Evaluation of patients with respiratory infections during the first pandemic wave in Germany: characteristics of COVID-19 versus non-COVID-19 patients

Abstract Background Characteristics of COVID-19 patients have mainly been reported within confirmed COVID-19 cohorts. By analyzing patients with respiratory infections in the emergency department during the first pandemic wave, we aim to assess differences in the characteristics of COVID-19 vs. Non-COVID-19 patients. This is particularly important regarding the second COVID-19 wave and the approaching influenza season. Methods We prospectively included 219 patients with suspected COVID-19 who received radiological imaging and RT-PCR for SARS-CoV-2. Demographic, clinical and laboratory parameters as well as RT-PCR results were used for subgroup analysis. Imaging data were reassessed using the following scoring system: 0 – not typical, 1 – possible, 2 – highly suspicious for COVID-19. Results COVID-19 was diagnosed in 72 (32,9%) patients. In three of them (4,2%) the initial RT-PCR was negative while initial CT scan revealed pneumonic findings. 111 (50,7%) patients, 61 of them (55,0%) COVID-19 positive, had evidence of pneumonia. Patients with COVID-19 pneumonia showed higher body temperature (37,7 ± 0,1 vs. 37,1 ± 0,1 °C; p = 0.0001) and LDH values (386,3 ± 27,1 vs. 310,4 ± 17,5 U/l; p = 0.012) as well as lower leukocytes (7,6 ± 0,5 vs. 10,1 ± 0,6G/l; p = 0.0003) than patients with other pneumonia. Among abnormal CT findings in COVID-19 patients, 57 (93,4%) were evaluated as highly suspicious or possible for COVID-19. In patients with negative RT-PCR and pneumonia, another third was evaluated as highly suspicious or possible for COVID-19 (14 out of 50; 28,0%). The sensitivity in the detection of patients requiring isolation was higher with initial chest CT than with initial RT-PCR (90,4% vs. 79,5%). Conclusions COVID-19 patients show typical clinical, laboratory and imaging parameters which enable a sensitive detection of patients who demand isolation measures due to COVID-19.

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Respiratory syncytial virus in severe lower respiratory infections in previously healthy young Ethiopian infants

BMC Pediatrics ◽

10.1186/s12887-021-02675-3 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Abate Yeshidinber Weldetsadik ◽

Frank Riedel

Keyword(s):

Respiratory Syncytial Virus ◽

Rainy Season ◽

Clinical Laboratory ◽

Respiratory Infections ◽

Clinical Parameter ◽

Imaging Data ◽

Chi Square ◽

Young Infants ◽

Rsv Infection ◽

Syncytial Virus

Abstract Background Respiratory Syncytial Virus (RSV) is the commonest cause of acute lower respiratory infections (ALRI) in infants. However, the burden of RSV is unknown in Ethiopia. We aimed to determine the prevalence, seasonality and predictors of RSV infection in young infants with ALRI for the first time in Ethiopia. Methods We performed RSV immuno-chromatographic assay from nasopharyngeal swabs of infants, 29 days to 6 months of age. We included the first 10 eligible infants in each month from June 2018 to May 2019 admitted in a tertiary pediatric center. Clinical, laboratory and imaging data were also collected, and chi-square test and regression were used to assess associated factors with RSV infection. Results Among a total of 117 study children, 65% were male and mean age was 3 months. Bronchiolitis was the commonest diagnosis (49%). RSV was isolated from 26 subjects (22.2%) of all ALRI, 37% of bronchiolitis and 11% of pneumonia patients. Although RSV infection occurred year round, highest rate extended from June to November. No clinical or laboratory parameter predicted RSV infection and only rainy season (Adjusted Odds Ratio (AOR) 10.46 [95%. C.I. 1.95, 56.18]) was independent predictor of RSV infection. Conclusions RSV was isolated in a fifth of young infants with severe ALRI, mostly in the rainy season. Diagnosis of RSV infection in our setting require specific tests as no clinical parameter predicted RSV infection. Since RSV caused less than a quarter of ALRI in our setting, the other causes should be looked for in future studies.

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Diagnostic value of chest CT in outpatient for COVID-19 compare with RT-PCR

10.21203/rs.3.rs-41757/v1 ◽

2020 ◽

Author(s):

Weiwei Zhang ◽

Meifen Zhu ◽

Min Zhang

Keyword(s):

Laboratory Test ◽

Ground Glass Opacity ◽

Diagnostic Value ◽

Chest Ct ◽

Test Results ◽

Imaging Data ◽

Rt Pcr ◽

Spider Web ◽

Lesion Location ◽

Laboratory Test Results

Abstract ObjectivesThe pneumonia caused by the 2019 novel coronavirus recently break out in Wuhan, China, and was named as COVID-19. With the spread of the disease, it bring numbers of casualties,so now we need a way could fast and accuracy diagnose the disease.This paper aims to compare two way for diagnose COVID-19 in outpatient :Chest CT and RT-PCR.Materials and methodsThe study picked 248 patients who treated in fever clinical of GanZhou people's hospital,their complete clinical and imaging data were analysed retrospectively.Epidemiological data,symoptoms,laboratory test results include RT-PCR and the CT results include CT features,lesion location,lesion distribution of suspected COVID-19 infected patients were gathered.ResultsAll of 248 patients,at last 20 patients confirmed COVID-19,15 patients were confirmed in outpatient.More than 200 cases has laboratory test results disnormal.Only 15/248 patients had initial positive RT-PCR for COVID-19,5 patients had COVID-19 confirmed by two or more RT-PCR.50 cases(20.2%) had Ground glass opacity,42 cases(16.9%) had Consolidation,39 cases(15.7%) had Spider web pattern,38 cases(15.3%) had Interlobular septal thickening.For lesion location,22 cases(8.9%) involved Single lobe of one lung,13 cases(5.2%) involved Multiple lobes of one lung,174 cases(70.2%) involved Multiple lobes of both lungs,9 cases(3.6%) involved Bilateral lower lungs,25 cases(10.1%) involved Bilateral middle and lower lungs.Regarding the distribution of the lesions in the lung lobes,119 cases(47.98%) involved Subpleural distribution,19 cases(7.7%) involved Diffuse distribution,7 cases(2.8%) involved Peribronchial distribution,81 cases(32.7%) involved Mixed distribution.ConclusionChest CT can be applied in outpatient to make early diagnosis with sensitivity and accuracy better than that of nucleic acid detection.Trial registrationChiCTR2000032574. Registered 3 May 2020. retrospectively registered

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Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort

10.1101/2020.05.04.20076349 ◽

2020 ◽

Author(s):

Egon Burian ◽

Friederike Jungmann ◽

Georgios A. Kaissis ◽

Fabian K. Lohöfer ◽

Christoph D. Spinner ◽

...

Keyword(s):

Intensive Care ◽

Clinical Laboratory ◽

Risk Estimation ◽

Severe Disease ◽

Lung Parenchyma ◽

Diagnostic Tools ◽

Imaging Data ◽

Forest Modelling ◽

Imaging Parameters ◽

Icu Treatment

AbstractThe evolving dynamics of coronavirus disease 2019 (COVID-19) and the increasing infection numbers require diagnostic tools to identify patients at high risk for a severe disease course. Here we evaluate clinical and imaging parameters for estimating the need of intensive care unit (ICU) treatment. We collected clinical, laboratory and imaging data from 65 patients with confirmed COVID-19 infection based on PCR testing. Two radiologists evaluated the severity of findings in computed tomography (CT) images on a scale from 1 (no characteristic signs of COVID-19) to 5 (confluent ground glass opacities in over 50% of the lung parenchyma). The volume of affected lung was quantified using commercially available software. Machine learning modelling was performed to estimate the risk for ICU treatment. Patients with a severe course of COVID-19 had significantly increased IL-6, CRP and leukocyte counts and significantly decreased lymphocyte counts. The radiological severity grading was significantly increased in ICU patients. Multivariate random forest modelling showed a mean ± standard deviation sensitivity, specificity and accuracy of 0.72 ± 0.1, 0.86 ± 0.16 and 0.80 ± 0.1 and a ROC-AUC of 0.79 ± 0.1.The need for ICU treatment is independently associated with affected lung volume, radiological severity score, CRP and IL-6.

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Chest CT for early detection and management of coronavirus disease (COVID-19): a report of 314 patients admitted to Emergency Department with suspected pneumonia

La radiologia medica ◽

10.1007/s11547-020-01256-1 ◽

2020 ◽

Vol 125 (10) ◽

pp. 931-942 ◽

Cited By ~ 1

Author(s):

Cartocci Gaia ◽

Colaiacomo Maria Chiara ◽

Lanciotti Silvia ◽

Andreoli Chiara ◽

De Cicco Maria Luisa ◽

...

Keyword(s):

Emergency Department ◽

Early Detection ◽

Patient Management ◽

Chest Ct ◽

Wall Thickening ◽

Italian Population ◽

Rt Pcr ◽

Arterial Blood ◽

Ct Findings ◽

Route Of Transmission

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.

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Ruling out COVID-19 by chest CT at emergency admission when prevalence is low: the prospective, observational SCOUT study

Respiratory Research ◽

10.1186/s12931-020-01611-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Ulf Teichgräber ◽

Amer Malouhi ◽

Maja Ingwersen ◽

Rotraud Neumann ◽

Marina Reljic ◽

...

Keyword(s):

Emergency Department ◽

Sensitivity And Specificity ◽

Virus Disease ◽

Negative Likelihood Ratio ◽

Chest Ct ◽

Rt Pcr ◽

Predictive Values ◽

Suspected Infection ◽

General Wards ◽

Rule Out

Abstract Background It is essential to avoid admission of patients with undetected corona virus disease 2019 (COVID-19) to hospitals’ general wards. Even repeated negative reverse transcription polymerase chain reaction (RT-PCR) results do not rule-out COVID-19 with certainty. The study aimed to evaluate a rule-out strategy for COVID-19 using chest computed tomography (CT) in adults being admitted to the emergency department and suspected of COVID-19. Methods In this prospective, single centre, diagnostic accuracy cohort study, consecutive adults (≥ 18 years) presenting with symptoms consistent with COVID-19 or previous contact to infected individuals, admitted to the emergency department and supposed to be referred to general ward were included in March and April 2020. All participants underwent low-dose chest CT. RT-PCR- and specific antibody tests were used as reference standard. Main outcome measures were sensitivity and specificity of chest CT. Predictive values were calculated based on the theorem of Bayes using Fagan’s nomogram. Results Of 165 participants (56.4% male, 71 ± 16 years) included in the study, the diagnosis of COVID-19 was confirmed with RT-PCR and AB tests in 13 participants (prevalence 7.9%). Sensitivity and specificity of chest CT were 84.6% (95% confidence interval [CI], 54.6–98.1) and 94.7% (95% CI, 89.9–97.7), respectively. Positive and negative likelihood ratio of chest CT were 16.1 (95% CI, 7.9–32.8) and 0.16 (95% CI, 0.05–0.58) and positive and negative predictive value were 57.9% (95% CI, 40.3–73.7) and 98.6% (95% CI, 95.3–99.6), respectively. Conclusion At a low prevalence of COVID-19, chest CT could be used as a complement to repeated RT-PCR testing for early COVID-19 exclusion in adults with suspected infection before referral to hospital’s general wards. Trial registration ClinicalTrials.gov: NCT04357938 April 22, 2020.

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Virological COVID-19 surveillance in Bavaria, Germany suggests no SARS-CoV-2 spread prior to the first German case in January 2020

Infection ◽

10.1007/s15010-021-01611-y ◽

2021 ◽

Author(s):

Ute Eberle ◽

◽

Susanne Heinzinger ◽

Regina Konrad ◽

Clara Wimmer ◽

...

Keyword(s):

Respiratory Infections ◽

Influenza Season ◽

Epidemiological Data ◽

Acute Respiratory Infections ◽

Rt Pcr

AbstractThe Bavarian Influenza Sentinel (BIS) monitors the annual influenza season by combining virological and epidemiological data. The 2019/2020 influenza season overlapped with the beginning COVID-19 pandemic thus allowing to investigate whether there was an unnoticed spread of SARS-CoV-2 among outpatients with acute respiratory infections in the community prior to the first COVID-19 cluster in Bavaria. Therefore, we retrospectively analysed oropharyngeal swabs obtained in BIS between calendar week (CW) 39 in 2019 and CW 14 in 2020 for the presence of SARS-CoV-2 RNA by RT-PCR. 610 of all 1376 BIS swabs-contained sufficient material to test for SARS-CoV-2, among them 260 oropharyngeal swabs which were collected prior to the first notified German COVID-19 case in CW 04/2020. In none of these swabs SARS-CoV-2 RNA was detected suggesting no SARS-CoV-2 spread prior to late January 2020 in Bavaria.

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Chest CT imaging characteristics of COVID-19 pneumonia in preschool children: a retrospective study

10.21203/rs.3.rs-21851/v1 ◽

2020 ◽

Author(s):

Yang Li ◽

Jianghui Cao ◽

Xiaolong Zhang ◽

Guangzhi Liu ◽

Xiaxia Wu ◽

...

Keyword(s):

Preschool Children ◽

Clinical Laboratory ◽

Ct Imaging ◽

Chest Ct ◽

World Health ◽

Imaging Data ◽

Pleural Thickening ◽

Ct Findings ◽

Imaging Characteristics ◽

The Right

Abstract Background : Recently, the World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) outbreak a public health emergency of international concern. So far, however, limited data are available for children. Therefore, we aimed to investigate the clinical and chest CT imaging characteristics of COVID-19 in preschool children. Methods: From January 26, 2020 to February 20, 2020, the clinical and initial chest CT imaging data of eight preschool children with laboratory-confirmed COVID-19 from two hospitals were retrospectively collected. The chest CT imaging characteristics, including the distribution, shape, and density of lesions, and the pleural effusion, pleural changes, and enlarged lymph nodes were evaluated. Results: Two cases (25%) were classified as mild type, and they showed no obvious abnormal CT findings or minimal pleural thickening on the right side. Five cases (62.5%) were classified as moderate type. Among these patients, one case showed consolidation located in the subpleural region of the right upper lobe, with thickening in the adjacent pleura; one case showed multiple consolidation and ground-glass opacities (GGO) with blurry margins; one case displayed bronchial pneumonia-like changes in the left upper lobe; and two cases displayed asthmatic bronchitis-like changes. One case (12.5%) was classified as critical type and showed bronchial pneumonia-like changes in the bilateral lungs, presenting blurred and messy bilateral lung markings and multiple patchy shadows scattered along the lung markings with blurry margins. Conclusions: The chest CT findings of COVID-19 in preschool children are atypical and various. Accurate diagnosis requires a comprehensive evaluation of epidemiological, clinical, laboratory and CT imaging data.

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Machine learning is the key to diagnose COVID-19: a proof-of-concept study

Scientific Reports ◽

10.1038/s41598-021-86735-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Cedric Gangloff ◽

Sonia Rafi ◽

Guillaume Bouzillé ◽

Louis Soulat ◽

Marc Cuggia

Keyword(s):

Machine Learning ◽

False Negative ◽

Laboratory Data ◽

Chest Ct ◽

Potential Contribution ◽

Imaging Data ◽

Learning Models ◽

Rt Pcr ◽

Negative Results ◽

Machine Learning Models

AbstractThe reverse transcription-polymerase chain reaction (RT-PCR) assay is the accepted standard for coronavirus disease 2019 (COVID-19) diagnosis. As any test, RT-PCR provides false negative results that can be rectified by clinicians by confronting clinical, biological and imaging data. The combination of RT-PCR and chest-CT could improve diagnosis performance, but this would requires considerable resources for its rapid use in all patients with suspected COVID-19. The potential contribution of machine learning in this situation has not been fully evaluated. The objective of this study was to develop and evaluate machine learning models using routine clinical and laboratory data to improve the performance of RT-PCR and chest-CT for COVID-19 diagnosis among post-emergency hospitalized patients. All adults admitted to the ED for suspected COVID-19, and then hospitalized at Rennes academic hospital, France, between March 20, 2020 and May 5, 2020 were included in the study. Three model types were created: logistic regression, random forest, and neural network. Each model was trained to diagnose COVID-19 using different sets of variables. Area under the receiving operator characteristics curve (AUC) was the primary outcome to evaluate model’s performances. 536 patients were included in the study: 106 in the COVID group, 430 in the NOT-COVID group. The AUC values of chest-CT and RT-PCR increased from 0.778 to 0.892 and from 0.852 to 0.930, respectively, with the contribution of machine learning. After generalization, machine learning models will allow increasing chest-CT and RT-PCR performances for COVID-19 diagnosis.

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Association between Clinical, Laboratory and CT Characteristics and RT-PCR Results in the Follow-up of COVID-19 patients

10.1101/2020.03.19.20038315 ◽

2020 ◽

Cited By ~ 7

Author(s):

Hang Fu ◽

Huayan Xu ◽

Na Zhang ◽

Hong Xu ◽

Zhenlin Li ◽

...

Keyword(s):

Polymerase Chain Reaction ◽

Reverse Transcriptase ◽

Clinical Laboratory ◽

Chest Ct ◽

Rt Pcr ◽

Chain Reaction ◽

Radiological Data ◽

Polymerase Chain ◽

Ct Features

AbstractBackgroundSince December 2019, more than 100,000 coronavirus disease 2019 (COVID-19) patients have been confirmed globally based on positive viral nucleic acids with real-time reverse transcriptase-polymerase chain reaction (RT-PCR). However, the association between clinical, laboratory and CT characteristics and RT-PCR results is still unclear. We sought to examine this association in detail, especially in recovered patients.MethodsWe analysed data from 52 confirmed patients who had been discharged with COVID-19. The clinical, laboratory, and radiological data were dynamically recorded and compared with the admission and follow-up RT-PCR results.ResultsIn this cohort, 52 admitted COVID-19 patients who had confirmed positive RT-PCR results were discharged after 2 rounds of consecutively negative RT-PCR results. Compared with admission levels, CRP levels (median 4.93 mg/L [IQR: 1.78-10.20]) decreased significantly (p<0.001). and lymphocyte counts (median 1.50×109/L [IQR: 1.11-1.88]) increased obviously after obtaining negative RT-PCR results (p<0.001). Additionally, substantially improved inflammatory exudation was observed on chest CT except for 2 progressed patients. At the two-week follow-up after discharge, 7 patients had re-positive RT-PCR results, including the abovementioned 2 progressed patients. Among the 7 patients, new GGO was demonstrated in 2 patients. There were no significant differences in CPR levels or lymphocyte counts when comparing the negative and re-positive PCT results (all p >0.05).ConclusionHeterogeneity between CT features and RT-PCR results was found in COVID-19, especially in some recovered patients with negative RT-PCR results. Our study highlights that both RT-PCR and chest CT should be considered as the key determinants for the diagnosis and management of COVID-19 patients.

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Chest CT imaging characteristics of COVID-19 pneumonia in preschool children: a retrospective study

10.21203/rs.3.rs-21851/v2 ◽

2020 ◽

Author(s):

Yang Li ◽

Jianghui Cao ◽

Xiaolong Zhang ◽

Guangzhi Liu ◽

Xiaxia Wu ◽

...

Keyword(s):

Preschool Children ◽

Clinical Laboratory ◽

Ct Imaging ◽

Chest Ct ◽

World Health ◽

Imaging Data ◽

Pleural Thickening ◽

Ct Findings ◽

Imaging Characteristics ◽

The Right

Abstract Background: Recently, the World Health Organization has declared the coronavirus disease 2019 (COVID-19) outbreak a public health emergency of international concern. So far, however, limited data are available for children. Therefore, we aimed to investigate the clinical and chest CT imaging characteristics of COVID-19 in preschool children.Methods: From January 26, 2020 to February 20, 2020, the clinical and initial chest CT imaging data of eight preschool children with laboratory-confirmed COVID-19 from two hospitals were retrospectively collected. The chest CT imaging characteristics, including the distribution, shape, and density of lesions, and the pleural effusion, pleural changes, and enlarged lymph nodes were evaluated. Results: Two cases (25%) were classified as mild type, and they showed no obvious abnormal CT findings or minimal pleural thickening on the right side. Five cases (62.5%) were classified as moderate type. Among these patients, one case showed consolidation located in the subpleural region of the right upper lobe, with thickening in the adjacent pleura; one case showed multiple consolidation and ground-glass opacities with blurry margins; one case displayed bronchial pneumonia-like changes in the left upper lobe; and two cases displayed asthmatic bronchitis-like changes. One case (12.5%) was classified as critical type and showed bronchial pneumonia-like changes in the bilateral lungs, presenting blurred and messy bilateral lung markings and multiple patchy shadows scattered along the lung markings with blurry margins.Conclusions: The chest CT findings of COVID-19 in preschool children are atypical and various. Accurate diagnosis requires a comprehensive evaluation of epidemiological, clinical, laboratory and CT imaging data.

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