ArticleERJ open research2025
Continuous digital cough monitoring during 6-month pulmonary tuberculosis treatment.
Article in ERJ open research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Accelerating Cough-Based Algorithms for Pulmonary Tuberculosis Screening: Results From the CODA TB DREAM Challenge.Open forum infectious diseases · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Recent advances in digital and wearable technologies with artificial intelligence (AI) enable the use of continuous cough monitoring (CCM) to objectively monitor symptoms as surrogate markers of treatment efficacy in pulmonary tuberculosis (PTB). The objectives of this study were to describe the evolution of cough during PTB treatment in adults and to assess the feasibility of community-based CCM. Methods: We prospectively enrolled PTB adult participants upon treatment initiation. Participants' coughs were continuously monitored during 6 months with a smartphone loaded with an app able to detect cough by using an AI algorithm. Results: 22 participants were included. The median (interquartile range (IQR)) age was 28.5 (22-42) years and 62% were male. The median (IQR) coughs per hour (medCPH) was 11.0 (7.0-27.0) at week 1. By the end of the intensive phase of PTB treatment at week 8, the medCPH was 3.5 (1.5-7.0), which was significantly lower than the medCPH at week 1 (p=0.002). At week 26 (end of treatment), the medCPH was 1.0 (1.0-2.5). The adherence to CCM was high during the first 13 weeks of PTB treatment and then waned over time. The adherence was similar during daytime and night-time. Conclusion: Cough counts rapidly drop during the intensive phase of PTB treatment and then slowly decrease to a low baseline level by the end of the treatment. Community-based CCM using digital technology is feasible in low-resource settings but requires evaluation of alternative approaches to overcome adherence issues and technical limitations (mobile internet and electricity availability).
Identifiers
What Socratic holds
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 Socratic graph.