Quantifying the effects of sleep on sensor-derived variables from upper limb accelerometry in people with and without upper limb impairment.

This was a secondary analysis of baseline data from a cohort study, not a trial of treatment, so it cannot show whether removing sleep improves clinical decisions or patient outcomes. The analysis included only 127 of 148 eligible people, because 16 had missing data or withdrew and 5 did not meet the full 48-hour wear rule. All upper limb impairments were grouped together, so the result does not tell you how stroke, multiple sclerosis, fracture, shoulder pain, or breast cancer differ. Sleep was detected with wrist actigraphy, not polysomnography, and the algorithm may have overestimated sleep, which could have overestimated the effect of sleep on the variables. The main paper reported only five variables, and the authors did not formally test whether a different sleep algorithm would change the result. The significant differences were small, but the paper did not define the smallest difference that would matter for patient care.

The study was funded by the National Institutes of Health. The supplied text does not list other conflicts of interest.

Do not conclude that sleep can be ignored for every upper limb sensor variable or clinical setting. The study found significant differences for three of five main variables, and it did not test whether ignoring sleep changes patient care decisions. The effect was 0.31 and 0.29 hours for arm-use time, but other variables may behave differently.