Evidence map›Paper›PMID 41111194›Full record

ArticleRespirology (Carlton, Vic.)2026

Identification of Clinically Distinct Clusters in Patients With Severe COPD Using Circulating Blood Cell Population Parameters.

Pauline J M Kuks, Jorine E Hartman, Else A M D Ter Haar, L Joost van Pelt, Dirk-Jan Slebos, Maarten van den Berge, Simon D Pouwels

Registry-linked trialAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Respirology (Carlton, Vic.), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04023409 (The Identification of Phenotypes in Patients With Severe Chronic Obstructive Pulmonary Disease), which is not on this map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

NCT04023409 completednot on this map

The Identification of Phenotypes in Patients With Severe Chronic Obstructive Pulmonary Disease (Groningen Severe COPD Cohort)

TypeobservationalSponsorUniversity Medical Center GroningenRan2014 to 2019Enrolled1,030ConditionsSevere COPDArmsNA: no intervention
3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Pauline J M KuksDepartment of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Jorine E HartmanDepartment of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID 0000-0001-8765-9673
Else A M D Ter HaarDepartment of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
L Joost van PeltDepartment of Laboratory Medicine, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Dirk-Jan SlebosDepartment of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Maarten van den BergeDepartment of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Simon D PouwelsDepartment of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.ORCID 0000-0001-7345-8061

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectivePeripheral blood cell counts are useful biomarkers in COPD, but may not fully reflect disease activity. The Sysmex XN-Series haematology analyser offers advanced measurements of immune cell populations, providing information about the number and activation status of peripheral blood cells. We hypothesized that assessing immune cell activation status, in addition to cell counts, could provide complementary insights into the clinical heterogeneity of severe COPD.

methodsFor this study, 499 extensively characterised patients with severe COPD were included from the Groningen Severe COPD cohort. A total of 24 Sysmex-derived systemic blood parameters were selected for analysis. Clustering of blood cell population data was performed using Self-Organising Maps.

resultsThe cell population parameters showed various associations with clinical characteristics, such as emphysema severity and lung function. Four clusters were identified based on their inflammatory profiles, each showing distinct clinical characteristics: the 'normal cell counts, resting pattern' cluster (n = 156) showed high emphysema severity scores and RV/TLC ratios; the 'normal cell counts, activated pattern' cluster (n = 241) was associated with few exacerbations; the 'elevated cell counts, activated pattern' cluster (n = 97) displayed high inflammatory cell counts and activity along with high exacerbation rates; and the small 'low-eosinophilic' cluster (n = 5) was characterised by inactive circulating eosinophils.

conclusionCell population data can be used to identify distinct inflammatory profiles with clinical relevance in severe COPD. Cell population data provide information beyond absolute cell counts, supporting the added value of including activation markers in COPD phenotyping.

trial registrationNCT04023409 at clinicaltrials.gov.

Indexed as

Pulmonary Disease, Chronic ObstructiveAgedBiomarkersBlood Cell CountCluster AnalysisFemaleHumansMaleMiddle AgedSeverity of Illness IndexBiomarkersbiomarkerscell population datacluster analysisCOPDinflammatory activity

Identifiers

PMID41111194
PMCPMC12865525

What Socratic holds

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Registered trials

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 Socratic graph.