scholarly journals Cohort Study: The Accuracy of Screening Methods of COVID-19 in Pregnancy: Practical Approach in Low Resources Health Services

2021 ◽  
Author(s):  
Muhammad Ilham Aldika Akbar ◽  
Khanizyah Erza Gumilar ◽  
Eccita Rahestyningtyas ◽  
Manggala Pasca Wardhana ◽  
Pungky Mulawardhana ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Pregnant Women ◽  
Antibody Test ◽  
Screening Methods ◽  
Rt Pcr ◽  
Predictive Values ◽  
X Ray ◽  
Low Middle Income Countries ◽  
Chest X Ray ◽  
Rapid Antibody

Background All pregnant women in labor should be universally screened for Coronavirus Disease 2019 (COVID-19) during pandemic periods using Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) test. In many low-middle income countries, screening method was developed as an initial examination because of limited availability of RT-PCR tests. Objectives This study aims to evaluate the screening methods of COVID-19 accuracy in pregnant women. Material and Methods We recruited all pregnant women with suspicion of COVID-19 from April - August 2020 at Universitas Airlangga hospital, Surabaya, Indonesia. The participant was divided into two groups based on RT-PCR results: COVID-19 and non-COVID-19 group. The proportion of positive signs & symptoms, rapid antibody test, abnormal findings in chest x-ray, and neutrophil to lymphocyte ratio (NLR) value were then compared between both groups. The sensitivity, specificity, positive predictive value (PPV), negative predictive values (NPV), and diagnostic accuracy (DOR) were calculated. Results A total 141 pregnant women with suspected COVID-19 cases were recruited for this study. This consist of 62 COVID-19 cases (43.9%) and 79 non COVID-19 pregnant women (56.1%). The sensitivity, spesificity, PPV, NPV, and diagnostic accuracy of each parameter are as follow: clinical sign & symptoms (24.19%, 75.95%, 3.92%, 96.11%, 65.87%), rapid antibody test (72.73%, 35.06%, 4.35%, 96.94%, 36.53%), chest x-ray (40.68%, 59.45%, 3.92%, 96.11%, 58.76%), and NLR > 5.8 (41.38%, 72%, 5.66%, 96.80%, 70.81%). Conclusions The use of combined screening methods can classify pregnant women with high-risk COVID-19 before definitively diagnosed with RT-PCR. This practice will help to reduce RT-PCR need in a limited resources country.

scholarly journals Chest X-Ray Has Poor Diagnostic Accuracy and Prognostic Significance in COVID-19: A Propensity Matched Database Study

2020 ◽  
Author(s):  
Aditya Borakati ◽  
Adrian Perera ◽  
James Johnson ◽  
Tara Sood
Keyword(s):  
Computed Tomography ◽  
Diagnostic Accuracy ◽  
Sensitivity And Specificity ◽  
Vital Signs ◽  
Health Science ◽  
British Society ◽  
Imaging Features ◽  
Rt Pcr ◽  
X Ray ◽  
Chest X Ray

Objectives: To identify the diagnostic accuracy of common imaging modalities, chest X-ray (CXR) and computed tomography (CT) for diagnosis of COVID-19 in the general emergency population in the UK and to find the association between imaging features and outcomes in these patients. Design: Retrospective analysis of electronic patient records Setting: Tertiary academic health science centre and designated centre for high consequence infectious diseases in London, UK. Participants: 1,198 patients who attended the emergency department with paired RT-PCR swabs for SARS-CoV 2 and CXR between 16th March and 16th April 2020 Main outcome measures: Sensitivity and specificity of CXR and CT for diagnosis of COVID-19 using the British Society of Thoracic Imaging reporting templates. Reference standard was any reverse transcriptase polymerase chain reaction (RT-PCR) positive naso-oropharyngeal swab within 30 days of attendance. Odds ratios of CXR in association with vital signs, laboratory values and 30-day outcomes were calculated. Results: Sensitivity and specificity of CXR for COVID-19 diagnosis were 0.56 (95% CI 0.51-0.60) and 0.60 (95% CI 0.54-0.65), respectively. For CT scans these were 0.85 (95% CI 0.79-0.90) and 0.50 (95% CI 0.41-0.60), respectively. This gave a statistically significant mean increase in sensitivity with CT compared with CXR, of 29% (95% CI 19%-38%, p<0.0001). Specificity was not significantly different between the two modalities. Chest X-ray findings were not statistically significantly or clinical meaningfully associated with vital signs, laboratory parameters or 30-day outcomes. Conclusions: Computed tomography has substantially improved diagnostic performance over CXR in COVID-19. CT should be strongly considered in the initial assessment for suspected COVID-19. This gives potential for increased sensitivity and considerably faster turnaround time, where capacity allows and balanced against excess radiation exposure risk.

scholarly journals Clinical Profile of Pregnant Women with COVID-19 Hospitalized in Regional Referral Hospital

2021 ◽  
pp. 5-9
Author(s):  
Juminten Saimin ◽  
Steven Ridwan ◽  
Irawaty Irawaty ◽  
Arimaswati Arimaswati ◽  
Sadly Salman ◽  
...  
Keyword(s):  
Pregnant Women ◽  
Fetal Distress ◽  
Referral Hospital ◽  
Clinical Profile ◽  
Rt Pcr ◽  
Regional Referral Hospital ◽  
X Ray ◽  
Education Levels ◽  
Chest X Ray ◽  
Death Cases

Objective: To determine the clinical profile of pregnant women with COVID-19 who hospitalized in a referral hospital.Methods: This was a descriptive study conducted on pregnant women with COVID-19 who were hospitalized at Regional Hospital of Bau-Bau and Bahteramas Hospital in Southeast Sulawesi from May to July 2020. The confirmation of COVID-19 was based on RT-PCR. Data including characteristics, clinical profile, laboratory test, imaging, management, and outcomes.Results: There were 41 pregnant women with COVID-19 and no maternal death cases. Maternal age was approximately 19 to 39 years, had middle education levels, and was a housewife. Most of them did not know their closed contacts, had no comorbidities, and referrals from other hospitals. They were 3rd-trimester and hospitalized with complaints related to pregnancy. Only 3 cases had complaints related to COVID-19, namely fever and cough. The majority of laboratory tests were leucocytosis. Chest X-ray shows bronchopneumonia, pneumonia, and normal imaging. Obstetrics management was performed according to the condition of the mother and fetus, including vaginal delivery, cesarean section, and curettage. The treatment was using broad-spectrum antibiotics and antiviral. Complications in the fetus/infant were abortion, fetal distress, LBW, and asphyxia.Conclusion: Pregnant women with COVID-19 have mild or asymptomatic symptoms, hospitalized with complaints related to their pregnancy, and treatment according to the condition of the mother and fetus. There are no complications in the mother, while complications in the baby are not clear.Keywords: COVID-19, pregnant women, referral hospital.   Abstrak Tujuan: Mengetahui gambaran klinis ibu hamil dengan COVID-19 yang masuk di rumah sakit rujukan COVID-19.Metode: Penelitian ini bersifat deskriptif yang dilakukan pada ibu hamil dengan COVID-19 yang dirawat di rumah sakit rujukan di Sulawesi Tenggara, yaitu RSUD Bau-Bau dan RSU Bahteramas di Kendari, pada bulan Mei sampai Juli 2020. Konfirmasi positif COVID-19 berdasarkan hasil pemeriksaan RT-PCR. Data berupa karakteristik, gambaran klinis, pemeriksaan penunjang, penatalaksanaan, dan luaran. Hasil: Terdapat 41 ibu hamil dengan COVID-19 dan tidak ada kasus kematian ibu. Usia ibu berkisar 19-39 tahun, tingkat pendidikan menengah, dan sebagai ibu rumah tangga. Sebagian besar kasus pada trimester-3, tidak tahu memiliki kontak erat, tidak memiliki komorbid, dan rujukan dari RS lain. Sebagian besar dirawat dengan keluhan terkait kehamilannya dan hanya 3 kasus dengan keluhan terkait COVID-19, yaitu demam dan batuk. Pemeriksaan laboratorium menunjukkan lekositosis. Gambaran foto toraks menunjukkan bronkopneumonia, pneumonia, dan normal. Tindakan obstetri dilakukan atas indikasi ibu dan janin, yaitu persalinan normal, seksio sesarea, dan kuretase. Terapi yang digunakan adalah antibiotic spectrum luas dan antivirus. Komplikasi pada janin/bayi berupa abortus, gawat janin, BBLR, dan asfiksia. Kesimpulan: Ibu hamil dengan COVID-19 memiliki gejala ringan atau asimtomatik, dirawat dengan keluhan terkait kehamilannya, dan dilakukan tindakan obstetri sesuai dengan indikasi ibu dan janin. Tidak ada komplikasi pada ibu, sedangkan komplikasi pada bayi belum jelas.Kata kunci: COVID-19, ibu hamil, rumah sakit rujukan

scholarly journals Higher Accuracy of Lung Ultrasound over Chest X-ray for Early Diagnosis of COVID-19 Pneumonia

2021 ◽  
Vol 18 (7) ◽  
pp. 3481
Author(s):  
Javier Martínez Redondo ◽  
Carles Comas Rodríguez ◽  
Jesús Pujol Salud ◽  
Montserrat Crespo Pons ◽  
Cristina García Serrano ◽  
...  
Keyword(s):  
Diagnostic Accuracy ◽  
Lung Ultrasound ◽  
Ultrasound Images ◽  
X Rays ◽  
Rt Pcr ◽  
X Ray ◽  
Lower Specificity ◽  
Chest X Ray ◽  
Interstitial Disease ◽  
Higher Sensitivity

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.

scholarly journals Chest CT as a Complement to RT-PCR to Confirm and Follow-up COVID-19 Patients

Medicinus ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 31
Author(s):  
Aziza Ghanie Icksan ◽  
Muhammad Hafiz ◽  
Annisa Dian Harlivasari
Keyword(s):  
Chest Ct ◽  
Rt Pcr ◽  
High Resolution Computed Tomography ◽  
X Ray ◽  
First Case ◽  
Chest X Ray ◽  
Polymerase Chain

<p><strong>Background : </strong>The first case of COVID-19 in Indonesia was recorded in March 2020. Limitation of reverse-transcription polymerase chain reaction (RT-PCR) has put chest CT as an essential complementary tool in the diagnosis and follow up treatment for COVID-19. Literatures strongly suggested that High-Resolution Computed Tomography (HRCT) is essential in diagnosing typical symptoms of COVID-19 at the early phase of disease due to its superior sensitivity  (97%) compared to chest x-ray (CXR).</p><p>The two cases presented in this case study showed the crucial role of chest CT with HRCT to establish the working diagnosis and follow up COVID-19 patients as a complement to RT-PCR, currently deemed a gold standard.<strong></strong></p>

scholarly journals A Fatal Case of COVID-19 in an Infant with Severe Acute Malnutrition Admitted to a Paediatric Ward in Niger

2020 ◽  
Vol 2020 ◽  
pp. 1-3
Author(s):  
Alido Soumana ◽  
Aboubacar Samaila ◽  
Lamine Mahaman Moustapha ◽  
Moumouni Kamaye ◽  
Balkissa Daouda ◽  
...  
Keyword(s):  
Nasal Swab ◽  
Severe Acute Malnutrition ◽  
Fatal Case ◽  
Acute Malnutrition ◽  
Rt Pcr ◽  
X Ray ◽  
Laboratory Confirmation ◽  
History Of ◽  
Chest X Ray ◽  
The Right

While there have been very few fatal cases, SARS-CoV-2 has been reported in paediatric patients. This study aims to describe a fatal case of COVID-19 in a child with severe acute malnutrition. The eight-month-old child presented with fever, diarrhoea, and difficulty in breathing. The mother of the child had fever and shortness of breath four weeks before she died. Physical examination revealed lethargy, dehydration, and severe weight loss with a weight of 5 kg at a height of 78 cm tall. The weight-for-height index was less than three Z-scores, which corresponds to severe acute malnutrition. The pulmonary examination revealed moderate respiratory distress, and the chest X-ray presented features suggestive of pneumonia in the right lung area. In the context of the COVID-19 outbreak in Niger and the circumstances of the mother’s death, a nasal swab was taken for laboratory confirmation. Treatment provided to the child included intranasal oxygen, antibiotics, and a dietary program with therapeutic milk. The child died 48 hours after his admission. The history of contact with a SARS-CoV-2 suspect or positive patient should lead to screening for infection by using RT-PCR. It is important to investigate malnutrition as a potential risk factor for severe SARS-CoV-2 infection and resultant mortality.

scholarly journals Population screening for coeliac disease in primary care by district nurses using a rapid antibody test: diagnostic accuracy and feasibility study

BMJ ◽  
2007 ◽  
Vol 335 (7632) ◽  
pp. 1244-1247 ◽  
Author(s):  
Ilma R Korponay-Szabó ◽  
Katalin Szabados ◽  
Jánosné Pusztai ◽  
Katalin Uhrin ◽  
Éva Ludmány ◽  
...  
Keyword(s):  
Primary Care ◽  
Diagnostic Accuracy ◽  
Coeliac Disease ◽  
Feasibility Study ◽  
Antibody Test ◽  
Population Screening ◽  
District Nurses ◽  
Rapid Antibody

scholarly journals ANALYZING CHEST X-RAY TO DIFFERENTIATE SYMPTOMS OF COVID-19 THROUGH ML APPROACH

2021 ◽  
Vol 5 (12) ◽  
Author(s):  
Deepali R Deshpande ◽  
Raj L Shah ◽  
Anish N Shaha
Keyword(s):  
Machine Learning ◽  
Learning Model ◽  
Time Constraints ◽  
X Rays ◽  
Rt Pcr ◽  
X Ray ◽  
Social Distancing ◽  
Machine Learning Model ◽  
Chest X Ray

The motive behind the project is to build a machine learning model for detection of Covid-19. Using this model, it is possible to classify images of chest x-rays into normal patients, pneumatic patients, and covid-19 positive patients. This CNN based model will help drastically to save time constraints among the patients. Instead of relying on limited RT-PCR kits, just a simple chest x-ray can help us determine health of the patient. Not only we get immediate results, but we can also practice social distancing norms more effectively.

scholarly journals Hybrid-COVID: A novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images

2020 ◽  
Author(s):  
Khaled Bayoudh ◽  
Fayçal Hamdaoui ◽  
Abdellatif Mtibaa
Keyword(s):  
Domain Adaptation ◽  
Respiratory Infections ◽  
Screening Methods ◽  
X Ray ◽  
Deep Model ◽  
Learning Techniques ◽  
Spatial Pyramid Pooling ◽  
Chest X Ray ◽  
3D Cnn ◽  
Novel Coronavirus

Abstract So far, COVID-19, the novel coronavirus, continues to spread rapidly in most countries of the world, putting people's lives at risk. According to the WHO, respiratory infections occur primarily in the majority of patients treated with COVID-19. For decades, chest X-ray (CXR) technologies have proven their ability to accurately detect and treat respiratory diseases. Deep learning techniques, as well as the availability of a large number of CXR samples, have made a significant contribution to the fight against this pandemic. However, the most common screening methods are based on 2D CNNs, since 3D counterparts are enormously costly and labor-intensive. In this study, a hybrid 2D/3D convolutional neural network (CNN) architecture for COVID-19 screening using CXRs has been developed. The proposed architecture consists of the incorporation of a pre-trained deep model (VGG-16) and a shallow 3D CNN, combined with a depth-wise separable convolution layer and a spatial pyramid pooling module (SPP). Specifically, the depth-wise separable convolution helps to preserve the useful features while reducing the computational burden of the model. The SPP module is designed to extract multi-level representations from intermediate ones. Experimental results show that the proposed framework can achieve reasonable performances when evaluated on a collected dataset (3 classes: COVID-19, Pneumonia, and Normal). Notably, it achieved a sensitivity of 98.33%, a specificity of 98.68% and an overall accuracy of 96.91%

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