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Impact of the COVID-19 pandemic on the kidney community: lessons learned and future directions.

ABSTRACT: The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected patients with kidney disease, causing significant challenges in disease management, kidney research and trainee education. For patients, increased infection risk and disease severity, often complicated by acute kidney injury, have contributed to high mortality. Clinicians were faced with high clinical demands, resource shortages and novel ethical dilemmas in providing patient care. In this review, we address the impact of COVID-19 on the entire spectrum of kidney care, including acute kidney injury, chronic kidney disease, dialysis and transplantation, trainee education, disparities in health care, changes in health care policies, moral distress and the patient perspective. Based on current evidence, we provide a framework for the management and support of patients with kidney disease, infection mitigation strategies, resource allocation and support systems for the nephrology workforce.

SUBMITTER: Geetha D

PROVIDER: S-EPMC9400561 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature

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Impact of the COVID-19 pandemic on the kidney community: lessons learned and future directions.

Geetha Duvuru D Kronbichler Andreas A Rutter Megan M Bajpai Divya D Menez Steven S Weissenbacher Annemarie A Anand Shuchi S Lin Eugene E Carlson Nicholas N Sozio Stephen S Fowler Kevin K Bignall Ray R Ducharlet Kathryn K Tannor Elliot K EK Wijewickrama Eranga E Hafidz Muhammad I A MIA Tesar Vladimir V Hoover Robert R Crews Deidra D Varnell Charles C Danziger-Isakov Lara L Jha Vivekanand V Mohan Sumit S Parikh Chirag C Luyckx Valerie V

Nature reviews. Nephrology 20220824 11

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected patients with kidney disease, causing significant challenges in disease management, kidney research and trainee education. For patients, increased infection risk and disease severity, often complicated by acute kidney injury, have contributed to high mortality. Clinicians were faced with high clinical demands, resource shortages and novel ethical dilemmas in providing patient care. In this review, we address the imp ...[more]

PMID: 36002770

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Project description:BackgroundDuring the COVID-19 pandemic corruption risks were amplified in health systems globally, increasing health inequities within and between countries. During the pandemic, the deployment of COVID-19 vaccines, particularly concerning their procurement and distribution, had corruption risks given the large amounts of public and private funding allocated to them, the need for speed, the involvement of a high number of stakeholders, and often insufficient oversight. To explore this issue further, we conducted a descriptive, qualitative study of corruption risks in the COVID-19 vaccine deployment process.MethodsWe conducted a descriptive, qualitative study triangulating two data sources between May and August 2022: (1) published academic and grey literature and (2) key informant interviews with representatives from organizations involved with the COVAX Facility, representatives from COVAX donor and recipient countries, and individuals with expert knowledge of the COVID-19 vaccine deployment process (e.g., consultants for international organizations involved in COVID-19 vaccine deployment, members of non-governmental organizations, etc.).ResultsWe identified 44 academic articles and policy documents and triangulated. Documentary data with 16 key informant interviews. A review of the literature identified several corruption risks in the international COVID-19 vaccine procurement and distribution process such as a lack of transparency in the vaccine procurement process; a lack of transparency in the operation of the COVAX Facility; a risk of bribery; and a risk of vaccine theft or the introduction of substandard and falsified vaccines at the point of distribution. Key informants further articulated concerns about a lack of transparency in vaccine pricing and contracts and the exclusion of civil society organizations from the vaccine deployment process. Reported anti-corruption, transparency, and accountability (ACTA) mechanisms implemented across the many levels of the vaccine procurement and distribution deployment included institutional oversight processes, blockchain-based supply-chain solutions, and civil society engagements.ConclusionPublic health emergencies require nimble and quick actions on the part of governments, international organizations and other actors Our study on the COVID-19 vaccine deployment process highlights the pressing need for more robust ACTA mechanisms to reduce corruption risks and ensure fair and equitable access to lifesaving vaccines for populations.

Project description:Due to the rapid increase in the availability of patient data, there is significant interest in precision medicine that could facilitate the development of a personalized treatment plan for each patient on an individual basis. Radiation oncology is particularly suited for predictive machine learning (ML) models due to the enormous amount of diagnostic data used as input and therapeutic data generated as output. An emerging field in precision radiation oncology that can take advantage of ML approaches is radiogenomics, which is the study of the impact of genomic variations on the sensitivity of normal and tumor tissue to radiation. Currently, patients undergoing radiotherapy are treated using uniform dose constraints specific to the tumor and surrounding normal tissues. This is suboptimal in many ways. First, the dose that can be delivered to the target volume may be insufficient for control but is constrained by the surrounding normal tissue, as dose escalation can lead to significant morbidity and rare. Second, two patients with nearly identical dose distributions can have substantially different acute and late toxicities, resulting in lengthy treatment breaks and suboptimal control, or chronic morbidities leading to poor quality of life. Despite significant advances in radiogenomics, the magnitude of the genetic contribution to radiation response far exceeds our current understanding of individual risk variants. In the field of genomics, ML methods are being used to extract harder-to-detect knowledge, but these methods have yet to fully penetrate radiogenomics. Hence, the goal of this publication is to provide an overview of ML as it applies to radiogenomics. We begin with a brief history of radiogenomics and its relationship to precision medicine. We then introduce ML and compare it to statistical hypothesis testing to reflect on shared lessons and to avoid common pitfalls. Current ML approaches to genome-wide association studies are examined. The application of ML specifically to radiogenomics is next presented. We end with important lessons for the proper integration of ML into radiogenomics.

Dataset Information

Impact of the COVID-19 pandemic on the kidney community: lessons learned and future directions.

Publications

Impact of the COVID-19 pandemic on the kidney community: lessons learned and future directions.

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