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1.
J Med Internet Res ; 23(4): e27468, 2021 04 26.
Article in English | MEDLINE | ID: covidwho-1219288

ABSTRACT

BACKGROUND: Owing to the COVID-19 pandemic and the imminent collapse of health care systems following the exhaustion of financial, hospital, and medicinal resources, the World Health Organization changed the alert level of the COVID-19 pandemic from high to very high. Meanwhile, more cost-effective and precise COVID-19 detection methods are being preferred worldwide. OBJECTIVE: Machine vision-based COVID-19 detection methods, especially deep learning as a diagnostic method in the early stages of the pandemic, have been assigned great importance during the pandemic. This study aimed to design a highly efficient computer-aided detection (CAD) system for COVID-19 by using a neural search architecture network (NASNet)-based algorithm. METHODS: NASNet, a state-of-the-art pretrained convolutional neural network for image feature extraction, was adopted to identify patients with COVID-19 in their early stages of the disease. A local data set, comprising 10,153 computed tomography scans of 190 patients with and 59 without COVID-19 was used. RESULTS: After fitting on the training data set, hyperparameter tuning, and topological alterations of the classifier block, the proposed NASNet-based model was evaluated on the test data set and yielded remarkable results. The proposed model's performance achieved a detection sensitivity, specificity, and accuracy of 0.999, 0.986, and 0.996, respectively. CONCLUSIONS: The proposed model achieved acceptable results in the categorization of 2 data classes. Therefore, a CAD system was designed on the basis of this model for COVID-19 detection using multiple lung computed tomography scans. The system differentiated all COVID-19 cases from non-COVID-19 ones without any error in the application phase. Overall, the proposed deep learning-based CAD system can greatly help radiologists detect COVID-19 in its early stages. During the COVID-19 pandemic, the use of a CAD system as a screening tool would accelerate disease detection and prevent the loss of health care resources.


Subject(s)
/diagnostic imaging , Deep Learning , Diagnosis, Computer-Assisted , Lung/diagnostic imaging , Lung/virology , /isolation & purification , Datasets as Topic , Early Diagnosis , Humans , Pandemics , Tomography, X-Ray Computed
2.
Rev. Bras. Saúde Mater. Infant. (Online) ; 21(supl.1): 311-313, Feb. 2021.
Article in English | LILACS (Americas) | ID: covidwho-1215193

ABSTRACT

Abstract The authors bring reflections about people with sickle cell disease in the pandemic era. They comment on some common clinical situations in these two diseases which may delay or confuse the diagnosis of COVID-19 in patients with sickle cell disease. We consider that people with sickle cell disease are part of the risk group for the complications of COVID-19 and the topic should be addressed in the scientific literature.


Resumo Os autores trazem reflexões sobre as pessoas com doença falciforme na era da pandemia. Eles comentam algumas situações clínicas comuns nessas duas doenças que podem retardar ou confundir o diagnóstico de COVID-19 em pacientes com doença falciforme. Consideramos que as pessoas com doença falciforme fazem parte do grupo de risco para complicações da COVID-19 e o tema deve ser abordado na literatura científica.


Subject(s)
Humans , Coronavirus Infections , Anemia, Sickle Cell/complications , Anemia, Sickle Cell/diagnosis , Early Diagnosis , Acute Chest Syndrome , Betacoronavirus
4.
Br J Radiol ; 94(1121): 20201263, 2021 May 01.
Article in English | MEDLINE | ID: covidwho-1190140

ABSTRACT

OBJECTIVE: Pneumonia is a lung infection and causes the inflammation of the small air sacs (Alveoli) in one or both lungs. Proper and faster diagnosis of pneumonia at an early stage is imperative for optimal patient care. Currently, chest X-ray is considered as the best imaging modality for diagnosing pneumonia. However, the interpretation of chest X-ray images is challenging. To this end, we aimed to use an automated convolutional neural network-based transfer-learning approach to detect pneumonia in paediatric chest radiographs. METHODS: Herein, an automated convolutional neural network-based transfer-learning approach using four different pre-trained models (i.e. VGG19, DenseNet121, Xception, and ResNet50) was applied to detect pneumonia in children (1-5 years) chest X-ray images. The performance of different proposed models for testing data set was evaluated using five performances metrics, including accuracy, sensitivity/recall, Precision, area under curve, and F1 score. RESULTS: All proposed models provide accuracy greater than 83.0% for binary classification. The pre-trained DenseNet121 model provides the highest classification performance of automated pneumonia classification with 86.8% accuracy, followed by Xception model with an accuracy of 86.0%. The sensitivity of the proposed models was greater than 91.0%. The Xception and DenseNet121 models achieve the highest classification performance with F1-score greater than 89.0%. The plotted area under curve of receiver operating characteristics of VGG19, Xception, ResNet50, and DenseNet121 models are 0.78, 0.81, 0.81, and 0.86, respectively. CONCLUSION: Our data showed that the proposed models achieve a high accuracy for binary classification. Transfer learning was used to accelerate training of the proposed models and resolve the problem associated with insufficient data. We hope that these proposed models can help radiologists for a quick diagnosis of pneumonia at radiology departments. Moreover, our proposed models may be useful to detect other chest-related diseases such as novel Coronavirus 2019. ADVANCES IN KNOWLEDGE: Herein, we used transfer learning as a machine learning approach to accelerate training of the proposed models and resolve the problem associated with insufficient data. Our proposed models achieved accuracy greater than 83.0% for binary classification.


Subject(s)
Deep Learning , Lung/diagnostic imaging , Pneumonia/diagnostic imaging , Radiographic Image Interpretation, Computer-Assisted/methods , Child, Preschool , Early Diagnosis , Humans , Infant , Pneumonia/classification , ROC Curve , Reproducibility of Results
5.
Infect Dis Poverty ; 10(1): 48, 2021 Apr 12.
Article in English | MEDLINE | ID: covidwho-1181127

ABSTRACT

BACKGROUND: COVID-19 has posed an enormous threat to public health around the world. Some severe and critical cases have bad prognoses and high case fatality rates, unraveling risk factors for severe COVID-19 are of significance for predicting and preventing illness progression, and reducing case fatality rates. Our study focused on analyzing characteristics of COVID-19 cases and exploring risk factors for developing severe COVID-19. METHODS: The data for this study was disease surveillance data on symptomatic cases of COVID-19 reported from 30 provinces in China between January 19 and March 9, 2020, which included demographics, dates of symptom onset, clinical manifestations at the time of diagnosis, laboratory findings, radiographic findings, underlying disease history, and exposure history. We grouped mild and moderate cases together as non-severe cases and categorized severe and critical cases together as severe cases. We compared characteristics of severe cases and non-severe cases of COVID-19 and explored risk factors for severity. RESULTS: The total number of cases were 12 647 with age from less than 1 year old to 99 years old. The severe cases were 1662 (13.1%), the median age of severe cases was 57 years [Inter-quartile range(IQR): 46-68] and the median age of non-severe cases was 43 years (IQR: 32-54). The risk factors for severe COVID-19 were being male [adjusted odds ratio (aOR) = 1.3, 95% CI: 1.2-1.5]; fever (aOR = 2.3, 95% CI: 2.0-2.7), cough (aOR = 1.4, 95% CI: 1.2-1.6), fatigue (aOR = 1.3, 95% CI: 1.2-1.5), and chronic kidney disease (aOR = 2.5, 95% CI: 1.4-4.6), hypertension (aOR = 1.5, 95% CI: 1.2-1.8) and diabetes (aOR = 1.96, 95% CI: 1.6-2.4). With the increase of age, risk for the severity was gradually higher [20-39 years (aOR = 3.9, 95% CI: 1.8-8.4), 40-59 years (aOR = 7.6, 95% CI: 3.6-16.3), ≥ 60 years (aOR = 20.4, 95% CI: 9.5-43.7)], and longer time from symtem onset to diagnosis [3-5 days (aOR = 1.4, 95% CI: 1.2-1.7), 6-8 days (aOR = 1.8, 95% CI: 1.5-2.1), ≥ 9 days(aOR = 1.9, 95% CI: 1.6-2.3)]. CONCLUSIONS: Our study showed the risk factors for developing severe COVID-19 with large sample size, which included being male, older age, fever, cough, fatigue, delayed diagnosis, hypertension, diabetes, chronic kidney diasease, early case identification and prompt medical care. Based on these factors, the severity of COVID-19 cases can be predicted. So cases with these risk factors should be paid more attention to prevent severity.


Subject(s)
Age Factors , Comorbidity , Severity of Illness Index , Sex Factors , Adolescent , Adult , Aged , Aged, 80 and over , Child , Child, Preschool , China/epidemiology , Early Diagnosis , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Risk Factors , Young Adult
6.
PLoS One ; 16(4): e0249668, 2021.
Article in English | MEDLINE | ID: covidwho-1170006

ABSTRACT

OBJECTIVE: To understand the clinical characteristics of COVID-19 patients with clinically diagnosed bacterial co-infection (CDBC), and therefore contributing to their early identification and prognosis estimation. METHOD: 905 COVID-19 patients from 7 different centers were enrolled. The demography data, clinical manifestations, laboratory results, and treatments were collected accordingly for further analyses. RESULTS: Around 9.5% of the enrolled COVID-19 patients were diagnosed with CDBC. Older patients or patients with cardiovascular comorbidities have increased CDBC probability. Increased body temperature, longer fever duration, anhelation, gastrointestinal symptoms, illness severity, intensive care unit attending, ventilation treatment, glucocorticoid therapy, longer hospitalization time are correlated to CDBC. Among laboratory results, increased white blood cell counting (mainly neutrophil), lymphocytopenia, increased procalcitonin, erythrocyte sedimentation rate, C-reaction protein, D-dimer, blood urea nitrogen, lactate dehydrogenase, brain natriuretic peptide, myoglobin, blood sugar and decreased albumin are also observed, indicating multiple system functional damage. Radiology results suggested ground glass opacity mixed with high density effusion opacities and even pleural effusion. CONCLUSION: The aged COVID-19 patients with increased inflammatory indicators, worse lymphopenia and cardiovascular comorbidities are more likely to have clinically diagnosed bacterial co-infection. Moreover, they tend to have severer clinical manifestations and increased probability of multiple system functional damage.


Subject(s)
Bacterial Infections , Coinfection , Adult , Aged , Bacterial Infections/diagnosis , Bacterial Infections/epidemiology , Coinfection/diagnosis , Coinfection/epidemiology , Comorbidity , Early Diagnosis , Female , Humans , Male , Middle Aged , Prognosis , Severity of Illness Index
7.
Medicina (Kaunas) ; 57(3)2021 Mar 18.
Article in English | MEDLINE | ID: covidwho-1167652

ABSTRACT

The COVID-19 pandemic dramatically changed medical care. Healthcare professionals are faced with new issues. Patients who survived COVID-19 have plenty of different continuing symptoms, of which the most common are fatigue and breathlessness. It is not well known how to care for patients with persistent or worsening respiratory symptoms and changes on chest X-ray following COVID-19 pneumonia. In this article, we talk about a subgroup of patients with organizing pneumonia following COVID-19 pneumonia that could be effectively treated with systemic glucocorticoids. It is important that patients with COVID-19 pneumonia be followed-up at least three weeks after diagnosis, in order to recognize early lung damage. We are providing a management algorithm for early diagnosis of lung diseases after COVID-19 pneumonia.


Subject(s)
/complications , Lung Diseases, Interstitial/diagnosis , Algorithms , Biopsy , /drug therapy , Computed Tomography Angiography , Disease Management , Early Diagnosis , Glucocorticoids/therapeutic use , Humans , Lung/diagnostic imaging , Lung/pathology , Lung/physiopathology , Lung Diseases, Interstitial/drug therapy , Lung Diseases, Interstitial/etiology , Lung Diseases, Interstitial/physiopathology , Pulmonary Diffusing Capacity , Spirometry , Tomography, X-Ray Computed , Walk Test
8.
Iran J Immunol ; 18(1): 13-33, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1160145

ABSTRACT

The COVID-19 pandemic is probably the most devastating worldwide challenge in recent century. COVID-19 leads to a mild to severe respiratory disease and affects different organs and has become a global concern since December 2019. Meanwhile, molecular biology and diagnostic laboratories played an essential role in diagnosis of the disease by introducing serological and molecular tests. Molecular-based techniques are reliable detection tools for SARS-CoV-2 and used for diagnosis of patients especially in the early stage of the disease. While, serological assays are considered as additional tools to verify the asymptomatic infections, tracing previous contacts of individuals, vaccine efficacy, and study the seroprevalance. The average time of the appearance of anti-SARS-CoV-2 antibodies in the patient's serum is 3-6 days after the onset of symptoms for both IgM and IgA and 10-18 days for IgG. Following the outbreak of COVID-19, FDA has approved and authorized a series of serological laboratory tests for early diagnosis. Serological assays have low-cost and provide fast results but have poor sensitivity in the early stage of the viral infection. Although the serological tests may not play an important role in the active case of COVID-19, it could be effective to determine the immunity of health care workers, and confirm late COVID-19 cases during the outbreak. In this review, we compared various laboratory diagnostic assays for COVID-19.


Subject(s)
Antibodies, Viral/blood , RNA, Viral/blood , /immunology , Biomarkers/blood , /genetics , Early Diagnosis , Host-Pathogen Interactions , Humans , Predictive Value of Tests , RNA, Viral/genetics , Reproducibility of Results
9.
Iran J Immunol ; 18(1): 34-46, 2021 Mar.
Article in English | MEDLINE | ID: covidwho-1159472

ABSTRACT

BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new global health threat. OBJECTIVES: to analyze the effectiveness of the measurement of specific antibodies to SARS-CoV2 (IgM and IgG) for the diagnosis of COVID-19 and to analyze the rate of SARS-CoV2 seroprevalence in the population. METHODS: 11 relevant studies, published before June 5, 2020, were included in this meta-analysis. These studies were identified by searching the MEDLINE and Scopus databases. The final selected studies were analyzed using STATA version 14. Publication bias was examined using both Egger's test and Funnel plots. Moreover, the I² statistic has been used to evaluate and verify heterogeneity. RESULTS: The 11 relevant studies selected for the present meta-analysis cover a total of 996 infection cases. According to the results, the average rate of positive cases for IgM (AU/mL) was 2.10 (95% CI: 1.65-2.55; I2=92.2%), and the sensitivity in individuals with positive IgM test was 63% (95% CI: 47-79; I2=94.9%). In addition, the average rate of positive cases for IgG (AU/mL) was 67.44 (95% CI: 28.79-106.09; I2=99.4%), and the sensitivity in individuals with positive IgG test was 79% (95% CI: 67-90; I2=89.5%). CONCLUSIONS: According to this analysis, detection of anti-SARS-CoV-2 IgM and IgG antibodies may assist early detection of SARS-CoV2 infection. Whether antibodies against SARS-CoV-2 confer protective immunity warrants further studies.


Subject(s)
Antibodies, Viral/blood , Immunoglobulin G/blood , Immunoglobulin M/blood , /immunology , Biomarkers/blood , /epidemiology , Early Diagnosis , Host-Pathogen Interactions , Humans , Predictive Value of Tests , Seroepidemiologic Studies
10.
Int J Environ Res Public Health ; 18(7)2021 03 27.
Article in English | MEDLINE | ID: covidwho-1154413

ABSTRACT

BACKGROUND: The COVID-19 pandemic rapidly strained healthcare systems worldwide. The reference standard for diagnosis is a positive reverse transcription polymerase chain reaction (RT-PCR) test, but results are not immediate and sensibility is variable. AIM: To evaluate the diagnostic accuracy of lung ultrasound compared to chest X-ray for COVID-19 pneumonia. DESIGN AND SETTING: A retrospective analysis of symptomatic patients admitted into one primary care centre in Spain between March and September 2020. METHOD: Patients' chest X-rays and lung ultrasounds were categorized as normal or pathologic. RT-PCR confirmed COVID-19 infection. Pathologic lung ultrasound images were further categorized as showing either local or diffuse interstitial disease. McNemar and Fisher tests were used to compare diagnostic accuracy. RESULTS: Most of the 212 patients presented fever at admission, either as a standalone symptom (37.74% of patients) or together with others (72.17% of patients). The positive predictive value of the lung ultrasound was 90% for the diffuse interstitial pattern and 46.92% for local pattern. The lung ultrasound had a significantly higher sensitivity (82.75%) (p < 0.001), but lower specificity (71%) than the chest X-ray (54.02% and 86%, respectively) (p = 0.008) for identifying interstitial lung disease. Moreover, sensitivity of the lung ultrasound for severe interstitial disease was 100%, and was significantly higher than the chest X-ray (58.33%) (p = 0.002). CONCLUSION: The lung ultrasound is more accurate than the chest X-ray for identifying patients with COVID-19 pneumonia and it is especially useful for those presenting diffuse interstitial disease.


Subject(s)
Pandemics , Early Diagnosis , Humans , Lung/diagnostic imaging , Retrospective Studies , Sensitivity and Specificity , Spain , Tomography, X-Ray Computed , X-Rays
11.
Recenti Prog Med ; 112(3): 216-218, 2021 03.
Article in English | MEDLINE | ID: covidwho-1154141

ABSTRACT

We analysed RRI and other hemodynamic, re-spiratory and inflammation parameters in critically ill pa-tients affected by severe covid-19 with acute distress respi-ratory syndrome (ARDS) aiming at verifying their modifica-tions during supine and prone positioning and any mutual correlation or interplay with RRI.


Subject(s)
Blood Flow Velocity , Inflammation/physiopathology , Kidney/physiopathology , Lung/physiopathology , Renal Artery/physiopathology , Renal Circulation , /physiopathology , Biomarkers , C-Reactive Protein/analysis , /complications , Creatinine/blood , Diastole , Early Diagnosis , Female , Humans , Inflammation/blood , Inflammation/diagnosis , Kidney Function Tests , Male , Middle Aged , Oxygen/blood , Prone Position , /etiology , Supine Position , Systole
12.
Am J Nephrol ; 52(2): 161-172, 2021.
Article in English | MEDLINE | ID: covidwho-1150270

ABSTRACT

INTRODUCTION: Renal involvement in COVID-19 is less well characterized in settings with vigilant public health surveillance, including mass screening and early hospitalization. We assessed kidney complications among COVID-19 patients in Hong Kong, including the association with risk factors, length of hospitalization, critical presentation, and mortality. METHODS: Linked electronic records of all patients with confirmed COVID-19 from 5 major designated hospitals were extracted. Duplicated records due to interhospital transferal were removed. Primary outcome was the incidence of in-hospital acute kidney injury (AKI). Secondary outcomes were AKI-associated mortality, incident renal replacement therapy (RRT), intensive care admission, prolonged hospitalization and disease course (defined as >90th percentile of hospitalization duration [35 days] and duration from symptom onset to discharge [43 days], respectively), and change of estimated glomerular filtration rate (GFR). Patients were further stratified into being symptomatic or asymptomatic. RESULTS: Patients were characterized by young age (median: 38.4, IQR: 28.4-55.8 years) and short time (median: 5, IQR: 2-9 days) from symptom onset to admission. Among the 591 patients, 22 (3.72%) developed AKI and 4 (0.68%) required RRT. The median time from symptom onset to in-hospital AKI was 15 days. AKI increased the odds of prolonged hospitalization and disease course by 2.0- and 3.5-folds, respectively. Estimated GFR 24 weeks post-discharge reduced by 7.51 and 1.06 mL/min/1.73 m2 versus baseline (upon admission) in the AKI and non-AKI groups, respectively. The incidence of AKI was comparable between asymptomatic (4.8%, n = 3/62) and symptomatic (3.7%, n = 19/519) patients. CONCLUSION: The overall rate of AKI among COVID-19 patients in Hong Kong is low, which could be attributable to a vigilant screening program and early hospitalization. Among patients who developed in-hospital AKI, the duration of hospitalization is prolonged and kidney function impairment can persist for up to 6 months post-discharge. Mass surveillance for COVID-19 is warranted in identifying asymptomatic subjects for earlier AKI management.


Subject(s)
Acute Kidney Injury/epidemiology , Mass Screening/organization & administration , Renal Replacement Therapy/statistics & numerical data , Acute Kidney Injury/diagnosis , Acute Kidney Injury/immunology , Acute Kidney Injury/therapy , Adult , Age Factors , Aged , /immunology , Critical Care/statistics & numerical data , Early Diagnosis , Female , Glomerular Filtration Rate/immunology , Hong Kong/epidemiology , Hospital Mortality , Humans , Incidence , Length of Stay , Male , Mass Screening/statistics & numerical data , Middle Aged , Patient Discharge , Retrospective Studies , Risk Factors , /isolation & purification , Severity of Illness Index
13.
J Med Internet Res ; 23(3): e24925, 2021 03 23.
Article in English | MEDLINE | ID: covidwho-1148271

ABSTRACT

BACKGROUND: Forecasting methods rely on trends and averages of prior observations to forecast COVID-19 case counts. COVID-19 forecasts have received much media attention, and numerous platforms have been created to inform the public. However, forecasting effectiveness varies by geographic scope and is affected by changing assumptions in behaviors and preventative measures in response to the pandemic. Due to time requirements for developing a COVID-19 vaccine, evidence is needed to inform short-term forecasting method selection at county, health district, and state levels. OBJECTIVE: COVID-19 forecasts keep the public informed and contribute to public policy. As such, proper understanding of forecasting purposes and outcomes is needed to advance knowledge of health statistics for policy makers and the public. Using publicly available real-time data provided online, we aimed to evaluate the performance of seven forecasting methods utilized to forecast cumulative COVID-19 case counts. Forecasts were evaluated based on how well they forecast 1, 3, and 7 days forward when utilizing 1-, 3-, 7-, or all prior-day cumulative case counts during early virus onset. This study provides an objective evaluation of the forecasting methods to identify forecasting model assumptions that contribute to lower error in forecasting COVID-19 cumulative case growth. This information benefits professionals, decision makers, and the public relying on the data provided by short-term case count estimates at varied geographic levels. METHODS: We created 1-, 3-, and 7-day forecasts at the county, health district, and state levels using (1) a naïve approach, (2) Holt-Winters (HW) exponential smoothing, (3) a growth rate approach, (4) a moving average (MA) approach, (5) an autoregressive (AR) approach, (6) an autoregressive moving average (ARMA) approach, and (7) an autoregressive integrated moving average (ARIMA) approach. Forecasts relied on Virginia's 3464 historical county-level cumulative case counts from March 7 to April 22, 2020, as reported by The New York Times. Statistically significant results were identified using 95% CIs of median absolute error (MdAE) and median absolute percentage error (MdAPE) metrics of the resulting 216,698 forecasts. RESULTS: The next-day MA forecast with 3-day look-back length obtained the lowest MdAE (median 0.67, 95% CI 0.49-0.84, P<.001) and statistically significantly differed from 39 out of 59 alternatives (66%) to 53 out of 59 alternatives (90%) at each geographic level at a significance level of .01. For short-range forecasting, methods assuming stationary means of prior days' counts outperformed methods with assumptions of weak stationarity or nonstationarity means. MdAPE results revealed statistically significant differences across geographic levels. CONCLUSIONS: For short-range COVID-19 cumulative case count forecasting at the county, health district, and state levels during early onset, the following were found: (1) the MA method was effective for forecasting 1-, 3-, and 7-day cumulative case counts; (2) exponential growth was not the best representation of case growth during early virus onset when the public was aware of the virus; and (3) geographic resolution was a factor in the selection of forecasting methods.


Subject(s)
/diagnosis , /epidemiology , Communicable Disease Control/organization & administration , Disease Transmission, Infectious/prevention & control , Early Diagnosis , Forecasting , Humans , Local Government , Pandemics , Residence Characteristics , State Health Plans , Virginia/epidemiology
15.
Intensive Care Med ; 47(4): 444-454, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1141400

ABSTRACT

PURPOSE: To analyze the application of a lung ultrasound (LUS)-based diagnostic approach to patients suspected of COVID-19, combining the LUS likelihood of COVID-19 pneumonia with patient's symptoms and clinical history. METHODS: This is an international multicenter observational study in 20 US and European hospitals. Patients suspected of COVID-19 were tested with reverse transcription-polymerase chain reaction (RT-PCR) swab test and had an LUS examination. We identified three clinical phenotypes based on pre-existing chronic diseases (mixed phenotype), and on the presence (severe phenotype) or absence (mild phenotype) of signs and/or symptoms of respiratory failure at presentation. We defined the LUS likelihood of COVID-19 pneumonia according to four different patterns: high (HighLUS), intermediate (IntLUS), alternative (AltLUS), and low (LowLUS) probability. The combination of patterns and phenotypes with RT-PCR results was described and analyzed. RESULTS: We studied 1462 patients, classified in mild (n = 400), severe (n = 727), and mixed (n = 335) phenotypes. HighLUS and IntLUS showed an overall sensitivity of 90.2% (95% CI 88.23-91.97%) in identifying patients with positive RT-PCR, with higher values in the mixed (94.7%) and severe phenotype (97.1%), and even higher in those patients with objective respiratory failure (99.3%). The HighLUS showed a specificity of 88.8% (CI 85.55-91.65%) that was higher in the mild phenotype (94.4%; CI 90.0-97.0%). At multivariate analysis, the HighLUS was a strong independent predictor of RT-PCR positivity (odds ratio 4.2, confidence interval 2.6-6.7, p < 0.0001). CONCLUSION: Combining LUS patterns of probability with clinical phenotypes at presentation can rapidly identify those patients with or without COVID-19 pneumonia at bedside. This approach could support and expedite patients' management during a pandemic surge.


Subject(s)
/diagnostic imaging , Lung/diagnostic imaging , Ultrasonography , Adult , Aged , Early Diagnosis , Humans , Middle Aged
16.
Clin Rev Allergy Immunol ; 59(1): 89-100, 2020 Aug.
Article in English | MEDLINE | ID: covidwho-1139384

ABSTRACT

The COVID-19 pandemic is a significant global event in the history of infectious diseases. The SARS-CoV-2 appears to have originated from bats but is now easily transmissible among humans, primarily through droplet or direct contact. Clinical features of COVID-19 include high fever, cough, and fatigue which may progress to ARDS. Respiratory failure can occur rapidly after this. The primary laboratory findings include lymphopenia and eosinopenia. Elevated D-dimer, procalcitonin, and CRP levels may correlate with disease severity. Imaging findings include ground-glass opacities and patchy consolidation on CT scan. Mortality is higher in patients with hypertension, cardiac disease, diabetes mellitus, cancer, and COPD. Elderly patients are more susceptible to severe disease and death, while children seem to have lower rates of infection and lower mortality. Diagnostic criteria and the identification of persons under investigation have evolved as more data has emerged. However, the approach to diagnosis is still very variable from region to region, country to country, and even among different hospitals in the same city. The importance of a clinical pathway to implement the most effective and relevant diagnostic strategy is of critical importance to establish the control of this virus that is responsible for more and more deaths each day.


Subject(s)
Antibodies, Viral/immunology , Clinical Laboratory Techniques/methods , Coronavirus Infections/diagnosis , Lung/diagnostic imaging , Pneumonia, Viral/diagnosis , RNA, Viral/analysis , Algorithms , Betacoronavirus/immunology , Critical Pathways , Early Diagnosis , Evidence-Based Practice , False Negative Reactions , Humans , Immunoglobulin G/immunology , Immunoglobulin M/immunology , Medical History Taking , Pandemics , Patient Isolation , Quarantine , Real-Time Polymerase Chain Reaction/methods , Reverse Transcriptase Polymerase Chain Reaction/methods , Serologic Tests/methods , Severity of Illness Index , Tomography, X-Ray Computed
17.
Appl Microbiol Biotechnol ; 105(7): 2615-2624, 2021 Apr.
Article in English | MEDLINE | ID: covidwho-1130755

ABSTRACT

A most discussed topic of the new decade, COVID-19 is an infectious disease caused by the recently discovered SARS-CoV-2. With an exceedingly high transmission rate, COVID-19 has affected almost all the countries in the world. Absent any vaccine or specific treatment, the humanity is left with nothing but the legacy method of quarantine. However, quarantine can only be effective when combined with early diagnosis of suspected cases. With their high sensitivity and unmatched specificity, biosensors have become an area of interest for development of novel diagnostic methods. Compared to the more traditional diagnostics, nanobiotechnology introduces biosensors as different diagnostics with greater versatility in application. Today, a growing number of analytes are being accurately identified by these nanoscopic sensing machines. Several reports of validated application with real samples further strengthen this idea. As of recent, there has been a rise in the number of studies on portable biosensors. Despite the slow progression, certain devices with embedded biosensors have managed to be of diagnostic value in several countries. The perceptible increase in development of mobile platforms has revolutionized the healthcare delivery system in the new millennium. The present article reviews the most recent advancements in development of diagnostic nanobiosensors and their application in the clinical fields. KEY POINTS: • There is no specific treatment for highly transmissible SARS-CoV-2. • Early diagnosis is critical for control of pandemic. • Highly sensitive/specific nanobiosensors are emerging assets against COVID-19.


Subject(s)
Biosensing Techniques/methods , Early Diagnosis , Biosensing Techniques/instrumentation , Humans , Molecular Diagnostic Techniques , Nanotechnology , Nucleic Acid Amplification Techniques , /isolation & purification
18.
Radiol Med ; 125(10): 931-942, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-684337

ABSTRACT

PURPOSE: The purpose of our study was to assess the potential role of chest CT in the early detection of COVID-19 pneumonia and to explore its role in patient management in an adult Italian population admitted to the Emergency Department. METHODS: Three hundred and fourteen patients presented with clinically suspected COVID-19, from March 3 to 23, 2020, were evaluated with PaO2/FIO2 ratio from arterial blood gas, RT-PCR assay from nasopharyngeal swab sample and chest CT. Patients were classified as COVID-19 negative and COVID-19 positive according to RT-PCR results, considered as a reference. Images were independently evaluated by two radiologists blinded to the RT-PCR results and classified as "CT positive" or "CT negative" for COVID-19, according to CT findings. RESULTS: According to RT-PCR results, 152 patients were COVID-19 negative (48%) and 162 were COVID-19 positive (52%). We found substantial agreement between RT-PCR results and CT findings (p < 0.000001), as well as an almost perfect agreement between the two readers. Mixed GGO and consolidation pattern with peripheral and bilateral distribution, multifocal or diffuse abnormalities localized in both upper lung and lower lung, in association with interlobular septal thickening, bronchial wall thickening and air bronchogram, showed higher frequency in COVID-positive patients. We also found a significant correlation between CT findings and patient's oxygenation status expressed by PaO2/FIO2 ratio. CONCLUSION: Chest CT has a useful role in the early detection and in patient management of COVID-19 pneumonia in a pandemic. It helps in identifying suspected patients, cutting off the route of transmission and avoiding further spread of infection.


Subject(s)
Betacoronavirus , Coronavirus Infections/diagnostic imaging , Mass Chest X-Ray/methods , Pneumonia, Viral/diagnostic imaging , Tomography, X-Ray Computed/methods , Adult , Aged , Aged, 80 and over , Coronavirus Infections/epidemiology , Early Diagnosis , Female , Humans , Italy/epidemiology , Lung/diagnostic imaging , Male , Middle Aged , Pandemics , Pneumonia, Viral/epidemiology , Real-Time Polymerase Chain Reaction , Retrospective Studies , Specimen Handling/methods , Young Adult
19.
Lancet Child Adolesc Health ; 5(5): 323-331, 2021 05.
Article in English | MEDLINE | ID: covidwho-1127105

ABSTRACT

BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a newly identified and serious health condition associated with SARS-CoV-2 infection. Clinical manifestations vary widely among patients with MIS-C, and the aim of this study was to investigate factors associated with severe outcomes. METHODS: In this retrospective surveillance study, patients who met the US Centers for Disease Control and Prevention (CDC) case definition for MIS-C (younger than 21 years, fever, laboratory evidence of inflammation, admitted to hospital, multisystem [≥2] organ involvement [cardiac, renal, respiratory, haematological, gastrointestinal, dermatological, or neurological], no alternative plausible diagnosis, and either laboratory confirmation of SARS-CoV-2 infection by RT-PCR, serology, or antigen test, or known COVID-19 exposure within 4 weeks before symptom onset) were reported from state and local health departments to the CDC using standard case-report forms. Factors assessed for potential links to severe outcomes included pre-existing patient factors (sex, age, race or ethnicity, obesity, and MIS-C symptom onset date before June 1, 2020) and clinical findings (signs or symptoms and laboratory markers). Logistic regression models, adjusted for all pre-existing factors, were used to estimate odds ratios between potential explanatory factors and the following outcomes: intensive care unit (ICU) admission, shock, decreased cardiac function, myocarditis, and coronary artery abnormalities. FINDINGS: 1080 patients met the CDC case definition for MIS-C and had symptom onset between March 11 and Oct 10, 2020. ICU admission was more likely in patients aged 6-12 years (adjusted odds ratio 1·9 [95% CI 1·4-2·6) and patients aged 13-20 years (2·6 [1·8-3·8]), compared with patients aged 0-5 years, and more likely in non-Hispanic Black patients, compared with non-Hispanic White patients (1·6 [1·0-2·4]). ICU admission was more likely for patients with shortness of breath (1·9 [1·2-2·9]), abdominal pain (1·7 [1·2-2·7]), and patients with increased concentrations of C-reactive protein, troponin, ferritin, D-dimer, brain natriuretic peptide (BNP), N-terminal pro B-type BNP, or interleukin-6, or reduced platelet or lymphocyte counts. We found similar associations for decreased cardiac function, shock, and myocarditis. Coronary artery abnormalities were more common in male patients (1·5 [1·1-2·1]) than in female patients and patients with mucocutaneous lesions (2·2 [1·3-3·5]) or conjunctival injection (2·3 [1·4-3·7]). INTERPRETATION: Identification of important demographic and clinical characteristics could aid in early recognition and prompt management of severe outcomes for patients with MIS-C. FUNDING: None.


Subject(s)
/complications , Systemic Inflammatory Response Syndrome/complications , Systemic Inflammatory Response Syndrome/therapy , Adolescent , Biomarkers/blood , /epidemiology , Child , Child, Preschool , Critical Care , Early Diagnosis , Ethnic Groups , Female , Humans , Infant , Infant, Newborn , Male , Retrospective Studies , Risk Factors , Systemic Inflammatory Response Syndrome/diagnosis , Systemic Inflammatory Response Syndrome/epidemiology , Time-to-Treatment , Treatment Outcome , United States , Young Adult
20.
Mikrochim Acta ; 188(4): 121, 2021 03 10.
Article in English | MEDLINE | ID: covidwho-1126559

ABSTRACT

A voltammetric genosensor has been developed for the early diagnosis of COVID-19 by determination of RNA-dependent RNA polymerase (RdRP) sequence as a specific target of novel coronavirus. The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) uses an RdRP for the replication of its genome and the transcription of its genes. Here, the silver ions (Ag+) in the hexathia-18-crown-6 (HT18C6) were used for the first time as a redox probe. Then, the HT18C6(Ag) incorporated carbon paste electrode (CPE) was further modified with chitosan and PAMAM dendrimer-coated silicon quantum dots (SiQDs@PAMAM) for immobilization of probe sequences (aminated oligonucleotides). The current intensity of differential pulse voltammetry using the redox probe was found to decrease with increasing the concentration of target sequence. Based on such signal-off trend, the proposed genosensor exhibited a good linear response to SARS-CoV-2 RdRP in the concentration range 1.0 pM-8.0 nM with a regression equation I (µA) = - 6.555 log [RdRP sequence] (pM) + 32.676 (R2 = 0.995) and a limit of detection (LOD) of 0.3 pM. The standard addition method with different spike concentrations of RdRP sequence in human sputum samples showed a good recovery for real sample analysis (> 95%). Therefore, the developed voltammetric genosensor can be used to determine SARS-CoV-2 RdRP sequence in sputum samples. PAMAM-functionalized SiQDs were used as a versatile electrochemical platform for the SARS-CoV-2 RdRP detection based on a signal off sensing strategy. In this study, for the first time, the silver ions (Ag+) in the hexathia-18-crown-6 carrier were applied as an electrochemical probe.


Subject(s)
/instrumentation , Nanotechnology/methods , /genetics , Biosensing Techniques , Dendrimers , Early Diagnosis , Electrodes , Humans , Limit of Detection , Sputum/virology , Virus Replication/genetics
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