Telerobotic ultrasound to provide obstetrical ultrasound services remotely during the COVID-19 pandemic.

INTRODUCTION: Obstetrical ultrasound imaging is critical in identifying at-risk pregnancies and informing clinical management. The coronavirus disease 2019 (COVID-19) pandemic has exacerbated challenges in accessing obstetrical ultrasound for patients in underserved rural and remote communities where this service is not available. This prospective descriptive study describes our experience of providing obstetrical ultrasound services remotely using a telerobotic ultrasound system in a northern Canadian community isolated due to a COVID-19 outbreak. METHODS: A telerobotic ultrasound system was used to perform obstetrical ultrasound exams remotely in La Loche, Canada, a remote community without regular access to obstetrical ultrasound. Using a telerobotic ultrasound system, a sonographer 605 km away remotely controlled an ultrasound probe and ultrasound settings. Twenty-one exams were performed in a five-week period during a COVID-19 outbreak in the community, including limited first-, second- and third-trimester exams (n = 11) and complete second-trimester exams (n = 10). Participants were invited to complete a survey at the end of the telerobotic ultrasound exam describing their experiences with telerobotic ultrasound. Radiologists subsequently interpreted all exams and determined the adequacy of the images for diagnosis. RESULTS: Of 11 limited obstetrical exams, radiologists indicated images were adequate in nine (81%) cases, adequate with some reservations in one (9%) case and inadequate in one (9%) case. Of 10 second-trimester complete obstetrical exams, radiologists indicated images were adequate in two (20%) cases, adequate with some reservations in three (30%) cases and inadequate in five (50%) cases. Second-trimester complete obstetrical exams were limited due to a combination of body habitus, foetal lie and telerobotic technology. DISCUSSION: A telerobotic ultrasound system may be used to answer focused clinical questions such as foetal viability, dating and foetal presentation in a timely manner while minimising patient travel to larger centres and potential exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), during the COVID-19 pandemic.

Pediatric chest radiograph interpretation: how far has artificial intelligence come? A systematic literature review.

Most artificial intelligence (AI) studies have focused primarily on adult imaging, with less attention to the unique aspects of pediatric imaging. The objectives of this study were to (1) identify all publicly available pediatric datasets and determine their potential utility and limitations for pediatric AI studies and (2) systematically review the literature to assess the current state of AI in pediatric chest radiograph interpretation. We searched PubMed, Web of Science and Embase to retrieve all studies from 1990 to 2021 that assessed AI for pediatric chest radiograph interpretation and abstracted the datasets used to train and test AI algorithms, approaches and performance metrics. Of 29 publicly available chest radiograph datasets, 2 datasets included solely pediatric chest radiographs, and 7 datasets included pediatric and adult patients. We identified 55 articles that implemented an AI model to interpret pediatric chest radiographs or pediatric and adult chest radiographs. Classification of chest radiographs as pneumonia was the most common application of AI, evaluated in 65% of the studies. Although many studies report high diagnostic accuracy, most algorithms were not validated on external datasets. Most AI studies for pediatric chest radiograph interpretation have focused on a limited number of diseases, and progress is hindered by a lack of large-scale pediatric chest radiograph datasets.

Program Report: Nîsohkamâtowak—Helping Patients and Families Living With Kidney Disease in Northern Saskatchewan

Purpose of the Program: Nîsohkamâtowak, the Cree word for Helping Each Other, is an initiative to close gaps in kidney health care for First Nations and Métis patients, their families, and communities in northern Saskatchewan. Nîsohkamâtowak emerged from a collaboration between the Kidney Health Community Program and First Nations and Métis Health Services to find ways to deliver better care and education to First Nations and Métis people living with kidney disease while acknowledging Truth and Reconciliation and the Calls to Action. Sources of Information: This article describes how traditional Indigenous protocols and storytelling were woven into the Nîsohkamâtowak events, gathering of patient and family voices in writing and video format, and how this work led to a collaborative co-designed process that incorporates the Truth and Reconciliation: Calls to Action into kidney care and the benefits we have seen so far. The teachings of the 4 Rs—respect, reciprocity, responsibility, and relevance, were critical to ensuring that Nîsohkamâtowak reports and learning were shared with participants and the communities represented in this initiative. Methods: Group discussions and sharing circles were facilitated in several locations throughout northern and central Saskatchewan. Main topics of discussion were traditional medicines, residential schools impact, community and peer supports for kidney disease patients, and cultural safety education for health care providers. Key Findings: The general themes selected for improvement were education, support within the local community, traditional practices and cultural competency, and delivery of services. To address these gaps in kidney care, the following objectives were co-created with First Nations and Métis patients, families, and communities for Kidney Health to provide culturally appropriate education and resources, to ensure appropriate follow-up support to include strengthening connections to communities and other health authorities, to incorporate traditional practices into program design, and to ensure appropriate service delivery across the spectrum of care with a focus on screening and referral, which is strongly linked to coordination of care with local health centers. Implications: As a result of this work, the Kidney Health Community Program restructured the delivery of services and continues to work with Nîsohkamâtowak advisors on safety initiatives and chronic kidney disease awareness, prevention, and management in their respective communities. The Truth and Reconciliation and Calls to Action are honored to close the gaps in kidney care. Limitations: Nîsohkamâtowak is a local Kidney Health initiative that has the good fortune of having dedicated funding and staff to carry out this work. The findings may be unique to the First Nations and Métis communities and people who shared their stories. Truth and Reconciliation is an ongoing commitment that must be nurtured. Although not part of this publication, the effects of COVID-19 have made it difficult to further advance the Calls to Action, with more limited staff resources and the inability to meet in person as in the past.

COVID-SAFE: An IoT-Based System for Automated Health Monitoring and Surveillance in Post-Pandemic Life.

In the early months of the COVID-19 pandemic with no designated cure or vaccine, the only way to break the infection chain is self-isolation and maintaining the physical distancing. In this article, we present a potential application of the Internet of Things (IoT) in healthcare and physical distance monitoring for pandemic situations. The proposed framework consists of three parts: a lightweight and low-cost IoT node, a smartphone application (app), and fog-based Machine Learning (ML) tools for data analysis and diagnosis. The IoT node tracks health parameters, including body temperature, cough rate, respiratory rate, and blood oxygen saturation, then updates the smartphone app to display the user health conditions. The app notifies the user to maintain a physical distance of 2 m (or 6 ft), which is a key factor in controlling virus spread. In addition, a Fuzzy Mamdani system (running at the fog server) considers the environmental risk and user health conditions to predict the risk of spreading infection in real time. The environmental risk conveys from the virtual zone concept and provides updated information for different places. Two scenarios are considered for the communication between the IoT node and fog server, 4G/5G/WiFi, or LoRa, which can be selected based on environmental constraints. The required energy usage and bandwidth (BW) are compared for various event scenarios. The COVID-SAFE framework can assist in minimizing the coronavirus exposure risk.