Evidence map›Paper›PMID 35905602›Full record

ArticleThe American journal of emergency medicine2022

Diagnostic utility of the Covichem score in predicting COVID-19 disease.

Cigdem Ozpolat, Erhan Altunbas

Open access · greenAbstract read
In one paragraph

Article in The American journal of emergency medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Cigdem OzpolatDepartment of Emergency Medicine, Marmara University Pendik Research and Training Hospital, 34890 Istanbul, Turkey. Electronic address: cumed17@gmail.com.
Erhan AltunbasDepartment of Emergency Medicine, Marmara University Pendik Research and Training Hospital, 34890 Istanbul, Turkey.
Marmara University · TR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIdentifying which patients with COVİD-19 have a high risk of severe illness is essential to optimizing management and resource utilization strategies.

objectivesThe aim of this study was to externally validate the diagnostic utility of the Covichem score for predicting COVID-19 disease severity, and secondarily to evaluate its utility in predicting intensive care unit (ICU) admission, and in-hospital mortality.

methodsAll consecutive COVID-19 patients who presented to the emergency department (ED) were included, and patients' demographic data, comorbidities, vital signs, oxygen requirement, and laboratory results were recorded. We calculated patients' Covichem scores and estimates (using a threshold of 0.5) and evaluated the utility of the Covichem score for predicting disease severity, ICU admission, and mortality.

resultsThe median Covichem score was significantly higher for patients with severe illness (Covichem score: 0.170, IQR: 0.298, n = 300 vs. Covichem score: 0.026, IQR: 0.065, n: 191; p < 0.001). Based on their Covichem scores, 12.4% (61/491) of the patients were predicted to experience severe illness (threshold: 0.5), the accuracy of the Covichem score was poor, as the area under curve (AUC) was 48.5% (18.1% sensitivity and 93.8% specificity). When we calculated a new ideal threshold, the AUC reached 82%, but the sensitivity was 79.9% and the specificity was 71.2%.

conclusionIn this external validation of the Covichem score, we found that it performed worse than in the original derivation and validation study, even with the assistance of a new cutoff.

Indexed as

COVID-19COVID-19 TestingEmergency Service, HospitalHospital MortalityHumansIntensive Care UnitsOxygenPrognosisRetrospective StudiesROC CurveOxygenCovichem scoreCOVID-19PrognosisSeverity

Identifiers

PMID35905602
PMCPMC9287589
OpenAlexW4285603916

What OpenQuestion holds

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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.