Evidence map›Paper›PMID 36017008›Full record

ArticleFrontiers in medicine2022

Development of a novel score model to predict hyperinflammation in COVID-19 as a forecast of optimal steroid administration timing.

Yuichiro Takeshita, Jiro Terada, Yasutaka Hirasawa, Taku Kinoshita, Hiroshi Tajima, Ken Koshikawa, Toru Kinouchi, Yuri Isaka, Yu Shionoya, Atsushi Fujikawa and 4 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 49% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

14 authors at 2 institutions in 1 country.

Yuichiro TakeshitaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Jiro TeradaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Yasutaka HirasawaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Taku KinoshitaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Hiroshi TajimaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Ken KoshikawaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Toru KinouchiDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Yuri IsakaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Yu ShionoyaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Atsushi FujikawaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Yasuyuki KatoDepartment of Infectious Disease, International University of Health and Welfare Narita Hospital, Narita, Japan.
Yasuo ToDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Yuji TadaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
Kenji TsushimaDepartment of Pulmonary Medicine, International University of Health and Welfare Narita Hospital, Narita, Japan.
International University of Health and Welfare · JPChiba University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: This study aims to create and validate a useful score system predicting the hyper-inflammatory conditions of COVID-19, by comparing it with the modified H-score. Methods: A total of 98 patients with pneumonia (without oxygen therapy) who received initial administration of casirivimab/imdevimab or remdesivir were included in the study. The enrolled patients were divided into two groups: patients who required corticosteroid due to deterioration of pneumonia, assessed by chest X-ray or CT or respiratory failure, and those who did not, and clinical parameters were compared. Results: Significant differences were detected in respiratory rate, breaths/min, SpO Conclusion: The steroid predicting score may be useful to predict the requirement of corticosteroid therapy in patients with COVID-19. The data may provide important information to facilitate a prospective study on a larger scale in this field.

Indexed as

corticosteroidCOVID-19cytokine stormhyper-inflammationpredicting score

Identifiers

PMID36017008
PMCPMC9395649
OpenAlexW4290739299

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.