Evidence map›Paper›PMID 37013651›Full record

ArticleDiagnostic and prognostic research2023

A study protocol of external validation of eight COVID-19 prognostic models for predicting mortality risk in older populations in a hospital, primary care, and nursing home setting.

Anum Zahra, Kim Luijken, Evertine J Abbink, Jesse M van den Berg, Marieke T Blom, Petra Elders, Jan Festen, Jacobijn Gussekloo, Karlijn J Joling, René Melis and 9 more

Open access · goldAbstract read
In one paragraph

Article in Diagnostic and prognostic research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

19 authors at 7 institutions in 1 country.

Anum ZahraJulius Center for Health Sciences and Primary Care, University Medical Center, Utrecht University, Utrecht, the Netherlands. a.zahra@umcutrecht.nl.ORCID http://orcid.org/0000-0003-1553-8092
Kim LuijkenJulius Center for Health Sciences and Primary Care, University Medical Center, Utrecht University, Utrecht, the Netherlands.
Evertine J AbbinkDepartment of Internal Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.
Jesse M van den BergDepartment of General Practice, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Marieke T BlomDepartment of General Practice, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Petra EldersDepartment of General Practice, Amsterdam Public Health Research Institute, Amsterdam UMC, Amsterdam, the Netherlands.
Jan FestenKBO-PCOB, Nieuwegein, the Netherlands.
Jacobijn GusseklooDepartment of Public Health and Primary Care & Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, the Netherlands.
Karlijn J JolingDepartment of Medicine for Older People, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
René MelisDepartment of Geriatric Medicine, Radboud University Medical Center, Nijmegen, the Netherlands.
Simon MooijaartDepartment of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Jeannette B PetersDepartment of Pulmonary Diseases, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, the Netherlands.
Harmke A Polinder-BosDepartment of Internal Medicine, Section of Geriatric Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
Bas F M van RaaijDepartment of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Annemieke SmorenbergDepartment of Internal Medicine, Section of Geriatric Medicine, Amsterdam UMC, Amsterdam, the Netherlands.
Hannah M la Roi-TeeuwJulius Center for Health Sciences and Primary Care, University Medical Center, Utrecht University, Utrecht, the Netherlands.
Karel G M MoonsJulius Center for Health Sciences and Primary Care, University Medical Center, Utrecht University, Utrecht, the Netherlands.
Maarten van SmedenJulius Center for Health Sciences and Primary Care, University Medical Center, Utrecht University, Utrecht, the Netherlands.
COOP Consortium
Utrecht University · NLRadboud University Nijmegen · NLLeiden University Medical Center · NLAmsterdam University Medical Centers · NLErasmus MC · NLGGD Amsterdam · NLPharmo Institute · NL

Funding

ZonMw 10430102110005
6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has a large impact worldwide and is known to particularly affect the older population. This paper outlines the protocol for external validation of prognostic models predicting mortality risk after presentation with COVID-19 in the older population. These prognostic models were originally developed in an adult population and will be validated in an older population (≥ 70 years of age) in three healthcare settings: the hospital setting, the primary care setting, and the nursing home setting.

methodsBased on a living systematic review of COVID-19 prediction models, we identified eight prognostic models predicting the risk of mortality in adults with a COVID-19 infection (five COVID-19 specific models: GAL-COVID-19 mortality, 4C Mortality Score, NEWS2 + model, Xie model, and Wang clinical model and three pre-existing prognostic scores: APACHE-II, CURB65, SOFA). These eight models will be validated in six different cohorts of the Dutch older population (three hospital cohorts, two primary care cohorts, and a nursing home cohort). All prognostic models will be validated in a hospital setting while the GAL-COVID-19 mortality model will be validated in hospital, primary care, and nursing home settings. The study will include individuals ≥ 70 years of age with a highly suspected or PCR-confirmed COVID-19 infection from March 2020 to December 2020 (and up to December 2021 in a sensitivity analysis). The predictive performance will be evaluated in terms of discrimination, calibration, and decision curves for each of the prognostic models in each cohort individually. For prognostic models with indications of miscalibration, an intercept update will be performed after which predictive performance will be re-evaluated. DISCUSSION: Insight into the performance of existing prognostic models in one of the most vulnerable populations clarifies the extent to which tailoring of COVID-19 prognostic models is needed when models are applied to the older population. Such insight will be important for possible future waves of the COVID-19 pandemic or future pandemics.

Indexed as

COVID-19COVID-19-related mortalityExternal validationOlderPrognostic models

Identifiers

PMID37013651
PMCPMC10069944
OpenAlexW4362520939

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.