ReviewThe European respiratory journal2025
Characterising research trends in bronchiectasis through AI-powered analytics.
Review in The European respiratory journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Targeting Inflammation in Bronchiectasis.Drugs · 2026Review
- The European Respiratory Society guideline for management of adult bronchiectasis: clinical summary.Breathe (Sheffield, England) · 2026Review
- Microbiome and its role in bronchiectasis.Therapeutic advances in respiratory diseaseReview
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundInterest in bronchiectasis is increasing and no prior study has used artificial intelligence (AI) to interrogate its rich, multidimensional literature to characterise research trends, themes and knowledge gaps.
methodsWe reviewed original bronchiectasis research between 1949 and 2024 (a 75-year period) to identify, characterise and assess research trends and trajectories using two AI-powered approaches: 1) Atlas, an AI topic-modelling tool; and 2) a custom model, leveraging ChatGPT embedding and text generation models.
resultsAI-powered analytics revealed a nine-fold increase in bronchiectasis research speed since 2000, typified by enhanced richness with four new research topics emerging every 5 years. Publication trends mirror clinical and technological advances, exemplified by significant rises in computed tomography, microbiome and clinical studies following the adoption of high-resolution computed tomography (1970s), next-generation sequencing (2005) and the first clinical guidelines (2008-2010), respectively. Topics with sustained growth (
conclusionAI captures bronchiectasis as a dynamic and interdisciplinary field in continuing growth. Emerging research topics extend beyond the vicious vortex framework, indicating a transition from disease-centric to patient-centric approaches to optimise clinical care.
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What OpenQuestion holds
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.