AGATA

# Time

# timeInHypoglycemia

function timeInHypoglycemia = timeInHypoglycemia(data)

Function that computes the percentage of time spent in hypoglycemia (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInHypoglycemia: double
    Percentage of time in hypoglycemia (i.e., < 70 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInL1Hypoglycemia

function timeInL1Hypoglycemia = timeInL1Hypoglycemia(data)

Function that computes the percentage of time spent in level 1 hypoglycemia (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInL1Hypoglycemia: double
    Percentage of time in level 1 hypoglycemia (i.e., 54-70 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInL2Hypoglycemia

function timeInL2Hypoglycemia = timeInL2Hypoglycemia(data)

Function that computes the percentage of time spent in level 2 hypoglycemia (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInL2Hypoglycemia: double
    Percentage of time in level 2 hypoglycemia (i.e., < 54 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInHyperglycemia

function timeInHyperglycemia = timeInHyperglycemia(data)

Function that computes the percentage of time spent in hyperglycemia (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInHyperglycemia: double
    Percentage of time in hyperglycemia (i.e., > 180 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInL1Hyperglycemia

function timeInL1Hyperglycemia = timeInL1Hyperglycemia(data)

Function that computes the percentage of time spent in level 1 hyperglycemia (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInL1Hyperglycemia: double
    Percentage of time in level 1 hyperglycemia (i.e., 180-250 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInL2Hyperglycemia

function timeInL2Hyperglycemia = timeInL2Hyperglycemia(data)

Function that computes the percentage of time spent in level 2 hyperglycemia (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInL2Hyperglycemia: double
    Percentage of time in level 2 hyperglycemia (i.e., > 250 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInTarget

function timeInTarget = timeInTarget(data)

Function that computes the percentage of time spent in the target range (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInTarget: double
    Percentage of time in the target range (i.e., >= 70 and <= 180 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInTightTarget

function timeInTightTarget = timeInTightTarget(data)

Function that computes the percentage of time spent in the tight target range (ignoring nan values).

# Input

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl).

# Output

  • timeInTightTarget: double
    Percentage of time in the tight target range (i.e., >= 70 and <= 140 mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose.

# Reference

  • Battelino et al., "Continuous glucose monitoring and merics for clinical trials: An international consensus statement", The Lancet Diabetes & Endocrinology, 2022, pp. 1-16. DOI: https://doi.org/10.1016/S2213-8587(22)00319-9.

# timeInGivenRange

function timeInGivenRange = timeInGivenRange(data, minValue, maxValue)

Function that computes the percentage of time spent in the given range (ignoring nan values).

# Inputs

  • data: timetable (required)
    A timetable with columns Time and glucose containing the glucose data to analyze (mg/dl);
  • minValue: double (required)
    A double containing the lower range value (mg/dl);
  • maxValue: double (required)
    A double containing the upper range value (mg/dl).

# Output

  • timeInTightTarget: double
    Percentage of time in the given range (i.e., >= minValue and <= maxValue mg/dl).

# Preconditions

  • data must be a timetable having an homogeneous time grid;
  • data must contain a column named Time and another named glucose;
  • minValue must be smaller or qual to maxValue.

# Reference

  • None

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