ABSTRACT
Coronavirus disease (Covid-19) is an infectious respiratory disease caused by SARS-CoV-2. Among the symptoms, the respiratory system of the sufferer is affected. This respiratory condition suggests that the chest imaging plays a key role in the diagnosis of the disease. Several pre-trained deep learning models have been developed to detect Covid-19 through chest radiographs. These models provide high precision for binary detection, however, when combined with other diseases such as pneumonia that also affect the respiratory system and lungs, they offer poorer quality performance and reduce screening performance. In this study, we analyze some neural networks models for binary and multiclass classification of X-ray images in order to find out the best accuracy of classification. The models are based on deep learning methodology to learn and classify images. They are extracted from well-known repositories such as Kaggle. The conducted experiments compare their performance in several scenarios: a multiclass classification model versus the combination of several binary classification models. Two methods for combining the output of the binary models are proposed to achieve the best performance. The results show that the best results are obtained with a well-trained multiclass model. However, a preliminary screening can be obtained from the binary models without creating and training a more complex model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Background. Over 5.74 million COVID-19 cases have been reported in Mexico as of May 1, 2022. Determining the impact of COVID-19 on functional status is essential to assess health services needs. The Post-COVID-19 Functional Status Scale (PCFS) is a patient-reported tool that evaluates functional status over time after COVID-19, listing a wide range of functional limitations. We aimed to assess the functional status of Mexican patients after recovery from COVID-19. Methods. This cross-sectional study was conducted fromApril 11 to May 1, 2022, through an online survey that included demographic and clinical data, PCFS grades 0-4 and persistent symptoms. We included Mexicans aged >=18 years who recovered from COVID-19 (>=14 days since diagnosis), who resided in Mexico and agreed to participate. We posted the survey on Facebook and Twitter. We performed a descriptive analysis of demographic and clinical variables and assessed the relationship between symptoms and PCFS grade. Statistical analyses were conducted in Stata/SE 17.0. Results. Of 959 respondents, 838 (87%) met inclusion and exclusion criteria. Mean age was 40 (IQR 34-46) years, 82% were female, and 40% lived in Mexico City. COVID-19 diagnosis ranged from March 21, 2020, to April 7, 2022, and mean days since diagnosis was 276 (IQR 91-480) days. Most (796, 95%) were treated as outpatients. In PCFS, 338 (40%) had no functional limitations (grade 0), 266 (32%) had negligible functional limitations (grade 1), 154 (18%) had slight functional limitations (grade 2), 44 (5%) had moderate functional limitations (grade 3), 12 (2%) had severe functional limitations (grade 4) and 24 (3%) had missing PCFS data. Overall, 654 (78%) completed the persistent symptoms section. Among them, 57% presented fatigue, 46% impaired concentration, and 10% were asymptomatic (Figure 1). Of those with >12 weeks since diagnosis, 88% (499/564) had at least one symptom. Conclusion. Although most participants had mild COVID-19 at diagnosis, we found a high prevalence of persistent symptoms (90%) and functional limitations (60%) after recovery, revealing the devastating impact of COVID-19 on quality of life. The PCFS may be a valuable and simple tool to screen patients who could benefit from referral to rehabilitation programs, particularly in resource-limited settings.
ABSTRACT
Anxiety and depression disorders have a high prevalence in the population, sometimes generated by exceptional situations such as the Covid-19 pandemic. The prevalence of these mental disorders could be inferred with Google Trends, a tool that analyzes Internet search holdings by time ranges and geographic location. In order to study the relationship between search trends for the terms “Anxiety” and “Depression” and their prevalence in Spain during the Covid-19 pandemic, a selective search analysis was carried out based on geographic variables (Madrid, Andalusia, Catalonia) and temporary (weeks in 2020). The words “Anxiety”, “Depression” and “Covid-19” were taken into account to make the estimates of search trends in Google Trends. The results showed significant differences between the autonomous communities in their interest in searching for information on depression, as well as a different temporal progression, both in anxiety and depression, which would reflect the fluctuations in the evolution of epidemiological data in each geographic region. Tools such as Google Trends would allow the health community to implement prevention strategies in the event of the detection of peaks of concern for certain mental disorders in specific regions and time periods. This is especially relevant if the prevalence of these disorders in the population can negatively interfere with the effectiveness of prevention and health containment policies in emergency situations © 2021,Ansiedad y Estres.All Rights Reserved
ABSTRACT
Introduction: During the present Sars cov-2 pandemic, pregnant women are considered high-risk group population due to a state of immune compromise. Previous knowledge regarding pregnant women and their newborns is rapidly changing as new covid discoveries are unraveled, paying special attention on newborns evolution during their first days of life. Objectives: To determine impact of Sars Cov2 infection on the expected birth weight of newborns of infected mothers. Methods: It is a descriptive, cross-sectional, observational and retrospective study involving the analysis of clinical records of patients from the infectiology service of the Hospital Español Mexico. The study includes newborns from mothers between the ages of 18 to 48 infected with Sars Cov2, confirmed by a PCR test. The study excludes patients with incomplete records. We evaluated the frequency and proportion of the qualitative variables;we obtained the arithmetic mean and the standard deviation for the quantitative variables with normal distribution. Results: Data included 36 patients from the infectology service between the months of March 2020 to April 2021, with positive PCR for sars cov 2, with a mean age of 34.28 ± 5.86 years, mainly presented the following comorbidities: : obesity in 27.8%, hypothyroidism 11.1%, diabetes 13.9%, gestational hypertension 13.9%. The principal symptoms presented by the mothers were respiratory in 19.4%, gastrointestinal 13.9%, asymptomatic presentation 47.2%. Newborns results were obtained with a mean gestational age of 37.3 ± 2.6, with a male predominance of 52.8%, with a mean birth weight of 2811.1 ± 616.7, height 47.64 ± 3.7. About 16.4% of the patients were premature, only 4 were admitted to the neonatal intensive care unit, due to sepsis, pediatric inflamatory multisystemic syndrome, and an intrauterine growth restriction. All the newborns had a negative PCR test despite the positive PCR of all the mothers Conclusion: Newborns from mothers infected with Sars cov 2, were born with appropriate weight for their gestational age. The immune system of newborn babies protects to have adequate nutrition during the gestational period, however, some presented inflammatory and vascular complications. Special emphasis should be done on maternal metabolic clinical history, such as obesity, metabolic syndrome, and hypothyroidism since these comorbidities can impact negatively in the prognosis of the infected mother and the newborn. It is very important to perform a nutritional screening during prenatal care for an adequate metabolic programming in early life in children.
ABSTRACT
An effective control of the COVID-19 pandemic requires a thorough epidemiological interview of reported cases. The interviewer's skills and preparation directly affect the outcome of the investigation. This study applied a self-assessment survey of the COVID-19 patient interviewing skills on a local public health department workforce. The findings may be used to improve the quality of the interview process and the overall response to the pandemic at a community level. A 50-item questionnaire using a four-point Likert scale was adapted from the COVID-19 Patient Interview Skills Assessment Form created by the Centers for Disease Control and Prevention (CDC) and applied to 50 healthcare workers involved in epidemiological investigation of COVID-19 cases in Almada and Seixal, two municipalities of the Lisbon Metropolitan Area, from January to April of 2021. The most frequently executed steps concern checking patient data in advance (92%), questioning symptoms (97.2%), contact tracing (100%) and determining isolation periods for high risk contacts (100%). Least performed tasks include confirming the testing technique used (50%), asking about hospitalization (44.4%), assessing conditions for home isolation (44%), explaining how to self-monitor symptoms (61%) and checking if the patient understood the instructions (47%). In addition, 8% admitted to not always keeping patient information confidential. While caution is necessary as the data was limited to a single public health local department, our findings show that a majority of healthcare workers fulfill the essential steps of an epidemiological investigation. Areas in need of improvement include inquiring about infection severity, assessing social conditions for quarantine and confirming instructions for self-monitoring and follow-up. In line with CDC recommendations, we believe regular evaluation and feedback of case investigators' skills are crucial to quality assurance of a public health department. Key messages A detailed interview provides critical data for monitoring infected individuals and quickly trace, test and isolate those who might have been exposed, thus breaking chains of transmission. The results of this assessment can be used to introduce training measures such as shadowing and role-playing to ensure continued improvement in epidemiological investigations.