ArticleLung2023
Feasibility and Utility of a Smartphone Application-Based Longitudinal Cough Monitoring in Chronic Cough Patients in a Real-World Setting.
Article in Lung, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Pooled it
- Article
- Article
- Observational
- The value of continuous cough monitoring: a narrative review.Journal of thoracic disease · 2025Review
- Asthma Symptom Self-Monitoring Methods for Children and Adolescents: Present and Future.Children (Basel, Switzerland) · 2025Review
- Nighttime Cough Characteristics in Chronic Obstructive Pulmonary Disease Patients.Sensors (Basel, Switzerland) · 2025Article
- Assessing the Clinical and Functional Status of COPD Patients Using Speech Analysis During and After Exacerbation.International journal of chronic obstructive pulmonary disease · 2025Article
- Cough frequency has a high daily variation in patients with chronic cough.ERJ open research · 2025Article
- Patient-reported assessments of chronic cough in clinical trials: accessory or primary endpoints?Journal of thoracic disease · 2024Review
- Article
- Decoding the impact of the placebo response in clinical trials for chronic cough.ERJ open research · 2024Article
- Article
- LUNG Year in Review: 2023.Lung · 2024Article
Corrections and comments
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Authors and funding
9 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThis study evaluated the feasibility and utility of longitudinal cough frequency monitoring with the Hyfe Cough Tracker, a mobile application equipped with cough-counting artificial intelligence algorithms, in real-world patients with chronic cough.
methodsPatients with chronic cough (> 8-week duration) were monitored continuously for cough frequency with the Hyfe app for at least one week. Cough was also evaluated using the Leicester Cough Questionnaire (LCQ) and daily cough severity scoring (0-10). The study analyzed adherence rate, the correlation between objective cough frequency and subjective scores, day-to-day variability, and patient experience.
resultsOf 65 subjects consecutively recruited, 43 completed the study. The median cough monitoring duration was 13.9 days, with a median adherence of 91%. Study completion was associated with baseline cough severity, and the adherence rate was higher in younger subjects. Cross-sectional correlation analyses showed modest correlations between objective and subjective cough measures at the group level. However, in time series correlation analyses, correlations between objective and subjective measures widely varied across individuals. Cough frequency had greater day-to-day variability than daily cough severity scores in most subjects. A patient experience survey found that 70% of participants found the cough monitoring helpful, 86% considered it acceptable, and 84% felt it was easy to use.
conclusionMonitoring cough frequency longitudinally for at least one week may be feasible. The substantial day-to-day variability in objective cough frequency highlights the need for continuous monitoring. Grasping the implications of daily cough variability is crucial in both clinical practice and clinical trials.
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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.