Back to all available

Development and validation of a model for early prediction of severe/critical COVID-19 in elderly patients

virology
emergency-and-critical-care
geriatrics
infectious-diseases
covid-19

Abstract

Background
The mortality rate of severe/critical coronavirus disease (COVID-19) is high in the elderly, and early prediction of its prognosis can facilitate timely treatment and reduce mortality. This study aims to identify early predictors of severe COVID-19 in elderly and construct a validated risk prediction model.
Methods
This retrospective study included 722 elderly COVID-19 patients (those aged ≥60) who attended Nanfang Hospital between July 2022 and August 2023. They were categorized as mild/moderate or severe/critical according to the extent of their condition during hospitalization. Predictive models were constructed using logistic regression analysis and visualized using nomograms. Receiver Operating Characteristic (ROC) Curves were used to assess the model's accuracy and predictive value. An external validation cohort containing 1243 elderly COVID-19 patients who were admitted to Huashan Hospital between March and May 2022 was also collected.
Results
Univariate and multifactorial logistic regression analyses showed that respiratory rate, comorbid diabetes mellitus, C-reactive protein, lymphocyte percentage, and D-dimer were independent risk factors for severe and critical COVID-19. ROC curves showed that C-reactive protein, lymphocyte percentage, and D-dimer had a predictive value for the severity of COVID-19 (P < 0.05); C-reactive protein and D-dimer were important predictors of death.
Conclusions
The predictive model incorporating features selected via logistic regression accurately predicts prognosis of severe COVID-19 in elderly, facilitating the implementation of early clinical interventions.
Keywords: COVID-19, risk stratification, logistic regression, predictive model, personalized medicine
Ask to review this manuscript

Notes for potential reviewers

  • Volunteering is not a guarantee that you will be asked to review. There are many reasons: reviewers must be qualified, there should be no conflicts of interest, a minimum of two reviewers have already accepted an invitation, etc.
  • This is NOT OPEN peer review. The review is single-blind, and all recommendations are sent privately to the Academic Editor handling the manuscript. All reviews are published and reviewers can choose to sign their reviews.
  • What happens after volunteering? It may be a few days before you receive an invitation to review with further instructions. You will need to accept the invitation to then become an official referee for the manuscript. If you do not receive an invitation it is for one of many possible reasons as noted above.
  • PeerJ does not judge submissions based on subjective measures such as novelty, impact or degree of advance. Effectively, reviewers are asked to comment on whether or not the submission is scientifically and technically sound and therefore deserves to join the scientific literature. Our Peer Review criteria can be found on the "Editorial Criteria" page - reviewers are specifically asked to comment on 3 broad areas: "Basic Reporting", "Experimental Design" and "Validity of the Findings".
  • Reviewers are expected to comment in a timely, professional, and constructive manner.
  • Until the article is published, reviewers must regard all information relating to the submission as strictly confidential.
  • When submitting a review, reviewers are given the option to "sign" their review (i.e. to associate their name with their comments). Otherwise, all review comments remain anonymous.
  • All reviews of published articles are published. This includes manuscript files, peer review comments, author rebuttals and revised materials.
  • Each time a decision is made by the Academic Editor, each reviewer will receive a copy of the Decision Letter (which will include the comments of all reviewers).

If you have any questions about submitting your review, please email us at [email protected].