Evidence map›Paper›PMID 38395766›Full record

ArticleBMC primary care2024

Limited incremental predictive value of the frailty index and other vulnerability measures from routine care data for mortality risk prediction in older patients with COVID-19 in primary care.

Hannah M la Roi-Teeuw, Kim Luijken, Marieke T Blom, Jacobijn Gussekloo, Simon P Mooijaart, Harmke A Polinder-Bos, Maarten van Smeden, Geert-Jan Geersing, Carline J van den Dries

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC primary care, 2024. 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 27% 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, 3 citations in OpenAlex.

  1. Observational
  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

9 authors at 5 institutions in 1 country.

Hannah M la Roi-TeeuwDepartment of General Practice and Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Stratenum 6.131, PO Box 85500, 3508 GA, Utrecht, The Netherlands. h.m.teeuw@umcutrecht.nl.
Kim LuijkenDepartment of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Marieke T BlomDepartment of General Practice, Amsterdam UMC Location Vrije Universiteit, Amsterdam, The Netherlands.
Jacobijn GusseklooLUMC Center for Medicine for Older People, Department of Public Health and Primary Care, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Simon P MooijaartLUMC Center for Medicine for Older People, Department of Public Health and Primary Care, Department of Internal Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Harmke A Polinder-BosSection of Geriatric Medicine, Department of Internal Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Maarten van SmedenDepartment of Epidemiology and Health Economics, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
Geert-Jan GeersingDepartment of General Practice and Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Stratenum 6.131, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
Carline J van den DriesDepartment of General Practice and Nursing Science, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Stratenum 6.131, PO Box 85500, 3508 GA, Utrecht, The Netherlands.
University Medical Center Utrecht · NLLeiden University Medical Center · NLErasmus MC · NLUtrecht University · NLVrije Universiteit Amsterdam · NL

Funding

The Netherlands Organisation for Health Research and Development "ZonMw" 10430102110005
6 · The paper itself

Abstract

backgroundDuring the COVID-19 pandemic, older patients in primary care were triaged based on their frailty or assumed vulnerability for poor outcomes, while evidence on the prognostic value of vulnerability measures in COVID-19 patients in primary care was lacking. Still, knowledge on the role of vulnerability is pivotal in understanding the resilience of older people during acute illness, and hence important for future pandemic preparedness. Therefore, we assessed the predictive value of different routine care-based vulnerability measures in addition to age and sex for 28-day mortality in an older primary care population of patients with COVID-19.

methodsFrom primary care medical records using three routinely collected Dutch primary care databases, we included all patients aged 70 years or older with a COVID-19 diagnosis registration in 2020 and 2021. All-cause mortality was predicted using logistic regression based on age and sex only (basic model), and separately adding six vulnerability measures: renal function, cognitive impairment, number of chronic drugs, Charlson Comorbidity Index, Chronic Comorbidity Score, and a Frailty Index. Predictive performance of the basic model and the six vulnerability models was compared in terms of area under the receiver operator characteristic curve (AUC), index of prediction accuracy and the distribution of predicted risks.

resultsOf the 4,065 included patients, 9% died within 28 days after COVID-19 diagnosis. Predicted mortality risk ranged between 7-26% for the basic model including age and sex, changing to 4-41% by addition of comorbidity-based vulnerability measures (Charlson Comorbidity Index, Chronic Comorbidity Score), more reflecting impaired organ functioning. Similarly, the AUC of the basic model slightly increased from 0.69 (95%CI 0.66 - 0.72) to 0.74 (95%CI 0.71 - 0.76) by addition of either of these comorbidity scores. Addition of a Frailty Index, renal function, the number of chronic drugs or cognitive impairment yielded no substantial change in predictions.

conclusionIn our dataset of older COVID-19 patients in primary care, the 28-day mortality fraction was substantial at 9%. Six different vulnerability measures had little incremental predictive value in addition to age and sex in predicting short-term mortality.

Indexed as

COVID-19FrailtyAgedCOVID-19 TestingHumansPandemicsPrimary Health CareCOVID-19FrailtyMultiple imputationOlder peoplePrimary carePrognosis researchPrognostic factor studyRegression modellingVulnerability

Identifiers

PMID38395766
PMCPMC10885372
OpenAlexW4392125886

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.