glucopy.metrics.bgi#
- glucopy.metrics.bgi(df: DataFrame, unit: str = 'mg/dL', index_type: str = 'h', maximum: bool = False)[source]#
Calculates the Low Blood Glucose Index (LBGI) or the High Blood Glucose Index (LBGI).
\[LBGI = \frac{1}{N} \sum_{i=1}^N rl(X_i)\]\[HBGI = \frac{1}{N} \sum_{i=1}^N rh(X_i)\]\(N\) is the number of glucose readings.
\(rl(X_i) = 22.77 * f(X_i)^2\) if \(f(X_i) < 0\) and \(0\) otherwise.
\(rh(X_i) = 22.77 * f(X_i)^2\) if \(f(X_i) > 0\) and \(0\) otherwise.
\(f(X_i) = 1.509 * (\ln(X_i)^{1.084} - 5.381)\) for glucose readings in mg/dL.
\(X_i\) is the glucose value in mg/dL at time i.
- Parameters:
df (pandas.DataFrame) – DataFrame containing the CGM values. The dataframe must contain ‘CGM’ column present in
glucopy.Gframe.data.unit (str, default 'mg/dL') – Unit of the CGM values. Can be ‘mg/dL’ or ‘mmol/L’.
index_type (str, default 'h') – Type of index to calculate. Can be ‘h’ (High Blood Glucose Index) or ‘l’ (Low Blood Glucose Index).
maximum (bool, default False) – If True, returns the maximum LBGI or HBGI. If False, returns the mean LBGI or HBGI.
- Returns:
bgi – Low Blood Glucose Index (LBGI) or High Blood Glucose Index (HBGI).
- Return type:
float
Notes
This function is meant to be used by
glucopy.Gframe.bgi()