Computer-aided COVID-19 diagnosis: a possibility?

Coronavirus Disease 2019 (COVID-19) is extremely contagious with a very high mortality rate. Effective and early diagnosis of COVID-19 is therefore crucial when treating patients and limiting its spread. The currently available methods for reliably identifying COVID are time-consuming. Infected people display various symptoms, some of which can be manifested by radiographic imaging such as chest X-rays and CT scans. Recently, many advanced machine learning and deep learning models have been proposed for predicting COVID using chest X-rays and CT scans that have paved the way for computer-aided COVID-19 diagnosis (CACD) systems. Unfortunately, most of these studies employ specific model(s) using a specific dataset making comparison difficult and inconclusive. We still lack a clear picture on which technique is best for a reliable CACD system. In this study, we provide a comprehensive analysis to determine if a CACD system can be developed that can reliably and automatically predict COVID-19 with zero human intervention using currently available tools and techniques? For this purpose, we explore and implement five machine learning models (SVM, LR, RF, KNN and ANN) and three pre-trained deep learning classifiers (VGG-16, Xception and ResNet-50) to compare their performance using 17 benchmark chest X-rays and CT-scans datasets to predict normal and infected samples. Using different classifiers and different datasets, we show that VGG16 with a superior average accuracy (99.10%) is the most suited classifier for CACD when chest X-rays are used. For CT scans, RF can also be used in addition to VGG16 as both records an average accuracy of 93% overall CT scan datasets. Based on the number of experiments, and an average accuracy of 99.10% for the chest X-rays datasets, we conclude that a reliable CACD system is possible. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Functional Improvement Trajectories After Surgery (FIT After Surgery) study: protocol for a multicentre prospective cohort study to evaluate significant new disability after major surgery in older adults.

INTRODUCTION: Older adults prioritise surviving surgery, but also preservation of their functional status and quality of life. Current approaches to measure postoperative recovery, which focus on death, complications and length of hospitalisation, may miss key relevant domains. We propose that postoperative disability is an important patient-centred outcome to measure intermediate-to-long recovery after major surgery in older adults. METHODS AND ANALYSIS: The Functional Improvement Trajectories After Surgery (FIT After Surgery) study is a multicentre cohort study of 2000 older adults (≥65 years) having major non-cardiac surgery. Its objectives are to characterise the incidence, trajectories, risk factors and impact of new significant disability after non-cardiac surgery. Disability is assessed using WHO Disability Assessment Schedule (WHODAS) 2.0 instrument and participants' level-of-care needs. Disability assessments occur before surgery, and at 1, 3, 6, 9 and 12 months after surgery. The primary outcome is significantly worse WHODAS score or death at 6 months after surgery. Secondary outcomes are (1) significantly worse WHODAS score or death at 1 year after surgery, (2) increased care needs or death at 6 months after surgery and (3) increased care needs or death at 1 year after surgery. We will use multivariable logistic regression models to determine the association of preoperative characteristics and surgery type with outcomes, joint modelling to characterise longitudinal time trends in WHODAS scores over 12 months after surgery, and longitudinal latent class mixture models to identify clusters following similar trajectories of disability. ETHICS AND DISSEMINATION: The FIT After Surgery study has received research ethics board approval at all sites. Recruitment began in December 2019 but was placed on hold in March 2020 because of the COVID-19 pandemic. Recruitment was gradually restarted in October 2020, with 1-year follow-up expected to finish in 2023. Publication of the primary results is anticipated to occur in 2024.

Electroconvulsive Therapy in Canada During the First Wave of COVID-19: Results of the "What Happened" National Survey.

OBJECTIVES: The COVID-19 pandemic has disrupted the provision of essential and potentially life-saving procedural treatments such as electroconvulsive therapy (ECT). We surveyed ECT providers across Canada to understand how the first wave of the pandemic affected ECT delivery between mid-March 2020 and mid-May 2020. METHODS: The survey was administered to ECT team members and decision makers at 107 Canadian health care centers with a focus on 5 domains: operations, decision-making, hospital resources, ECT procedure, and patient impact. Responses were obtained from 72 institutions, and collected answers were used to derive representative responses reflecting the situation at each ECT center. For specific domains, responses were split into 2 databases representing the perspective of psychiatrists (n = 67 centers) and anesthesiologists (n = 24 centers). RESULTS: Provision of ECT decreased in 64% centers and was completely suspended in 27% of centers after the onset of the pandemic. Outpatient and maintenance ECT were more affected than inpatient and acute ECT. Programs reported a high level of collaboration between psychiatry and hospital leadership (59%) but a limited input from clinical ethicists (18%). Decisions were mostly made ad hoc leading to variability across institutions in adopted resource allocation, physical location of ECT delivery, and triaging frameworks. The majority of centers considered ECT to be aerosol-generating and incorporated changes to airway management. CONCLUSIONS: Electroconvulsive therapy services in Canada were markedly disrupted by the COVID-19 pandemic. The variability in decision-making across centers warrants the development of a rational approach toward offering ECT in pandemic contexts.

Pityriasis rubra pilaris-like eruption following administration of the BNT163b2 (Pfizer-BioNTech) mRNA COVID-19 vaccine.

We describe a case of a pityriasis rubra pilaris (PRP)-like eruption occurring following administration of the Pfizer-Biontech mRNA COVID-19 vaccine, with worsening of the condition following the second dose. To our knowledge, this is the first reported case of a PRP-like eruption as a cutaneous adverse event of the Pfizer-Biontech mRNA COVID-19 vaccine.

Intrauterine injection of HCG before embryo transfer: a parallel, double-blind randomized trial.

RESEARCH QUESTION: Does intrauterine administration of HCG before embryo transfer improve live birth rate during IVF cycles? DESIGN: A parallel, randomized controlled trial conducted between July 2018 and February 2020. Infertile women (n = 181) scheduled for fresh or vitrified-warmed embryo transfer after IVF carried out for any indication were randomized in a 1:1 ratio to receive either HCG (500 IU in 0.1 ml of tissue culture media) or culture media (0.1 ml of tissue culture media) via intrauterine injection 4 min before embryo transfer. In both groups, an intrauterine insemination catheter was used for administering the medication. Primary outcome was live birth, with ongoing pregnancy and clinical pregnancy as secondary outcomes. Analysis was based on intention-to-treat principle. RESULTS: Baseline and cycle characteristics were comparable between the two groups. In the control group, one woman with a confirmed clinical pregnancy was lost to follow-up. Live birth rates were 24% (22/90) in the HCG group versus 19% (17/90) in the control group (RR 1.29, 95% CI 0.74 to 2.27). Clinical pregnancy and ongoing pregnancy rates were 34% versus 26% (RR 1.31, 95% CI 0.84 to 2.04) and 24% versus 19% (RR 1.29, 95% CI 0.74 to 2.27) in the HCG and the control groups, respectively. CONCLUSION: Intrauterine injection of HCG before embryo transfer did not improve live birth rates in women undergoing IVF. As the study was designed to detect a 20% difference between groups, a smaller, clinically important difference could not be ruled out. Treatment outcomes were lower than expected in the control group.

Criminalisation of transmission of SARS-CoV-2: A potential challenge to controlling the outbreak in South Africa.

In March 2020, two cases of attempted murder were opened against people who had tested positive for COVID-19 and had not remained in quarantine. Criminal law has previously been used to criminalise intentional transmission of HIV in both South Africa (SA) and other countries. However, it has been found that criminalisation laws undermine public health and measures to control outbreaks by stigmatising those infected and deterring testing. This article explores whether SA's existing HIV criminalisation laws can be applied to the transmission of SARS-CoV-2, and the potential effect such measures could have on efforts to control the COVID-19 epidemic.

Criminalisation of transmission of SARS-CoV-2: A potential challenge to controlling the outbreak in South Africa

In March 2020, two cases of attempted murder were opened against people who had tested positive for COVID-19 and had not remained in quarantine. Criminal law has previously been used to criminalise intentional transmission of HIV in both South Africa (SA) and other countries. However, it has been found that criminalisation laws undermine public health and measures to control outbreaks by stigmatising those infected and deterring testing. This article explores whether SA's existing HIV criminalisation laws can be applied to the transmission of SARS-CoV-2, and the potential effect such measures could have on efforts to control the COVID-19 epidemic.