Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 57
Filter
Add filters

Year range
1.
Gut ; 2021 Nov 26.
Article in English | MEDLINE | ID: covidwho-1622066

ABSTRACT

OBJECTIVE: Helicobacter pylori infection is mostly a family-based infectious disease. To facilitate its prevention and management, a national consensus meeting was held to review current evidence and propose strategies for population-wide and family-based H. pylori infection control and management to reduce the related disease burden. METHODS: Fifty-seven experts from 41 major universities and institutions in 20 provinces/regions of mainland China were invited to review evidence and modify statements using Delphi process and grading of recommendations assessment, development and evaluation system. The consensus level was defined as ≥80% for agreement on the proposed statements. RESULTS: Experts discussed and modified the original 23 statements on family-based H. pylori infection transmission, control and management, and reached consensus on 16 statements. The final report consists of three parts: (1) H. pylori infection and transmission among family members, (2) prevention and management of H. pylori infection in children and elderly people within households, and (3) strategies for prevention and management of H. pylori infection for family members. In addition to the 'test-and-treat' and 'screen-and-treat' strategies, this consensus also introduced a novel third 'family-based H. pylori infection control and management' strategy to prevent its intrafamilial transmission and development of related diseases. CONCLUSION: H. pylori is transmissible from person to person, and among family members. A family-based H. pylori prevention and eradication strategy would be a suitable approach to prevent its intra-familial transmission and related diseases. The notion and practice would be beneficial not only for Chinese residents but also valuable as a reference for other highly infected areas.

2.
Clin Infect Dis ; 73(11): e4154-e4165, 2021 12 06.
Article in English | MEDLINE | ID: covidwho-1559099

ABSTRACT

BACKGROUND: Children and older adults with coronavirus disease 2019 (COVID-19) display a distinct spectrum of disease severity yet the risk factors aren't well understood. We sought to examine the expression pattern of angiotensin-converting enzyme 2 (ACE2), the cell-entry receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the role of lung progenitor cells in children and older patients. METHODS: We retrospectively analyzed clinical features in a cohort of 299 patients with COVID-19. The expression and distribution of ACE2 and lung progenitor cells were systematically examined using a combination of public single-cell RNA-seq data sets, lung biopsies, and ex vivo infection of lung tissues with SARS-CoV-2 pseudovirus in children and older adults. We also followed up patients who had recovered from COVID-19. RESULTS: Compared with children, older patients (>50 years.) were more likely to develop into serious pneumonia with reduced lymphocytes and aberrant inflammatory response (P = .001). The expression level of ACE2 and lung progenitor cell markers were generally decreased in older patients. Notably, ACE2 positive cells were mainly distributed in the alveolar region, including SFTPC positive cells, but rarely in airway regions in the older adults (P < .01). The follow-up of discharged patients revealed a prolonged recovery from pneumonia in the older (P < .025). CONCLUSIONS: Compared to children, ACE2 positive cells are generally decreased in older adults and mainly presented in the lower pulmonary tract. The lung progenitor cells are also decreased. These risk factors may impact disease severity and recovery from pneumonia caused by SARS-Cov-2 infection in older patients.

3.
Preprint in English | EuropePMC | ID: ppcovidwho-294625

ABSTRACT

Background: Although chest computed tomography (CT) is the gold standard for diagnosing the majority of lung conditions, its use in screening patients for coronavirus disease 2019(COVID-19) pneumonia is not recommended. Lung ultrasound (LUS) is an alternative modality. To investigate the characteristics and diagnostic accuracy (DA) of bedside ultrasound for lung lesions in patients with COVID-19 and to determine the factors influencing the DA of lung ultrasound (LUS). Methods: A total of 330 patients with COVID-19 admitted to the hospital between February and March 2020 were retrospectively recruited. The imaging characteristics of LUS and computed tomography (CT) scans were analysed and summarized. DA was calculated using a chest CT scan as the reference standard. Furthermore, a binary logistic regression analysis was conducted to investigate the factors influencing the DA of LUS for interstitial syndrome. Results: The ultrasound findings of COVID-19 patients presented mainly as B lines (195/330, 59.1%), unsmooth or interrupted pleural lines (118/330, 35.8%), consolidation lesions (74/330, 22.4%), and pleural effusion (11/330, 3.33%). Compared with the chest CT scan, the DA of LUS for interstitial syndrome, consolidation, pleural effusion, and pleural thickening were 0.821, 0.927, 0.988, and 0.863, respectively. The diagnostic coincidence rate of LUS and chest CT in the mild, common, severe, and critical groups were 93%, 68.6%, 100%, and 100%, respectively. According to the results of the binary logistic regression, sex, disease duration, experience of the doctor, and involved lobes were independent predictors of the DA for interstitial syndrome. Conclusions: LUS had good diagnostic performance for diagnosing COVID-19 pneumonia, and showed a relatively low DA for interstitial syndrome. Female sex, doctors with less experience, long disease duration, and lesions limited to the upper or lower lobes may decrease the DA.

4.
Front Med (Lausanne) ; 7: 611460, 2020.
Article in English | MEDLINE | ID: covidwho-1389196

ABSTRACT

Background: The data on long-term outcomes of patients infected by SARS-CoV-2 and treated with extracorporeal membrane oxygenation (ECMO) in China are merely available. Methods: A retrospective study included 73 patients infected by SARS-CoV-2 and treated with ECMO in 21 intensive care units in Hubei, China. Data on demographic information, clinical features, laboratory tests, ECMO durations, complications, and living status were collected. Results: The 73 ECMO-treated patients had a median age of 62 (range 33-78) years and 42 (63.6%) were males. Before ECMO initiation, patients had severe respiratory failure on mechanical ventilation with a median PO2/FiO2 of 71.9 [interquartile range (IQR), 58.6-87.0] mmHg and a median PCO2 of 62 [IQR, 43-84] mmHg on arterial blood analyses. The median duration from symptom onset to invasive mechanical ventilation, and to ECMO initiation was19 [IQR, 15-25] days, and 23 [IQR, 19-31] days. Before and after ECMO initiation, the proportions of patients receiving prone position ventilation were 58.9 and 69.9%, respectively. The median duration of ECMO support was 18.5 [IQR 12-30] days. During the treatments with ECMO, major hemorrhages occurred in 31 (42.5%) patients, and oxygenators were replaced in 21 (28.8%) patients. Since ECMO initiation, the 30-day mortality and 60-day mortality were 63.0 and 80.8%, respectively. Conclusions: In Hubei, China, the ECMO-treated patients infected by SARS-CoV-2 were of a broad age range and with severe hypoxemia. The durations of ECMO support, accompanied with increased complications, were relatively long. The long-term mortality in these patients was considerably high.

5.
Sensors (Basel) ; 21(16)2021 Aug 07.
Article in English | MEDLINE | ID: covidwho-1376954

ABSTRACT

In order to achieve high precision from non-contact temperature measurement, the hardware structure of a broadband correlative microwave radiometer, calibration algorithm, and temperature inversion algorithm are innovatively designed in this paper. The correlative radiometer is much more sensitive than a full power radiometer, but its accuracy is challenging to improve due to relatively large phase error. In this study, an error correction algorithm is designed, which reduces the phase error from 69.08° to 4.02°. Based on integral calibration on the microwave temperature measuring system with a known radiation source, the linear relationship between the output voltage and the brightness temperature of the object is obtained. Since the metal aluminum plate, antenna, and transmission line will have a non-linear influence on the receiver system, their temperature characteristics and the brightness temperature of the object are used as the inputs of the neural network to obtain a higher accuracy of inversion temperature. The temperature prediction mean square error of a back propagation (BP) neural network is 0.629 °C, and its maximum error is 3.351 °C. This paper innovatively proposed the high-precision PSO-LM-BP temperature inversion algorithm. According to the global search ability of the particle swarm optimization (PSO) algorithm, the initial weight of the network can be determined effectively, and the Levenberg-Marquardt (LM) algorithm makes use of the second derivative information, which has higher convergence accuracy and iteration efficiency. The mean square error of the PSO-LM-BP temperature inversion algorithm is 0.002 °C, and its maximum error is 0.209 °C.

7.
Clin Infect Dis ; 73(3): e805-e807, 2021 08 02.
Article in English | MEDLINE | ID: covidwho-1338676

ABSTRACT

During April 2020-August 2020, a preemptive testing strategy combined with accessible isolation and symptom screening among people experiencing homelessness in congregant living settings in San Diego, California, contributed to a low incidence proportion of coronavirus disease 2019 (0.9%). Proactively addressing challenges specific to a vulnerable population may prove impactful.


Subject(s)
COVID-19 , Homeless Persons , Humans , Pandemics , SARS-CoV-2 , Vulnerable Populations
8.
BMJ Open ; 11(7): e052451, 2021 07 22.
Article in English | MEDLINE | ID: covidwho-1322828

ABSTRACT

OBJECTIVES: To observe the weight change in Chinese youth during a 4-month COVID-19 lockdown, and the association between weight change and mental health, physical activity and sedentary time changes, and dietary habits. DESIGN: A retrospective observational study. SETTINGS: Two universities located in Zhejiang and Hunan provinces, China. PARTICIPANTS: This study enrolled 12 889 college students whose body weight was measured before the lockdown (1 December 2019-20 January 2020) at the two universities, and reported their weight measured at home or community after the end of the lockdown (1-23 May 2020) via an online follow-up questionnaire. PRIMARY AND SECONDARY OUTCOME MEASURES: The primary outcome was the weight change in Chinese youth during a 4-month lockdown resulting from the COVID-19 pandemic. The secondary outcomes were the relationships of weight change to COVID-19-related stress, depression, anxiety, physical activity and sedentary time changes, and dietary habits. RESULTS: Participants' ages ranged from 17 to 27 years (M=19, SD=1) with 80.2% identified as female. The average absolute and relative changes in body weight were 2.6 (95% CI 2.0 to 3.2)) kg and 4.2% (95% CI 4.0% to 4.3%) for men, and 2.1 (1.9 to 2.4) kg and 4.2% (95% CI 3.9% to 4.4%) for women. An increase in overweight and obese individuals according to Asian cut-off points as a demographic percentage by 4.5% and 2.7% and 4.8% and 3.4% in men and women, respectively (P<0.001), was observed. Weight gain was significantly associated with increased sedentary time and an increase in COVID-19-related stress and depression score. CONCLUSION: The present study's results suggest that the risk of weight gain in Chinese youth during the lockdown increased and that strategies to decrease sedentary time and improve mental health may be warranted to mitigate weight gain during and after the COVID-19 pandemic.


Subject(s)
COVID-19 , Pandemics , Adolescent , Adult , China/epidemiology , Communicable Disease Control , Female , Humans , Male , SARS-CoV-2 , Weight Gain , Young Adult
9.
J Thorac Dis ; 13(6): 3628-3642, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1296313

ABSTRACT

Background: To analyze the clinical characteristics and predictors for mortality of adult younger than 60 years old with severe coronavirus disease 2019 (COVID-19). Methods: We retrospectively retrieved data for 152 severe inpatients with COVID-19 including 60 young patients in the Eastern Campus of Wuhan University affiliated Renmin Hospital in Wuhan, China, from January 31, 2020 to February 20, 2020. We recorded and analyzed patients' demographic, clinical, laboratory, and chest CT findings, treatment and outcomes data. Results: Of those 60 severe young patients, 15 (25%) were died. Male was more predominant in deceased young patients (12, 80%) than that in recovered young patients (22, 49%). Hypertension was more common among deceased young patients (8, 53%) than that in recovered young patients (7, 16%). Compared with the recovered young patients, more deceased young patients presented with sputum (11, 73%), dyspnea (12, 80%) and fatigue (13, 87%). Only sputum, PSI and neutrophil counts were remained as independent predictors of death in a multivariate logistic regression model. Among ARDS patients, the recovered were administrated with corticosteroid earlier and anticoagulation. The addition of neutrophil counts >6.3×109/L to the SMART-COP score resulted in improved area under the curves. Conclusions: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) infection in young deceased patients appears to cause exuberant inflammatory responses, leading to compromised oxygen exchange, coagulation and multi-organ dysfunction. In addition, young patients with ARDS could benefit from adjuvant early corticosteroid and anticoagulation therapy. The expanded SMART-COP could predict the fatal outcomes with optimal efficiency.

10.
Eur Radiol ; 32(1): 205-212, 2022 Jan.
Article in English | MEDLINE | ID: covidwho-1293361

ABSTRACT

OBJECTIVES: Early recognition of coronavirus disease 2019 (COVID-19) severity can guide patient management. However, it is challenging to predict when COVID-19 patients will progress to critical illness. This study aimed to develop an artificial intelligence system to predict future deterioration to critical illness in COVID-19 patients. METHODS: An artificial intelligence (AI) system in a time-to-event analysis framework was developed to integrate chest CT and clinical data for risk prediction of future deterioration to critical illness in patients with COVID-19. RESULTS: A multi-institutional international cohort of 1,051 patients with RT-PCR confirmed COVID-19 and chest CT was included in this study. Of them, 282 patients developed critical illness, which was defined as requiring ICU admission and/or mechanical ventilation and/or reaching death during their hospital stay. The AI system achieved a C-index of 0.80 for predicting individual COVID-19 patients' to critical illness. The AI system successfully stratified the patients into high-risk and low-risk groups with distinct progression risks (p < 0.0001). CONCLUSIONS: Using CT imaging and clinical data, the AI system successfully predicted time to critical illness for individual patients and identified patients with high risk. AI has the potential to accurately triage patients and facilitate personalized treatment. KEY POINT: • AI system can predict time to critical illness for patients with COVID-19 by using CT imaging and clinical data.


Subject(s)
COVID-19 , Artificial Intelligence , Humans , Retrospective Studies , SARS-CoV-2 , Tomography, X-Ray Computed
11.
Nat Commun ; 12(1): 3907, 2021 06 23.
Article in English | MEDLINE | ID: covidwho-1281720

ABSTRACT

SARS-CoV-2 (2019-nCoV) is the pathogenic coronavirus responsible for the global pandemic of COVID-19 disease. The Spike (S) protein of SARS-CoV-2 attaches to host lung epithelial cells through the cell surface receptor ACE2, a process dependent on host proteases including TMPRSS2. Here, we identify small molecules that reduce surface expression of TMPRSS2 using a library of 2,560 FDA-approved or current clinical trial compounds. We identify homoharringtonine and halofuginone as the most attractive agents, reducing endogenous TMPRSS2 expression at sub-micromolar concentrations. These effects appear to be mediated by a drug-induced alteration in TMPRSS2 protein stability. We further demonstrate that halofuginone modulates TMPRSS2 levels through proteasomal-mediated degradation that involves the E3 ubiquitin ligase component DDB1- and CUL4-associated factor 1 (DCAF1). Finally, cells exposed to homoharringtonine and halofuginone, at concentrations of drug known to be achievable in human plasma, demonstrate marked resistance to SARS-CoV-2 infection in both live and pseudoviral in vitro models. Given the safety and pharmacokinetic data already available for the compounds identified in our screen, these results should help expedite the rational design of human clinical trials designed to combat active COVID-19 infection.


Subject(s)
COVID-19/drug therapy , Homoharringtonine/pharmacology , Piperidines/pharmacology , Quinazolinones/pharmacology , SARS-CoV-2/drug effects , SARS-CoV-2/physiology , Serine Endopeptidases/metabolism , Virus Internalization/drug effects , Angiotensin-Converting Enzyme 2/metabolism , Animals , COVID-19/metabolism , COVID-19/pathology , COVID-19/virology , Cells, Cultured , Chlorocebus aethiops , High-Throughput Screening Assays/methods , Humans , Lung/drug effects , Lung/metabolism , Lung/pathology , Lung/virology , Mice , Protein Synthesis Inhibitors/pharmacology , SARS-CoV-2/isolation & purification , Spike Glycoprotein, Coronavirus/metabolism
12.
Front Cardiovasc Med ; 8: 633539, 2021.
Article in English | MEDLINE | ID: covidwho-1266656

ABSTRACT

Background: Lung injury is a common condition among hospitalized patients with coronavirus disease 2019 (COVID-19). However, whether lung ultrasound (LUS) score predicts all-cause mortality in patients with COVID-19 is unknown. The aim of the present study was to explore the predictive value of lung ultrasound score for mortality in patients with COVID-19. Methods: Patients with COVID-19 who underwent lung ultrasound were prospectively enrolled from three hospitals in Wuhan, China between February 2020 and March 2020. Demographic, clinical, and laboratory data were collected from digital patient records. Lung ultrasound scores were analyzed offline by two observers. Primary outcome was in-hospital mortality. Results: Of the 402 patients, 318 (79.1%) had abnormal lung ultrasound. Compared with survivors (n = 360), non-survivors (n = 42) presented with more B2 lines, pleural line abnormalities, pulmonary consolidation, and pleural effusion (all p < 0.05). Moreover, non-survivors had higher global and anterolateral lung ultrasound score than survivors. In the receiver operating characteristic analysis, areas under the curve were 0.936 and 0.913 for global and anterolateral lung ultrasound score, respectively. A cutoff value of 15 for global lung ultrasound score had a sensitivity of 92.9% and specificity of 85.3%, and 9 for anterolateral score had a sensitivity of 88.1% and specificity of 83.3% for prediction of death. Kaplan-Meier analysis showed that both global and anterolateral scores were strong predictors of death (both p < 0.001). Multivariate Cox regression analysis showed that global lung ultrasound score was an independent predictor (hazard ratio, 1.08; 95% confidence interval, 1.01-1.16; p = 0.03) of death together with age, male sex, C-reactive protein, and creatine kinase-myocardial band. Conclusion: Lung ultrasound score as a semiquantitative tool can be easily measured by bedside lung ultrasound. It is a powerful predictor of in-hospital mortality and may play a crucial role in risk stratification of patients with COVID-19.

13.
Clin Nutr ; 2021 Jun 07.
Article in English | MEDLINE | ID: covidwho-1260691

ABSTRACT

BACKGROUND: About 10-20% of patients with Coronavirus disease 2019 (COVID-19) infection progressed to severe illness within a week or so after initially diagnosed as mild infection. Identification of this subgroup of patients was crucial for early aggressive intervention to improve survival. The purpose of this study was to evaluate whether computer tomography (CT) - derived measurements of body composition such as myosteatosis indicating fat deposition inside the muscles could be used to predict the risk of transition to severe illness in patients with initial diagnosis of mild COVID-19 infection. METHODS: Patients with laboratory-confirmed COVID-19 infection presenting initially as having the mild common-subtype illness were retrospectively recruited between January 21, 2020 and February 19, 2020. CT-derived body composition measurements were obtained from the initial chest CT images at the level of the twelfth thoracic vertebra (T12) and were used to build models to predict the risk of transition. A myosteatosis nomogram was constructed using multivariate logistic regression incorporating both clinical variables and myosteatosis measurements. The performance of the prediction models was assessed by receiver operating characteristic (ROC) curve including the area under the curve (AUC). The performance of the nomogram was evaluated by discrimination, calibration curve, and decision curve. RESULTS: A total of 234 patients were included in this study. Thirty-one of the enrolled patients transitioned to severe illness. Myosteatosis measurements including SM-RA (skeletal muscle radiation attenuation) and SMFI (skeletal muscle fat index) score fitted with SMFI, age and gender, were significantly associated with risk of transition for both the training and validation cohorts (P < 0.01). The nomogram combining the SM-RA, SMFI score and clinical model improved prediction for the transition risk with an AUC of 0.85 [95% CI, 0.75 to 0.95] for the training cohort and 0.84 [95% CI, 0.71 to 0.97] for the validation cohort, as compared to the nomogram of the clinical model with AUC of 0.75 and 0.74 for the training and validation cohorts respectively. Favorable clinical utility was observed using decision curve analysis. CONCLUSION: We found CT-derived measurements of thoracic myosteatosis to be associated with higher risk of transition to severe illness in patients affected by COVID-19 who presented initially as having the mild common-subtype infection. Our study showed the relevance of skeletal muscle examination in the overall assessment of disease progression and prognosis of patients with COVID-19 infection.

14.
Res Sq ; 2021 Apr 23.
Article in English | MEDLINE | ID: covidwho-1237034

ABSTRACT

The endo-lysosomal pathway plays an important role in pathogen clearance and both bacteria and viruses have evolved complex mechanisms to evade this host system. Here, we describe a novel aspect of coronaviral infection, whereby the master transcriptional regulator of lysosome biogenesis - TFEB - is targeted for proteasomal-mediated degradation upon viral infection. Through mass spectrometry analysis and an unbiased siRNA screen, we identify that TFEB protein stability is coordinately regulated by the E3 ubiquitin ligase subunit DCAF7 and the PAK2 kinase. In particular, viral infection triggers marked PAK2 activation, which in turn, phosphorylates and primes TFEB for ubiquitin-mediated protein degradation. Deletion of either DCAF7 or PAK2 blocks viral-mediated TFEB degradation and protects against viral-induced cytopathic effects. We further derive a series of small molecules that interfere with the DCAF7-TFEB interaction. These agents inhibit viral-triggered TFEB degradation and demonstrate broad anti-viral activities including attenuating in vivo SARS-CoV-2 infection. Together, these results delineate a viral-triggered pathway that disables the endogenous cellular system that maintains lysosomal function and suggest that small molecule inhibitors of the E3 ubiquitin ligase DCAF7 represent a novel class of endo-lysosomal, host-directed, anti-viral therapies.

15.
Int J Med Sci ; 18(11): 2394-2400, 2021.
Article in English | MEDLINE | ID: covidwho-1222284

ABSTRACT

Objectives: Comparative analysis of laboratory data in moderate-to-severe COVID-19 patients presenting with or without ground-glass opacities (GGOs). Methods: This retrospective study examined 61 patients with moderate-to-severe COVID-19, as defined by the report of the WHO-China Joint Mission on COVID-19. All patients were admitted to the Department of Infectious Diseases, Wuhan Union Hospital from Dec 28, 2019 to Feb 22, 2020 and classified into a GGO group or a non-GGO group based on CT results. The clinical characteristics and laboratory data of the two groups were compared. Data were analyzed using univariate and multivariate analysis, and using receiver operating characteristic (ROC) analysis. Results: Forty-five patients were in the GGO group (73.8%, 21 females, 24 males, mean age 54.8±17.8 years) and 16 were in the non-GGO group (26.2%, 11 females, 5 males, mean age 53±14.9 years). The levels of IL-2, IL-4, and IFN-γ were greater in the GGO group (all P<0.05). ROC analysis indicated that an elevated level of IL-2 was a good predictor of GGO (area under the curve: 0.716, optimal cutoff: 3.205 pg/mL, 53.8% sensitivity, 87.5% specificity, p<0.05). Multivariate analysis showed that IL-2 level was a significant and independent risk factor for lung GGO (OR: 8.167; 95% CI: 1.63, 40.8; P<0.05). Conclusions: There were correlations between GGO in the lungs of patients with moderate-to-severe COVID-19 and the levels of IL-2, IL-4, and INF-γ. IL-2 was a significant and independent risk factor for GGO. These findings provide a basis for studying the mechanism of pulmonary lesions in COVID-19 patients.


Subject(s)
COVID-19/diagnostic imaging , Cytokines/blood , Lung/diagnostic imaging , SARS-CoV-2 , Tomography, X-Ray Computed/methods , Adult , Aged , COVID-19/immunology , Female , Humans , Male , Middle Aged , Severity of Illness Index
16.
Journal of Medical Internet Research ; 23(4), 2021.
Article in English | ProQuest Central | ID: covidwho-1209585

ABSTRACT

Background: Effectively and efficiently diagnosing patients who have COVID-19 with the accurate clinical type of the disease is essential to achieve optimal outcomes for the patients as well as to reduce the risk of overloading the health care system. Currently, severe and nonsevere COVID-19 types are differentiated by only a few features, which do not comprehensively characterize the complicated pathological, physiological, and immunological responses to SARS-CoV-2 infection in the different disease types. In addition, these type-defining features may not be readily testable at the time of diagnosis. Objective: In this study, we aimed to use a machine learning approach to understand COVID-19 more comprehensively, accurately differentiate severe and nonsevere COVID-19 clinical types based on multiple medical features, and provide reliable predictions of the clinical type of the disease. Methods: For this study, we recruited 214 confirmed patients with nonsevere COVID-19 and 148 patients with severe COVID-19. The clinical characteristics (26 features) and laboratory test results (26 features) upon admission were acquired as two input modalities. Exploratory analyses demonstrated that these features differed substantially between two clinical types. Machine learning random forest models based on all the features in each modality as well as on the top 5 features in each modality combined were developed and validated to differentiate COVID-19 clinical types. Results: Using clinical and laboratory results independently as input, the random forest models achieved >90% and >95% predictive accuracy, respectively. The importance scores of the input features were further evaluated, and the top 5 features from each modality were identified (age, hypertension, cardiovascular disease, gender, and diabetes for the clinical features modality, and dimerized plasmin fragment D, high sensitivity troponin I, absolute neutrophil count, interleukin 6, and lactate dehydrogenase for the laboratory testing modality, in descending order). Using these top 10 multimodal features as the only input instead of all 52 features combined, the random forest model was able to achieve 97% predictive accuracy. Conclusions: Our findings shed light on how the human body reacts to SARS-CoV-2 infection as a unit and provide insights on effectively evaluating the disease severity of patients with COVID-19 based on more common medical features when gold standard features are not available. We suggest that clinical information can be used as an initial screening tool for self-evaluation and triage, while laboratory test results should be applied when accuracy is the priority.

17.
Int J Med Sci ; 18(10): 2128-2136, 2021.
Article in English | MEDLINE | ID: covidwho-1190599

ABSTRACT

Purpose: To analyze the chest CT imaging findings of patients with initial negative RT-PCR and to compare with the CT findings of the same sets of patients when the RT-PCR turned positive for SARS-CoV-2 a few days later. Materials and methods: A total of 32 patients (8 males and 24 females; 52.9±7years old) with COVID-19 from 27 January and 26 February 2020 were enrolled in this retrospective study. Clinical and radiological characteristics were analyzed. Results: The median period (25%, 75%) between initial symptoms and the first chest CT, the initial negative RT-PCR, the second CT and the positive RT-PCR were 7(4.25,11.75), 7(5,10.75), 15(11,23) and 14(10,22) days, respectively. Ground glass opacities was the most frequent CT findings at both the first and second CTs. Consolidation was more frequently observed on lower lobes, and more frequently detected during the second CT (64.0%) with positive RT-PCR than the first CT with initial negative RT-PCR (53.1%). The median of total lung severity score and the number of lobes affected had significant difference between twice chest CT (P=0.007 and P=0.011, respectively). Conclusion: In the first week of disease course, CT was sensitive to the COVID-19 with initial negative RT-PCR. Throat swab test turned positive while chest CT mostly demonstrated progression.


Subject(s)
COVID-19 Nucleic Acid Testing/methods , COVID-19/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Tomography, X-Ray Computed/methods , COVID-19/etiology , Female , Humans , Male , Middle Aged , Pneumonia, Viral/etiology , Reverse Transcriptase Polymerase Chain Reaction , Thorax , Time Factors
18.
Int J Infect Dis ; 105: 442-447, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1147704

ABSTRACT

OBJECTIVE: The emergence of a novel coronavirus, SARS-CoV-2, and its subsequent spread outside of Wuhan, China, led to the human society experiencing a pandemic of coronavirus disease 2019 (COVID-19). While the development of vaccines and pharmaceutical treatments are ongoing, government authorities in China have implemented unprecedented non-pharmaceutical interventions as primary barriers to curb the spread of the deadly SARS-CoV-2 virus. Although the decline of COVID-19 cases coincided with the implementation of such interventions, we searched for evidence to demonstrate the efficacy of these interventions, since artifactual factors, such as the environment, the pathogen itself, and the phases of epidemic, may also alter the patterns of case development. METHODS: We surveyed common viral respiratory infections that have a similar pattern of transmission, tropism, and clinical manifestation, as COVID-19 under a series of non-pharmaceutical interventions during the current pandemic season. We then compared this data with historical data from previous seasons without such interventions. RESULTS: Our survey showed that the rates of common respiratory infections, such as influenza and respiratory syncytial virus infections, decreased dramatically from 13.7% (95% CI, 10.82-16.58) and 4.64% (95% CI, 2.88-7.64) in previous years to 0.73% (95% CI, 0.02-1.44) and 0.0%, respectively, in the current season. CONCLUSIONS: Our surveillance provides compelling evidence that non-pharmaceutical interventions are cost-effective ways to curb the spread of contagious agents, and may represent the only practical approach to limit the evolving epidemic until specific vaccines and pharmaceutical treatments are available.


Subject(s)
COVID-19/prevention & control , Communicable Disease Control/methods , Respiratory Tract Infections/epidemiology , Adolescent , Adult , Aged , COVID-19/epidemiology , China/epidemiology , Female , Humans , Influenza, Human/epidemiology , Male , Middle Aged , Pandemics/prevention & control , Respiratory Syncytial Virus Infections/epidemiology , Respiratory Tract Infections/virology , SARS-CoV-2 , Virus Diseases/epidemiology , Young Adult
19.
Health Qual Life Outcomes ; 19(1): 103, 2021 Mar 22.
Article in English | MEDLINE | ID: covidwho-1147072

ABSTRACT

BACKGROUND: More than 210,000 medical workers have fought against the outbreak of Coronavirus Disease 2019 (COVID-19) in Hubei in China since December 2019. However, the prevalence of mental health problems in frontline medical staff after fighting COVID-19 is still unknown. METHODS: Medical workers in Wuhan and other cities in Hubei Province were invited to participate a cross-sectional and convenience sampling online survey, which assessed the prevalence of anxiety, insomnia, depression, and post-traumatic stress disorder (PTSD). RESULTS: A total of 1,091 responses (33% male and 67% female) were valid for statistical analysis. The prevalence was anxiety 53%, insomnia 79%, depression 56%, and PTSD 11%. Healthcare workers in Wuhan were more likely to face risks of anxiety (56% vs. 52%, P = 0.03) and PTSD (15% vs. 9%, P = 0.03) than those in other cities of Hubei. In terms of educational attainment, those with doctoral and masters' (D/M) degrees may experience more anxiety (median of 7.0, [interquartile range (IQR) 2.0-8.5] vs. median 5.0 [IQR 5.0-8.0], P = 0.02) and PTSD (median 26.0 [IQR 19.5-33.0] vs. median 23.0 [IQR 19.0-31.0], P = 0.04) than those with lower educational degrees. CONCLUSIONS: The mental problems were an important issue for the healthcare workers after COVID-19. Thus, an early intervention on such mental problems is necessary for healthcare workers.


Subject(s)
COVID-19 , Depressive Disorder/epidemiology , Disease Outbreaks , Health Personnel/psychology , Occupational Diseases/epidemiology , SARS-CoV-2 , Adult , China/epidemiology , Cross-Sectional Studies , Depressive Disorder/psychology , Female , Humans , Male , Middle Aged , Occupational Diseases/psychology , Prevalence , Psychometrics , Quality of Life , Surveys and Questionnaires , Young Adult
20.
PeerJ ; 9: e11091, 2021.
Article in English | MEDLINE | ID: covidwho-1143799

ABSTRACT

Background: The COVID-19 pandemic has led to a spike in deleterious mental health. This dual-center retrospective cross-sectional study assessed the prevalence of depression in young adults during this pandemic and explored its association with various physical fitness measures. Methods: This study enrolled 12,889 (80% female) young adults (mean age 20 ± 1) who performed a National Student Physical Fitness battery from December 1st, 2019, to January 20th, 2020, and completed a questionnaire including Beck's Depression Inventory in May 2020. Independent associations between prior physical fitness and depression during the pandemic were assessed using multivariable linear and binary logistic regressions accordingly, covariates including age, dwelling location, economic level, smoking, alcohol, living status, weight change, and exercise volume during the pandemic. Sex- and baseline stress-stratified analyses were performed. Results: Of the study population 13.9% of men and 15.0% of women sampled qualified for a diagnosis of depression. After multivariable adjustment, anaerobic (mean change 95% CI -3.3 [-4.8 to 1.8]) aerobic (-1.5 [-2.64 to -0.5]), explosive (-1.64 [-2.7 to -0.6]) and muscular (-1.7 [-3.0 to -0.5]) fitness were independently and inversely associated with depression for the overall population. These remained consistent after sex- and baseline stress-stratification. In binary logistic regression, the combined participants with moderate, high or excellent fitness also showed a much lower risk compared to those least fit in anaerobic (odd ratio (OR) 95% CI 0.68 [0.55-0.82]), aerobic (0.80 [0.68-0.91]), explosive (0.72 [0.61-0.82]), and muscular (0.66 [0.57-0.75]) fitness. Conclusions: These findings suggest that prior physical fitness may be inversely associated with depression in young adults during a pandemic.

SELECTION OF CITATIONS
SEARCH DETAIL
...