glucopy.Gframe.qscore#

Gframe.qscore(slack: int = 0)[source]#

Calculates the Q-Score.

Q - s c o r e = 8 + \frac{\bar{X} - 7.8}{1.7} + \frac{R a n g e - 7.5}{2.9} + \frac{t_{G < 3.9} - 0.6}{2.9} + \frac{t_{G > 8.9} - 6.2}{5.7} + \frac{M O D D - 1.8}{0.9}

$\bar{X}$ is the sample mean (glucopy.Gframe.mean())
$R a n g e$ is the mean of the differences between the maximum and minimum glucose for each day.
$t_{G < 3.9}$ is the mean time [h] spent under 3.9 mmol/L in each day.
$t_{G > 8.9}$ is the mean time [h] spent over 8.9 mmol/L in each day.
$M O D D$ is the Mean of Daily Differences (glucopy.Gframe.modd()).

Parameters:: slack (int, default 0) – Maximum number of minutes that the given time can differ from the actual time in the data in the calculation of glucopy.Gframe.modd().
Returns:: qscore – Q-Score.
Return type:: float

Examples

Calculating the Q-Score with a 5 minutes slack for MODD:

In [1]: import glucopy as gp

In [2]: gf = gp.data('prueba_1')

In [3]: gf.qscore(slack=5)
Out[3]: 13.717336818929455