Referral rates and barriers to lung transplantation based on pulmonary function criteria in interstitial lung diseases: a retrospective cohort study
Bibliographic record
Abstract
Background: Interstitial lung diseases (ILD) unresponsive to medical therapy often require lung transplantation (LTx), which prolongs quality of life and survival. Ideal timing for referral for LTx remains challenging, with late referral associated with significant morbidity and mortality. Among other criteria, patients with ILD should be considered for LTx if forced vital capacity (FVC) is less than 80% or diffusion capacity for carbon monoxide (DLCO) is less than 40%. However, data on referral rates are lacking. Objectives: To evaluate referral rates for LTx based on pulmonary function tests (PFTs) and identify barriers associated with non-referral. Design: A single-center retrospective cohort study. Methods: The study consisted of ILD patients who performed PFT between 2014 and 2020. Patients with FVC < 80% or a DLCO < 40% were included in the study. Patients with absolute contraindications to LTx were excluded. Referral rates were computed, and a comparison was made between referred and non-referred subjects. Results: Out of 114 ILD patients meeting criteria for referral to LTx, 35 were referred (30.7%), and 7 proceeded to undergo LTx. Median time from PFT to referral for assessment was 255 days [interquartile range (IQR) 35–1077]. Median time from referral to LTx was 89 days (IQR 59–143). Referred patients were younger ( p = 0.003), had lower FVC ( p < 0.001), DLCO ( p < 0.001), and a higher rate of pulmonary hypertension ( p = 0.04). Relatively better PFT, and older age, were significantly associated with non-referral of patients. Conclusion: There is under-referral of ILD patients who are eligible for LTx, which is associated with severe disease and missed opportunities for LTx. Further research is required to validate these findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".