Patient Adherence and Perceptions in a Pilot Home Spirometry Monitoring Program for Lung Transplant Recipients
Bibliographic record
Abstract
Abstract Rationale Lung transplant recipients require regular monitoring post-transplant. Frequent spirometry assessments facilitate early detection of potential complications including allograft dysfunction and infection, with most centers offering remote home spirometry. Recent advancements in connected home spirometry devices, integrated with digital health applications, now enable seamless data collection and real-time tracking of spirometry, offering the potential for improved monitoring of lung health status, adherence and patient user experience. We sought to evaluate patients’ adherence and gather patient and healthcare providers opinions on digitally-enabled home spirometry as part of a pilot home monitoring program for lung transplant recipients. Methods 40 Lung transplant recipients were enrolled in a remote monitoring program (patient-facing app + Bluetooth-connected spirometer) between August 2023 and Oct 2024. Patient-recorded data were visible to clinicians in real time via a secure browser-based portal. Patients were instructed to complete spirometry measurements daily. In October 2024, a patient opinion questionnaire was provided to all enrolled patients and one to healthcare providers. We analysed the results from these questionnaire and patients’ adherence to home spirometry. Results 39 patients (97.5%) provided ≥1 spirometry measurement and were included in the analysis of adherance. 9 patients (23%) acheived >80% of days they were enrolled. 14 patients (35%) responded to the patient opinion questionnaire, with their results summarised in the chart below. All patients indicated they would continue using the app with the Bluetooth spirometer and recommend it to other lung transplant patients. 6 healthcare providers responded to the questionnaire. Responses to the four structured questions were as follows: Preference for using the monitoring platform: Yes 66.7% (n=4), No 16.7% (n=1), No preference 16.7% (n=1).Ease of use: Easy 50% (n=3), Very easy 33.3% (n=2), Difficult 16.7% (n=1).Usefulness for managing post-transplant care: Yes 100% (n=6).Support for continued use vs. conventional spirometry post-pilot: Yes 83.3% (n=5), No 16.7% (n=1). Conclusions Most respondents expressed positive experiences with the patient-facing app and Bluetooth-connected spirometer, with 100% indicating they would continue using it and recommend it to others. Adherence to daily spirometry was substantially lower than expected, highlighting that lung transplant centers should be aware that despite careful instructions, one cannot assume patient adherence. These findings also indicate strong provider support for the application and spirometer, for its usability and potential to enhance patient management in the post-transplant period.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".