Evidence map›Paper›PMID 35204539›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Cross-Sectional and Time-Dependent Analyses on Inflammatory Markers following Natural Killer Cell Activity.

Yun-Kyong Lee, Ji-Hee Haam, Sung-Hoon Cho, Young-Sang Kim

Open access · goldAbstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

9 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

4 authors at 3 institutions in 1 country.

Yun-Kyong LeeChaum Life Center, CHA University, Seoul 06062, Korea.ORCID 0000-0002-4972-0047
Ji-Hee HaamChaum Life Center, CHA University, Seoul 06062, Korea.
Sung-Hoon ChoTS Bio, Seoul 08389, Korea.
Young-Sang KimDepartment of Family Medicine, CHA Bundang Medical Center, CHA University, Seongnam 13496, Korea.ORCID 0000-0002-7397-5410
CHA University · KRBio-Medical Science (South Korea) · KRCHA University Bundang Medical Center · KR

Funding

NKMAX Co., Ltd. 2021-09-047Schumitt Health Korea LLC 2021-04-034
6 · The paper itself

Abstract

The function of natural killer (NK) cells in inflammation has not been explored enough in large-scale population studies. The cross-sectional and time-dependent relationship between NK cell activity (NKA) and inflammatory markers was examined.

methodsA total of 7031 subjects were involved in the cross-sectional analyses. Non-linear relationship between NKA and inflammatory indices was analyzed using generalized additive models. The time-dependent changes were analyzed in 1005 subjects with repeated measurement in 3-6 months. The changes in inflammatory markers were analyzed based on the changes in NKA.

resultsAs NKA reduces to a very low level, the white blood cell (WBC) and neutrophil counts increase sharply, and the lymphocyte count exhibits a slow decline. With increasing NKA larger than about 500 pg/mL, WBC and neutrophil-lymphocyte ratio (NLR) reduces in a mild slope. Among the subjects with repeated measurements, the follow-up NKA was increased with advancing baseline NKA levels. The subjects with a reduction in NKA indicated increment in WBC count, neutrophil count, and NLR, and decrease in lymphocyte count.

conclusionsVery low levels of NKA suggest a high inflammatory immune response. The changes in NKA may interact with the balance between neutrophils and lymphocytes.

Indexed as

immunityinflammationnatural killer cell activityneutrophil-to-lymphocyte ratio

Identifiers

PMID35204539
PMCPMC8870889
OpenAlexW4210972398

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.