Dataset Information

Nocturnal Cough and Sleep Quality to Assess Asthma Control and Predict Attacks.

ABSTRACT:

Introduction

Objective markers for asthma, that can be measured without extra patient effort, could mitigate current shortcomings in asthma monitoring. We investigated whether smartphone-recorded nocturnal cough and sleep quality can be utilized for the detection of periods with uncontrolled asthma or meaningful changes in asthma control and for the prediction of asthma attacks.

Methods

We analyzed questionnaire and sensor data of 79 adults with asthma. Data were collected in situ for 29 days by means of a smartphone. Sleep quality and nocturnal cough frequencies were measured every night with the Pittsburgh Sleep Quality Index and by manually annotating coughs from smartphone audio recordings. Primary endpoint was asthma control assessed with a weekly version of the Asthma Control Test. Secondary endpoint was self-reported asthma attacks.

Results

Mixed-effects regression analyses showed that nocturnal cough and sleep quality were statistically significantly associated with asthma control on a between- and within-patient level (p < 0.05). Decision trees indicated that sleep quality was more useful for detecting weeks with uncontrolled asthma (balanced accuracy (BAC) 68% vs 61%; ? sensitivity -12%; ? specificity -2%), while nocturnal cough better detected weeks with asthma control deteriorations (BAC 71% vs 56%; ? sensitivity 3%; ? specificity -34%). Cut-offs using both markers predicted asthma attacks up to five days ahead with BACs between 70% and 75% (sensitivities 75 - 88% and specificities 57 - 72%).

Conclusion

Nocturnal cough and sleep quality have useful properties as markers for asthma control and seem to have prognostic value for the early detection of asthma attacks. Due to the limited study duration per patient and the pragmatic nature of the study, future research is needed to comprehensively evaluate and externally validate the performance of both biomarkers and their utility for asthma self-management.

SUBMITTER: Tinschert P

PROVIDER: S-EPMC7754262 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Nocturnal Cough and Sleep Quality to Assess Asthma Control and Predict Attacks.

Tinschert Peter P Rassouli Frank F Barata Filipe F Steurer-Stey Claudia C Fleisch Elgar E Puhan Milo Alan MA Kowatsch Tobias T Brutsche Martin Hugo MH

Journal of asthma and allergy 20201214

<h4>Introduction</h4>Objective markers for asthma, that can be measured without extra patient effort, could mitigate current shortcomings in asthma monitoring. We investigated whether smartphone-recorded nocturnal cough and sleep quality can be utilized for the detection of periods with uncontrolled asthma or meaningful changes in asthma control and for the prediction of asthma attacks.<h4>Methods</h4>We analyzed questionnaire and sensor data of 79 adults with asthma. Data were collected in situ ...[more]

PMID: 33363391

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Project description:INTRODUCTION:Nocturnal cough is a burdensome asthma symptom. However, knowledge about the prevalence of nocturnal cough in asthma is limited. Furthermore, prior research has shown that nocturnal cough and impaired sleep quality are associated with asthma control, but the association between these two symptoms remains unclear. This study further investigates the potential of these symptoms as markers for asthma control and the accuracy of automated, smartphone-based passive monitoring for nocturnal cough detection and sleep quality assessment. METHODS AND ANALYSIS:The study is a multicentre, longitudinal observational study with two stages. Sensor and questionnaire data of 94 individuals with asthma will be recorded for 28 nights by means of a smartphone. On the first and the last study day, a participant's asthma will be clinically assessed, including spirometry and fractionated exhaled nitric oxide levels. Asthma control will be assessed by the Asthma Control Test and sleep quality by means of the Pittsburgh Sleep Quality Index. In addition, nocturnal coughs from smartphone microphone recordings will be labelled and counted by human annotators. Relatively unrestrictive eligibility criteria for study participation are set to support external validity of study results. Analysis of the first stage is concerned with the prevalence and trends of nocturnal cough and the accuracies of smartphone-based automated detection of nocturnal cough and sleep quality. In the second stage, patient-reported asthma control will be predicted in a mixed effects regression model with nocturnal cough frequencies and sleep quality of past nights as the main predictors. ETHICS AND DISSEMINATION:The study was reviewed and approved by the ethics commission responsible for research involving humans in eastern Switzerland (BASEC ID: 2017-01872). All study data will be anonymised on study termination. Results will be published in medical and technical peer-reviewed journals. TRIAL REGISTRATION NUMBER:NCT03635710; Pre-results.

Project description:ObjectiveSeveral plausible mechanisms and anecdotal descriptions suggest that gout attacks often occur at night, although there are no scientific data supporting this. We undertook this study to evaluate the hypothesis that gout attacks occur more frequently at night.MethodsWe conducted a case-crossover study to examine the risk of acute gout attacks in relation to the time of the day. Gout patients were prospectively recruited and followed up via the internet for 1 year. Participants were asked about the following information concerning their gout attacks: the date and hour of attack onset, symptoms and signs, medication use, and purported risk factors during the 24- and 48-hour periods prior to the gout attack. We calculated the odds ratios (ORs) of gout attacks (with 95% confidence intervals [95% CIs]) according to three 8-hour time blocks of the day (i.e., 12:00 AM to 7:59 AM, 8:00 AM to 3:59 PM [reference], and 4:00 PM to 11:59 PM) using conditional logistic regression.ResultsOur study included 724 gout patients who experienced a total of 1,433 attacks (733, 310, and 390 attacks during the first, second, and third 8-hour time blocks, respectively) over 1 year. The risk of gout flares in the 8-hour overnight time block (12:00 AM to 7:59 AM) was 2.36 times higher than in the daytime (8:00 AM to 3:59 PM) (OR 2.36 [95% CI 2.05-2.73]). The corresponding OR in the evening (4:00 PM to 11:59 PM) was 1.26 (95% CI 1.07-1.48). These associations persisted among those with no alcohol use and in the lowest quintile of purine intake in the 24 hours prior to attack onset. Furthermore, these associations persisted in subgroups according to sex, age group, obesity status, diuretic use, and use of allopurinol, colchicine, and nonsteroidal antiinflammatory drugs.ConclusionThese findings provide the first prospective evidence that the risk of gout attacks during the night and early morning is 2.4 times higher than in the daytime. Further, these data support the purported mechanisms and historical descriptions of the nocturnal onset of gout attacks and may have implications for antigout prophylactic measures.

Dataset Information

Nocturnal Cough and Sleep Quality to Assess Asthma Control and Predict Attacks.

Introduction

Methods

Results

Conclusion

Publications

Nocturnal Cough and Sleep Quality to Assess Asthma Control and Predict Attacks.

Similar Datasets

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