Evidence map›Paper›PMID 34401147›Full record

ArticleAnnals of medicine and surgery (2012)2021

Association of serum KL-6 levels on COVID-19 severity: A cross-sectional study design with purposive sampling.

Titah Dhadhari Suryananda, Resti Yudhawati

Open access · diamondAbstract read
In one paragraph

Article in Annals of medicine and surgery (2012), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 15% 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

15 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 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

2 authors at 1 institution in 1 country.

Titah Dhadhari SuryanandaDepartment of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Airlangga - Dr. Soetomo General Academic Hospital, Surabaya, Indonesia.
Resti YudhawatiDepartment of Pulmonology and Respiratory Medicine, Faculty of Medicine, Universitas Airlangga - Dr. Soetomo General Academic Hospital, Surabaya, Indonesia.
Airlangga University · ID

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe main target of SARS-CoV2 is the alveolar type II (AT2) cells of the lung. SARS-CoV2 evades the innate immune system resulting in the release of proinflammatory cytokines (IL-1β, IL-6, TNF-α) which causes AT2 cell damage. Krebs von den Lungen (KL-6) is a specific biomarker of AT2 cell damage. KL-6 is produced in AT2 cells that are injured/regenerated.

objectiveResearch that discusses the role of KL-6 in COVID-19 is still being debated and not much has been done in Indonesia.

methodsThis study was an analytical study with a prospective design on 75 COVID-19 patients who were treated. Subjects were divided into two large groups according to their degree of severity, 57 subjects with severe degrees and 18 subjects with non-severe degrees. The serum KL-6 levels were measured on days 0 and 6. Data were analyzed using paired

resultIn this study, the mean serum KL-6 for day 0 in the severe group was higher than the non-severe group with values of 45.70 U/mL and 44.85 U/mL. On day 6, the mean serum KL-6 in the severe group was lower than that in the non-severe group with values of 41.3 U/mL and 41.95 U/mL. Serum KL-6 in the severe group experienced an even greater decrease than the non-severe group.

conclusionThere was no significant association between serum KL-6 values on 0 days in the severity of COVID-19.

Indexed as

AT2COVID-19KL-6

Identifiers

PMID34401147
PMCPMC8359564
OpenAlexW3194982192

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.