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1.
Indian J Med Microbiol ; 38(1): 18-23, 2020.
Article in English | MEDLINE | ID: covidwho-688890

ABSTRACT

Background and Objectives: Timely diagnosis is essential for the containment of the disease and breaks in the chain of transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The present situation demands the countries to scale up their testing and design innovative strategies to conserve diagnostic kits and reagents. The pooling of samples saves time, workforce and most importantly diagnostic kits and reagents. In the present study, we tried to define the pool size that could be applied with acceptable confidence for testing. Materials and Methods: We used repeatedly tested positive clinical sample elutes having different levels of SARS CoV 2 RNA and negative sample elutes to prepare seven series of 11 pools each, having pool sizes ranging from 2 to 48 samples to estimate the optimal pool size. Each pool had one positive sample elute in different compositions. All the pools were tested by SARS CoV 2 reverse transcriptase quantitative polymerase chain reaction. Results: Out of the 77 pools, only 53 (68.8%) were found positive. The sensitivity of pools of 2-48 samples was decreased from 100% (95% confidence interval [CL]; 98.4-100) to 41.41% (95% CL; 34.9-48.1). The maximum size of the pool with acceptable sensitivity (>95%) was found to be of six samples. For the pool size of six samples, the sensitivity was 97.8% and the efficiency of pooling was 0.38. Conclusions: The pooling of samples is a practical way for scaling up testing and ultimately containing the further spread of the CoV disease 2019 pandemic.


Subject(s)
Betacoronavirus/isolation & purification , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Reverse Transcriptase Polymerase Chain Reaction/methods , Specimen Handling/methods , Betacoronavirus/genetics , Humans , Pandemics , Sensitivity and Specificity
2.
Acad Emerg Med ; 27(6): 461-468, 2020 06.
Article in English | MEDLINE | ID: covidwho-686322

ABSTRACT

OBJECTIVES: Rapid and early severity-of-illness assessment appears to be important for critically ill patients with novel coronavirus disease (COVID-19). This study aimed to evaluate the performance of the rapid scoring system on admission of these patients. METHODS: A total of 138 medical records of critically ill patients with COVID-19 were included in the study. Demographic and clinical characteristics on admission used for calculating Modified Early Warning Score (MEWS) and Rapid Emergency Medicine Score (REMS) and outcomes (survival or death) were collected for each case and extracted for analysis. All patients were divided into two age subgroups (<65 years and ≥65 years). The receiver operating characteristic (ROC) curve analyses were performed for overall patients and both subgroups. RESULTS: The median [25th quartile, 75th quartile] of MEWS of survivors versus nonsurvivors were 1 [1, 2] and 2 [1, 3] and those of REMS were 5 [2, 6] and 7 [6, 10], respectively. In overall analysis, the area under the ROC curve for the REMS in predicting mortality was 0.833 (95% confidence interval [CI] = 0.737 to 0.928), higher than that of MEWS (0.677, 95% CI = 0.541 to 0.813). An optimal cutoff of REMS (≥6) had a sensitivity of 89.5%, a specificity of 69.8%, a positive predictive value of 39.5%, and a negative predictive value of 96.8%. In the analysis of subgroup of patients aged <65 years, the area under the ROC curve for the REMS in predicting mortality was 0.863 (95% CI = 0.743 to 0.941), higher than that of MEWS (0.603, 95% CI = 0.462 to 0.732). CONCLUSION: To our knowledge, this study was the first exploration on rapid scoring systems for critically ill patients with COVID-19. The REMS could provide emergency clinicians with an effective adjunct risk stratification tool for critically ill patients with COVID-19, especially for the patients aged <65 years. The effectiveness of REMS for screening these patients is attributed to its high negative predictive value.


Subject(s)
Coronavirus Infections/mortality , Hospital Mortality , Pneumonia, Viral/mortality , Adult , Age Factors , Aged , Aged, 80 and over , Betacoronavirus , Blood Pressure , Cerebrovascular Disorders/epidemiology , China , Comorbidity , Coronavirus , Critical Illness , Early Warning Score , Emergency Medicine , Female , Glasgow Coma Scale , Humans , Lung Diseases/epidemiology , Male , Middle Aged , Oxygen/metabolism , Pandemics , Prognosis , ROC Curve , Respiratory Rate , Retrospective Studies , Risk Assessment , Sensitivity and Specificity
4.
J Clin Microbiol ; 58(8)2020 Jul 23.
Article in English | MEDLINE | ID: covidwho-684350

ABSTRACT

Molecular testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the gold standard for diagnosis of coronavirus disease 2019 (COVID-19), but the clinical performance of these tests is still poorly understood, particularly with regard to disease course, patient-specific factors, and viral shedding. From 10 March to 1 May 2020, NewYork-Presbyterian laboratories performed 27,377 SARS-CoV-2 molecular assays from 22,338 patients. Repeat testing was performed for 3,432 patients, of which 2,413 had initial negative and 802 had initial positive results. Repeat-tested patients were more likely to have severe disease and low viral loads. The negative predictive value of the first-day result among repeat-tested patients was 81.3% The clinical sensitivity of SARS-CoV-2 molecular assays was estimated between 58% and 96%, depending on the unknown number of false-negative results in single-tested patients. Conversion to negative was unlikely to occur before 15 to 20 days after initial testing or 20 to 30 days after the onset of symptoms, with 50% conversion occurring at 28 days after initial testing. Conversion from first-day negative to positive results increased linearly with each day of testing, reaching 25% probability in 20 days. Sixty patients fluctuated between positive and negative results over several weeks, suggesting that caution is needed when single-test results are acted upon. In summary, our study provides estimates of the clinical performance of SARS-CoV-2 molecular assays and suggests time frames for appropriate repeat testing, namely, 15 to 20 days after a positive test and the same day or next 2 days after a negative test for patients with high suspicion for COVID-19.


Subject(s)
Betacoronavirus/isolation & purification , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Diagnostic Tests, Routine/methods , Pneumonia, Viral/diagnosis , Adolescent , Adult , Aged , Aged, 80 and over , Betacoronavirus/genetics , Child , Child, Preschool , Coronavirus Infections/pathology , Coronavirus Infections/virology , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , New York , Pandemics , Pneumonia, Viral/pathology , Pneumonia, Viral/virology , Predictive Value of Tests , Sensitivity and Specificity , Viral Load , Young Adult
5.
Int J Med Sci ; 17(12): 1773-1782, 2020.
Article in English | MEDLINE | ID: covidwho-680183

ABSTRACT

Rationale: Acute respiratory distress syndrome (ARDS) is one of the major reasons for ventilation and intubation management of COVID-19 patients but there is no noninvasive imaging monitoring protocol for ARDS. In this study, we aimed to develop a noninvasive ARDS monitoring protocol based on traditional quantitative and radiomics approaches from chest CT. Methods: Patients diagnosed with COVID-19 from Jan 20, 2020 to Mar 31, 2020 were enrolled in this study. Quantitative and radiomics data were extracted from automatically segmented regions of interest (ROIs) of infection regions in the lungs. ARDS existence was measured by Pa02/Fi02 <300 in artery blood samples. Three different models were constructed by using the traditional quantitative imaging metrics, radiomics features and their combinations, respectively. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the models. Decision curve analysis (DCA) was used to test the clinical value of the proposed model. Results: The proposed models were constructed using 352 CT images from 86 patients. The median age was 49, and the male proportion was 61.9%. The training dataset and the validation dataset were generated by randomly sampling the patients with a 2:1 ratio. Chi-squared test showed that there was no significant difference in baseline of the enrolled patients between the training and validation datasets. The areas under the ROC curve (AUCs) of the traditional quantitative model, radiomics model and combined model in the validation dataset was 0.91, 0.91 and 0.94, respectively. Accordingly, the sensitivities were 0.55, 0.82 and 0.58, while the specificities were 0.97, 0.86 and 0.98. The DCA curve showed that when threshold probability for a doctor or patients is within a range of 0 to 0.83, the combined model adds more net benefit than "treat all" or "treat none" strategies, while the traditional quantitative model and radiomics model could add benefit in all threshold probability. Conclusions: It is feasible to monitor ARDS from CT images using radiomics or traditional quantitative analysis in COVID-19. The radiomics model seems to be the most practical one for possible clinical use. Multi-center validation with a larger number of samples is recommended in the future.


Subject(s)
Betacoronavirus , Coronavirus Infections/complications , Lung/diagnostic imaging , Models, Theoretical , Pandemics , Pneumonia, Viral/complications , Respiratory Distress Syndrome, Adult/diagnostic imaging , Tomography, X-Ray Computed , Adult , Algorithms , Area Under Curve , China/epidemiology , Coronavirus Infections/epidemiology , Datasets as Topic , Female , Humans , Image Processing, Computer-Assisted/methods , Male , Middle Aged , Pneumonia, Viral/epidemiology , ROC Curve , Respiratory Distress Syndrome, Adult/etiology , Retrospective Studies , Sampling Studies , Sensitivity and Specificity , Translational Medical Research/methods , Workflow
6.
PLoS One ; 15(7): e0236564, 2020.
Article in English | MEDLINE | ID: covidwho-676213

ABSTRACT

To circumvent the limited availability of RNA extraction reagents, we aimed to develop a protocol for direct RT-qPCR to detect SARS-CoV-2 in nasopharyngeal swabs without RNA extraction. Nasopharyngeal specimens positive for SARS-CoV-2 and other coronaviruses collected in universal viral transport (UVT) medium were pre-processed by several commercial and laboratory-developed methods and tested by RT-qPCR assays without RNA extraction using different RT-qPCR master mixes. The results were compared to that of standard approach that involves RNA extraction. Incubation of specimens at 65°C for 10 minutes along with the use of TaqPath™ 1-Step RT-qPCR Master Mix provides higher analytical sensitivity for detection of SARS-CoV-2 RNA than many other conditions tested. The optimized direct RT-qPCR approach demonstrated a limit of detection of 6.6x103 copy/ml and high reproducibility (co-efficient of variation = 1.2%). In 132 nasopharyngeal specimens submitted for SARS-CoV-2 testing, the sensitivity, specificity and accuracy of our optimized approach were 95%, 99% and 98.5%, respectively, with reference to the standard approach. Also, the RT-qPCR CT values obtained by the two methods were positively correlated (Pearson correlation coefficient r = 0.6971, p = 0.0013). The rate of PCR inhibition by the direct approach was 8% compared to 9% by the standard approach. Our simple approach to detect SARS-CoV-2 RNA by direct RT-qPCR may help laboratories continue testing for the virus despite reagent shortages or expand their testing capacity in resource limited settings.


Subject(s)
Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , RNA, Viral/isolation & purification , Real-Time Polymerase Chain Reaction , Specimen Handling/methods , Betacoronavirus , Humans , Nasopharynx/virology , Pandemics , Reproducibility of Results , Sensitivity and Specificity
7.
Int J Mol Med ; 46(3): 957-964, 2020 Sep.
Article in English | MEDLINE | ID: covidwho-676117

ABSTRACT

Reverse transcription­quantitative polymerase chain reaction (RT­qPCR) is the gold standard method for the diagnosis of COVID­19 infection. Due to pre­analytical and technical limitations, samples with low viral load are often misdiagnosed as false­negative samples. Therefore, it is important to evaluate other strategies able to overcome the limits of RT­qPCR. Blinded swab samples from two individuals diagnosed positive and negative for COVID­19 were analyzed by droplet digital PCR (ddPCR) and RT­qPCR in order to assess the sensitivity of both methods. Intercalation chemistries and a World Health Organization (WHO)/Center for Disease Control and Prevention (CDC)­approved probe for the SARS­CoV­2 N gene were used. SYBR­Green RT­qPCR is not able to diagnose as positive samples with low viral load, while, TaqMan Probe RT­qPCR gave positive signals at very late Ct values. On the contrary, ddPCR showed higher sensitivity rate compared to RT­qPCR and both EvaGreen and probe ddPCR were able to recognize the sample with low viral load as positive even at 10­fold diluted concentration. In conclusion, ddPCR shows higher sensitivity and specificity compared to RT­qPCR for the diagnosis of COVID­19 infection in false­negative samples with low viral load. Therefore, ddPCR is strongly recommended in clinical practice for the diagnosis of COVID­19 and the follow­up of positive patients until complete remission.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , RNA, Viral/analysis , Real-Time Polymerase Chain Reaction/methods , Reverse Transcriptase Polymerase Chain Reaction/methods , Humans , Nucleocapsid Proteins/genetics , Pandemics , Sensitivity and Specificity , Spike Glycoprotein, Coronavirus/genetics , Viral Proteins/genetics
8.
BMC Infect Dis ; 20(1): 536, 2020 Jul 23.
Article in English | MEDLINE | ID: covidwho-670669

ABSTRACT

BACKGROUND: As the COVID-19 pandemic continues to spread, early, ideally real-time, identification of SARS-CoV-2 infected individuals is pivotal in interrupting infection chains. Volatile organic compounds produced during respiratory infections can cause specific scent imprints, which can be detected by trained dogs with a high rate of precision. METHODS: Eight detection dogs were trained for 1 week to detect saliva or tracheobronchial secretions of SARS-CoV-2 infected patients in a randomised, double-blinded and controlled study. RESULTS: The dogs were able to discriminate between samples of infected (positive) and non-infected (negative) individuals with average diagnostic sensitivity of 82.63% (95% confidence interval [CI]: 82.02-83.24%) and specificity of 96.35% (95% CI: 96.31-96.39%). During the presentation of 1012 randomised samples, the dogs achieved an overall average detection rate of 94% (±3.4%) with 157 correct indications of positive, 792 correct rejections of negative, 33 incorrect indications of negative or incorrect rejections of 30 positive sample presentations. CONCLUSIONS: These preliminary findings indicate that trained detection dogs can identify respiratory secretion samples from hospitalised and clinically diseased SARS-CoV-2 infected individuals by discriminating between samples from SARS-CoV-2 infected patients and negative controls. This data may form the basis for the reliable screening method of SARS-CoV-2 infected people.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/diagnosis , Coronavirus Infections/virology , Mass Screening/methods , Odorants/analysis , Pneumonia, Viral/diagnosis , Pneumonia, Viral/virology , Animals , Bronchi/chemistry , Bronchi/virology , Case-Control Studies , Dogs , Double-Blind Method , Humans , Pandemics/prevention & control , Pilot Projects , Saliva/chemistry , Saliva/virology , Sensitivity and Specificity
9.
Radiology ; 296(2): E65-E71, 2020 08.
Article in English | MEDLINE | ID: covidwho-657750

ABSTRACT

Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to detect COVID-19 using chest CT and evaluate its performance. Materials and Methods In this retrospective and multicenter study, a deep learning model, the COVID-19 detection neural network (COVNet), was developed to extract visual features from volumetric chest CT scans for the detection of COVID-19. CT scans of community-acquired pneumonia (CAP) and other non-pneumonia abnormalities were included to test the robustness of the model. The datasets were collected from six hospitals between August 2016 and February 2020. Diagnostic performance was assessed with the area under the receiver operating characteristic curve, sensitivity, and specificity. Results The collected dataset consisted of 4352 chest CT scans from 3322 patients. The average patient age (±standard deviation) was 49 years ± 15, and there were slightly more men than women (1838 vs 1484, respectively; P = .29). The per-scan sensitivity and specificity for detecting COVID-19 in the independent test set was 90% (95% confidence interval [CI]: 83%, 94%; 114 of 127 scans) and 96% (95% CI: 93%, 98%; 294 of 307 scans), respectively, with an area under the receiver operating characteristic curve of 0.96 (P < .001). The per-scan sensitivity and specificity for detecting CAP in the independent test set was 87% (152 of 175 scans) and 92% (239 of 259 scans), respectively, with an area under the receiver operating characteristic curve of 0.95 (95% CI: 0.93, 0.97). Conclusion A deep learning model can accurately detect coronavirus 2019 and differentiate it from community-acquired pneumonia and other lung conditions. © RSNA, 2020 Online supplemental material is available for this article.


Subject(s)
Artificial Intelligence , Betacoronavirus , Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Adult , Aged , Clinical Laboratory Techniques/methods , Community-Acquired Infections/diagnostic imaging , Coronavirus Infections/diagnosis , Deep Learning , Diagnosis, Differential , Female , Humans , Imaging, Three-Dimensional/methods , Male , Middle Aged , Pandemics , ROC Curve , Radiographic Image Interpretation, Computer-Assisted/methods , Retrospective Studies , Sensitivity and Specificity , Tomography, X-Ray Computed/methods
11.
Euro Surveill ; 25(27)2020 07.
Article in English | MEDLINE | ID: covidwho-652787

ABSTRACT

Laboratory preparedness with quality-assured diagnostic assays is essential for controlling the current coronavirus disease (COVID-19) outbreak. We conducted an external quality assessment study with inactivated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) samples to support clinical laboratories with a proficiency testing option for molecular assays. To analyse SARS-CoV-2 testing performance, we used an online questionnaire developed for the European Union project RECOVER to assess molecular testing capacities in clinical diagnostic laboratories.


Subject(s)
Clinical Laboratory Techniques/methods , Clinical Laboratory Techniques/standards , Coronavirus Infections/diagnosis , Coronavirus/isolation & purification , Molecular Diagnostic Techniques/methods , Pandemics , Pneumonia, Viral/diagnosis , Betacoronavirus , Clinical Laboratory Services , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Disease Outbreaks , Europe , Humans , Pandemics/prevention & control , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , Real-Time Polymerase Chain Reaction/standards , Reverse Transcriptase Polymerase Chain Reaction/standards , Sensitivity and Specificity , Surveys and Questionnaires
12.
BMC Infect Dis ; 20(1): 517, 2020 Jul 16.
Article in English | MEDLINE | ID: covidwho-651422

ABSTRACT

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a public health emergency of major international concern. Real-time RT-PCR assays are recommended for diagnosis of COVID-19. Here we report a rare case of COVID-19 with multiple negative results for PCR assays outside Wuhan, China. CASE PRESENTATION: A 32-year old male was admitted to our hospital because of 6 days of unexplained fever on January 29, 2020. He had come from Wuhan city 10 days before admission. Five days before admission, no abnormality was noted in laboratory test, chest radiography, and nasopharyngeal swab test for the SARS-CoV-2 nucleic acid. The patient was treated with ibuprofen for alleviating fever. On admission, chest computed tomography showed multiple ground-glass opacities in right lower lung field. COVID-19 was suspected. Three times of nasopharyngeal swab specimens were collected after admission. However, none of the specimens were positive. The patient was confirmed with COVID-19 after fifth SARS-CoV-2 nucleic acid test. He was treated with lopinavir/ritonavir, recombinant human interferon alfa-2b inhalation, methylprednisolone. After 18 days of treatment, he was discharged with improved symptoms, lung lesions and negative results of nasopharyngeal swab. CONCLUSION: This case reminds clinician that a patient with high clinical suspicion of COVID-19 but multiple negative RT-PCR result should not be taken out of isolation. A combination of patient's exposure history, clinical manifestations, laboratory tests, and typical imaging findings plays a vital role in making preliminary diagnosis and guide early isolation and treatment. Repeat swab tests are helpful in diagnosis for this kind of patients.


Subject(s)
Betacoronavirus/isolation & purification , Coronavirus Infections/diagnosis , Coronavirus Infections/virology , Negative Results , Pneumonia, Viral/diagnosis , Pneumonia, Viral/virology , Adult , Betacoronavirus/genetics , China/epidemiology , Coronavirus Infections/diagnostic imaging , Coronavirus Infections/physiopathology , Fever/etiology , Fever/virology , Hospitalization , Humans , Male , Pandemics , Pneumonia, Viral/diagnostic imaging , Pneumonia, Viral/physiopathology , Quarantine , Radiography , Real-Time Polymerase Chain Reaction , Sensitivity and Specificity , Tomography, X-Ray Computed , Uncertainty
14.
Rev Esp Quimioter ; 33(4): 267-273, 2020 Aug.
Article in Spanish | MEDLINE | ID: covidwho-643658

ABSTRACT

OBJECTIVE: Identify which biomarkers performed in the first emergency analysis help to stratify COVID-19 patients according to mortality risk. METHODS: Observational, descriptive and cross-sectional study performed with data collected from patients with suspected COVID-19 in the Emergency Department from February 24 to March 16, 2020. The univariate and multivariate study was performed to find independent mortality markers and calculate risk by building a severity score. RESULTS: A total of 163 patients were included, of whom 33 died and 29 of them were positive for the COVID-19 PCR test. We obtained as possible factors to conform the Mortality Risk Score age> 75 years ((adjusted OR = 12,347, 95% CI: 4,138-36,845 p = 0.001), total leukocytes> 11,000 cells / mm3 (adjusted OR = 2,649, 95% CI: 0.879-7.981 p = 0.083), glucose> 126 mg / dL (adjusted OR = 3.716, 95% CI: 1.247-11.074 p = 0.018) and creatinine> 1.1 mg / dL (adjusted OR = 2.566, 95% CI: 0.889- 7.403, p = 0.081) This score was called COVEB (COVID, Age, Basic analytical profile) with an AUC 0.874 (95% CI: 0.816-0.933, p <0.001; Cut-off point = 1 (sensitivity = 89.66 % (95% CI: 72.6% -97.8%), specificity = 75.59% (95% CI: 67.2% -82.8%). A score <1 has a negative predictive value = 100% (95% CI: 93.51% -100%) and a positive predictive value = 18.59% (95% CI: 12.82% -25.59%). CONCLUSIONS: Clinical severity scales, kidney function biomarkers, white blood cell count parameters, the total neutrophils / total lymphocytes ratio and procalcitonin are early risk factors for mortality. The variables age, glucose, creatinine and total leukocytes stand out as the best predictors of mortality. A COVEB score <1 indicates with a 100% probability that the patient with suspected COVID-19 will not die in the next 30 days.


Subject(s)
Betacoronavirus , Coronavirus Infections/blood , Coronavirus Infections/mortality , Pneumonia, Viral/blood , Pneumonia, Viral/mortality , Age Factors , Aged , Analysis of Variance , Area Under Curve , Biomarkers/blood , Blood Glucose/analysis , Coronavirus Infections/diagnosis , Creatinine/blood , Cross-Sectional Studies , Emergency Service, Hospital , Female , Humans , Hypertension/mortality , Leukocyte Count , Male , Odds Ratio , Pandemics , Pneumonia, Viral/diagnosis , Predictive Value of Tests , Retrospective Studies , Reverse Transcriptase Polymerase Chain Reaction , Risk Assessment/methods , Sensitivity and Specificity
15.
J Infect Dis ; 222(2): 189-193, 2020 06 29.
Article in English | MEDLINE | ID: covidwho-643587

ABSTRACT

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel ß-coronavirus, causes severe pneumonia and has spread throughout the globe rapidly. The disease associated with SARS-CoV-2 infection is named coronavirus disease 2019 (COVID-19). To date, real-time reverse-transcription polymerase chain reaction (RT-PCR) is the only test able to confirm this infection. However, the accuracy of RT-PCR depends on several factors; variations in these factors might significantly lower the sensitivity of detection. METHODS: In this study, we developed a peptide-based luminescent immunoassay that detected immunoglobulin (Ig)G and IgM. The assay cutoff value was determined by evaluating the sera from healthy and infected patients for pathogens other than SARS-CoV-2. RESULTS: To evaluate assay performance, we detected IgG and IgM in the sera from confirmed patients. The positive rate of IgG and IgM was 71.4% and 57.2%, respectively. CONCLUSIONS: Therefore, combining our immunoassay with real-time RT-PCR might enhance the diagnostic accuracy of COVID-19.


Subject(s)
Antibodies, Viral/blood , Betacoronavirus/immunology , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Immunoenzyme Techniques/methods , Pneumonia, Viral/diagnosis , Serologic Tests/methods , Adult , Coronavirus Infections/immunology , Female , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Luminescent Measurements , Male , Middle Aged , Pandemics , Peptides/immunology , Pneumonia, Viral/immunology , Real-Time Polymerase Chain Reaction , Reverse Transcriptase Polymerase Chain Reaction , Sensitivity and Specificity , Viral Proteins/immunology
16.
Med Sci Monit ; 26: e924582, 2020 Jul 12.
Article in English | MEDLINE | ID: covidwho-641223

ABSTRACT

In December 2019, an outbreak of coronavirus infection emerged in Wuhan, Hubei Province of China, which is now named Coronavirus Disease 2019 (COVID-19). The outbreak spread rapidly within mainland China and globally. This paper reviews the different imaging modalities used in the diagnosis and treatment process of COVID-19, such as chest radiography, computerized tomography (CT) scan, ultrasound examination, and positron emission tomography (PET/CT) scan. A chest radiograph is not recommended as a first-line imaging modality for COVID-19 infection due to its lack of sensitivity, especially in the early stages of infection. Chest CT imaging is reported to be a more reliable, rapid, and practical method for diagnosis of COVID-19, and it can assess the severity of the disease and follow up the disease time course. Ultrasound, on the other hand, is portable and involves no radiation, and thus can be used in critically ill patients to assess cardiorespiratory function, guide mechanical ventilation, and identify the presence of deep venous thrombosis and secondary pulmonary thromboembolism. Supplementary information can be provided by PET/CT. In the absence of vaccines and treatments for COVID-19, prompt diagnosis and appropriate treatment are essential. Therefore, it is important to exploit the advantages of different imaging modalities in the fight against COVID-19.


Subject(s)
Betacoronavirus , Clinical Laboratory Techniques , Coronavirus Infections/diagnostic imaging , Pandemics , Pneumonia, Viral/diagnostic imaging , Betacoronavirus/genetics , Betacoronavirus/isolation & purification , China/epidemiology , Coronavirus Infections/complications , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Diagnosis, Differential , Disease Progression , Follow-Up Studies , Humans , Lung/diagnostic imaging , Lung/pathology , Lung Diseases, Interstitial/diagnostic imaging , Lung Diseases, Interstitial/etiology , Pneumonia/diagnostic imaging , Pneumonia, Viral/complications , Pneumonia, Viral/epidemiology , Positron Emission Tomography Computed Tomography , Radiography, Thoracic , Respiratory Distress Syndrome, Adult/diagnostic imaging , Respiratory Distress Syndrome, Adult/etiology , Reverse Transcriptase Polymerase Chain Reaction , Sensitivity and Specificity , Tomography, X-Ray Computed , Ultrasonography
17.
Scand J Trauma Resusc Emerg Med ; 28(1): 66, 2020 Jul 13.
Article in English | MEDLINE | ID: covidwho-641101

ABSTRACT

BACKGROUND: There is a need for validated clinical risk scores to identify patients at risk of severe disease and to guide decision-making during the covid-19 pandemic. The National Early Warning Score 2 (NEWS2) is widely used in emergency medicine, but so far, no studies have evaluated its use in patients with covid-19. We aimed to study the performance of NEWS2 and compare commonly used clinical risk stratification tools at admission to predict risk of severe disease and in-hospital mortality in patients with covid-19. METHODS: This was a prospective cohort study in a public non-university general hospital in the Oslo area, Norway, including a cohort of all 66 patients hospitalised with confirmed SARS-CoV-2 infection from the start of the pandemic; 13 who died during hospital stay and 53 who were discharged alive. Data were collected consecutively from March 9th to April 27th 2020. The main outcome was the ability of the NEWS2 score and other clinical risk scores at emergency department admission to predict severe disease and in-hospital mortality in covid-19 patients. We calculated sensitivity and specificity with 95% confidence intervals (CIs) for NEWS2 scores ≥5 and ≥ 6, quick Sequential Organ Failure Assessment (qSOFA) score ≥ 2, ≥2 Systemic Inflammatory Response Syndrome (SIRS) criteria, and CRB-65 score ≥ 2. Areas under the curve (AUCs) for the clinical risk scores were compared using DeLong's test. RESULTS: In total, 66 patients (mean age 67.9 years) were included. Of these, 23% developed severe disease. In-hospital mortality was 20%. Tachypnoea, hypoxemia and confusion at admission were more common in patients developing severe disease. A NEWS2 score ≥ 6 at admission predicted severe disease with 80.0% sensitivity and 84.3% specificity (Area Under the Curve (AUC) 0.822, 95% CI 0.690-0.953). NEWS2 was superior to qSOFA score ≥ 2 (AUC 0.624, 95% CI 0.446-0.810, p < 0.05) and other clinical risk scores for this purpose. CONCLUSION: NEWS2 score at hospital admission predicted severe disease and in-hospital mortality, and was superior to other widely used clinical risk scores in patients with covid-19.


Subject(s)
Betacoronavirus , Coronavirus Infections/epidemiology , Early Warning Score , Hospital Mortality , Patient Admission , Pneumonia, Viral/epidemiology , Adult , Aged , Aged, 80 and over , Cohort Studies , Female , Humans , Male , Middle Aged , Norway/epidemiology , Pandemics , Risk Assessment , Sensitivity and Specificity , Severity of Illness Index
18.
Theranostics ; 10(16): 7150-7162, 2020.
Article in English | MEDLINE | ID: covidwho-639991

ABSTRACT

In December 2019, a new coronavirus disease (COVID-19) outbreak occurred in Wuhan, China. Severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), which is the seventh coronavirus known to infect humans, is highly contagious and has rapidly expanded worldwide since its discovery. Quantitative nucleic acid testing has become the gold standard for diagnosis and guiding clinical decisions regarding the use of antiviral therapy. However, the RT-qPCR assays targeting SARS-CoV-2 have a number of challenges, especially in terms of primer design. Primers are the pivotal components of a RT-qPCR assay. Once virus mutation and recombination occur, it is difficult to effectively diagnose viral infection by existing RT-qPCR primers. Some primers and probes have also been made available on the WHO website for reference. However, no previous review has systematically compared the previously reported primers and probes and described how to design new primers in the event of a new coronavirus infection. This review focuses on how primers and probes can be designed methodically and rationally, and how the sensitivity and specificity of the detection process can be improved. This brief review will be useful for the accurate diagnosis and timely treatment of the new coronavirus pneumonia.


Subject(s)
Betacoronavirus/genetics , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , RNA, Viral/genetics , RNA/genetics , Real-Time Polymerase Chain Reaction/methods , Base Sequence , Coronavirus Infections/epidemiology , Coronavirus Infections/virology , Drug Design , Genes, Viral , Humans , Nucleic Acid Conformation , Pandemics , Pneumonia, Viral/epidemiology , Pneumonia, Viral/virology , RNA/chemistry , RNA Probes/genetics , RNA, Viral/chemistry , Real-Time Polymerase Chain Reaction/statistics & numerical data , Sensitivity and Specificity , Theranostic Nanomedicine
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