Diffusing capacity of the lung for carbon monoxide: association with long-term outcomes after lung transplantation in a 20-year longitudinal study
Bibliographic record
Abstract
Rationale The diffusing capacity of the lung for carbon monoxide corrected for haemoglobin ( D LCOcor ) measures gas movement across the alveolar–capillary interface. We hypothesised that D LCOcor is a sensitive measure of injurious allograft processes disrupting this interface. Objectives To determine the prognostic significance of the D LCOcor trajectory on chronic lung allograft dysfunction (CLAD) and survival. Methods A retrospective analysis was conducted of all bilateral lung transplant recipients at a single centre, between January 1998 and January 2018, with one or more D LCOcor measurements. Low baseline D LCOcor was defined as the failure to achieve a D LCOcor >75% predicted. Drops in D LCOcor were defined as >15% below recent baseline. Results 1259 out of 1492 lung transplant recipients were included. The median (range) time to peak D LCOcor was 354 (181–737) days and the mean± sd D LCOcor was 80.2±21.2% pred. Multivariable analysis demonstrated that low baseline D LCOcor was significantly associated with death (hazrd ratio (HR) 1.68, 95% CI 1.27–2.20; p<0.001). Low baseline D LCOcor was not independently associated with CLAD after adjustment for low baseline forced expiratory volume in 1 s or forced vital capacity. Any D LCOcor declines ≥15% were significantly associated with death, independent of concurrent spirometric decline. Lower percentage predicted D LCOcor values at CLAD onset were associated with shorter post-CLAD survival (HR 0.75 per 10%-unit change, p<0.01). Conclusion Low baseline D LCOcor and post-transplant declines in D LCOcor were significantly associated with survival, independent of spirometric measurements. We propose that D LCOcor testing may allow identification of a subphenotype of baseline and chronic allograft dysfunction not captured by spirometry. There may be benefit in routine monitoring of D LCOcor after lung transplantation to identify patients at risk of poor outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".