical comorbidities and history of chronic acid suppression use were manually extracted from health records by physicians following a pre-specified protocol. Socio-behavioral factors by geomapping publicly-available data to patient zip codes were incorporated. We identified no evidence to support an association between chronic acid suppression and COVID-19 (adjusted odds ratio 1.04, 95% CI 0.92-1.17, P = 0.515). However, several medical and social features were positive (Latinx ethnicity, BMI ≥ 30, dementia, public transportation use, month of the pandemic) and negative (female sex, concurrent solid tumor, alcohol use disorder) predictors of new infection. These findings demonstrate the value of integrating publicly-available databases with medical data to identify critical features of communicable diseases.


Subject(s)
COVID-19/epidemiology , COVID-19/therapy , Gastroesophageal Reflux/complications , Social Determinants of Health , Aged , Behavior , COVID-19/psychology , California , Case-Control Studies , Computational Biology/methods , Databases, Factual , Female , Gastroenterology , Gastroesophageal Reflux/drug therapy , Geography , Histamine H2 Antagonists/pharmacology , Humans , Incidence , Male , Middle Aged , Odds Ratio , Proton Pump Inhibitors/pharmacology , Risk Factors , Social Class
4.
Genomics Proteomics Bioinformatics ; 2021 Oct 22.
Article in English | MEDLINE | ID: covidwho-1474586

ABSTRACT

COVID-19 has swept globally and Pakistan is no exception. To investigate the initial introductions and transmissions of the SARS-CoV-2 in Pakistan, we performed the largest genomic epidemiology study of COVID-19 in Pakistan and generated 150 complete SARS-CoV-2 genome sequences from samples collected before June 2, 2020. We identified a total of 347 mutated positions, 31 of which were over-represented in Pakistan. Meanwhile, we found over 1000 intra-host single-nucleotide variants (iSNVs). Several of them occurred concurrently, indicating possible interactions among them or coevolution. Some of the high-frequency iSNVs in Pakistan were not observed in the global population, suggesting strong purifying selections. The genomic epidemiology revealed five distinctive spreading clusters. The largest cluster consisted of 74 viruses which were derived from different geographic locations of Pakistan and formed a deep hierarchical structure, indicating an extensive and persistent nation-wide transmission of the virus that was probably attributed to a signature mutation (G8371T in ORF1ab) of this cluster. Furthermore, 28 putative international introductions were identified, several of which are consistent with the epidemiological investigations. In all, this study has inferred the possible pathways of introduction and transmissions of SARS-CoV-2 in Pakistan, which could aid ongoing and future viral surveillance and COVID-19 control.

5.
Chinese Journal of Virology ; 36(4):570-577, 2020.
Article in Chinese | GIM | ID: covidwho-1407616

ABSTRACT

We wished to explore the interference factors causing false-positive results for immunoglobulin M (IgM) and IgG antibodies in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detected by the gold immunochromatography assaym (GICA). In this way, we wanted to improve the detection method and scheme of laboratory detection. Seventy-four serum samples from outpatients and inpatients from the Affiliated Hospital of North Sichuan Medical College and Nanchong Central Hospital in China from 2 January 2020 to 5 March 2020 were collected 19 patients with the nucleic acids of SARS-CoV-2;10 cases with IgM antibodies against other respiratory viruses;10 patients with IgM antibodies against hepatitis viruses;20 patients with IgM antibodies against rheumatoid factor (RF);15 patients with antinuclear antibody (ANA). Colloidal GICA (kit A and kit B) was used to detect IgM and IgG antibodies against SARS-CoV-2 in patient sera. Positive results of SARS-CoV-2 IgM or SARS-CoV -2 IgG antibodies were analyzed, and possible factors causing false-positive results were found. Then, the sera of SARS- CoV - 2 IgM/IgG positive and 3 early coronavirus disease 2019 (COVID-19) patients were dissociated with an appropriate concentration of urea, and levels of IgM and IgG antibodies against SARS-CoV-2 were redetermined. SPSS v19.0 was used to analyze data. In the sera of 19 patients with SARS-CoV-2 infection 15 of SARS -CoV-2 IgM antibodies and 18 cases SARS-CoV-2 IgG antibodies were detected in kit A;12 cases of SARS-CoV-2 IgM antibodies and 12 cases of SARS-CoV-2 IgG antibodies were detected in kit B;16 cases of SARS-CoV-2 IgM antibodies and 14 cases of SARS-CoV -2 IgG antibodies were detected in 20 patients who had IgM antibodies against RF. In the sera of 15 patients with high - titer ANA, SARS-CoV- 2 IgG antibodies were detected in four cases using kit B. When the urea dissociation concentration was 2 mol/L, 14 of 16 RF- IgM - positive sera detected using kit A turned negative, 13 of 14 SARS- CoV- 2 IgG antibodies turned negative, but patients with COVID-19 detected by kit A did not show negative conversion of IgM or IgG antibodies. When the urea dissociation concentration was 4 mol/L, ANA -positive serum detected by kit B turned negative in four cases, whereas SARS-CoV-2 IgM and IgG antibodies in patients with COVID-19 did not turn negative. After urea dissociation, the SARS-CoV- 2 IgM antibodies detected by kit A and kit B in the sera of three patients with early COVID- 19 did not turn negative. RF could cause false-positive results for SARS-CoV-2 IgM and IgG antibodies detected by kit A, and a high titer of ANA could cause false-positive results of SARS-CoV-2 IgG antibodies detected by kit B. Urea dissociation could be helpful for reducing the probability of false-positive results of SARS-CoV-2 IgM and IgG antibodies. The effect of urea dissociation on the detection sensitivity of early COVID-19 merits further study.

8.
Ann Palliat Med ; 10(7): 7329-7339, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-1311480

ABSTRACT

BACKGROUND: This study aimed to build a radiomics model with deep learning (DL) and human auditing and examine its diagnostic value in differentiating between coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP). METHODS: Forty-three COVID-19 patients, whose diagnoses had been confirmed with reverse-transcriptase polymerase-chain-reaction (RT-PCR) tests, and 60 CAP patients, whose diagnoses had been confirmed with sputum cultures, were enrolled in this retrospective study. The candidate regions of interest (ROIs) on the computed tomography (CT) images of the 103 patients were determined using a DL-based segmentation model powered by transfer learning. These ROIs were manually audited and corrected by 3 radiologists (with an average of 12 years of experience; range 6-17 years) to check the segmentation acceptance for the radiomics analysis. ROI-derived radiomics features were subsequently extracted to build the classification model and processed using 4 different algorithms (L1 regularization, Lasso, Ridge, and Z test) and 4 classifiers, including the logistic regression (LR), multi-layer perceptron (MLP), support vector machine (SVM), and extreme Gradient Boosting (XGboost). A receiver operating characteristic curve (ROC) analysis was conducted to evaluate the performance of the model. RESULTS: Quantitative CT measurements derived from human-audited segmentation results showed that COVID-19 patients had significantly decreased numbers of infected lobes compared to patients in the CAP group {median [interquartile range (IQR)]: 4 [3, 4] and 4 [4, 5]; P=0.031}. The infected percentage (%) of the whole lung was significantly more elevated in the CAP group [6.40 (2.77, 11.11)] than the COVID-19 group [1.83 (0.65, 4.42); P<0.001], and the same trend applied to each lobe, except for the superior lobe of the right lung [1.81 (0.09, 5.28) for COVID-19 vs. 1.32 (0.14, 7.02) for CAP; P=0.649]. Additionally, the highest proportion of infected lesions were observed in the CT value range of (-470, -370) Hounsfield units (HU) in the COVID-19 group. Conversely, the CAP group had a value range of (30, 60) HU. Radiomic model using corrected ROIs exhibited the highest area under ROC (AUC) of 0.990 [95% confidence interval (CI): 0.962-1.000] using Lasso for feature selection and MLP for classification. CONCLUSIONS: The proposed radiomics model based on human-audited segmentation made accurate differential diagnoses of COVID-19 and CAP. The quantification of CT measurements derived from DL could potentially be used as effective biomarkers in current clinical practice.


Subject(s)
COVID-19 , Deep Learning , Computers , Humans , Retrospective Studies , SARS-CoV-2
9.
Nonlinear Dyn ; : 1-13, 2021 May 21.
Article in English | MEDLINE | ID: covidwho-1242810

ABSTRACT

The world is experiencing an ongoing pandemic of coronavirus disease-2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In attempts to control the pandemic, a range of nonpharmaceutical interventions (NPIs) has been implemented worldwide. However, the effect of synchronized NPIs for the control of COVID-19 at temporal and spatial scales has not been well studied. Therefore, a meta-population model that incorporates essential nonlinear processes was constructed to uncover the transmission characteristics of SARS-CoV-2 and then assess the effectiveness of synchronized NPIs on COVID-19 dynamics in China. Regional synchronization of NPIs was observed in China, and it was found that a combination of synchronized NPIs (the travel restrictions, the social distancing and the infection isolation) prevented 93.7% of SARS-CoV-2 infections. The use of synchronized NPIs at the time of the Wuhan lockdown may have prevented as much as 38% of SARS-CoV-2 infections, compared with the unsynchronized scenario. The interconnectivity of the epicenter, the implementation time of synchronized NPIs, and the number of regions considered all affected the performance of synchronized NPIs. The results highlight the importance of using synchronized NPIs in high-risk regions for the control of COVID-19 and shed light on effective strategies for future pandemic responses. Supplementary Information: The online version contains supplementary material available at 10.1007/s11071-021-06505-0.

10.
Chin Med Sci J ; 36(1): 17-26, 2021 Mar 31.
Article in English | MEDLINE | ID: covidwho-1187236

ABSTRACT

Objective This study aimed to determine the association of hyperlipidemia with clinical endpoints among hospitalized patients with COVID-19, especially those with pre-existing cardiovascular diseases (CVDs) and diabetes. Methods This multicenter retrospective cohort study included all patients who were hospitalized due to COVID-19 from 21 hospitals in Hubei province, China between December 31, 2019 and April 21, 2020. Patients who were aged < 18 or ≥ 85 years old, in pregnancy, with acute lethal organ injury (e.g., acute myocardial infarction, severe acute pancreatitis, acute stroke), hypothyroidism, malignant diseases, severe malnutrition, and those with normal lipid profile under lipid-lowering medicines (e.g., statin, niacin, fenofibrate, gemfibrozil, and ezetimibe) were excluded. Propensity score matching (PSM) analysis at 1:1 ratio was performed to minimize baseline differences between patient groups of hyperlipidemia and non-hyperlipidemia. PSM analyses with the same strategies were further conducted for the parameters of hyperlipidemia in patients with increased triglyceride (TG), increased low-density lipoprotein cholesterol (LDL-C), and decreased high-density lipoprotein cholesterol (HDL-C). Mixed-effect Cox model analysis was performed to investigate the associations of the 28-days all-cause deaths of COVID-19 patients with hyperlipidemia and the abnormalities of lipid parameters. The results were verified in male, female patients, and in patients with pre-existing CVDs and type 2 diabetes. Results Of 10 945 inpatients confirmed as COVID-19, there were 9822 inpatients included in the study, comprising 3513 (35.8%) cases without hyperlipidemia and 6309 (64.2%) cases with hyperlipidemia. Based on a mixed-effect Cox model after PSM at 1:1 ratio, hyperlipidemia was not associated with increased or decreased 28-day all-cause death [adjusted hazard ratio (HR), 1.17 (95% CI, 0.95-1.44), P =0.151]. We found that the parameters of hyperlipidemia were not associated with the risk of 28-day all-cause mortality [adjusted HR, 1.23 (95% CI, 0.98-1.55), P = 0.075 in TG increase group; 0.78 (95% CI, 0.57-1.07), P = 0.123 in LDL-C increase group; and 1.12 (95% CI, 0.9-1.39), P = 0.299 in HDL-C decrease group, respectively]. Hyperlipidemia was also not significantly associated with the increased mortality of COVID-19 in patients accompanied with CVDs or type 2 diabetes, and in both male and female cohorts. Conclusion Our study support that the imbalanced lipid profile is not significantly associated with the 28-day all-cause mortality of COVID-19 patients, even in those accompanied with CVDs or diabetes. Similar results were also obtained in subgroup analyses of abnormal lipid parameters. Therefore, hyperlipidemia might be not a major causative factor for poor outcome of COVID-19, which provides guidance for the intervention of inpatients during the epidemic of COVID-19.


Subject(s)
COVID-19/mortality , Hyperlipidemias/complications , Adult , Aged , Aged, 80 and over , COVID-19/complications , COVID-19/therapy , Cardiovascular Diseases/complications , Case-Control Studies , Cause of Death , China/epidemiology , Diabetes Mellitus, Type 2/complications , Female , Hospitalization , Humans , Male , Middle Aged , Propensity Score , Proportional Hazards Models , Retrospective Studies , Risk Factors
12.
Curr Med Res Opin ; 37(6): 917-927, 2021 06.
Article in English | MEDLINE | ID: covidwho-1137872

ABSTRACT

BACKGROUND: To develop a sensitive and clinically applicable risk assessment tool identifying coronavirus disease 2019 (COVID-19) patients with a high risk of mortality at hospital admission. This model would assist frontline clinicians in optimizing medical treatment with limited resources. METHODS: 6415 patients from seven hospitals in Wuhan city were assigned to the training and testing cohorts. A total of 6351 patients from another three hospitals in Wuhan, 2169 patients from outside of Wuhan, and 553 patients from Milan, Italy were assigned to three independent validation cohorts. A total of 64 candidate clinical variables at hospital admission were analyzed by random forest and least absolute shrinkage and selection operator (LASSO) analyses. RESULTS: Eight factors, namely, Oxygen saturation, blood Urea nitrogen, Respiratory rate, admission before the date the national Maximum number of daily new cases was reached, Age, Procalcitonin, C-reactive protein (CRP), and absolute Neutrophil counts, were identified as having significant associations with mortality in COVID-19 patients. A composite score based on these eight risk factors, termed the OURMAPCN-score, predicted the risk of mortality among the COVID-19 patients, with a C-statistic of 0.92 (95% confidence interval [CI] 0.90-0.93). The hazard ratio for all-cause mortality between patients with OURMAPCN-score >11 compared with those with scores ≤ 11 was 18.18 (95% CI 13.93-23.71; p < .0001). The predictive performance, specificity, and sensitivity of the score were validated in three independent cohorts. CONCLUSIONS: The OURMAPCN score is a risk assessment tool to determine the mortality rate in COVID-19 patients based on a limited number of baseline parameters. This tool can assist physicians in optimizing the clinical management of COVID-19 patients with limited hospital resources.


Subject(s)
COVID-19 , Risk Assessment/methods , COVID-19/epidemiology , COVID-19/mortality , China , Hospitalization/statistics & numerical data , Humans , Italy , Risk Factors
13.
Sci Rep ; 10(1): 3963, 2020 03 03.
Article in English | MEDLINE | ID: covidwho-659769

ABSTRACT

The diversity of pathogens associated with acute respiratory infection (ARI) makes diagnosis challenging. Traditional pathogen screening tests have a limited detection range and provide little additional information. We used total RNA sequencing ("meta-transcriptomics") to reveal the full spectrum of microbes associated with paediatric ARI. Throat swabs were collected from 48 paediatric ARI patients and 7 healthy controls. Samples were subjected to meta-transcriptomics to determine the presence and abundance of viral, bacterial, and eukaryotic pathogens, and to reveal mixed infections, pathogen genotypes/subtypes, evolutionary origins, epidemiological history, and antimicrobial resistance. We identified 11 RNA viruses, 4 DNA viruses, 4 species of bacteria, and 1 fungus. While most are known to cause ARIs, others, such as echovirus 6, are rarely associated with respiratory disease. Co-infection of viruses and bacteria and of multiple viruses were commonplace (9/48), with one patient harboring 5 different pathogens, and genome sequence data revealed large intra-species diversity. Expressed resistance against eight classes of antibiotic was detected, with those for MLS, Bla, Tet, Phe at relatively high abundance. In summary, we used a simple total RNA sequencing approach to reveal the complex polymicrobial infectome in ARI. This provided comprehensive and clinically informative information relevant to understanding respiratory disease.


Subject(s)
Metagenome/genetics , Respiratory Tract Infections/microbiology , Respiratory Tract Infections/virology , Bacteria/classification , Bacteria/genetics , Bacteria/pathogenicity , DNA Viruses/classification , DNA Viruses/genetics , DNA Viruses/pathogenicity , Drug Resistance, Microbial/genetics , Female , Fungi/classification , Fungi/genetics , Fungi/pathogenicity , Humans , Male , Phylogeny , RNA Viruses/classification , RNA Viruses/genetics , RNA Viruses/pathogenicity , Viruses/classification , Viruses/genetics , Viruses/pathogenicity
14.
Hepatology ; 73(1): 470-471, 2021 01.
Article in English | MEDLINE | ID: covidwho-1098892

Subject(s)
COVID-19 , Humans , Liver , SARS-CoV-2
15.
Cell Metab ; 33(2): 258-269.e3, 2021 02 02.
Article in English | MEDLINE | ID: covidwho-1064967

ABSTRACT

Corticosteroid therapy is now recommended as a treatment in patients with severe COVID-19. But one key question is how to objectively identify severely ill patients who may benefit from such therapy. Here, we assigned 12,862 COVID-19 cases from 21 hospitals in Hubei Province equally to a training and a validation cohort. We found that a neutrophil-to-lymphocyte ratio (NLR) > 6.11 at admission discriminated a higher risk for mortality. Importantly, however, corticosteroid treatment in such individuals was associated with a lower risk of 60-day all-cause mortality. Conversely, in individuals with an NLR ≤ 6.11 or with type 2 diabetes, corticosteroid treatment was not associated with reduced mortality, but rather increased risks of hyperglycemia and infections. These results show that in the studied cohort corticosteroid treatment is associated with beneficial outcomes in a subset of COVID-19 patients who are non-diabetic and with severe symptoms as defined by NLR.


Subject(s)
Adrenal Cortex Hormones/therapeutic use , COVID-19/drug therapy , Lymphocytes/cytology , Neutrophils/cytology , Adrenal Cortex Hormones/adverse effects , Area Under Curve , COVID-19/mortality , COVID-19/pathology , COVID-19/virology , Diabetes Mellitus, Type 2/complications , Diabetes Mellitus, Type 2/pathology , Humans , Hyperglycemia/complications , Hyperglycemia/pathology , Length of Stay , Proportional Hazards Models , ROC Curve , Risk Factors , SARS-CoV-2/isolation & purification , Severity of Illness Index , Survival Rate , Treatment Outcome
16.
Med (N Y) ; 2(4): 435-447.e4, 2021 Apr 09.
Article in English | MEDLINE | ID: covidwho-1057073

ABSTRACT

Background: To develop a sensitive risk score predicting the risk of mortality in patients with coronavirus disease 2019 (COVID-19) using complete blood count (CBC). Methods: We performed a retrospective cohort study from a total of 13,138 inpatients with COVID-19 in Hubei, China, and Milan, Italy. Among them, 9,810 patients with ≥2 CBC records from Hubei were assigned to the training cohort. CBC parameters were analyzed as potential predictors for all-cause mortality and were selected by the generalized linear mixed model (GLMM). Findings: Five risk factors were derived to construct a composite score (PAWNN score) using the Cox regression model, including platelet counts, age, white blood cell counts, neutrophil counts, and neutrophil:lymphocyte ratio. The PAWNN score showed good accuracy for predicting mortality in 10-fold cross-validation (AUROCs 0.92-0.93) and subsets with different quartile intervals of follow-up and preexisting diseases. The performance of the score was further validated in 2,949 patients with only 1 CBC record from the Hubei cohort (AUROC 0.97) and 227 patients from the Italian cohort (AUROC 0.80). The latent Markov model (LMM) demonstrated that the PAWNN score has good prediction power for transition probabilities between different latent conditions. Conclusions: The PAWNN score is a simple and accurate risk assessment tool that can predict the mortality for COVID-19 patients during their entire hospitalization. This tool can assist clinicians in prioritizing medical treatment of COVID-19 patients. Funding: This work was supported by National Key R&D Program of China (2016YFF0101504, 2016YFF0101505, 2020YFC2004702, 2020YFC0845500), the Key R&D Program of Guangdong Province (2020B1111330003), and the medical flight plan of Wuhan University (TFJH2018006).

17.
Ann Palliat Med ; 10(3): 2429-2438, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1029919

ABSTRACT

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is the causative agent of coronavirus disease 2019 (COVID-19). Lung lesions are considered to be the main damage caused by SARSCoV-2 infection. In addition, liver injury has also been reported to occur during the course of the disease in severe cases. However, the effect of antiviral treatment on liver injury in critically ill patients is not yet clear. METHODS: We retrospectively evaluated the effect of antiviral treatment and antiviral drug arbidol on liver injury in COVID-19 critically ill patients. Baseline characteristics were collected from patients who were admitted to intensive care units of Tongji Hospital in Wuhan, China, and confounders were balanced by propensity score matching (PSM) and inverse probability of treatment weighting (IPTW) analyses. RESULTS: Both the PSM (OR=2.77; 95% CI: 1.03, 7.48; P=0.045) and the IPTW-adjusted (OR=2.33; 95% CI: 1.02, 5.34; P=0.047) results showed that COVID-19 critically ill patients receiving antiviral treatment had a significantly higher risk of liver injury. However, arbidol treatment did not have a significant effect on liver injury (IPTW: OR=2.11; 95% CI: 0.79, 5.67; P=0.14). CONCLUSIONS: Our results show that although arbidol treatment does not seem to be significantly associated with liver injury complications, the overall use of antiviral drugs increases the risk of liver injury for critically ill patients with COVID-19. Antiviral drugs are widely used to treat COVID-19, but we recommend that for critically ill patients, antiviral treatment should be used with caution considering both effectiveness and potential adverse effects.


Subject(s)
Antiviral Agents/adverse effects , COVID-19/drug therapy , Indoles/adverse effects , Liver/drug effects , Antiviral Agents/therapeutic use , Chemical and Drug Induced Liver Injury , China , Critical Illness , Humans , Indoles/therapeutic use , Liver/pathology , Retrospective Studies
18.
Hypertension ; 76(4): 1104-1112, 2020 10.
Article in English | MEDLINE | ID: covidwho-992137

ABSTRACT

The prognostic power of circulating cardiac biomarkers, their utility, and pattern of release in coronavirus disease 2019 (COVID-19) patients have not been clearly defined. In this multicentered retrospective study, we enrolled 3219 patients with diagnosed COVID-19 admitted to 9 hospitals from December 31, 2019 to March 4, 2020, to estimate the associations and prognostic power of circulating cardiac injury markers with the poor outcomes of COVID-19. In the mixed-effects Cox model, after adjusting for age, sex, and comorbidities, the adjusted hazard ratio of 28-day mortality for hs-cTnI (high-sensitivity cardiac troponin I) was 7.12 ([95% CI, 4.60-11.03] P<0.001), (NT-pro)BNP (N-terminal pro-B-type natriuretic peptide or brain natriuretic peptide) was 5.11 ([95% CI, 3.50-7.47] P<0.001), CK (creatine phosphokinase)-MB was 4.86 ([95% CI, 3.33-7.09] P<0.001), MYO (myoglobin) was 4.50 ([95% CI, 3.18-6.36] P<0.001), and CK was 3.56 ([95% CI, 2.53-5.02] P<0.001). The cutoffs of those cardiac biomarkers for effective prognosis of 28-day mortality of COVID-19 were found to be much lower than for regular heart disease at about 19%-50% of the currently recommended thresholds. Patients with elevated cardiac injury markers above the newly established cutoffs were associated with significantly increased risk of COVID-19 death. In conclusion, cardiac biomarker elevations are significantly associated with 28-day death in patients with COVID-19. The prognostic cutoff values of these biomarkers might be much lower than the current reference standards. These findings can assist in better management of COVID-19 patients to improve outcomes. Importantly, the newly established cutoff levels of COVID-19-associated cardiac biomarkers may serve as useful criteria for the future prospective studies and clinical trials.


Subject(s)
Coronavirus Infections , Creatine Kinase, MB Form/blood , Heart Diseases , Natriuretic Peptide, Brain/blood , Pandemics , Peptide Fragments/blood , Pneumonia, Viral , Troponin I/blood , Betacoronavirus/isolation & purification , Biomarkers/blood , COVID-19 , China/epidemiology , Coronavirus Infections/blood , Coronavirus Infections/mortality , Coronavirus Infections/therapy , Female , Heart Diseases/blood , Heart Diseases/mortality , Heart Diseases/virology , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Mortality , Outcome Assessment, Health Care , Pneumonia, Viral/blood , Pneumonia, Viral/mortality , Pneumonia, Viral/therapy , Predictive Value of Tests , Prognosis , Retrospective Studies , SARS-CoV-2
19.
Psychol Med ; : 1-10, 2020 Dec 10.
Article in English | MEDLINE | ID: covidwho-968898

ABSTRACT

BACKGROUND: This study aimed to explore the impacts of COVID-19 outbreak on mental health status in general population in different affected areas in China. METHODS: This was a comparative study including two groups of participants: (1) general population in an online survey in Ya'an and Jingzhou cities during the COVID-19 outbreak from 10-20 February 2020; and (2) matching general population selected from the mental health survey in Ya'an in 2019 (from January to May 2019). General Health Questionnaire (GHQ-12), Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS) were used. RESULTS: There were 1775 participants (Ya'an in 2019 and 2020: 537 respectively; Jingzhou in 2020: 701). Participants in Ya'an had a significantly higher rate of general health problems (GHQ scores ⩾3) in 2020 (14.7%) than in 2019 (5.2%) (p < 0.001). Compared with Ya'an (8.0%), participants in Jingzhou in 2020 had a significantly higher rate of anxiety (SAS scores ⩾50, 24.1%) (p < 0.001). Participants in Ya'an in 2020 had a significantly higher rate of depression (SDS scores ⩾53, 55.3%) than in Jingzhou (16.3%) (p < 0.001). The risk factors of anxiety symptoms included female, number of family members (⩾6 persons), and frequent outdoor activities. The risk factors of depression symptoms included participants in Ya'an and uptake self-protective measures. CONCLUSIONS: The prevalence of psychological symptoms has increased sharply in general population during the COVID-19 outbreak. People in COVID-19 severely affected areas may have higher scores of GHQ and anxiety symptoms. Culture-specific and individual-based psychosocial interventions should be developed for those in need during the COVID-19 outbreak.

20.
Quant Imaging Med Surg ; 10(11): 2191-2207, 2020 Nov.
Article in English | MEDLINE | ID: covidwho-854853

ABSTRACT

Started during December 2019, following the emergence of several COVID-19 cases in Wuhan City, Hubei Province, there was a rapid surge and spread of new COVID-19 cases throughout China. The disease has since been included in the Class B infectious diseases category, as stipulated in the Law of the People's Republic of China on the Prevention and Treatment of Infectious Diseases and shall be managed according to Class A infectious diseases. During the early phases of COVID-19 infection, no specific pulmonary imaging features may be evident, or features overlapping with other pneumonia may be observed. Although CT is not the gold standard for the diagnosis of COVID-19, it nonetheless is a convenient and fast method, and its application can be deployed in community hospitals. Furthermore, CT can be used to render a suggestive diagnosis and evaluate the severity as well as the effects of therapeutic interventions for typical cases of COVID-19. The mobile emergency special CT device described in this document (also known as Emergency Mobile Cabin CT) has several unique characteristics, including its mobility, flexibility, and networking capabilities. Furthermore, it adopts a fully independent isolation design to avoid cross-infection between patients and medical staff. It can play an important role in screening suspected cases presenting with imaging features of COVID-19 in hospitals of various levels that provide care to suspected or confirmed COVID-19 patients as part of the first line procedures of epidemic prevention and control.

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