Evidence map›Paper›PMID 32997542›Full record

ArticleAnnals of medicine2021

External validation of a clinical risk score to predict hospital admission and in-hospital mortality in COVID-19 patients.

Alexandra Halalau, Zaid Imam, Patrick Karabon, Nikhil Mankuzhy, Aciel Shaheen, John Tu, Christopher Carpenter

Registry-linked trialOpen access · hybridAbstract readMulticenter Study
In one paragraph

Article in Annals of medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05582382 (Validation of Prognostic Clinical Risk Scores in Predicting Outcomes for Patients Diagnosed With COVID-19 During Initial Triage Assessment), which is not on this map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
4.4field-weighted citation impact, top 4% 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.

NCT05582382 unknown statusnot on this mapstarted 2023, after this paper: background citation

Validation of Prognostic Clinical Risk Scores in Predicting Outcomes for Patients Diagnosed With COVID-19 During Initial Triage Assessment

TypeobservationalSponsorDr Adnan AghaRan2023 to 2024Enrolled2,000ConditionsCOVID-19Armslogistic regression of known prognostic markers of severity of COVID19
3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 63 citations in OpenAlex.

  1. Article
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  4. Telemedicine and Otolaryngology in the COVID-19 Era.The Annals of otology, rhinology, and laryngology · 2023
    Article
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  6. Diagnostic utility of the Covichem score in predicting COVID-19 disease.The American journal of emergency medicine · 2022
    Article
  7. The Pitfalls of Mining for QuantiFERON Gold in Severely Ill Patients With COVID-19.Mayo Clinic proceedings. Innovations, quality & outcomes · 2022
    Article
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  16. ABCInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021
    Article
  17. Article
  18. Zoonotic coronavirus epidemics: Severe acute respiratory syndrome, Middle East respiratory syndrome, and coronavirus disease 2019.Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology · 2021
    Review
  19. Article
  20. 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

7 authors at 2 institutions in 1 country.

Alexandra HalalauInternal Medicine Department, Beaumont Health, Royal Oak, MI, USA.
Zaid ImamInternal Medicine Department, Beaumont Health, Royal Oak, MI, USA.ORCID 0000-0002-3030-6188
Patrick KarabonOakland University William Beaumont School of Medicine, Rochester, MI, USA.
Nikhil MankuzhyOakland University William Beaumont School of Medicine, Rochester, MI, USA.
Aciel ShaheenInternal Medicine Department, Beaumont Health, Royal Oak, MI, USA.
John TuInternal Medicine Department, Beaumont Health, Royal Oak, MI, USA.
Christopher CarpenterInternal Medicine Department, Beaumont Health, Royal Oak, MI, USA.
Oakland University · USBeaumont Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentification of patients with novel coronavirus disease 2019 (COVID-19) requiring hospital admission or at high-risk of in-hospital mortality is essential to guide patient triage and to provide timely treatment for higher risk hospitalized patients.

methodsA retrospective multi-centre (8 hospital) cohort at Beaumont Health, Michigan, USA, reporting on COVID-19 patients diagnosed between 1 March and 1 April 2020 was used for score validation. The COVID-19 Risk of Complications Score was automatically computed by the EHR. Multivariate logistic regression models were built to predict hospital admission and in-hospital mortality using individual variables constituting the score. Validation was performed using both discrimination and calibration.

resultsCompared to Green scores, Yellow Scores (OR: 5.72) and Red Scores (OR: 19.1) had significantly higher odds of admission (both

conclusionsThe COVID-19 Risk of Complications Score predicts the need for hospital admission and in-hospital mortality patients with COVID-19. Key points: Can an electronic health record generated risk score predict the risk of hospital admission and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19)? In both validation cohorts of 2,025 and 1,290 COVID-19, the cross-validated C-Statistics showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)), respectively. The COVID-19 Risk of Complications Score may help predict the need for hospital admission if a patient contracts SARS-CoV-2 infection and in-hospital mortality for a hospitalized patient with COVID-19.

Indexed as

BetacoronavirusHospital MortalityAdultAgedCohort StudiesCoronavirus InfectionsCOVID-19Critical IllnessDatabases, FactualFemaleHumansMaleMiddle AgedPandemicsPneumonia, ViralRetrospective Studiesadmissioncorona virusCOVID-19emergency medicinehospitalizationinternal medicineMortalitytriage

Identifiers

PMID32997542
PMCPMC7877986
OpenAlexW3091483014

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Registered trials

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.