Evidence map›Paper›PMID 41257182›Full record

ArticleERJ open research2025

Heart rate, respiratory rate and airflow variability differences between stable and exacerbating COPD patients.

Amar J Shah, Anita Saigal, Renard Pramono, Orsina Dessi, John R Hurst, Ali R Mani, Esther Rodriguez Villegas, Swapna Mandal

Abstract read
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Article in ERJ open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Amar J ShahUCL Respiratory, University College London, London, UK.ORCID https://orcid.org/0000-0002-7278-6909
Anita SaigalUCL Respiratory, University College London, London, UK.ORCID https://orcid.org/0000-0002-4170-8000
Renard PramonoWearable Technologies Lab, Department of Electrical and Electronic Engineering, Imperial College London, London, UK.
Orsina DessiAcurable Ltd, London, UK.
John R HurstUCL Respiratory, University College London, London, UK.ORCID https://orcid.org/0000-0002-7246-6040
Ali R ManiNetwork Physiology Laboratory, Division of Medicine, University College London, London, UK.
Esther Rodriguez VillegasWearable Technologies Lab, Department of Electrical and Electronic Engineering, Imperial College London, London, UK.
Swapna MandalUCL Respiratory, University College London, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rationale: Earlier identification and treatment of COPD exacerbations leads to improved clinical outcomes. Wearable technology has the ability to measure physiological signal variability, which is likely to be different in states of stability and exacerbation. The objectives of the present study were to analyse signals, including heart rate, respiratory rate and airflow, from a novel small wearable device, AcuPebble RE100 and compare differences in a group of stable and exacerbating participants. Methods: Groups of stable and exacerbating adult participants with COPD were asked to wear AcuPebble RE100, which records physiological signals including heart rate, respiratory rate and airflow. Linear and nonlinear variability analysis was conducted on each of these time-series to detect differences between groups. Results: A total of 51 participants (33 stable and 18 exacerbating) were analysed. Stable participants used the device for a median (interquartile range) of 18 nights (10-26). The exacerbating participants had significantly higher heart rate variability measures and a significantly lower heart rate complexity measure compared with stable participants. Respiratory rate variability and complexity were significantly increased in the exacerbating participants. Detrended fluctuation analysis demonstrated two crossover points in both populations, with the exacerbating participants demonstrating a significantly lower median α3 (0.50 (0.47-0.56) Conclusion: We have shown that significant differences exist in heart rate, respiratory rate and airflow variability measures between stable and exacerbating groups of COPD. This will help build exacerbation detection algorithms in the future.

Identifiers

PMID41257182
PMCPMC12621118

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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.