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Three Spirometry-Based At-Risk Phenotypes Predict Incident Airflow Limitation: A Population-Based Study
Hendrik Pott1,2, Roman Martin3, Wilhelm Bertrams2
1Department of Medicine, Pulmonary and Critical Care Medicine, Clinic for Airway Infections, University Medical Centre Marburg, Philipps-University Marburg, Marburg, Germany.
A new spirometry framework, TriSpi, identifies individuals at risk for airflow limitation. This approach enables early intervention in primary care by detecting early airflow limitation, small airway dysfunction, and preserved-ratio impaired spirometry.
Area of Science:
- Pulmonary Medicine
- Epidemiology
- Diagnostic Tools
Background:
- Incident airflow limitation is often diagnosed late, hindering timely intervention.
- Primary care spirometry can identify at-risk individuals, but validated frameworks are needed.
Purpose of the Study:
- To develop and validate a pragmatic spirometry-based framework (TriSpi) for identifying individuals at risk of incident airflow limitation in primary care.
Main Methods:
- Applied the Three-Phenotype Spirometry-Based Identification (TriSpi) framework to 6123 participants from KORA and SHIP cohorts.
- Defined three phenotypes: Early airflow limitation (EAL), small airway dysfunction (SAD), and preserved-ratio impaired-spirometry (PRISm).
- Assessed associations with incident airflow limitation using Firth's regression.
Main Results:
- TriSpi identified 26%-36% of the population as at-risk (TriSpi+), capturing 74%-93% of future airflow limitation cases.
- TriSpi+ individuals had a 10-25-fold increased risk; negative predictive values exceeded 95%.
- Early airflow limitation (EAL) showed the strongest individual association with incident airflow limitation.
Conclusions:
- Combining EAL, PRISm, and SAD definitions provides robust prediction of incident airflow limitation.
- The TriSpi framework offers a scalable, pragmatic approach for early risk stratification in primary care without post-bronchodilator spirometry.
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