Evidence map›Paper›PMID 36045057›Full record

ArticleAnnals of laboratory medicine2023

Indirect Method for Estimation of Reference Intervals of Inflammatory Markers.

Taewon Kang, Jeaeun Yoo, Dong Wook Jekarl, Hyojin Chae, Myungshin Kim, Yeon-Joon Park, Eun-Jee Oh, Yonggoo Kim

Abstract read
In one paragraph

Article in Annals of laboratory medicine, 2023. 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
–field-weighted citation impact
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.

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  5. A modelling approach to derive population-specific cutoff for plasma p-Tau217.The journal of prevention of Alzheimer's disease · 2025
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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

8 authors.

Taewon KangDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0002-0452-3322
Jeaeun YooDepartment of Laboratory Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0001-9917-5393
Dong Wook JekarlDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0002-6269-5501
Hyojin ChaeDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0001-5870-1887
Myungshin KimDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0001-8632-0168
Yeon-Joon ParkDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0003-2182-5821
Eun-Jee OhDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0001-5870-915X
Yonggoo KimDepartment of Laboratory Medicine, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea.ORCID 0000-0003-2808-3795

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The direct method for reference interval (RI) estimating is limited due to the requirement of resources, difficulties in defining a non-diseased population, or ethical problems in obtaining samples. We estimated the RI for inflammatory biomarkers using an indirect method (RII). Methods: C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and presepsin (PSEP) data of patients visiting a single hospital were retrieved from April 2009 to April 2021. Right-skewed data were transformed using the Box-Cox transformation method. A mixed population of non-diseased and diseased distributions was assumed, followed by latent profile analysis for the two classes. The intersection point of the distribution curve was estimated as the RI. The influence of measurement size was evaluated as the ratio of abnormal values and adjustment (n×bandwidth) of the distribution curve. Results: The RIs estimated by the proposed RII method (existing method) were as follows: CRP, 0-4.1 (0-4.7) mg/L; ESR, 0-10.2 (0-15) mm/hr and PSEP, 0-411 (0-300) pg/mL. Measurement sizes ≥2,500 showed stable results. An abnormal-to-normal value ratio of 0.5 showed the most accurate result for CRP. Adjustment values ≤5 or >5 were applicable for a measurement size <25,000 or ≥25,000, respectively. Conclusions: The proposed RII method could provide additional information for RI verification or estimation with some limitations.

Indexed as

C-Reactive ProteinPeptide FragmentsBiomarkersBlood SedimentationHumansLipopolysaccharide ReceptorsReference ValuesBiomarkersC-Reactive ProteinLipopolysaccharide ReceptorsPeptide Fragmentspresepsin protein, humanLatent variable modelingReference rangeStatistical data interpretationStatistical distributions

Identifiers

PMID36045057
PMCPMC9467833

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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.