Home oscillometry monitoring after lung transplant is feasible and reliable
Bibliographic record
Abstract
Introduction: Oscillometry (Osc) has been shown to be more sensitive for detecting allograft rejection after lung transplant (LTx) than spirometry, the current gold standard. Osc is performed during normal tidal breathing and easy to complete. Its utility as a home-based monitoring tool has not been well investigated. While LTx patients are followed frequently with spirometry, daily home monitoring with Osc could provide earlier markers for graft injury. Aim: To evaluate the feasibility of home Osc and compare it to pulmonary function lab-based testing in the first 3 months after LTx. Methods: All double LTx patients are eligible if discharged from hospital within 3 months of surgery. At enrolment, a qualified personnel teaches and sends the patient home with a C-100 tremoflo, the same device used in the lab. Patients are taught to perform Osc with the lab-based protocol and quality control standards. Home testing occurs daily and lab-based, weekly. Results: 9 patients (6 men, mean age 63±11 years) have completed the study to-date. Home Osc started at 60±1 days post-LTx. 3 patients were excluded due to technical difficulty (1) and lack of paired home-lab tests within a 2-day window (2). The remaining 6 patients had 17 paired home-lab Osc tests over 3 months. Agreement between home and lab Osc was high with mean differences in R5 and X5 (resistance and reactance at 5 Hz) being 5.5±15.8% and 2.8%±17.6%, respectively. Patients were highly satisfied with Osc; all preferred it to spirometry. Conclusion: Home Osc monitoring is feasible post LTx, with measurements similar to lab-based tests. Deployment of home Osc could lead to earlier detection of graft injury and is the focus of ongoing work.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".