Evidence map›Paper›PMID 36579493›Full record

ArticleJournal of personalized medicine2022

External Validation of COVID-19 Risk Scores during Three Waves of Pandemic in a German Cohort-A Retrospective Study.

Lukas Häger, Philipp Wendland, Stephanie Biergans, Simone Lederer, Marius de Arruda Botelho Herr, Christian Erhardt, Kristina Schmauder, Maik Kschischo, Nisar Peter Malek, Stefanie Bunk and 3 more

Open access · goldAbstract read
In one paragraph

Article in Journal of personalized medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.0field-weighted citation impact, top 23% of its field
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

2 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. 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 at 4 institutions in 1 country.

Lukas HägerDepartment of Internal Medicine 1, University Hospital Tübingen, Otfried-Müllerstrasse 10, 72076 Tubingen, Germany.
Philipp WendlandDepartment of Mathematics and Technology, University of Applied Sciences Koblenz, Joseph-Rovan-Allee 2, 53424 Remagen, Germany.ORCID 0000-0002-7170-0915
Stephanie BiergansMedical Data Integration Center (meDIC), University Hospital Tübingen, Schaffhausenstraße 77, 72072 Tubingen, Germany.
Simone LedererMedical Data Integration Center (meDIC), University Hospital Tübingen, Schaffhausenstraße 77, 72072 Tubingen, Germany.
Marius de Arruda Botelho HerrMedical Data Integration Center (meDIC), University Hospital Tübingen, Schaffhausenstraße 77, 72072 Tubingen, Germany.
Christian ErhardtMedical Data Integration Center (meDIC), University Hospital Tübingen, Schaffhausenstraße 77, 72072 Tubingen, Germany.
Kristina SchmauderInstitute of Medical Microbiology and Hospital Hygiene, University Hospital Tübingen, Elfriede-Aulhorn-Str. 6, 72076 Tubingen, Germany.
Maik KschischoDepartment of Mathematics and Technology, University of Applied Sciences Koblenz, Joseph-Rovan-Allee 2, 53424 Remagen, Germany.
Nisar Peter MalekDepartment of Internal Medicine 1, University Hospital Tübingen, Otfried-Müllerstrasse 10, 72076 Tubingen, Germany.
Stefanie BunkDepartment of Internal Medicine 1, University Hospital Tübingen, Otfried-Müllerstrasse 10, 72076 Tubingen, Germany.
Michael BitzerDepartment of Internal Medicine 1, University Hospital Tübingen, Otfried-Müllerstrasse 10, 72076 Tubingen, Germany.ORCID 0000-0002-4463-8263
Beryl Primrose GladstoneDepartment of Internal Medicine 1, University Hospital Tübingen, Otfried-Müllerstrasse 10, 72076 Tubingen, Germany.ORCID 0000-0002-4733-5890
Siri GöpelDepartment of Internal Medicine 1, University Hospital Tübingen, Otfried-Müllerstrasse 10, 72076 Tubingen, Germany.ORCID 0000-0002-7666-4634
University Children's Hospital Tübingen · DEGerman Center for Infection Research · DEKoblenz University of Applied Sciences · DEInstitute of Medical Microbiology and Hygiene · DE

Funding

University of Tübingen open access fund
6 · The paper itself

Abstract

Several risk scores were developed during the COVID-19 pandemic to identify patients at risk for critical illness as a basic step to personalizing medicine even in pandemic circumstances. However, the generalizability of these scores with regard to different populations, clinical settings, healthcare systems, and new epidemiological circumstances is unknown. The aim of our study was to compare the predictive validity of qSOFA, CRB65, NEWS, COVID-GRAM, and 4C-Mortality score. In a monocentric retrospective cohort, consecutively hospitalized adults with COVID-19 from February 2020 to June 2021 were included; risk scores at admission were calculated. The area under the receiver operating characteristic curve and the area under the precision-recall curve were compared using DeLong's method and a bootstrapping approach. A total of 347 patients were included; 23.6% were admitted to the ICU, and 9.2% died in a hospital. NEWS and 4C-Score performed best for the outcomes ICU admission and in-hospital mortality. The easy-to-use bedside score NEWS has proven to identify patients at risk for critical illness, whereas the more complex COVID-19-specific scores 4C and COVID-GRAM were not superior. Decreasing mortality and ICU-admission rates affected the discriminatory ability of all scores. A further evaluation of risk assessment is needed in view of new and rapidly changing epidemiological evolution.

Indexed as

4C-Mortality scoreCOVID-19 risk scoreCOVID-GRAMICUNEWSpandemic

Identifiers

PMID36579493
PMCPMC9693591
OpenAlexW4308049320

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.