Use of the patientMpower App With Home-Based Spirometry to Monitor the Symptoms and Impact of Fibrotic Lung Conditions: Longitudinal Observational Study
Bibliographic record
Abstract
BACKGROUND: Daily home-based spirometry in idiopathic pulmonary fibrosis (IPF) has been shown to be feasible and clinically informative. The patientMpower app facilitates home-based spirometry along with home-based monitoring of IPF-related symptoms. The patientMpower app can be downloaded to the user's mobile phone or tablet device, enabling the recording of objective and subjective data. OBJECTIVE: The aim of this paper is to report on the 1-year experience of using patientMpower with home-based spirometry by 36 participants with self-reported pulmonary fibrosis (PF) treated with usual care. METHODS: Self-selecting participants enrolled in this community-based participatory research program through a patient advocacy group in their country: Irish Lung Fibrosis Association in Ireland and PF Warriors in the United States. Disease severity was comparable with a baseline mean predicted forced vital capacity (FVC) of 64% and 62% in the Irish and US participants, respectively. Both groups of participants were allocated to identical, in-country, open-label, single-group observational studies and were provided with a Bluetooth-active Spirobank Smart spirometer integrated directly with patientMpower. Data collected via patientMpower included seated FVC (daily), breathlessness grade (modified Medical Research Council scale score), step count, medication adherence, and symptoms and impact of IPF on daily life, which were measured by a patient-reported outcome measure (PROM) scale that was specifically developed for IPF. Longitudinal patient-reported data on oximetry and oxygen consumption were also collected. RESULTS: A large majority of the 36 participants reported that their experience using patientMpower was positive, and they wanted to continue its use after the initial 6-week observation. Out of 36 participants, 21 (58%) recorded home-based spirometry without prompting for ≥180 days, and 9 (25%) participants continued with recording home-based spirometry for ≥360 days. CONCLUSIONS: The patientMpower app with associated Bluetooth-connected devices (eg, spirometer and pulse oximeter) offers an acceptable and accessible approach to collecting patient-reported objective and subjective data in fibrotic lung conditions.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".