Evidence map›Paper›PMID 37230764›Full record

ArticleBMJ open respiratory research2023

Serum KL-6 levels predict clinical outcomes and are associated with

Shuhei Azekawa, Shotaro Chubachi, Takanori Asakura, Ho Namkoong, Yasunori Sato, Ryuya Edahiro, Ho Lee, Hiromu Tanaka, Shiro Otake, Kensuke Nakagawara and 18 more

Open access · goldAbstract read
In one paragraph

Article in BMJ open respiratory research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.8field-weighted citation impact, top 9% 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

6 citing papers in PubMed, 11 citations in OpenAlex.

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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

28 authors at 7 institutions in 2 countries.

Shuhei AzekawaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Shotaro Chubachi *Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan bachibachi472000@z6.keio.jp.
Takanori Asakura *Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Ho NamkoongDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
Yasunori SatoDepartment of Preventive Medicine and Public Health, Keio University School of Medicine, Tokyo, Japan.
Ryuya EdahiroDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Ho LeeDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Hiromu TanakaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Shiro OtakeDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Kensuke NakagawaraDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Takahiro FukushimaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Mayuko WataseDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Kaori SakuraiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Tatsuya KusumotoDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Katsunori MasakiDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.ORCID 0000-0003-0909-9409
Hirofumi KamataDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Makoto IshiiDepartment of Respiratory Medicine, Nagoya University Graduate School of Medicine Faculty of Medicine, Nagoya, Japan.
Naoki HasegawaDepartment of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
Yukinori OkadaDepartment of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
Ryuji KoikeMedical Innovation Promotion Center, Tokyo Medical and Dental University, Tokyo, Japan.
Yuko KitagawaDepartment of Surgery, Keio University School of Medicine, Tokyo, Japan.
Akinori KimuraInstitute of Research, Tokyo Medical and Dental University, Tokyo, Japan.
Seiya ImotoDivision of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
Satoru MiyanoM&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan.
Seishi OgawaDepartment of Pathology and Tumor Biology, Kyoto University Graduate School of Medicine Faculty of Medicine, Kyoto, Japan.
Takanori KanaiDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Koichi FukunagaDivision of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine Graduate School of Medicine, Tokyo, Japan.
Japan COVID-19 Task Force
Keio University · JPTokyo Medical and Dental University · JPKyoto University · JPNagoya University · JPRIKEN Center for Integrative Medical Sciences · JPThe University of Osaka · JPThe University of Tokyo · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundKrebs von den Lungen-6 (KL-6) is a known biomarker for diagnosis and monitoring of interstitial lung diseases. However, the role of serum KL-6 and the mucin 1 (

methodsThis is a secondary analysis of a multicentre retrospective study using data from the Japan COVID-19 Task Force collected from February 2020 to November 2021, including 2226 patients with COVID-19 whose serum KL-6 levels were measured. An optimal serum KL-6 level cut-off to predict critical outcomes was determined and used for multivariable logistic regression analysis. Furthermore, the relationship among the allele dosage of the

resultsSerum KL-6 levels were significantly higher in patients with COVID-19 with critical outcomes (511±442 U/mL) than those without (279±204 U/mL) (p<0.001). Serum KL-6 levels ≥304 U/mL independently predicted critical outcomes (adjusted OR (aOR) 3.47, 95% CI 2.44 to 4.95). Moreover, multivariable logistic regression analysis with age and sex indicated that the

conclusionSerum KL-6 levels predicted critical outcomes in Japanese patients with COVID-19 and were associated with the

Indexed as

COVID-19Mucin-1BiomarkersEast Asian PeopleGenome-Wide Association StudyHumansRetrospective StudiesBiomarkersMUC1 protein, humanMucin-1COVID-19viral infection

Identifiers

PMID37230764
PMCPMC10230347
OpenAlexW4378211707

What OpenQuestion holds

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LicenceCC BY-NC
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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.