Evidence map›Paper›PMID 36295478›Full record

ArticleMedicina (Kaunas, Lithuania)2022

Usefulness of KL-6 for Predicting Clinical Outcomes in Hospitalized COVID-19 Patients.

Mikyoung Park, Mina Hur, Hanah Kim, Chae Hoon Lee, Jong Ho Lee, Minjeong Nam

Open access · goldAbstract read
In one paragraph

Article in Medicina (Kaunas, Lithuania), 2022. 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
0.9field-weighted citation impact, top 25% 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, 6 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

6 authors at 4 institutions in 1 country.

Mikyoung ParkDepartment of Laboratory Medicine, Eunpyeong St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul 03312, Korea.ORCID 0000-0002-4815-6958
Mina HurDepartment of Laboratory Medicine, Konkuk University School of Medicine, Seoul 05030, Korea.ORCID 0000-0002-4429-9978
Hanah KimDepartment of Laboratory Medicine, Konkuk University School of Medicine, Seoul 05030, Korea.ORCID 0000-0002-3266-638X
Chae Hoon LeeDepartment of Laboratory Medicine, Yeungnam University College of Medicine, Daegu 42415, Korea.
Jong Ho LeeDepartment of Laboratory Medicine, Yeungnam University College of Medicine, Daegu 42415, Korea.ORCID 0000-0002-6837-838X
Minjeong NamDepartment of Laboratory Medicine, Korea University Anam Hospital, Seoul 02841, Korea.ORCID 0000-0003-3542-3487
Konkuk University · KRYeungnam University CollegeKorea University · KRThe Catholic University of Korea Seoul St. Mary's Hospital · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Krebs von den Lungen 6 (KL-6) is a novel biomarker for interstitial lung disease, and it reflects acute lung injury. We explored the usefulness of KL-6 to predict clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: In a total of 48 hospitalized COVID-19 patients, KL-6 levels were measured using the HISCL KL-6 assay (Sysmex, Kobe, Japan) with the HISCL 5000 automated analyzer (Sysmex). Clinical outcomes (intensive care unit [ICU] admission, ventilator use, extracorporeal membrane oxygenation [ECMO] use, and 30-day mortality) were analyzed according to KL-6 percentiles. Age, initial KL-6 level, Charlson comorbidity index (CCI), and critical disease were compared using the receiver operating characteristic (ROC) curve and Kaplan-Meier methods for clinical outcomes. Results: KL-6 quartiles were associated with ICU admission, ventilator use, and ECMO use (all p < 0.05), except 30-day mortality (p = 0.187). On ROC curve analysis, initial KL-6 level predicted ICU admission, ventilator use, and ECMO use significantly better than age, CCI, and critical disease (all p < 0.05); age, initial KL-6 level, CCI, and critical disease predicted 30-day mortality comparably. On Kaplan−Meier survival analysis, hazard ratios (95% confidence interval) were 4.8 (1.2−19.3) for age, 4.7 (1.1−21.6) for initial KL-6 level, 3.9 (0.9−16.2) for CCI, and 2.1 (0.5−10.3) for critical disease. Conclusions: This study demonstrated that KL-6 could be a useful biomarker to predict clinical outcomes in hospitalized COVID-19 patients. KL-6 may contribute to identifying COVID-19 patients requiring critical care, including ICU admission and ventilator and/or ECMO use.

Indexed as

COVID-19Lung Diseases, InterstitialBiomarkersChild, PreschoolHumansJapanROC CurveBiomarkersbiomarkerclinical outcomeCOVID-19KL-6prediction

Identifiers

PMID36295478
PMCPMC9608840
OpenAlexW4296621710

What OpenQuestion holds

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LicenceCC BY
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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.