Evidence map›Paper›PMID 38622608›Full record

Observational studyRespiratory research2024

Feasibility and acceptability of remotely monitoring spirometry and pulse oximetry as part of interstitial lung disease clinical care: a single arm observational study.

Sarah Barth, Colin Edwards, Gauri Saini, Yussef Haider, Nicholas Paul Williams, Will Storrar, Gisli Jenkins, Iain Stewart, Melissa Wickremasinghe

Registry-linked trialAbstract readObservational StudyMulticenter Study
In one paragraph

Observational study in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04850521 (Remote Monitoring of Interstitial Lung Disease to Provide Continuity of Care and Shielding From Risks Associated With In-clinic Assessment), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04850521 completednot on this map

Remote Monitoring of Interstitial Lung Disease to Provide Continuity of Care and Shielding From Risks Associated With In-clinic Assessment

TypeobservationalSponsorpatientMpower Ltd.Ran2021 to 2022Enrolled60ConditionsInterstitial Lung DiseaseArmsRemote monitoring
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Observational
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Sarah BarthImperial College Healthcare NHS Trust, ILD Service, Mint Wing, St Mary?s Hospital, Praed Street, London, W2 1NY, UK. s.barth@nhs.net.
Colin EdwardsPatientMpower Ltd, Dublin, Ireland.
Gauri SainiNottingham University Hospitals NHS Trust, Nottingham, UK.
Yussef HaiderLancashire Teaching Hospitals NHS Trust, Preston, UK.
Nicholas Paul WilliamsHampshire Hospitals NHS Foundation Trust, Winchester, UK.
Will StorrarHampshire Hospitals NHS Foundation Trust, Basingstoke, UK.
Gisli JenkinsNational Heart & Lung Institute, Imperial College London, London, UK.
Iain StewartNational Heart & Lung Institute, Imperial College London, London, UK.
Melissa WickremasingheImperial College Healthcare NHS Trust, ILD Service, Mint Wing, St Mary?s Hospital, Praed Street, London, W2 1NY, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRemote monitoring of patient-recorded spirometry and pulse oximetry offers an alternative approach to traditional hospital-based monitoring of interstitial lung disease (ILD). Remote spirometry has been observed to reasonably reflect clinic spirometry in participants with ILD but remote monitoring has not been widely incorporated into clinical practice. We assessed the feasibility of remotely monitoring patients within a clinical ILD service.

methodsProspective, single-arm, open-label observational multi-centre study (NCT04850521). Inclusion criteria included ILD diagnosis, age ≥ 18 years, FVC ≥ 50% predicted. 60 participants were asked to record a single spirometry and oximetry measurement at least once daily, monitored weekly by their local clinical team. Feasibility was defined as ≥ 68% of participants with ≥ 70% adherence to study measurements and recording measurements ≥ 3 times/week throughout.

resultsA total of 60 participants were included in the analysis. 42/60 (70%) were male; mean age 67.8 years (± 11.2); 34/60 (56.7%) had idiopathic pulmonary fibrosis (IPF), Median ILD-GAP score was 3 (IQR 1-4.75). Spirometry adherence was achieved for ≥ 70% of study days in 46/60 participants (77%) and pulse oximetry adherence in 50/60 participants (83%). Recording ≥ 3 times/week every week was provided for spirometry in 41/60 participants (68%) and pulse oximetry in 43/60 participants (72%). Mean difference between recent clinic and baseline home spirometry was 0.31 L (± 0.72). 85.7% (IQR 63.9-92.6%) home spirometry attempts/patient were acceptable or usable according to ERS/ATS spirometry criteria. Positive correlation was observed between ILD-GAP score and adherence to spirometry and oximetry (rho 0.24 and 0.38 respectively). Adherence of weekly monitoring by clinical teams was 80.95% (IQR 64.19-95.79). All participants who responded to an experience questionnaire (n = 33) found remote measurements easy to perform and 75% wished to continue monitoring their spirometry at the conclusion of the study.

conclusionFeasibility of remote monitoring within an ILD clinical service was demonstrated over 3 months for both daily home spirometry and pulse oximetry of patients. Remote monitoring may be more acceptable to participants who are older or have more advanced disease.

trial registrationclinicaltrials.gov NCT04850521 registered 20

Indexed as

Lung Diseases, InterstitialAdolescentAgedFeasibility StudiesFemaleHumansMaleOximetryProspective StudiesSpirometryVital CapacityeHealthInterstitial lung diseasePhysiological monitoring

Identifiers

PMID38622608
PMCPMC11020645

What OpenQuestion holds

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.