ArticleBiomedicines2022
Systemic Inflammatory Biomarkers Define Specific Clusters in Patients with Bronchiectasis: A Large-Cohort Study.
Article in Biomedicines, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Analysis of clinical characteristics and bronchoalveolar lavage fluid microbial community diversity in non-cystic fibrosis bronchiectasis patients withMicrobiology spectrum · 2026Article
- Phenotypes and endotypes in bronchiectasis: a narrative review of progress toward precision medicine.Journal of thoracic disease · 2025Review
- Blood Neutrophil Counts Define Specific Clusters of Bronchiectasis Patients: A Hint to Differential Clinical Phenotypes.Biomedicines · 2022Article
- Chronic Obstructive Pulmonary Disease: The Present and Future.Biomedicines · 2022Article
Corrections and comments
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Authors and funding
18 authors at 13 institutions in 1 country.
Funding
Abstract
Differential phenotypic characteristics using data mining approaches were defined in a large cohort of patients from the Spanish Online Bronchiectasis Registry (RIBRON). Three differential phenotypic clusters (hierarchical clustering, scikit-learn library for Python, and agglomerative methods) according to systemic biomarkers: neutrophil, eosinophil, and lymphocyte counts, C reactive protein, and hemoglobin were obtained in a patient large-cohort (
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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 OpenQuestion graph.