Evidence map›Paper›PMID 32845042›Full record

ReviewReviews in medical virology2021

Predictors of COVID-19 severity: A literature review.

Benjamin Gallo Marin, Ghazal Aghagoli, Katya Lavine, Lanbo Yang, Emily J Siff, Silvia S Chiang, Thais P Salazar-Mather, Luba Dumenco, Michael C Savaria, Su N Aung and 2 more

Open access · greenAbstract readReview
In one paragraph

Review in Reviews in medical virology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 510 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
510citing papers in PubMed, 3 pooled it
16.7field-weighted citation impact, top 1% 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

510 citing papers in PubMed, 3 syntheses or guidelines pooled it, 869 citations in OpenAlex.

  1. A Systematic Review of Predictor Composition, Outcomes, Risk of Bias, and Validation of COVID-19 Prognostic Scores.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024
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450 more citing papers are in PubMed but not listed here.

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

12 authors at 2 institutions in 1 country.

Benjamin Gallo MarinWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.ORCID 0000-0003-4877-354X
Ghazal AghagoliWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Katya LavineWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Lanbo YangWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Emily J SiffDepartment of Cognitive, Linguistic, & Psychological Sciences, Brown University, Providence, Rhode Island, USA.
Silvia S ChiangDepartment of Pediatrics, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Thais P Salazar-MatherWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Luba DumencoWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Michael C SavariaWarren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Su N AungDepartment of Medicine, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Timothy FlaniganDepartment of Medicine, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Ian C MichelowDepartment of Pediatrics, Division of Infectious Diseases, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Brown University · USRhode Island Department of Health · US

Funding

Emerging Infectious Disease Scholars at Brown UniversityR25AI140490 · NIAID · BROWN UNIVERSITY · PI Silvia Shinpei Chiang · 2018 to 2026
$3.0M
National Institute of Allergy and Infectious Diseases R25AI140490NIAID NIH HHS R25 AI140490NIH HHS
6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic is a rapidly evolving global emergency that continues to strain healthcare systems. Emerging research describes a plethora of patient factors-including demographic, clinical, immunologic, hematological, biochemical, and radiographic findings-that may be of utility to clinicians to predict COVID-19 severity and mortality. We present a synthesis of the current literature pertaining to factors predictive of COVID-19 clinical course and outcomes. Findings associated with increased disease severity and/or mortality include age > 55 years, multiple pre-existing comorbidities, hypoxia, specific computed tomography findings indicative of extensive lung involvement, diverse laboratory test abnormalities, and biomarkers of end-organ dysfunction. Hypothesis-driven research is critical to identify the key evidence-based prognostic factors that will inform the design of intervention studies to improve the outcomes of patients with COVID-19 and to appropriately allocate scarce resources.

Indexed as

COVID-19Severity of Illness IndexAdultAgingBiomarkersChildComorbidityHumansHypoxiaPrognosisSARS-CoV-2BiomarkersCOVID-19predictorsSARS-CoV-2severity

Identifiers

PMID32845042
PMCPMC7855377
OpenAlexW3046496943

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.