detect_all_events: Detect All Glycemic Events

In cgmguru: Advanced Continuous Glucose Monitoring Analysis with High-Performance C++ Backend

Detect All Glycemic Events

Description

Comprehensive function to detect all types of glycemic events aligned with international consensus CGM metrics (Battelino et al., 2023). This function provides a unified interface for detecting multiple event types including Level 1/2/Extended hypo- and hyperglycemia, and Level 1 excluded events.

Usage

detect_all_events(df, reading_minutes = NULL)

Arguments

df	A dataframe containing continuous glucose monitoring (CGM) data. Must include columns: id: Subject identifier (string or factor) time: Time of measurement (POSIXct) gl: Glucose value (integer or numeric, mg/dL)
reading_minutes	Time interval between readings in minutes (optional). Can be a single integer/numeric value (applied to all subjects) or a vector matching data length (different intervals per subject)

Value

A tibble containing comprehensive event analysis with columns:

• id: Subject identifier

• type: Event type (hypo/hyper)

• level: Event level (lv1/lv2/extended/lv1_excl)

• total_episodes: Total number of episodes

• avg_ep_per_day: Average episodes per day

• avg_episode_duration_below_54: Average episode duration below 54 mg/dL in minutes (hypoglycemic events only)

Event types

- Hypoglycemia: lv1 (< 70 mg/dL, \geq 15 min), lv2 (< 54 mg/dL, \geq 15 min), extended (< 70 mg/dL, \geq 120 min). - Hyperglycemia: lv1 (> 180 mg/dL, \geq 15 min), lv2 (> 250 mg/dL, \geq 15 min), extended (> 250 mg/dL, \geq 90 min in 120 min, end \leq 180 mg/dL for \geq 15 min).

References

Battelino, T., et al. (2023). Continuous glucose monitoring and metrics for clinical trials: an international consensus statement. The Lancet Diabetes & Endocrinology, 11(1), 42-57.

See Also

detect_hyperglycemic_events, detect_hypoglycemic_events

Examples

# Load sample data
library(iglu)
data(example_data_5_subject)
data(example_data_hall)

# Detect all glycemic events with 5-minute reading intervals
all_events <- detect_all_events(example_data_5_subject, reading_minutes = 5)
print(all_events)

# Detect all events on larger dataset
large_all_events <- detect_all_events(example_data_hall, reading_minutes = 5)
print(paste("Total event types analyzed:", nrow(large_all_events)))

# Filter for specific event types
hyperglycemia_events <- all_events[all_events$type == "hyper", ]
hypoglycemia_events <- all_events[all_events$type == "hypo", ]

print("Hyperglycemia events:")
print(hyperglycemia_events)
print("Hypoglycemia events:")
print(hypoglycemia_events)

cgmguru documentation built on Nov. 6, 2025, 1:07 a.m.