Nursing Perspectives on the Use of Continuous Glucose Monitoring in the Intensive Care Unit.

BACKGROUND: The COVID-19 pandemic necessitated rapid implementation of continuous glucose monitoring (CGM) in the intensive care unit (ICU). Although rarely reported, perceptions from nursing staff who used the systems are critical for successful implementation and future expanded use of CGM in the inpatient setting. METHODS: A 22-item survey focused on CGM use was distributed to ICU nurses at two large academic medical centers in the United States in 2022. Both institutions initiated inpatient CGM in the spring of 2020 using the same CGM+point of care (POC) hybrid protocol. The survey employed a 1- to 5-point Likert scale regarding CGM sensor insertion, accuracy, acceptability, usability, training, and perceptions on workload. RESULTS: Of the 71 surveys completed, 68 (96%) nurses reported they cared for an ICU patient on CGM and 53% reported they had independently performed CGM sensor insertion. The ICU nurses overwhelmingly reported that CGM was accurate, reduced their workload, provided safer patient care, and was preferred over POC glucose testing alone. Interestingly, nearly half of nurses (49%) reported that they considered trend arrows in dosing decisions although trends were not included in the CGM+POC hybrid protocol. Nurses received training through multiple modalities, with the majority (80%) of nurses reporting that CGM training was sufficient and prepared them for its use. CONCLUSION: These results confirm nursing acceptance and preference for CGM use within a hybrid glucose monitoring protocol in the ICU setting. These data lay a blueprint for successful implementation and training strategies for future widespread use.

Sudden Changes in Interstitial Glucose Sensing by Remote Real-Time Continuous Glucose Monitoring as a Marker of Hypoperfusion in Critically-Ill Patients with COVID-19

Introduction: During the COVID-19 pandemic, we implemented a protocol combining continuous glucose monitoring (CGM) with a computerized intravenous insulin infusion algorithm to care for patients with severe COVID-19. Objective: To examine glucose trends surrounding cardiac arrest events to evaluate the performance of CGM sensors during severe clinical instability. Methods: We reviewed eight cases of patients with type 2 diabetes diagnosed with COVID-19 requiring ICU care on IV insulin and CGM therapy experiencing severe clinical decompensation leading to cardiac arrest. Index events (cardiac arrest) were identified by staff documentation in the electronic health record. Clinical characteristics, mean arterial pressure (MAP), and point-of-care (POC) glucose values surrounding the index event were collected. CGM data was paired with MAP and POC glucose values. Rapid declines in the glucose trend [rate of change (ROC) ≥3mg/dl/min] were identified during this time of clinical instability. Results: The mean age of patients was 61.3±13.8 years. All patients were treated with steroid therapy, vasopressors, and mechanical ventilation. 62.5% were on CRRT. Four (50%) patients had sudden cardiac arrest and drop in MAP, while the other four patients had a more prolonged decline in MAP prior to cardiac arrest. CGM values in those with sudden arrest showed an abrupt decline (≥3mg/dl/min) an average of 16.7±13.7 min following cardiac arrest. Rapid down trending of CGM values in those with prolonged hypotension occurred on average about 6 hours prior to cardiac arrest. During these episodes, the CGM values stopped correlating with POC tests. Conclusions: Real-time CGM in critically-ill patients may provide clinical information beyond glucose control. Rapid declines in CGM values (≥3mg/dl/min) not correlating with POC glucose testing are associated with both sudden and prolonged changes in arterial pressure.

Remote Continuous Glucose Monitoring With a Computerized Insulin Infusion Protocol for Critically Ill Patients in a COVID-19 Medical ICU: Proof of Concept.

OBJECTIVE: The use of remote real-time continuous glucose monitoring (CGM) in the hospital has rapidly emerged to preserve personal protective equipment and reduce potential exposures during coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS: We linked a hybrid CGM and point-of-care (POC) glucose testing protocol to a computerized decision support system for continuous insulin infusion and integrated a validation system for sensor glucose values into the electronic health record. We report our proof-of-concept experience in a COVID-19 intensive care unit. RESULTS: All nine patients required mechanical ventilation and corticosteroids. During the protocol, 75.7% of sensor values were within 20% of the reference POC glucose with an associated average reduction in POC of 63%. Mean time in range (70-180 mg/dL) was 71.4 ± 13.9%. Sensor accuracy was impacted by mechanical interferences in four patients. CONCLUSIONS: A hybrid protocol integrating real-time CGM and POC is helpful for managing critically ill patients with COVID-19 requiring insulin infusion.