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Biomedicines
Special Issues
Emerging Trends in Diagnosis for COVID-19
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Emerging Trends in Diagnosis for COVID-19

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 1679

Special Issue Editor

Dr. Chia-Yu Chi

E-Mail Website
Guest Editor
Division of Clinical Research, National Health Research Institutes, Miaoli, Taiwan
Interests: clinical microbiology; viral infection; pediatric infectious disease

Special Issue Information

Dear Colleagues,

The COVID-19 pandemic has caused high number of fatalities as well as economic and societal impacts. For a prompt return to previous levels of social interaction and business, virus spread must be kept under control; to achieve this, the development of new approaches for virus testing will be centralized. Diagnostic screening should be performed at mass scale and repeated over time. Different types of diagnostic tests are now available, with alternative methods and benefits. As monitoring capacity is limited, there is a demand for new strategies that could greatly increase laboratory efficiency while maintaining the benefits of time and cost effectiveness.

This Special Issue aims to focus on the increasing need for multidisciplinary approaches in which clinical and diagnostic concerns and insights incorporate to develop new efficient surveillance strategies, tailored to the characteristics of different monitoring contexts.

Dr. Chia-Yu Chi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • COVID-19
  • molecular testing
  • antigenic testing
  • clinical manifestations
  • mortality

Published Papers (1 paper)

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Research

9 pages, 587 KiB  
Article
Risk Stratification Model for Severe COVID-19 Disease: A Retrospective Cohort Study
by Miri Mizrahi Reuveni, Jennifer Kertes, Shirley Shapiro Ben David, Arnon Shahar, Naama Shamir-Stein, Keren Rosen, Ori Liran, Mattan Bar-Yishay and Limor Adler
Biomedicines 2023, 11(3), 767; https://doi.org/10.3390/biomedicines11030767 - 2 Mar 2023
Cited by 3 | Viewed by 1260
Abstract
Background: Risk stratification models have been developed to identify patients that are at a higher risk of COVID-19 infection and severe illness. Objectives To develop and implement a scoring tool to identify COVID-19 patients that are at risk for severe illness during the [...] Read more.
Background: Risk stratification models have been developed to identify patients that are at a higher risk of COVID-19 infection and severe illness. Objectives To develop and implement a scoring tool to identify COVID-19 patients that are at risk for severe illness during the Omicron wave. Methods: This is a retrospective cohort study that was conducted in Israel’s second-largest healthcare maintenance organization. All patients with a new episode of COVID-19 between 26 November 2021 and 18 January 2022 were included. A model was developed to predict severe illness (COVID-19-related hospitalization or death) based on one-third of the study population (the train group). The model was then applied to the remaining two-thirds of the study population (the test group). Risk score sensitivity, specificity, and positive predictive value rates, and receiver operating characteristics (ROC) were calculated to describe the performance of the model. Results: A total of 409,693 patients were diagnosed with COVID-19 over the two-month study period, of which 0.4% had severe illness. Factors that were associated with severe disease were age (age > 75, OR-70.4, 95% confidence interval [CI] 42.8–115.9), immunosuppression (OR-4.8, 95% CI 3.4–6.7), and pregnancy (5 months or more, OR-82.9, 95% CI 53–129.6). Factors that were associated with a reduced risk for severe disease were vaccination status (patients vaccinated in the previous six months OR-0.6, 95% CI 0.4–0.8) and a prior episode of COVID-19 (OR-0.3, 95% CI 0.2–0.5). According to the model, patients who were in the 10th percentile of the risk severity score were considered at an increased risk for severe disease. The model accuracy was 88.7%. Conclusions: This model has allowed us to prioritize patients requiring closer follow-up by their physicians and outreach services, as well as identify those that are most likely to benefit from anti-viral treatment during the fifth wave of infection in Israel, dominated by the Omicron variant. Full article
(This article belongs to the Special Issue Emerging Trends in Diagnosis for COVID-19)
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