The diagnosis of pneumonia in a pregnant woman with coronavirus disease 2019 using maternal lung ultrasound.
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ABSTRACT:
SUBMITTER: Inchingolo R
PROVIDER: S-EPMC7194742 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Lung ultrasound has been suggested recently by the Chinese Critical Care Ultrasound Study Group and Italian Academy of Thoracic Ultrasound as an accurate tool to detect lung involvement in COVID-19. Although chest computed tomography (CT) represents the gold standard to assess lung involvement, with a specificity superior even to that of the nasopharyngeal swab for diagnosis, lung ultrasound examination can be a valid alternative to CT scan, with certain advantages, particularly for pregnant women. Ultrasound can be performed directly at the bed-side by a single operator, reducing the risk of spreading the disease among health professionals. Furthermore, it is a radiation-free exam, making it safer and easier to monitor those patients who require a series of exams. We report on four cases of pregnant women affected by COVID-19 who were monitored with lung ultrasound examination. All patients showed sonographic features indicative of COVID-19 pneumonia at admission: irregular pleural lines and vertical artifacts (B-lines) were observed in all four cases, and patchy areas of white lung were observed in two. Lung ultrasound was more sensitive than was chest X-ray in detecting COVID-19. In three patients, we observed almost complete resolution of lung pathology on ultrasound within 96 h of admission. Two pregnancies were ongoing at the time of writing, and two had undergone Cesarean delivery with no fetal complications. Reverse transcription polymerase chain reaction analysis of cord blood and newborn swabs was negative in both of these cases. Copyright © 2020 ISUOG. Published by John Wiley & Sons Ltd.
| S-EPMC7267364 | biostudies-literature
Project description:Background Radiologists are proficient in differentiating between chest radiographs with and without symptoms of pneumonia but have found it more challenging to differentiate coronavirus disease 2019 (COVID-19) pneumonia from non-COVID-19 pneumonia on chest radiographs. Purpose To develop an artificial intelligence algorithm to differentiate COVID-19 pneumonia from other causes of abnormalities at chest radiography. Materials and Methods In this retrospective study, a deep neural network, CV19-Net, was trained, validated, and tested on chest radiographs in patients with and without COVID-19 pneumonia. For the chest radiographs positive for COVID-19, patients with reverse transcription polymerase chain reaction results positive for severe acute respiratory syndrome coronavirus 2 with findings positive for pneumonia between February 1, 2020, and May 30, 2020, were included. For the non-COVID-19 chest radiographs, patients with pneumonia who underwent chest radiography between October 1, 2019, and December 31, 2019, were included. Area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were calculated to characterize diagnostic performance. To benchmark the performance of CV19-Net, a randomly sampled test data set composed of 500 chest radiographs in 500 patients was evaluated by the CV19-Net and three experienced thoracic radiologists. Results A total of 2060 patients (5806 chest radiographs; mean age, 62 years ± 16 [standard deviation]; 1059 men) with COVID-19 pneumonia and 3148 patients (5300 chest radiographs; mean age, 64 years ± 18; 1578 men) with non-COVID-19 pneumonia were included and split into training and validation and test data sets. For the test set, CV19-Net achieved an AUC of 0.92 (95% CI: 0.91, 0.93). This corresponded to a sensitivity of 88% (95% CI: 87, 89) and a specificity of 79% (95% CI: 77, 80) by using a high-sensitivity operating threshold, or a sensitivity of 78% (95% CI: 77, 79) and a specificity of 89% (95% CI: 88, 90) by using a high-specificity operating threshold. For the 500 sampled chest radiographs, CV19-Net achieved an AUC of 0.94 (95% CI: 0.93, 0.96) compared with an AUC of 0.85 (95% CI: 0.81, 0.88) achieved by radiologists. Conclusion CV19-Net was able to differentiate coronavirus disease 2019-related pneumonia from other types of pneumonia, with performance exceeding that of experienced thoracic radiologists. © RSNA, 2021 Online supplemental material is available for this article.
| S-EPMC7841876 | biostudies-literature
Project description:Given the general utility of lung ultrasound for the evaluation of respiratory failure in acutely ill patients, it is logical to consider its specific advantages in coronavirus disease 2019-related pulmonary disease. The authors, representing the extensive experience of the North American and European coronavirus disease 2019 epicenters, present an ultrasound scanning protocol and report on the common associated ultrasound findings.
| S-EPMC7442124 | biostudies-literature
Project description:BackgroundA novel coronavirus of zoonotic origin (2019-nCoV) has recently been identified in patients with acute respiratory disease. This virus is genetically similar to SARS coronavirus and bat SARS-like coronaviruses. The outbreak was initially detected in Wuhan, a major city of China, but has subsequently been detected in other provinces of China. Travel-associated cases have also been reported in a few other countries. Outbreaks in health care workers indicate human-to-human transmission. Molecular tests for rapid detection of this virus are urgently needed for early identification of infected patients.MethodsWe developed two 1-step quantitative real-time reverse-transcription PCR assays to detect two different regions (ORF1b and N) of the viral genome. The primer and probe sets were designed to react with this novel coronavirus and its closely related viruses, such as SARS coronavirus. These assays were evaluated using a panel of positive and negative controls. In addition, respiratory specimens from two 2019-nCoV-infected patients were tested.ResultsUsing RNA extracted from cells infected by SARS coronavirus as a positive control, these assays were shown to have a dynamic range of at least seven orders of magnitude (2x10-4-2000 TCID50/reaction). Using DNA plasmids as positive standards, the detection limits of these assays were found to be below 10 copies per reaction. All negative control samples were negative in the assays. Samples from two 2019-nCoV-infected patients were positive in the tests.ConclusionsThe established assays can achieve a rapid detection of 2019n-CoV in human samples, thereby allowing early identification of patients.
| S-EPMC7108203 | biostudies-literature
Project description:BackgroundChest radiography (CXR) and computerized tomography (CT) are the standard methods for lung imaging in diagnosing COVID-19 pneumonia in the intensive care unit (ICU), despite their limitations. This study aimed to assess the performance of bedside lung ultrasound examination by a critical care physician for the diagnosis of COVID-19 pneumonia during acute admission to the ICU.MethodThis was an observational, prospective, single-center study conducted in the intensive care unit of Adan General Hospital from April 10, 2020, to May 26, 2020. The study included adults with suspicion of COVID-19 Infection who were transferred to the ICU. Patients were admitted to the ICU directly from the ED after reverse transcriptase-polymerase chain reaction (RT-PCR) swabs were sent to the central virology laboratory in Kuwait, and the results were released 16 to 24 hours after the time of admission. A certified intensivist in critical care ultrasound performed the lung ultrasound within 12 hours of the patient's admission to the ICU.The treating physician confirmed the diagnosis of COVID-19 pneumonia based on a set of clinical features, inflammatory markers, biochemical profile studies, RT-PCR test results, and CXR.ResultsOf 77 patients with suspected COVID-19 pneumonia, 65 (84.4%) were confirmed. The median age of the patients was 48 (31-68) years, and 51 (71%) were men.In the group of patients with confirmed COVID-19 pneumonia, LUS revealed four signs suggestive of COVID-19 pneumonia in 63 patients (96.9%) (sensitivity 96.9%, CI 85%-99.5%). Two patients presented with unilateral lobar pneumonia without other ultrasonic signs of COVID-19 pneumonia but with positive RT-PCR results. Among patients in the group without COVID-19 pneumonia who had negative RT-PCR results, 11 (91.7%) were LUS negative for COVID-19 pneumonia (specificity 91.7%, 95% CI 58.72%-99.77%).ConclusionsDuring the COVID-19 outbreak, LUS allows the identification of early signs of interstitial pneumonia. LUS patterns that show a combination of the four major signs offer high sensitivity and specificity compared to nasopharyngeal RT-PCR.
| S-EPMC8142626 | biostudies-literature
Project description:BackgroundClinical manifestation and neonatal outcomes of pregnant women with coronavirus disease 2019 (COVID-19) were unclear in Wuhan, China.MethodsWe retrospectively analyzed clinical characteristics of pregnant and nonpregnant women with COVID-19 aged from 20 to 40, admitted between January 15 and March 15, 2020 at Union Hospital, Wuhan, and symptoms of pregnant women with COVID-19 and compared the clinical characteristics and symptoms to historic data previously reported for H1N1.ResultsAmong 64 patients, 34 (53.13%) were pregnant, with higher proportion of exposure history (29.41% vs 6.67%) and more pulmonary infiltration on computed tomography test (50% vs 10%) compared to nonpregnant women. Of pregnant patients, 27 (79.41%) completed pregnancy, 5 (14.71%) had natural delivery, 18 (52.94%) had cesarean section, and 4 (11.76%) had abortion; 5 (14.71%) patients were asymptomatic. All 23 newborns had negative reverse-transcription polymerase chain results, and an average 1-minute Apgar score was 8-9 points. Pregnant and nonpregnant patients show differences in symptoms such as fever, expectoration, and fatigue and on laboratory tests such as neurophils, fibrinogen, D-dimer, and erythrocyte sedimentation rate. Pregnant patients with COVID-19 tend to have more milder symptoms than those with H1N1.ConclusionsClinical characteristics of pregnant patients with COVID-19 are less serious than nonpregnant. No evidence indicated that pregnant women may have fetal infection through vertical transmission of COVID-19. Pregnant patients with H1N1 had more serious condition than those with COVID-19.
| S-EPMC7384380 | biostudies-literature
Project description:BACKGROUND:Guidelines currently do not recommend the routine use of chest x-ray (CXR) in bronchiolitis. However, CXR is still performed in a high percentage of cases, mainly to diagnose or rule out pneumonia. The inappropriate use of CXR results in children exposure to ionizing radiations and increased medical costs. Lung Ultrasound (LUS) has become an emerging diagnostic tool for diagnosing pneumonia in the last decades. The purpose of this study was to assess the diagnostic accuracy and reliability of LUS for the detection of pneumonia in hospitalized children with bronchiolitis and to evaluate the agreement between LUS and CXR in diagnosing pneumonia in these patients. METHODS:We enrolled children admitted to our hospital in 2016-2017 with a diagnosis of bronchiolitis and undergone CXR because of clinical suspicion of concomitant pneumonia. LUS was performed in each child by a pediatrician blinded to the patient's clinical, laboratory and CXR findings. An exploratory analysis was done in the first 30 patients to evaluate the inter-observer agreement between a pediatrician and a radiologist who independently performed LUS. The diagnosis of pneumonia was established by an expert clinician based on the recommendations of the British Thoracic Society guidelines. RESULTS:Eighty seven children with bronchiolitis were investigated. A final diagnosis of concomitant pneumonia was made in 25 patients. Sensitivity and specificity of LUS for the diagnosis of pneumonia were 100% and 83.9% respectively, with an area under-the-curve of 0.92, while CXR showed a sensitivity of 96% and specificity of 87.1%. When only consolidation >?1?cm was considered consistent with pneumonia, the specificity of LUS increased to 98.4% and the sensitivity decreased to 80.0%, with an area under-the-curve of 0.89. Cohen's kappa between pediatrician and radiologist sonologists in the first 30 patients showed an almost perfect agreement in diagnosing pneumonia by LUS (K 0.93). CONCLUSIONS:This study shows the good accuracy of LUS in diagnosing pneumonia in children with clinical bronchiolitis. When including only consolidation size >?1?cm, specificity of LUS was higher than CXR, avoiding the need to perform CXR in these patients. Added benefit of LUS included high inter-observer agreement. TRIAL REGISTRATION:Identifier: NCT03280732 . Registered 12 September 2017 (retrospectively registered).
| S-EPMC6286612 | biostudies-literature
Project description:Background and objectivePneumonia is the leading cause of death of children. Diagnostic tools include chest radiography, but guidelines do not currently recommend the use of lung ultrasound (LUS) as a diagnostic method. We conducted a meta-analysis to summarize evidence on the diagnostic accuracy of LUS for childhood pneumonia.MethodsWe performed a systematic search in PubMed, Embase, the Cochrane Library, Scopus, Global Health, World Health Organization-Libraries, and Latin American and Caribbean Health Sciences Literature of studies comparing LUS diagnostic accuracy against a reference standard. We used a combination of controlled key words for age <18 years, pneumonia, and ultrasound. We identified 1475 studies and selected 15 (1%) for further review. Eight studies (765 children) were retrieved for analysis, of which 6 (75%) were conducted in the general pediatric population and 2 (25%) in neonates. Eligible studies provided information to calculate sensitivity, specificity, and positive and negative likelihood ratios. Heterogeneity was assessed by using Q and I(2) statistics.ResultsFive studies (63%) reported using highly skilled sonographers. Overall methodologic quality was high, but heterogeneity was observed across studies. LUS had a sensitivity of 96% (95% confidence interval [CI]: 94%-97%) and specificity of 93% (95% CI: 90%-96%), and positive and negative likelihood ratios were 15.3 (95% CI: 6.6-35.3) and 0.06 (95% CI: 0.03-0.11), respectively. The area under the receiver operating characteristic curve was 0.98. Limitations included the following: most studies included in our analysis had a low number of patients, and the number of eligible studies was also small.ConclusionsCurrent evidence supports LUS as an imaging alternative for the diagnosis of childhood pneumonia. Recommendations to train pediatricians on LUS for diagnosis of pneumonia may have important implications in different clinical settings.
| S-EPMC9923609 | biostudies-literature
Project description:BackgroundThe aim of this study was to evaluate sonographic features that may aid in risk stratification and to propose a focused cardiac and lung ultrasound (LUS) algorithm in patients with coronavirus disease 2019.MethodsTwo hundred consecutive hospitalized patients with coronavirus disease 2019 underwent comprehensive clinical and echocardiographic examination, as well as LUS, irrespective of clinical indication, within 24 hours of admission as part of a prospective predefined protocol. Assessment included calculation of the modified early warning score (MEWS), left ventricular systolic and diastolic function, hemodynamic and right ventricular assessment, and a calculated LUS score. Outcome analysis was performed to identify echocardiographic and LUS predictors of mortality or the composite event of mortality or need for invasive mechanical ventilation and to assess their adjunctive value on top of clinical parameters and MEWS.ResultsA simplified echocardiographic risk score composed of left ventricular ejection fraction < 50% combined with tricuspid annular plane systolic excursion < 18 mm was associated with mortality (P = .0002) and with the composite event (P = .0001). Stepwise analyses evaluating echocardiographic and LUS parameters on top of existing clinical risk scores showed that addition of tricuspid annular plane systolic excursion and stroke volume index improved prediction of mortality when added to clinical variables but not when added to MEWS. Once echocardiography was added, and patients were recategorized as high risk only if having both high-risk MEWS and high-risk cardiac features, specificity increased from 63% to 87%, positive predictive value from 28% to 48%, and accuracy from 66% to 85%. Although LUS was not associated with incremental risk prediction for mortality above clinical and echocardiographic criteria, it improved prediction of need for invasive mechanical ventilation.ConclusionsIn hospitalized patients with coronavirus disease 2019, a very limited echocardiographic examination is sufficient for outcome prediction. The addition of echocardiography in patients with high-risk MEWS decreases the rate of falsely identifying patients as high risk to die and may improve resource allocation in case of high patient load.
| S-EPMC7870445 | biostudies-literature
Project description:In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named "2019 novel coronavirus (2019-nCoV)" by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world's attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.
| S-EPMC7003341 | biostudies-literature