Table 3.
Comparison of algorithm, visual inspectio n, and logs in the identification of the window of consecutive days of wear
| Total sample n = 169 | Sample with logs n = 74 | ||
|---|---|---|---|
| Visual inspection vs. algorithm N (%) | Visual inspection vs. logs N (%) | Algorithm vs. log N (%) | |
| Same number of days in wear window | |||
| Complete agreement | 93 (55.0) | 50 (67.6) | 39 (52.7) |
| Wear window shifted by 1 day in one method | 46 (27.2) | 10 (13.5) | 15 (20.3) |
| Average difference in hours of wear | 0.3 (more in visual inspection) | 5.3 (more in visual inspection) | 1.5 (more in algorithm) |
| Wear window shifted by ≥2 days in one method | 2 (1.2) | 0 (0) | 1 (1.4) |
| Average difference in hours of wear | 2.2 (more in algorithm) | N/A | 4.5 (more in algorithm) |
| Total, N (%) | 141 (83.4) | 60 (81.1) | 55 (74.3) |
| Different number of days in wear window | |||
| Differed by 1 day | 25 (14.8) | 13 (17.6) | 19 (25.7) |
| Method with more days of wear | Visual inspection | Visual inspection | See footnotea |
| Differed by ≥2 days | 3 (1.8) | 1 (1.4) | 0 (0) |
| Method with more days of wear | Visual inspection | Visual inspection | N/A |
| Total, N (%) | 28 (16.6) | 14 (18.9) | 19 (25.7) |
aAlgorithm had more days for 9 (12.2%) signals; log had more days for 10 (13.5%) signals.