Evidence map›Paper›PMID 33770140›Full record

ArticlePloS one2021

Risk factors for in-hospital mortality in laboratory-confirmed COVID-19 patients in the Netherlands: A competing risk survival analysis.

Gerine Nijman, Maike Wientjes, Jordache Ramjith, Nico Janssen, Jacobien Hoogerwerf, Evertine Abbink, Marc Blaauw, Ton Dofferhoff, Marjan van Apeldoorn, Karin Veerman and 6 more

Abstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  12. Survival of COVID-19 with Multimorbidity Patients.Healthcare (Basel, Switzerland) · 2021
    Article
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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

16 authors.

Gerine NijmanDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Maike WientjesDepartment of Research, Sint Maartenskliniek, Nijmegen, The Netherlands.
Jordache RamjithDepartment of Health Evidence, Section Biostatistics, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0003-4431-7395
Nico JanssenRadboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0002-9629-8627
Jacobien HoogerwerfDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Evertine AbbinkDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Marc BlaauwDepartment of Internal Medicine, Bernhoven Hospital, Uden, The Netherlands.
Ton DofferhoffDepartment of Internal Medicine, Canisius Wilhelmina Hospital, Nijmegen, The Netherlands.
Marjan van ApeldoornDepartment of Internal Medicine, Jeroen Bosch Hospital, Den Bosch, The Netherlands.
Karin VeermanDepartment of Internal Medicine, Sint Maartenskliniek, Nijmegen, The Netherlands.
Quirijn de MastDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Jaap Ten OeverDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Wouter HoefslootRadboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands.
Monique H ReijersRadboud Centre for Infectious Diseases (RCI), Radboud University Medical Centre, Nijmegen, The Netherlands.
Reinout van CrevelDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.
Josephine S van de MaatDepartment of Internal Medicine, Radboud University Medical Centre, Nijmegen, The Netherlands.ORCID 0000-0001-7351-4596

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo date, survival data on risk factors for COVID-19 mortality in western Europe is limited, and none of the published survival studies have used a competing risk approach. This study aims to identify risk factors for in-hospital mortality in COVID-19 patients in the Netherlands, considering recovery as a competing risk.

methodsIn this observational multicenter cohort study we included adults with PCR-confirmed SARS-CoV-2 infection that were admitted to one of five hospitals in the Netherlands (March to May 2020). We performed a competing risk survival analysis, presenting cause-specific hazard ratios (HRCS) for the effect of preselected factors on the absolute risk of death and recovery.

results1,006 patients were included (63.9% male; median age 69 years, IQR: 58-77). Patients were hospitalized for a median duration of 6 days (IQR: 3-13); 243 (24.6%) of them died, 689 (69.9%) recovered, and 74 (7.4%) were censored. Patients with higher age (HRCS 1.10, 95% CI 1.08-1.12), immunocompromised state (HRCS 1.46, 95% CI 1.08-1.98), who used anticoagulants or antiplatelet medication (HRCS 1.38, 95% CI 1.01-1.88), with higher modified early warning score (MEWS) (HRCS 1.09, 95% CI 1.01-1.18), and higher blood LDH at time of admission (HRCS 6.68, 95% CI 1.95-22.8) had increased risk of death, whereas fever (HRCS 0.70, 95% CI 0.52-0.95) decreased risk of death. We found no increased mortality risk in male patients, high BMI or diabetes.

conclusionOur competing risk survival analysis confirms specific risk factors for COVID-19 mortality in a the Netherlands, which can be used for prediction research, more intense in-hospital monitoring or prioritizing particular patients for new treatments or vaccination.

Indexed as

Hospital MortalityAgedAnticoagulantsBody Mass IndexCohort StudiesCOVID-19Diabetes ComplicationsFemaleHumansImmunocompromised HostLength of StayL-Lactate DehydrogenaseMaleMiddle AgedNetherlandsProportional Hazards ModelsAnticoagulantsL-Lactate DehydrogenaseRNA, Viral

Identifiers

PMID33770140
PMCPMC7997038

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.