Multiple-Breath Washout Quality Control Data for Pediatric Cystic Fibrosis

A dataset of 2,471 multiple-breath washout (MBW) measurements from 87 children with cystic fibrosis, used to validate an automated quality control algorithm. The algorithm quantifies the impact of irregular breathing behaviors on primary lung function outcomes like Lung Clearance Index (LCI) and functional residual capacity. The data was authored by Florian Wyler and was last updated in April 2026.

Use Cases

• Validate automated QC algorithm performance against a reference dataset of 2,471 MBW measurements.
• Analyze the impact of specific irregular behaviors (e.g., leaks, changes in end-expiratory lung volume) on the Lung Clearance Index (LCI) outcome.
• Compare automated QC results with assessments from experienced human raters using a subset of 100 measurements.
• Investigate sources of within-visit variability in LCI, which the study found was 45% explained by QC-related factors.

Strengths

• Contains 2,471 individual MBW measurements providing a substantial validation set.
• Algorithm validation includes comparison against human expert ratings on 100 measurements.
• Quantifies specific effect sizes, e.g., leaks/trapped gas affected LCI in 31% of measurements.

Limitations

• Dataset scope is limited to 87 pediatric patients with cystic fibrosis, limiting generalizability to other populations.
• The 804.7 KB file size suggests the dataset is a summary or documentation, not the raw measurement time-series data.
• Primary data format is a DOCX document, which is not a standard structured data format for analysis.

Provenance

Source

Figshare, authored by Florian Wyler.

Collection Method

MBW measurements collected from children with cystic fibrosis, used to validate a model-based automated QC algorithm.

Freshness

Last updated April 2026.