Home Monitoring in Interstitial Lung Disease: Protocol for a Real-World Observational Study
Bibliographic record
Abstract
BACKGROUND: Interstitial lung diseases (ILDs), a group of parenchymal lung disorders, present with varying degrees of inflammation and fibrosis, which lead to symptoms such as progressive breathlessness, impaired quality of life (QoL), and reduced life expectancy. Patients with ILD can experience a sudden worsening of their condition, known as an acute exacerbation, which is associated with inappropriate hospital admissions, concomitant National Health Service (NHS) costs, impaired QoL, and high mortality. The heterogeneity of ILDs, the unpredictability of acute exacerbations, and significant variation in disease progression and response to treatment present numerous management challenges. Standard care typically involves 3-6 monthly hospital outpatient visits to monitor disease and assess response to treatment. Home monitoring with remote review of spirometry, pulse oximetry, and patient-reported measures offers an alternative approach to in-person clinic review and laboratory-based physiological measurements. Clinical trials indicate home monitoring of patients with ILD is acceptable, and results correlate with laboratory-based pulmonary function tests (PFTs). The impact of implementing home monitoring for patients with ILD in a real-world setting is not well understood. OBJECTIVE: We aim to evaluate the safety, effectiveness, and acceptability of home monitoring with standard care in the management of patients with ILD. METHODS: This study has been registered as a quality improvement project at Guy's and St Thomas' NHS Foundation Trust (reference 13660) and Royal Devon University Healthcare NHS Foundation Trust (reference 24-1378). The project has been co-designed by the steering group, including clinicians, researchers, technology partners, a patient advocacy charity, and patients diagnosed with ILD. Patients who meet the inclusion criteria will be provided a handheld spirometer, pulse oximeter, and access to patientMpower, an electronic health app, on their smart devices and followed up for 12 months. All participants will be asked to complete at least once weekly home spirometry and pulse oximetry measurements and 3 monthly patient-reported measures, including outcome, engagement, and experience measures, using the patientMpower app. Results will be available to the clinicians in real time and used to monitor disease progression, symptoms, and QoL, and to assess treatment response. RESULTS: This study was funded by NHS Digital in September 2021. Patient recruitment and data collection started in March 2022. By January 2024, 186 patients were enrolled. All patients will have home monitoring for at least 12 months. Results are expected to be published at the end of 2025. CONCLUSIONS: We hypothesize home monitoring will be safe, effective and acceptable for patients with ILD and result in a 50% reduction in routine laboratory-based pulmonary function tests and in-person clinic consultations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/65339.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.048 | 0.044 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.051 | 0.010 |
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".