Evidence map›Paper›PMID 35911666›Full record

ArticleJAMIA open2022

An ordinal severity scale for COVID-19 retrospective studies using Electronic Health Record data.

Maryam Khodaverdi, Bradley S Price, J Zachary Porterfield, H Timothy Bunnell, Michael T Vest, Alfred Jerrod Anzalone, Jeremy Harper, Wes D Kimble, Hamidreza Moradi, Brian Hendricks and 3 more

Abstract read
In one paragraph

Article in JAMIA open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Observational
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Maryam KhodaverdiWest Virginia Clinical and Translational Sciences Institute, Morgantown, West Virginia, USA.ORCID https://orcid.org/0000-0002-7559-1656
Bradley S PriceWest Virginia Clinical and Translational Sciences Institute, Morgantown, West Virginia, USA.
J Zachary PorterfieldDepartment of Medicine, University of Kentucky, Lexington, Kentucky, USA.
H Timothy BunnellBiomedical Research Informatics Center, Nemours Children's Health, Wilmington, Delaware, USA.
Michael T VestSection of Pulmonary and Critical Care Medicine, Christiana Care Health System, Newark, Delaware, USA.
Alfred Jerrod AnzaloneDepartment of Neurological Sciences, University of Nebraska Medical Center, Omaha, Nebraska, USA.
Jeremy HarperOwl Health Works LLC, Indianapolis, Indiana, USA.ORCID https://orcid.org/0000-0003-1244-8948
Wes D KimbleWest Virginia Clinical and Translational Sciences Institute, Morgantown, West Virginia, USA.
Hamidreza MoradiDepartment of Data Science, University of Mississippi Medical Center, Jackson, Mississippi, USA.
Brian HendricksDepartment of Epidemiology, West Virginia University, Morgantown, West Virginia, USA.
Susan L SantangeloCenter for Psychiatric Research, Maine Medical Center Research Institute, and Maine Medical Center, Portland, Maine, USA.
Sally L HodderWest Virginia Clinical and Translational Sciences Institute, Morgantown, West Virginia, USA.
N3C Consortium Collaborators

Funding

West Virginia IDEA-CTRU54GM104942 · NIGMS · WEST VIRGINIA UNIVERSITY · PI Sally Lynn Hodder · 2012 to 2026
$81.0M
Tracking and Evaluation CoreU54GM115458 · NIGMS · UNIVERSITY OF NEBRASKA MEDICAL CENTER · PI RIZZO, MATTHEW · 2016 to 2025
$42.8M
CD2H - The National COVID Cohort Collaborative (N3C) IDeA CTR CollaborationU24TR002306 · NCATS · UNIVERSITY OF COLORADO DENVER · PI CHUTE, CHRISTOPHER G, EICHMANN, DAVID A. · 2017 to 2021
$28.9M
NCATS NIH HHS U24 TR002306NIGMS NIH HHS U54 GM104942NIGMS NIH HHS U54 GM115458
6 · The paper itself

Abstract

Objectives: Although the World Health Organization (WHO) Clinical Progression Scale for COVID-19 is useful in prospective clinical trials, it cannot be effectively used with retrospective Electronic Health Record (EHR) datasets. Modifying the existing WHO Clinical Progression Scale, we developed an ordinal severity scale (OS) and assessed its usefulness in the analyses of COVID-19 patient outcomes using retrospective EHR data. Materials and Methods: An OS was developed to assign COVID-19 disease severity using the Observational Medical Outcomes Partnership common data model within the National COVID Cohort Collaborative (N3C) data enclave. We then evaluated usefulness of the developed OS using heterogenous EHR data from January 2020 to October 2021 submitted to N3C by 63 healthcare organizations across the United States. Principal component analysis (PCA) was employed to characterize changes in disease severity among patients during the 28-day period following COVID-19 diagnosis. Results: The data set used in this analysis consists of 2 880 456 patients. PCA of the day-to-day variation in OS levels over the totality of the 28-day period revealed contrasting patterns of variation in disease severity within the first and second 14 days and illustrated the importance of evaluation over the full 28-day period. Discussion: An OS with well-defined, robust features, based on discrete EHR data elements, is useful for assessments of COVID-19 patient outcomes, providing insights on the progression of COVID-19 disease severity over time. Conclusions: The OS provides a framework that can facilitate better understanding of the course of acute COVID-19, informing clinical decision-making and resource allocation.

Indexed as

COVID-19 ordinal scaleElectronic Health RecordN3CNational COVID Cohort Collaborative

Identifiers

PMID35911666
PMCPMC9278199

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.