Is oscillometry a better metric of respiratory functional capacity compared to conventional pulmonary function tests during the first 6-months post lung transplant?
Bibliographic record
Abstract
Background: Lung function improves over 6-12 months after lung transplant (LTx). Risk of acute rejection and infection are high at this time. Thus, patients are monitored frequently with conventional pulmonary function tests (cPFT). cPFT with spirometry is a forced manoeuvre and insensitive to small airway dysfunction. Airway oscillometry (OSc) measures total respiratory impedance during tidal breathing and is very sensitive to small airway function. OSc may offer superior assessment of lung function following LTx. Objective: To compare OSc and cPFT in assessment of respiratory functional capacity. Methods: Prospectively enrolled bilateral LTx patients were assessed with paired OSc-cPFT, and at 3 and 6 months, with the six-minute walk test (6MWT) and Borg Dyspnea Scale. Results: Pulmonary restriction was common in the initial 6 months with low %TLC, %FEV1 and %FVC but normal %FEV1/FVC. At both 3 (n=79) and 6 months (n=60) post-LTx, 6MWT distance was significantly correlated with cPFT parameters: positively with %FEV1 and %FVC and negatively with %RV. The above remains true when considering changes from 3 to 6 months. In contrast, the Borg Dyspnea Scale between 3 and 6 months correlated best with OSc parameters of small airway function, including reactance at 5Hz (X5) and area of reactance (Ax). Conclusion: Objective respiratory functional capacity, measured by 6MWT at 6 months post-LTx, correlated with cPFT indices of lung volumes, while OSc, particularly indices of peripheral airway dysfunction, correlated well with the more subjective Borg Dyspnea Scale.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".