Evidence map›Paper›PMID 36589196›Full record

ArticleCureus2022

Utility of the HScore for Predicting COVID-19 Severity.

William Hannah, Anthony Shadiack, Melissa Markofski, Kevin Dao, Eric Shaw, Craig Odum, Nayda Parisio-Poldiak, Alexis Finer, Mike Flynn

Open access · diamondAbstract read
In one paragraph

Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 83% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 4 institutions in 1 country.

William HannahGraduate Medical Education, Memorial Health University Medical Center, Savannah, USA.
Anthony ShadiackFamily Medicine, Grand Strand Medical Center, Myrtle Beach, USA.
Melissa MarkofskiHealth and Human Performance, University of Houston, Houston, USA.
Kevin DaoInternal Medicine, Grand Strand Medical Center, Myrtle Beach, USA.
Eric ShawGraduate Medical Education, Memorial Health University Medical Center, Savannah, USA.
Craig OdumGraduate Medical Education, Coliseum Medical Centers, Macon, USA.
Nayda Parisio-PoldiakGraduate Medical Education, Grand Strand Medical Center, Hospital Corporation of America (HCA) Healthcare, Myrtle Beach, USA.
Alexis FinerData Analytics, Optum, Eden Prairie, USA.
Mike FlynnGraduate Medical Education, Hospital Corporation of America (HCA) Healthcare, Charleston, USA.
Memorial Health University Medical Center · USNavicent Health · USHCA Healthcare · USHamilton Medical Center · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCytokine release syndrome is a life-threatening condition known to cause fever and multiple organ dysfunction and is suspected to be related to the severity of coronavirus disease 2019 (COVID-19). We sought to examine the utility of the HScore and non-cytokine markers of inflammation for predicting COVID-19 outcomes. We hypothesized that cytokine storm, assessed by a modified HScore, would be linked to more severe COVID-19 symptoms and higher mortality.

methodsA retrospective review of records from a large, private hospital system was conducted on patients with hemophagocytic lymphohistiocytosis (HLH) (2014-2019) and compared to a large cohort of COVID-19-positive patients (2020). Patients with a sufficient number of elements in their record for a modified HScore calculation (n=4663), were further subdivided into population 1 (POP1, n=67; HLH, n=493 COVID-19), which had eight HScore elements, and population 2 (POP2) with six available HScore elements (POP2, n=102; HLH, n=4561 COVID-19).

resultsModified HScore predicted COVID-19 severity in POP1 and POP2 as measured by higher odds of being on a ventilator (POP2 OR: 1.46, CI: 1.42-1.5), ICU admission (POP2 OR: 1.38, CI: 1.34-1.42), a longer length of stay (p<0.0001), and higher mortality (POP2 OR: 1.34, CI: 1.31-1.39). C-reactive protein (CRP) and white blood cell (WBC) count were the most consistent non-cytokine predictors of COVID-19 severity.

conclusionCytokine storm, evaluated using a modified HScore, appeared to play a role in the severity of COVID-19 infection, and selected non-cytokine markers of inflammation were predictive of disease severity.

Indexed as

anti-cytokinecovid-19covid-19 retrocytokine stormhscore

Identifiers

PMID36589196
PMCPMC9795835
OpenAlexW4310173002

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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.