Evidence map›Paper›PMID 35328157›Full record

ArticleDiagnostics (Basel, Switzerland)2022

The AIFELL Score as a Predictor of Coronavirus Disease 2019 (COVID-19) Severity and Progression in Hospitalized Patients.

Ian Levenfus, Enrico Ullmann, Katja Petrowski, Jutta Rose, Lars C Huber, Melina Stüssi-Helbling, Macé M Schuurmans

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. 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
0.4field-weighted citation impact, top 41% 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, 4 citations in OpenAlex.

  1. 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

7 authors at 4 institutions in 3 countries.

Ian LevenfusDepartment of Pulmonology, University Hospital Zurich, 8091 Zurich, Switzerland.ORCID 0000-0002-9566-9705
Enrico UllmannDepartment of Medicine, Technical University Dresden, 01307 Dresden, Germany.ORCID 0000-0002-5690-7029
Katja PetrowskiMedical Psychology and Sociology, Johannes Gutenberg University Mainz, 55131 Mainz, Germany.
Jutta RoseClinic for Internal Medicine, Department of Internal Medicine, City Hospital Zurich Triemli, 8063 Zurich, Switzerland.
Lars C HuberClinic for Internal Medicine, Department of Internal Medicine, City Hospital Zurich Triemli, 8063 Zurich, Switzerland.
Melina Stüssi-HelblingClinic for Internal Medicine, Department of Internal Medicine, City Hospital Zurich Triemli, 8063 Zurich, Switzerland.
Macé M SchuurmansDepartment of Pulmonology, University Hospital Zurich, 8091 Zurich, Switzerland.ORCID 0000-0001-5404-7566
Triemli Hospital · CHUniversity of Zurich · CHJohannes Gutenberg University Mainz · DESouth Ural State University · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the beginning of the COVID-19 pandemic, SARS-CoV-2 has caused a global burden for health care systems due to high morbidity and mortality rates, leading to caseloads that episodically surpass hospital resources. Due to different disease manifestations, the triage of patients at high risk for a poor outcome continues to be a major challenge for clinicians. The AIFELL score was developed as a simple decision instrument for emergency rooms to distinguish COVID-19 patients in severe disease stages from less severe COVID-19 and non-COVID-19 cases. In the present study, we aimed to evaluate the AIFELL score as a prediction tool for clinical deterioration and disease severity in hospitalized COVID-19 patients. During the second wave of the COVID-19 pandemic in Switzerland, we analyzed consecutively hospitalized patients at the Triemli Hospital Zurich from the end of November 2020 until mid-February 2021. Statistical analyses were performed for group comparisons and to evaluate significance. AIFELL scores of patients developing severe COVID-19 stages IIb and III during hospitalization were significantly higher upon admission compared to those patients not surpassing stages I and IIa. Group comparisons indicated significantly different AIFELL scores between each stage. In conclusion, the AIFELL score at admission was useful to predict the disease severity and progression in hospitalized COVID-19 patients.

Indexed as

COVID-19predictionSARS-CoV-2scoresevere disease

Identifiers

PMID35328157
PMCPMC8947178
OpenAlexW4214543240

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.