Post-COVID-19 syndrome/impairment. definition, diagnosis and classification. a brief position paper of the Czech Pneumological and Phthisiological Society (June 2021 update)

The Working Group of the Czech Pneumological and Phthisiological Society proposed a simple classification of post-COVID-19 patients into four originally established clinical groups. These groups (A-B-C-D) are based on the presence or absence of respiratory symptoms (dyspnea, cough, chest pain) and signs of pulmonary involvement (decreased Theo, latent respiratory insufficiency, lung impairment according to chest X-ray/HRCT) at least three months after COVID-19 diagnosis.

COVID-19 patients' characteristic in COVID-19 referral hospital, surabaya, Indonesia

Background: Coronavirus 2019 (COVID-19) is a global pandemic with various clinical manifestations and is affected by multifactor. Epidemiological data of COVID-19 in Indonesia, especially in Surabaya have not been well established yet. Purpose: This study aims to provide the COVID-19 patients profile in Surabaya City, Indonesia. Method: The study data were retrospectively collected from electrical medical records in Primasatya Husada Citra (PHC) Hospital of Surabaya, one of the referral hospitals for COVID-19 in Surabaya. Descriptive and Spearman correlation statistics were done for data analysis.

POSTER: Diagnosis of COVID-19 through Transfer Learning Techniques on CT Scans: A Comparison of Deep Learning Models

The novel coronavirus disease (COVID-19) constitutes a public health emergency globally. It is a deadly disease which has infected more than 230 million people worldwide. Therefore, early and unswerving detection of COVID-19 is necessary. Evidence of this virus is most commonly being tested by RT-PCR test. This test is not 100% reliable as it is known to give false positives and false negatives. Other methods like X-Ray images or CT scans show the detailed imaging of lungs and have been proven more reliable. This paper compares different deep learning models used to detect COVID-19 through transfer learning technique on CT scan dataset. VGG-16 outperforms all the other models achieving an accuracy of 85.33 % on the dataset. © 2022 IEEE.

A domestic cat with respiratory symptoms caused by severe acute respiratory syndrome Coronavirus 2 infection

A 12-year-old indoor cat showed severe respiratory symptoms such as sneezing, nasal discharge and cough. On Day 5 after disease onset, an oral swab was collected and a real-time RT-PCR test was performed to detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), indicating that the sample from the cat was positive for SARS-CoV-2 genes. Since the symptoms worsened on Day 8, a general physical examination, blood tests, chest x-rays and treatment were carried out and oral, nasal and rectal swabs were collected. Mild bronchitis and increased serum amyloid A (SAA) were observed, but it did not lead to pneumonia. In addition, whole-genome analysis revealed that it was the delta variant of SARS-CoV-2. Then the cat recovered, and a significant increase of virus-neutralizing antibody titer was observed in the convalescent serum. In conclusion, this is the first report on a cat with respiratory symptoms caused by SARS-CoV-2 infection in Japan.

Analysis and prediction of COVID-19 disease using CNN-ResNet algorithm

In this paper presents the deep learning diagnostic functions for chest x-rays and a COVID-Net-based image classifier for classifying chest x-ray images. In this article, we use model integration and transfer learning to classify chest x-rays in two ways: covid and non-covid. CNN can be used to make our result, which is more sensitive than radiologists in the detection and diagnosis of lung modules. According to the precision and loss value, choose the CNN model with good effect for the fusion and dynamically improve your weight ratio during the training process. This algorithm, using the RESNET50 model, is more sensitive than radiologists in screening and diagnosing lung modules.

Management of pregnancy and childbirth with COVID - 19 infection during the operation of the multidisciplinary city hospital no. 3 of Nursultan in the infectious mode

Relevance. The Coronavirus pandemic, which has changed the lives of people and the medical community around the world, was announced by WHO in March 2020. The reason was the rapidly spreading new coronavirus infection SARS - CoV-2. It is important to know that in the future outbreaks of infections, crown-like or any other infections are not excluded and medical workers should be prepared to work in special conditions. The pandemic has not revealed a more severe course of the disease in pregnant women compared to the general population of adults, but medical workers need to be prepared for any development of the situation in case of changes in the epidemiological situation in the regions, the country and the world. The purpose of the study: analysis of the management of pregnancy and childbirth in patients infected with the COVID-19 virus in the mode of the infectious hospital of the Multidisciplinary City Hospital No. 3. Materials and methods research: A retrospective study was conducted based on the analysis of statistical data of 1541 medical records histories for the period from May to August 2021 in dynamics in the obstetric unit of the Multidisciplinary City Hospital No. 3 in Nur-Sultan. The inclusion criteria are pregnant patients with confirmed analysis of SARS - CoV-2 coronavirus infection. Clinical manifestations of COVID-19 coronavirus infection, laboratory, X-ray and CT data, timing and methods of delivery, severity and complications caused by this disease were taken for analysis in medical records. Quantitative data and percentage ratio are presented. Research results: 1501 (97.4%) hospitalized pregnant women had an average degree of CVI and a severe degree - 40 (2.6%). The following symptoms were most often noted: fever, cough, shortness of breath, diarrhea, sore throat, myalgia, chills. Less common: rash, headache, malaise and loss of appetite. Radiographs and CT data showed both typical bilateral signs of lung damage in 357 (30%) and unilateral signs in 618 (51.9%). Changes in laboratory parameters in these women included: an increase in the level of D-dimer, an increase in C-reactive protein, lymphocytopenia, a moderate increase in liver enzymes (aspartate aminotransferase, alanine aminotransferase), thrombocytopenia. Maternal mortality was not recorded during the study period. Conclusions: The management and treatment of pregnant women with coronavirus infection in MGB No. 3 in an infectious mode according to clinical protocols approved by the Joint Commission on the Quality of Medical Services of the Ministry of Health of the Republic of Kazakhstan allowed to improve pregnancy outcomes and prevent cases of maternal mortality. Further studies of the course of pregnancy and its outcomes in pregnant women with coronavirus infection are needed.

Triage and management of probable COVID-19 patients in the intensive care unit during the pandemic period

Aim: Republic of Turkey Ministry of Health dedicated our hospital as a transplant center during the pandemic period. We admitted probable Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) infection (COVID-19) cases and intensive care unit (ICU) patients from other centers, while confirmed COVID-19 cases were transferred to dedicated pandemic hospitals. The aim of this study was to determine the demographic parameters, clinical courses and outcomes of probable COVID-19 patients and to compare survivors with non-survivors admitted to our ICU. Materials and Methods: After Ethics Committee approval, 93 patients admitted to our ICU between March 23 and May 13 were analyzed retrospectively.