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Physical Activity Measured by Pams vs. Cgm Trends: Correlation Analysis

This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

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Abstract

Objective: Physical activity (PA) effect on glucose variability is very important in diabetes management. In the present study, we investigated the correlations between PA, measured by PAMS (Physical Activity Monitoring System: a device that records body posture and movement exploiting accelerometers and inclinometers) and first- and second-order derivatives of glucose concentration measured by CGM with the DexCom Seven Plus. Method: 19 type-1 diabetic (T1D) and 19 control subjects were studied in the Clinical Research Unit at Mayo Clinic (Rochester, MN) for 88 hours. Each day, subjects alternated 26.5 min of walking on treadmill (1.2 mph) with 33.5 min of sitting, for 4-6 consecutive times. First- and second-order glucose derivatives were estimated using a Bayesian smoothing procedure. Their correlation with PAMS signal was assessed at various delays in the range 0-60 min. Result: In T1D patients the negative correlation between PA and first-order glucose derivative is maximal after 15 min of PA, and the positive correlation is maximal after 15 min of rest. Furthermore, the negative correlation between PA and second-order glucose derivative is maximal after 5 min of PA, and the positive correlation is maximal after 5 min of rest. Results on control subjects are similar, but the degree of correlation is smaller (in absolute terms) and PA effect commences within 5 minutes. Conclusion: Low intensity PA correlates with glucose trend: PA decreases glucose concentration or slows its increase. Further work will rely on how to exploit this quantitative result in short-term prediction of glycemia on artificial pancreas algorithms.