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In a prospective study of patients with muco-obstructive lung disease, aiming to develop a cough alert system based on nocturnal cough monitoring, to identify patient-individual thresholds at which cough frequency exceeds normal variability, so far 92 of intended 220 patients were included.
From den Brinker et al. in a study with 30 COPD patients it is known, that the day-to-day variation of the number of coughs is high and that instances of high counts occur at isolated days (1). Both observations motivate the use of temporal smoothing - advantageous to reduce the noise-like variations - using a first-order infinite impulse response (IIR) filter with pole at 0.75 for the cough count on the B-scale. The linear relation between average and standard deviation of the cough count was assumed to hold in general and motivated the mapping of the cough count onto a new scale B. This scale B is constructed such that 1 unit step on the B-scale approximately corresponds to a step of one standard deviation at the original scale. The B-scale then is the natural basis for the aspired alert system. They noted that the independence of cough counts between consecutive 24 h periods implies that time-averaging could be an effective means for uncertainty (noise) reduction and that arithmetic averaging is a more proper operation here than in the original domain where, in view of the logarithmic nature, geometric averaging would be the preferred operation. Furthermore, they opted in a heuristic approach for a 9-days consecutive period (out of at most 90 days of observation) having a minimum average value for a baseline definition.
We observe that our patients tend to monitor their nocturnal cough less consistently than intended. Of the 75/92 patients with at least 9 days of follow-up data, only 2/3 have data for a 9-days consecutive period. Depending on the missingness pattern for patients with less than 9 consecutive days different multiple imputation options will be applied and their impact on resulting baseline definitions will be investigated. Potential alert frequencies will be compared between these baseline-definitions for patients with continued follow-up after an incomplete “baseline”-period. (data collection/ work in progress)
1 den Brinker et.al. Alert system design based on experimental findings from long-term unobtrusive monitoring in COPD. Biomed Signal Process Control. 2021 Jan;63: 102205.
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