When diagnosing chronic cough (cough lasting longer than 8 weeks), the physician nowadays very often relies on the patient's narrative and description. In our research project we want to find out whether a cough detector can continuously and reliably record the cough, how the user-friendliness of the cough detector is assessed and whether this continuous recording can support the physician in his diagnosis.
After chronic cough diagnosis, the Principal Investigator (or his designee) will identify patients who are potentially eligible to participate in this pilot study, based on the predefined inclusion criteria. A number of 25 participants will be recruited for this pilot study: 10 suffering from chronic cough with unclear underlying cause, 4-6 suffering from COPD, 4-6 suffering from Asthma and 4-6 suffering from interstitial lung disease. Patients who choose to participate will be entered into the pilot study after obtaining their informed consent, when they will receive the SIVA-P3 wearable (and charging device), helped to download the SIVA-P3 smartphone application and couple the wearable component with the smartphone. Furthermore, they will be asked to rate their current cough severity on a visual analog scale (Cough Severity VAS). Participants will receive an envelope with a second Cough Severity VAS and a return envelope to send back the SIVA-P3 wearable and charging device at the end of the study. Participants will receive standard care and will be asked to wear the wearable component during the day, charge it on the bedside while sleeping and to otherwise go about daily life as they would do normally for a duration of seven days. In the evening of every day, they will be prompted by the SIVA-P3 smartphone application to indicate the timing of their main meals. On day 8, the study nurse will conduct a pre-scheduled phone interview with each participant. The phone interview will include instructing the patient to fill in the final Cough Severity VAS, asking the questions of the Participant User Feedback Questionnaire, and instructing the patient to send the Cough Severity VAS form and the SIVA-P3 wearable (and charging device) back to the trial site using the return envelope. The Participant User Feedback Questionnaire will include ratings of wearing comfort, usability and likeliness to wear for extended period of time.
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Enrollment
29
Digital cough recording: Participants receive a small, wearable data recorder, wear it during waking hours and keep it on the nightstand during sleep for 7x24 hours. The data is sent to a smartphone application, where a cough detection algorithm converts it into time-stamped cough events. Participants respond to questions on their smartphone once a day for additional context data. The cough events and context data are sent to a secure online database for further evaluation. For the first 24 hours, segments of audio data are sent to be able to validate the performance of the cough detection algorithm. Afterwards, only cough events and context data are sent from the participant's smartphone.
University Hospital Zurich
Zurich, Switzerland
Validation
The primary outcomes are sensitivity, specificity and related metrics (positive and negative predictive values, rates of false positive and false negative detections per hour) for cough frequency measurement of SIVA-P3 in the target patient population over a 24-hour validation phase (first 24 hours after baseline visit). Sensitivity, specificity and positive and negative predictive values contribute to a description of cough monitor performance.
Time frame: 24 hours
Wearing Time
The wearable device continuously records movement data. This movement data is used to determine if the wearable device is being worn.
Time frame: 7 days
Wearing Comfort
Wearing Comfort will be determined through quantitative analysis of closed and open questions in the Participant User Feedback Questionnaire.
Time frame: 7 days
Awareness of wearing the device
Patients will be questioned via the smartphone application how many times they have approximately noticed during the day that they have been wearing the device.
Time frame: 7 days
Usability
Usability from the patient's perspective will be determined through quantitative analysis of closed questions in the Participant User Feedback Questionnaire.
Time frame: 7 days
Continued Wearing Likeliness
Continued Wearing Likeliness will be determined through quantitative analysis of closed and open questions in the Participant User Feedback Questionnaire.
Time frame: 7 days
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Correlation of patient-reported cough severity
Cough Severity Correlation will be determined by correlating daily cough counts determined by the SIVA-P3 algorithm with the patient's self-reported Cough Severity VAS.
Time frame: 7 days
Variations of time course of coughing between different days within individual patients
To compare the variations of time course of coughing, the hourly profiles of each day will be interpreted as discrete distribution functions. A range of statistical features associated with properties of distributions will be calculated for all profiles and compared both within individual patients and across the whole population. These features will include mean, median, variance, skewness, kurtosis and additional descriptive statistics for multimodal distributions.
Time frame: 7 days
Diagnostic prediction models
To evaluate the predictive performance of a mathematical model, different models will be explored. The outcome is the performance of the best predictive model identified.
Time frame: 7 days