1. Continuous Glucose Monitor Metrics Are Associated with Emergency Department Visits and Hospitalizations for Hypoglycemia and Hyperglycemia, but Have Low Predictive Value.
- Author
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Gilliam LK, Parker MM, Moffet HH, Lee AK, and Karter AJ
- Subjects
- Adult, Aged, Female, Humans, Male, Middle Aged, Blood Glucose analysis, Case-Control Studies, Diabetes Mellitus, Type 2 blood, Emergency Room Visits, Hypoglycemic Agents therapeutic use, Hypoglycemic Agents adverse effects, Insulin administration & dosage, Insulin therapeutic use, Insulin adverse effects, Predictive Value of Tests, Emergency Service, Hospital statistics & numerical data, Hospitalization statistics & numerical data, Hyperglycemia epidemiology, Hyperglycemia blood, Hypoglycemia epidemiology, Hypoglycemia blood, Continuous Glucose Monitoring
- Abstract
Objective: Determine whether continuous glucose monitor (CGM) metrics can provide actionable advance warning of an emergency department (ED) visit or hospitalization for hypoglycemic or hyperglycemic (dysglycemic) events. Research Design and Methods: Two nested case-control studies were conducted among insulin-treated diabetes patients at Kaiser Permanente, who shared their CGM data with their providers. Cases included dysglycemic events identified from ED and hospital records (2016-2021). Controls were selected using incidence density sampling. Multiple CGM metrics were calculated among patients using CGM >70% of the time, using CGM data from two lookback periods (0-7 and 8-14 days) before each event. Generalized estimating equations were specified to estimate odds ratios and C-statistics. Results: Among 3626 CGM users, 108 patients had 154 hypoglycemic events and 165 patients had 335 hyperglycemic events. Approximately 25% of patients had no CGM data during either lookback; these patients had >2 × the odds of a hypoglycemic event and 3-4 × the odds of a hyperglycemic event. While several metrics were strongly associated with a dysglycemic event, none had good discrimination. Conclusion: Several CGM metrics were strongly associated with risk of dysglycemic events, and these can be used to identify higher risk patients. Also, patients who are not using their CGM device may be at elevated risk of adverse outcomes. However, no CGM metric or absence of CGM data had adequate discrimination to reliably provide actionable advance warning of an event and thus justify a rapid intervention.
- Published
- 2024
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