glucopy.metrics.grade

glucopy.metrics.grade(df: DataFrame, percentage: bool = True, unit: str = 'mg/dL')

Calculates the contributions of the Glycaemic Risk Assessment Diabetes Equation (GRADE) to Hypoglycaemia, Euglycaemia and Hyperglycaemia. Or the GRADE scores for each value.

\[GRADE = 425 * [\log_{10}(\log_{10} (X_i) + 0.16)]^2\]

• \(X_i\) is the glucose value in mmol/L at time i.

The GRADE contribution percentages are calculated as follows:

\begin{align*} \text{Hypoglycaemia %} &= 100 * \frac{\sum \text{GRADE}(X_i < 3.9 [\text{mmol/L}])}{\sum \text{GRADE}(X_i)} \\ \text{Euglycaemia %} &= 100 * \frac{\sum \text{GRADE}(3.9 [\text{mmol/L}] \leq X_i \leq 7.8 [\text{mmol/L}])}{\sum \text{GRADE}(X_i)} \\ \text{Hyperglycaemia %} &= 100 * \frac{\sum \text{GRADE}(X_i > 7.8 [\text{mmol/L}])}{\sum \text{GRADE}(X_i)} \end{align*}

Parameters:

• df (pandas.DataFrame) – DataFrame containing the CGM values. The dataframe must contain ‘CGM’ column present in glucopy.Gframe.data.

• percentage (bool, default True) – If True, returns a pandas.Series of GRADE score contribution percentage for Hypoglycaemia, Euglycaemia and Hyperglycaemia. If False, returns a list of GRADE scores for each value.

• unit (str, default 'mg/dL') – Unit of the CGM values. Can be ‘mg/dL’ or ‘mmol/L’.

Returns:

grade – Series of GRADE score contribution percentage for Hypoglycaemia, Euglycaemia and Hyperglycaemia. Or a list of GRADE scores for each value.

Return type:

pandas.Series | numpy.ndarray

Notes

This function is meant to be used by glucopy.Gframe.grade()