H.J.P Fokkenrood

Innovative strategies for
intermittent claudication

towards a stepped care approach and new outcome measures



 A total of 27 patients were eligible and all consented to this study. However, data of 6 patients were excluded for reasons listed in figure 2. Patient characteristics of the remaining 21 participants are shown in table 2. Bilateral IC symptoms were observed in 71% of the population. More than half (13/21, 62%) had undergone peripheral vascular surgery but still reported IC symptoms. A total of 27.9 hours of video film was obtained and analysed. Mean video time was 83 minutes per patient (range: 48 – 110 min).

Inter-rate reliability (IRR) of video observations

 IRR data were normally distributed. IRR between both video observers was excellent for most activity categories (ICC of 1.00 for lying, sitting and walking, 0.98 for standing, p<0.005). Moreover, the ICC for "device not worn" and "not recorded" detections were also excellent (1.00 and 0.99, respectively (p<0.005)). However, the ICC for shuffling was poor (0.38).


Validity of the DynaPort MoveMonitor

 Mean duration (±SD) of the postures standing, locomotion, lying and sitting per patient were 8.7 (± 6.1), 15.8 (±5.9), 15.2 (±6.9) and 35.3 (±17.1) minutes, respectively. Total duration of these four postures ranged from 183 to 707 minutes (table 3). In

contrast, shuffling was measured for a mere 5 minutes (mean (±SD) per patient: 24±18 sec) and occurred in twelve patients only. The "device not worn" category was registered in just seven participants with a total measured time of 160 minutes (mean (±SD) per patient: 22.9±9.8 min). Just 22 seconds (<0.1% of total time registered) were labelled as a "not recorded" event leading to removal from further analysis. In total, 5 of the 126 obtained activities (3.9%) were defined as outliers (>4 times SD of agreement) and were detected in the categories locomotion, sitting and "not worn" (table 5). These activities were also removed from analysis. Table 5 shows these outliers; activity as observed by video recording compared to the result of DP detection.



 The agreement between video observation and DP data of observed activities is depicted in table 3. High levels of sensitivity were found for locomotion (86.1%), lying (96.8%), sitting (90.6%) and 'device not worn' (88.7%). High specificities and PPVs were also found regarding these four categories (>88.3%; table 4).



 In contrast, the DP showed a low 46.2% sensitivity value (table 3). In reality "sitting" was performed in 37.1% of this 'standing' time (table 3). This poor agreement is likely due to aberrant data obtained from 10 of the 21 patients. Eight of these 10 patients were actually sitting (instead of standing) in 49.9 to 74.9% of the videoed time. In the two other measurements, the patient was moving in 27.5% and 29.3% of the "standing" time respectively. Video observations and DP data did also show a low agreement regarding the category shuffling (17.5%; table 3) although a high specificity (98.7%) was found.



 Data of walks during patient' hospital visit (mean number of steps: 1561 ± 675 steps) and treadmill walking (mean number of steps: 473 ± 155 steps) were normally distributed and used for step analysis. The ICC of calculated steps between video observation and DP data was 0.90 (95% confidence interval (CI): 0.77 - 0.96, p=.001) and 0.84 for treadmill walking (95% CI: 0.63 – 0.93). One patient performed 2199 steps while the DP detected just 908 steps. Analysis revealed that this patient wore the DP upside down. The data set of this patient was defined as outlier and excluded for the activity analysis ("locomotion activity", table 5) but not for the step analysis.