Evidence map›Paper›PMID 36529450›Full record

ArticleJournal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy2023

Validation of a specialized evaluation system for COVID-19 in Japan: A retrospective, multicenter cohort study.

Hiroki Furuhata, Kenji Araki

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in Journal of infection and chemotherapy : official journal of the Japan Society of Chemotherapy, 2023. 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 82% 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

2 authors at 1 institution in 1 country.

Hiroki FuruhataGraduate School of Medicine and Veterinary Medicine, University of Miyazaki, 5200 Kibara Kiyotake-cho, Miyazaki, 8891692, Japan. Electronic address: hiroki_furuhata@med.miyazaki-u.ac.jp.
Kenji ArakiDepartment of Patient Advocacy Center, University of Miyazaki Hospital, 5200 Kibara Kiyotake-cho, Miyazaki, 8891692, Japan.
University of Miyazaki · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionEvaluation of a severity grade (SG) is important to classify patients for efficient use of limited medical resources. This study validates two existing evaluation systems for the prevention of the coronavirus disease 2019 (COVID-19) in Japan: a criterion of SG and a list of 14 specialized underlying diseases (SUDs).

methodsA retrospective cohort was created using electronic medical records from 18 research institutes. The cohort includes 6,050 COVID-19 patients with two types of diagnosis information as follows: SG at hospitalization among mild, moderate I, moderate II, and severe and aggravation after hospitalization.

resultsA crude mortality rate and an aggravation rate increased by the worsening of SG in the COVID-19 cohort. The transition of the aggravation rate was notable for COVID-19 patients with SUD. A conditional probability of the mortality given the aggravation in the COVID-19 cohort was 87.4% compared to mild or moderate patients (approximately 21%-45%) who have the possibility of the aggravation. An odds ratio of the mortality and aggravation information about the SUD list was higher than other variables.

conclusionsWe demonstrated the possibility of improving the criteria of SG by including the SUD list for more effective operation of the criteria of SG. Furthermore, we demonstrated the importance of the prevention of the aggravation based on the conditional probability, and the possibility of predicting the aggravation using the risk factors.

Indexed as

COVID-19HumansJapanRetrospective StudiesRisk FactorsSARS-CoV-2COVID-19InfectionSeverityUnderlying disease

Identifiers

PMID36529450
PMCPMC9753483
OpenAlexW4311548904

What OpenQuestion holds

Textmetadata
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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.