Evidence map›Paper›PMID 29117798›Full record

ArticleChronic respiratory disease2018

Inflammatory biomarkers and radiologic measurements in never-smokers with COPD: A cross-sectional study from the CODA cohort.

Hyun Lee, Yoonki Hong, Myoung Nam Lim, So Hyeon Bak, Min-Ji Kim, Kyunga Kim, Woo Jin Kim, Hye Yun Park

Open access · goldAbstract read
In one paragraph

Article in Chronic respiratory disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 pooled it
1.6field-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, 3 syntheses or guidelines pooled it, 21 citations in OpenAlex.

  1. Pooled it
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  3. Pooled it
  4. Article
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  6. Article
  7. Article
  8. Observational
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  10. Article
  11. Long-term exposure to PMRespiratory research · 2020
    Article
  12. Article
  13. Review
  14. Article
  15. Blood eosinophil count as a prognostic biomarker in COPD.International journal of chronic obstructive pulmonary disease
    Article
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 at 4 institutions in 1 country.

Hyun Lee1 Samsung Medical Center, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Yoonki Hong2 Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Chuncheon, South Korea.
Myoung Nam Lim2 Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Chuncheon, South Korea.
So Hyeon Bak3 Department of Radiology, Kangwon National University Hospital, Chuncheon, South Korea.
Min-Ji Kim4 Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea.
Kyunga Kim4 Statistics and Data Center, Research Institute for Future Medicine, Samsung Medical Center, Seoul, South Korea.
Woo Jin Kim2 Department of Internal Medicine and Environmental Health Center, Kangwon National University Hospital, Chuncheon, South Korea.
Hye Yun Park1 Samsung Medical Center, Division of Pulmonary and Critical Care Medicine, Department of Medicine, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Kangwon National University Hospital · KRSamsung Medical Center · KRSamsung (South Korea) · KRSungkyunkwan University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various biomarkers have emerged as potential surrogates to represent various subgroups of chronic obstructive pulmonary disease (COPD), which manifest with different phenotypes. However, the biomarkers representing never-smokers with COPD have not yet been well elucidated. The aim of this study was to evaluate the associations of certain serum and radiological biomarkers with the presence of COPD in never-smokers. To explore the associations of serum and radiological biomarkers with the presence of COPD in never-smokers, we conducted a cross-sectional patient cohort study composed of never-smokers from the COPD in Dusty Areas (CODA) cohort, consisting of subjects living in dusty areas near cement plants in South Korea. Of the 131 never-smokers in the cohort, 77 (58.8%) had COPD. There were no significant differences in the number of subjects with high levels of inflammatory biomarkers (>90th percentile of never-smokers without COPD), including white blood cell count, total bilirubin, interleukin (IL)-6, IL-8, and C-reactive protein, or radiologic measurements (including emphysema index and mean wall area percentage) between never-smokers with COPD and those without COPD. However, the number of subjects with high uric acid was significantly higher in never-smokers with COPD than never-smokers without COPD (31.2% (24/77) vs. 11.1% (6/54); p = 0.013). In addition, multivariate analysis revealed that high uric acid was significantly associated with the presence of COPD in never-smokers (adjusted relative risk: 1.63; 95% confidence interval: 1.21, 2.18; p = 0.001). Our study suggests that high serum levels of uric acid might be a potential biomarker for assessing the presence of COPD in never-smokers.

Indexed as

Non-SmokersAgedBilirubinCase-Control StudiesCohort StudiesC-Reactive ProteinCross-Sectional StudiesDustDyspneaFemaleForced Expiratory VolumeHumansInflammationInterleukin-6Interleukin-8LungBilirubinC-Reactive ProteinCXCL8 protein, humanDustIL6 protein, humanInterleukin-6Interleukin-8Uric Acidchronic obstructive pulmonary diseasenever-smokerSerum and radiologic biomarkeruric acid

Identifiers

PMID29117798
PMCPMC5958470
OpenAlexW2767687609

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.