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The recent studies have indicated the requisite of computed tomography scan analysis by radiologists extensively to find out the suspected patients of SARS-CoV-2 (COVID-19). The existing deep learning methods distribute one or more of the subsequent bottlenecks. Therefore, a straight forward method for detecting COVID-19 infection using real-world computed tomography scans is presented. The detection process consists of image processing techniques such as segmentation of lung parenchyma and extraction of effective texture features. The kernel-based support vector machine is employed over feature vectors for classification. The performance parameters of the proposed method are calculated and compared with the existing methodology on the same dataset. The classification results are found outperforming and the method is less probabilistic which can be further exploited for developing more realistic detection system.Copyright © 2023 Inderscience Enterprises Ltd.
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The human coronavirus disease 2019 (COVID-19) pandemic has affected overall healthcare delivery, including prenatal, antenatal and postnatal care. Hyperglycemia in pregnancy (HIP) is the most common medical condition encountered during pregnancy. There is little guidance for primary care physicians for providing delivery of optimal perinatal care while minimizing the risk of COVID-19 infection in pregnant women. This review aims to describe pragmatic modifications in the screening, detection and management of HIP during the COVID- 19 pandemic. In this review, articles published up to June 2021 were searched on multiple databases, including PubMed, Medline, EMBASE and ScienceDirect. Direct online searches were conducted to identify national and international guidelines. Search criteria included terms to extract articles describing HIP with and/or without COVID-19 between 1st March 2020 and 15th June 2021. Fasting plasma glucose, glycosylated hemoglobin (HbA1c) and random plasma glucose could be alternative screening strategies for gestational diabetes mellitus screening (at 24-28 weeks of gestation), instead of the traditional 2 h oral glucose tolerance test. The use of telemedicine for the management of HIP is recommended. Hospital visits should be scheduled to coincide with obstetric and ultrasound visits. COVID-19 infected pregnant women with HIP need enhanced maternal and fetal vigilance, optimal diabetes care and psychological support in addition to supportive measures. This article presents pragmatic options and approaches for primary care physicians, diabetes care providers and obstetricians for GDM screening, diagnosis and management during the pandemic, to be used in conjunction with routine antenatal care.
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OBJECTIVE: To assess the psychological impact of suspension/postponement of various fertility treatments on infertile women during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: This was a cross-sectional study conducted as an online survey among infertile women consulting either through teleconsultation or physical consultation at a fertility clinic of a tertiary care referral unit. A validated questionnaire was given as a WhatsApp link to the women who were consulting for the resumption of services. Questions asked were based on their socio-demographic parameters, fertility treatment at the time of suspension, anxiety (self-reported) and stress (perceived stress scale-4, PSS-4) due to delay in treatment, psychosocial effect of pandemic, and wishes regarding the resumption of fertility services. RESULTS: Of 430 patients who received the questionnaire, 250 completed the survey (response rate: 58%). The mean age of participants was 29.26±4.18 years and the majority (70.4%) had lower socioeconomic status. The average PSS-4 score was 7.8±0.71, and the prevalence of self-reported anxiety was 72%. Those who suffered migration during the pandemic had significantly higher PSS-4 scores, and increasing age was associated with increased self-reported anxiety due to the suspension of fertility services. The top three priorities reported were infertility and treatment delay (48.4%), job loss (19.2%), and the risk of contracting COVID-19 infection (16%). The degree of spousal support was significantly correlated with lower PSS-4 scores (r=-0.30, P<0.01). On multivariate logistic analysis, duration of infertility, delay in treatment due to suspension of services, and fear of COVID-19 infection were significant predictors of stress and anxiety. CONCLUSION: This study emphasizes the need to investigate psychosocial health and to provide psychological support to this vulnerable population in addition to triaging fertility treatments in a phased manner.
RESUMEN
Coronavirus disease (COVID-19) is caused by severe acute respiratory syndrome corona virus 2 (SARS-Cov-2), an RNA virus which has caused pandemic in the whole world. It has put an unprecedented burden on healthcare system globally, and neither obstetricians nor labour rooms are spared as deliveries and caesarean sections cannot be postponed. There is a threat of collapse of healthcare system in maternity wards and labour rooms due to risk for transmission to healthy patients, obstetricians, midwives and other staff. It is not possible to screen all pregnant women especially in developing countries but due to asymptomatic cases, risk of infection looms large. Many countries including India have declared lockdown to stop the transmission but delivery services have to continue. Proper planning and division of the healthcare system into COVID-positive and negative areas with separate staff can help minimise the spread and preserve precious resources. Hospital staff must protect themselves by wearing personal protective equipment (PPE) in COVID-positive and suspected cases.