Baseline characteristics and comorbidities in the CAnadian REgistry for Pulmonary Fibrosis
Bibliographic record
Abstract
BACKGROUND: The CAnadian REgistry for Pulmonary Fibrosis (CARE-PF) is a multi-center, prospective registry designed to study the natural history of fibrotic interstitial lung disease (ILD) in adults. The aim of this cross-sectional sub-study was to describe the baseline characteristics, risk factors, and comorbidities of patients enrolled in CARE-PF to date. METHODS: Patients completed study questionnaires and clinical measurements at enrollment and each follow-up visit. Environmental exposures were assessed by patient self-report and comorbidities by the Charlson Comorbidity Index (CCI). Baseline characteristics, exposures, and comorbidities were described for the overall study population and for incident cases, and were compared across ILD subtypes. RESULTS: The full cohort included 1285 patients with ILD (961 incident cases (74.8%)). Diagnoses included connective tissue disease-associated ILD (33.3%), idiopathic pulmonary fibrosis (IPF) (24.7%), unclassifiable ILD (22.3%), chronic hypersensitivity pneumonitis (HP) (7.5%), sarcoidosis (3.2%), non-IPF idiopathic interstitial pneumonias (3.0%, including idiopathic nonspecific interstitial pneumonia (NSIP) in 0.9%), and other ILDs (6.0%). Patient-reported exposures were most frequent amongst chronic HP, but common across all ILD subtypes. The CCI was ≤2 in 81% of patients, with a narrow distribution and range of values. CONCLUSIONS: CTD-ILD, IPF, and unclassifiable ILD made up 80% of ILD diagnoses at ILD referral centers in Canada, while idiopathic NSIP was rare when adhering to recommended diagnostic criteria. CCI had a very narrow distribution across our cohort suggesting it may be a poor discriminator in assessing the impact of comorbidities on patients with ILD.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".