Expanding Use of Continuous Glucose Monitoring Beyond COVID in Critical Care: Impact on Nurse Work Patterns and Patient Outcomes
Phase: PHASE1
Conditions: Hyperglycemia
Sponsor: Ohio State University

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Study Title 
Expanding use of continuous glucose monitoring beyond 
COVID in critical care: Impact on nurse work patterns 
and patient outcomes 
NCT Number 
N/A 
Document Description 
Study Protocol and Statistical Analysis Plan  
Date 
April 26, 2022 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

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Research Protocol 
 
Expanding use of continuous glucose monitoring beyond COVID in critical care: 
Impact on nurse work patterns and patient outcomes 
 
I. Objectives 
 
The primary objective of this mixed methods hybrid II implementation study is to assess the feasibility of 
real time continuous glucose monitoring (CGM) implementation using a CGM plus (+) point-of-care (POC) 
protocol among patients on IV insulin or those with hyperglycemia (>250mg/dl) in the critical care hospital 
environments. Use of the hybrid II implementation study design will allow simultaneous evaluation of 
implementation and effectiveness outcomes to promote more rapid adoption of CGM as routine care for 
hospitalized patients.  
The research Questions (RQ) we hope to address in this study are: 
 
RQ 1: Establish the clinical utility, fidelity, and adoption of Dexcom G6 CGM as a tool for making dosing 
decisions within a CGM+POC protocol among medical intensive care unit (MICU) patients. We will conduct 
a prospective observational cohort study among MICU patients using Dexcom G6 CGM therapy (N=100). Clinical 
utility criteria: Time to CGM validation within protocol parameters, mean percent of dosing decisions determined 
by CGM, changes in insulin dosing from standard guideline or outside standard times in response to alarm and/or 
trend data (as measured by manufacturer download data and corresponding electronic health record (EHR) 
documentation). Fidelity criteria: Proportion of times CGM used non-adjunctively/number of times non-adjunctive 
use indicated per protocol. Adoption criteria: Proportion of patients who consent to received initial CGM 
monitoring/number of patients eligible to receive initial CGM monitoring. Hypothesis: The majority of insulin 
dosing decisions will be made using non-adjunctive CGM and CGM will alter nursing dosing decisions from 
standard guidelines.   
RQ 2: Assess the effects of CGM implementation on nursing workload and factors influencing nursing care 
delivery. We examine nursing workload and care delivery factors through surveys administered to MICU 
nurses and through a MICU staff nurse focus group (N=10). Nursing care delivery factors: Acceptability of 
CGM measured by the Acceptability of Intervention Measure (AIM), appropriateness of CGM measured by the 
intervention appropriateness measure (IAM), and feasibility, measured by the Feasibility of Intervention Measure 
(FIM). Nursing care delivery factors, evaluation of CGM support, and CGM knowledge will be evaluated through 
focus groups and CGM Satisfaction Questionnaire (modified for healthcare workers). Hypothesis: The use of 
CGM will significantly reduce nursing workload while increasing frequency of glucose monitoring.  
RQ 3: To assess glycemic control among patients receiving CGM in the CGM enabled MICU compared to 
historical control patients who received POC glucose monitoring in the MICU. Among critically ill patients on 
CGM (N=100) we will examine time in range (70-180mg/dl), time 100-180mg/dl, time 140-180mg/dl, time in 
hypoglycemia (<55mg/dl, <70mg/dl), and time in hyperglycemia (180-250mg/dl, >250mg/dl) compared to 
matched historical control patients using 3-tiered linear mixed models to control for patient, unit, and nurse specific 
variability. Hypothesis: Patients with CGM will exhibit greater time in range (100-180mg/dl, 140-180mg/dl, 70-
180mg/dl) and experience less frequent time in hypoglycemia than patients on fingerstick POC. 
RQ 4: (exploratory) To assess hospitalization outcomes and conduct economic evaluation of the costs to 
deliver CGM implementation in the MICU. We will track time and resources needed for CGM implementation 
including personnel, training, facilities, materials, equipment, and other necessary inputs. Hospitalization outcomes 
criteria: Length of stay [ICU, total stay], cost of stay, cost of CGM vs. standard POC glucose monitoring, 
discharge level of care [home, SNF], 30-day readmission, morbidity, and mortality. Hypothesis: Patients with 
CGM will experience shorter length of stay, lower cost of stay, will be more likely to discharge to home vs. SNF, 

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have lower 30-day readmission rate, and experience lower mortality/morbidity than matched historical control 
patients receiving fingerstick POC in the MICU.  
 
II. 
Background and Rationale 
 
During the COVID-19 pandemic, CGM has provided a means for reducing healthcare worker exposure to the virus 
and a reduction in care delivery burden during a period of staffing crisis. In April 2020, the FDA issued a statement 
indicating they would permit the use of these systems within the hospital setting during the pandemic.1 Since then, 
CGM has been integrated into routine care within The Ohio State University Wexner Medical Center (OSUWMC) 
MICU.2 OSUWMC began using CGM within a hybrid POC plus CGM protocol in May of 2020 and have 
demonstrated successful and safe use of these devices within the health system for over 132 MICU patients.3 In 
concert, other health systems across the United States have used inpatient CGM and have disseminated valuable 
real-world data that demonstrates safe and effective inpatient use of the technology within a hybrid point-of-care 
(POC) plus CGM protocol.4-10 Across all of these studies, no adverse events were reported. While these studies did 
demonstrate a reduction in POC glucose testing, reasonable accuracy, and safe use among critically ill COVID-19 
patient, they were limited by small sample sizes and a restricted patient population.  
At our institution we examined data from the initial cohort of 19 COVID-19 patients to use CGM in 
OSUWMC MICU. Among these patients, 89% were on ventilators, 37% on vasopressors, and 42% on 
hemodialysis at the time of sensor placement.11 Despite the severity of critical illness, MARD was 13.9% with no 
apparent association with oxygen saturation, mean arterial pressure, vasopressor use, renal replacement, 
anticoagulation, or ventilator support. Time in range (70-180 mg/dl) on day 1 was 64+/- 23%, and on days 2-7 was 
72+/-16%. Time below range (<70 mg/dl) was 1.5+/-4.1% on day 1 and 0.16+/-0.35% on days 2-7 11.  We have 
since expanded our analysis to include a larger cohort of the first 50 COVID-19 patients on CGM. Of these 
patients, 92% were on ventilators, 46% on vasopressors, 33% on hemodialysis, and 74% were on steroids at the 
time of sensor placement. In our larger cohort, the aforementioned factors were again not associated with sensor 
accuracy. Hybrid protocols of POC glucose checks with CGM use have been used in other small studies of 
extremely critically ill ICU patients with COVID-19 (n=61 subjects total in four studies)5-7,10. One study did find 
decreased accuracy with cardiac arrest.5 Across these studies, MARD ranged between 11.1-13.9% for Dexcom 
G66,10,11 and Clarke error grid analysis showed 98-98.2% in zones A+B.6,10 In a recent larger study conducted 
among 218 hospitalized non-ICU patients, mild to moderate anemia was not shown to impact sensor accuracy, 
however more severe anemia (hemoglobin <7g/dL) was found to correlate with higher ARD (17.8%).12 This same 
study demonstrated no association between hyperglycemia and sensor accuracy but did demonstrated a slight 
increase in MARD (18.8%) and ARD (14.5%) with glucose <70mg/dl.12 In a study by Boom et al. focused on 
hypoglycemia reduction, 177 medical ICU patients were randomized to CGM or standard of care. In this study, 
hypoglycemia and was reduced from 12 times per day to fewer than 1 time per day and overall glucose control was 
similar between groups.13 Other ICU studies have also showed acceptable accuracy in ICU patients, despite the use 
of older technologies.14,15 Moreover, there is evidence that accuracy can be offset by increased frequency of 
monitoring, as is the case with CGM.16 While there is some concern surrounding the effects of edema or changes in 
fluid volume on sensor accuracy, a study among congestive heart failure patients demonstrated no association 
between MARD and BNP or changes in plasma volume, this despite the use of older less accurate technology.17  
 
Diabetes is a worsening epidemic worldwide. In the United States, the prevalence has quadrupled between 
1980 and 2020 with an estimated 21.9 million adults living with diabetes 18.  Hospitalizations among patients with 
diabetes account for 30% of the total medical cost of inpatient care with more than 7.8 million hospital discharges 
in 2017 in the United States 19.  Hypoglycemia, hyperglycemia, and glycemic variability in the hospital are 
associated with poor health outcomes including infection, acute renal failure, and death 20-24. Traditional POC 
capillary glucose monitoring measures glucose at one point in time and often misses hypoglycemia 23,25,26, 
especially overnight or asymptomatic episodes, whereas continuous glucose monitoring (CGM) can help provide 
details of glucose continuously as well as velocity and direction of change over time. The ability to visualize 

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glucose trends or direction and velocity of glucose offers tremendous additional benefit over traditional discrete 
POC glucose monitoring.  
Additionally, CGM can improve efficiencies in the critical care environment and reduce nursing care 
burden.2,13 According to the Bureau of Labor Statistics the United States is facing an unprecedented nursing 
shortage which is expected to worsen over the upcoming decade. Intensive inpatient POC glucose monitoring is an 
arduous, time-consuming task, often resulting in insufficient frequency of  testing and testing that is mistimed with 
oral intake or insulin administration.27 The use of inpatient CGM holds tremendous promise to improve patient 
outcomes, reduce nursing workload, and associated healthcare costs, however, the inpatient implementation of 
CGM beyond the pandemic presents unique implementation challenges and warrants further inquiry.  
Description of Technology.  
The Dexcom G6 CGM (Dexcom Inc) measures interstitial fluid glucose. The G6 system consists of 3 key parts: the 
sensor wire, a transmitter, and a display device. In addition, a CGM Dashboard will be used to display data at the 
nurse’s stations.  
The sensor comprises a water-resistant sensor pod that is worn on the skin, and the sensor wire that is 
inserted just under the skin (depth is less than 0.5 inches) using the single-use applicator. The sensor can be worn 
for 10 days and continuously measures glucose levels. In this study the sensor will be worn on the back of the arm.  
The transmitter attaches to the sensor pod and sends glucose information to the display device using 
Bluetooth. Interstitial glucose concentration estimates are sent from the transmitter to the receiving device at 
5-minute intervals and can be checked at any time.  
The G6 software app is downloaded onto the compatible smart device (Android phone), that is paired with 
the transmitter before use. The app continuously and automatically sends data to the Dexcom remote server, where 
the data are stored and displayed in the CLARITY diabetes management software. Alarms for hypoglycemia, 
hyperglycemia and predicted hypoglycemia will be set per the CGM + POC protocol. Android phones are kept just 
outside of the patient rooms. The patient’s hospital identification label will be placed on the back of the phone to 
ensure data is correctly matched to patient participant.  
In addition to the G6 app, glucoses will be displayed on a laptop computer at the nurse’s station using 
investigational Dashboard software. Investigational, unapproved Dashboard software will allow continuous remote 
monitoring of Dexcom G6 data from multiple patients on a secondary display at the nurse’s station. Individual 
CGM tracings for each patient wearing Dexcom G6 will be displayed simultaneously on the investigational 
Dashboard software for multiplex remote monitoring. The Dashboard is programmed with trend arrows, an alarm, 
and glucose threshold alerts to facilitate real-time surveillance of impending hypo and hyperglycemia that warrants 
prevention or intervention. Treatment decisions will not be made using data displayed on this software; glucose 
will be confirmed on G6 app before treatment decisions are made. 
 
CGM + POC Protocol.  
A CGM + POC protocol was developed and implemented within OSUWMC MICU unit. The protocol, which 
allows for intermittent non-adjunctive CGM use with requisite initial validation within each patient and continued 
validation Q6 hours, proved successful in facilitating safe and effective CGM implementation in over 132 critically 
ill patients with COVID-19. The CGM + POC protocol require comparison of paired sensor-meter readings. The 
comparison standard method (Novo StatStrip POC meter) and source (capillary, arterial, venous) are FDA 
approved for inpatient use. In an effort to mitigate risk in this study among critically ill MICU patients, we propose 
a more conservative strategy with increased frequency of ongoing POC testing and validation every 4 hours. 
Additionally, more frequent testing at Q2 or Q1 hours will occur during periods of clinical change that could 
proceed a decline in CGM accuracy. The standard is compared to the CGM value obtained within 5 minutes. The 
threshold criterion for nonadjunctive (stand-alone) use of the CGM to inform insulin dosing decisions appears in 
Table 1. CGM values will be used to determine insulin doses within standard OSUWMC guidelines (e.g., IV 
infusion guideline) and provider prescribed orders. Alert thresholds are set at 100 mg/dl (lower threshold) and 300 

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mg/dl (upper threshold). In addition, the Urgent Low Soon alert will be activated and designed to provide a 20-
minute advance warning of impending hypoglycemia, so nurses can act quickly to avoid a potential severe 
hypoglycemic event.  
 
Table 1. Initial and Ongoing CGM Validation 
Stage 
POC glucose testing procedures 
CGM validation 
POC glucose testing Q1 hour compared to CGM glucose 
Proceed to Q4 hour POC testing when two consecutive sensor-meter pairs approximately 1-hour apart meet 
either of the following criteria:  
1) CGM <20% difference from the POC when the glucose is >100 mg/dl 
2) CGM <20 mg/dl difference from the POC when the glucose is <100 mg/dl 
Sustained use  
Revert from Q4 hour to Q1 hour POC testing if:  
1) CGM >20% difference from the POC when the glucose is >100 mg/dl 
2) CGM >20 mg/dl difference from the POC when the glucose is <100 mg/dl 
3) Revert back to Q4 hour POC testing when two consecutive sensor-meter pairs approximately 1-hour 
apart meet the initial validation criteria 
Revert from Q4 hour to Q2 hour POC testing for a duration of 6 hours for one of the following clinical status 
events occurring in isolation:   
4) Intubation  
5) Pressor support initiated (Levophed dose <0.5 mcg/kg/min or equivalent) 
6) New cardiovascular event (MI, CVA)  
7) Initiation or discontinuation of nutrition support (i.e., enteral feed, total parenteral nutrition) 
8) Hemoglobin <7g/dL 
9) CGM or POC glucose <70mg/dl (follow OSUWMC hypoglycemia policy for initial treatment and 
monitoring) 
10) Predicted low alert (glucose predicted to be <55mg/dl in the following 20 minutes) 
11) Acidosis with pH <7.3 
12) Signs and symptoms do not match glucose readings, particularly for hypoglycemia   
Revert from Q4 hour to Q1 hour POC testing for a duration of 6 hours for two or more of the above clinical 
status events occurring together (example: patient is intubated and starts pressor support)  
If after 6 hours no additional clinical scenarios featured above have developed than Q4 hour POC testing can 
resume after initial validation using two consecutive sensor-meter pairs. 
Obtain 1 time POC glucose if:  
13) No glucose value appears on android screen (due to signal loss, Low/High measure) 
14) Low threshold alert (<100mg/dl) 
Stop CGM use 
Stop use of CGM for insulin titration or glucose monitoring and revert from Q4 hour to Q1 hour POC testing 
(do not remove CGM sensor until sensor expires) for the following conditions:  
1) Refractory shock (Levophed dose >0.5 mcg/kg/min or equivalent)  
2) Cardiac arrest  
3) Newly developed diabetic ketoacidosis (DKA) (pH <7.3 or serum bicarbonate <15 mEq/L in the 
setting of elevated ketones)  
4) Newly developed hyperosmolar non-ketoacidosis (HONK)  
5) Pitting edema, anasarca, blue or purple discoloration to bilateral upper extremity 
6) Initiation of treatment with high dose acetaminophen (>1 gram Q6 hours)  
Initiation of treatment with hydroxyurea 
 
III. 
Procedures 
 
A. Research Design 
 
Hybrid Research Design 

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A hybrid research design that combines elements of effectiveness and implementation research will be used to 
enable more rapid adoption of CGM as standard of care. Traditional step-wise approaches to research which 
progress from clinical efficacy research, to clinical effectiveness research, and finally implementation research 
limit application and slow routine uptake in real-world environments. A hybrid research II design allows for two 
objectives within the research with equal emphasis placed on (1) testing the effectiveness of the intervention and 
(2) determining feasibility and potential impact of the implementation strategy. The use of this design allows us to 
craft a blueprint for successful deployment of CGM therapy within health systems, while at the same time 
gathering valuable real-world effectiveness data. It also allows us to examine how clinical outcomes relate to levels 
of adoption and fidelity.  
APPROACH. Overview: This proposal analyzes the feasibility of inpatient real time CGM implementation 
through the use of a CGM + POC protocol as routine care for glycemic monitoring among patients with 
hyperglycemia (>250mg/dl). The research addresses essential components of ICU implementation including the 
clinical utility of the system to inform glycemic management and insulin dose administration (Aim 1), effects on 
nursing workflow and care delivery (Aim 2), and effects on patient glycemic control compared to matched 
historical control patients from the MICU who received fingerstick POC. Additionally, we propose an exploratory 
aim to examine the effects of CGM use on hospital associated outcomes including length of stay, cost of stay, cost 
of CGM vs. POC glucose monitoring, discharge level of care, 30-day readmission rates, morbidity and mortality 
compared to matched historical control patients (Aim 4). The study will be conducted using a staggered enrollment 
of 20 patients in each wave (20% of target enrollment) with a respite between waves to allow analysis of safety and 
fidelity data prior to continued enrollment. The initial wave (n=20) will be conducted as a “pilot” with full analysis 
including examination of benchmark criteria study continuation. If pilot analysis demonstrates safe use and fidelity, 
then subsequent recruitment will proceed. The analytic approach for each Aim is described below. STATA 15.0 
(StataCorp, College Station, TX) will be used for quantitative analysis and NVIVO (version 10, Doncaster, 
Australia) will be used for qualitative data management. 
Table 2. Study Timeline 
Activity 
Pre-award 
Year 1 
Year 2 
FDA & IRB submission & approvals 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Nursing union approvals  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Patient recruitment   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CGM data collection   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
EHR data collection  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Nursing recruitment  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Nursing focus group & surveys   
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Analysis 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Manuscript & conference dissemination  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Aim 1 & 3: ICU Clinical Utility/Implementation & 
Glycemic control 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  Aim 2: Nursing workload and Care delivery  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 Aim 4: Hospital outcomes  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
FDA 
 
Figure 1. Study Flow Diagram 

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Prior to  
Enrollment 
 
 
 
MICU  
 
 
 
 
 
 
 
MICU  
Historical  
Controls  
 
 
 
 
                            -----------------------------------------------                            ------------------------------------------------- 
 
Nursing  
Survey 
 
 
 
 
Nursing  
Focus Group 
 
 
B. Sample  
The study will take place at OSUWMC. At OSUWMC there are approximately 13,000 hospitalizations with a 
diagnosis code for diabetes each year and current annual inpatient diabetes consult service and diabetes educator 
consults are roughly 3000 per year. OSUWMC has implemented a comprehensive, hospital-wide inpatient diabetes 
program since 2006, including streamlined computerized diabetes related order sets, carbohydrate-based insulin 
dosing, education, and ongoing review of outcomes.  OSUWMC converted to EPIC EHR in 2011 for both inpatient 
and outpatient electronic medical records. The medical centers MICU has been utilizing Dexcom G6 CGM for 
COVID-19 patients since May of 2020 and to date has utilized CGM in over 132 critically ill COVID-19 patients. 
The study will take place in the MICU. The MICU is a 48-bed critical care center and employs 152 staff nurses. 
Patients will be identified through daily screening of patients and associated glycemic control in the MICU to 
identify potential participants with hyperglycemia (glucose >250mg/dl) or those currently on IV insulin. In 2019, 
prior to the COVID-19 pandemic, OSUWMC had 1,065 unique patient admissions in which the patient had a 
glucose >250mg/dl over the course of their MICU stay. Within the MICU patient population, patients with more 
severe illness and those with conditions that may interfere with CGM sensor accuracy will be excluded from 
participation. Full inclusion and exclusion criteria are as follows:  
Eligible individuals are:  
1) adults >18 years old,  
2) admitted to OSUWMC MICU and  
N=100 MICU Patients:  Screen potential participants by inclusion and exclusion criteria. Obtain 
informed consent. 
Collect laboratory, treatment, and hospital cost data from HER. CGM glucose data will be collected 
from Dexcom Clarity Download Software. See Section 1.3, Schedule of Activities for specific data to 
be collected and schedule 
Historical controls meeting the gateway criteria (glucose >250mg/dl or on IV insulin during admission) 
from the same MICU will be matched on the following factors: Diagnosis and type of diabetes, home 
insulin use, steroid use during hospitalization, vasopressor use, North vs. South MICU wings (NP team 
floor vs. resident team floor, respectively), and diabetic ketoacidosis (DKA)/hyperosmolar 
hyperglycemic syndrome (HHS) status. Data from Section 1.3 Schedule of Activities will pulled for 
historical controls.
Place CGM sensor. Collect baseline data from EHR. 
A focus group will be conducted among MICU staff nurses (N=10) to gage their experience using 
CGM.  
All MICU staff nurses (N=152) will be recruited/consented for survey participation. Acceptability of 
Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), and Feasibility of 
Intervention Measure (FIM), CGM Satisfaction Questionnaire (modified for healthcare workers) will 
be administered.  

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3) have hyperglycemia (glucose >250mg/dl) or are currently on IV insulin.  
 
Non-eligible individuals are:  
7) Current COVID-19 infection,  
8) Refractory shock (Levophed dose >0.5 mcg/kg/min or equivalent)  
9) Actively being treated for diabetic ketoacidosis (DKA) 
10) Actively being treated for hyperosmolar non-ketoacidosis (HONK)  
11) Pitting edema, anasarca, blue or purple discoloration to left upper extremity  
12) Treated with high dose acetaminophen (>1 gram Q6 hours)  
13) Treated with hydroxyurea 
14) Are pregnant, patients  
15) Using home insulin pump therapy during hospitalization, or  
16) Reside in a corrections institution. 
 
Sample Size Justification. The primary outcome for the power analysis is the percentage of time spent in target 
(70-180mg/dl). We estimate from previous studies13,28 that these values may have a standard deviation as high as 
25 percentage points, in which case with 100 patients in each group we will have 80% power to detect a difference 
of 10 percentage points in time in range (e.g., 65 vs. 75); a moderate effect size of 0.4. If the standard deviation is 
lower (e.g., 15 as has been true in some studies), we will have greater power (99%) to detect a 10 point difference 
and are still well powered to detect smaller differences (e.g., 90% power for a 7 point difference). All power 
calculations assume an alpha of 0.05 and minimal statistical effects of clustering within the hospitals (e.g., unit or 
nurse level).  
 
C. Detailed study procedures 
 
Recruitment: Critical care clinical research coordinators will screen for preliminary eligibility and forward 
potential participant names to study team using a secure medical record in-basket process. The study team will 
determine eligibility. The study team will ask for permission for the patient to be approached. If permission is 
granted, the study team will verify eligibility and obtain informed consent from the patient or the patient’s legally 
authorized representative. Consent will be obtained prior to research participation and CGM placement. 
Recruitment is expected at a rate of 5 patients per week over seven months. Our target recruitment will be 100 
MICU patients.  
Nurse training: OSUWMC MICU nurses have significant experience with CGM use in an extremely ill cohort of 
COVID-19 patients. Each nurse in the MICU receives training on CGM set-up, insertion, pairing, and CGM 
glucose monitoring features as part of their annual critical care competencies. OSUWMC MICU nurses are trained 
and experienced in using POC glucose measurement to validate the CGM system, however the protocol at use in 
this study differs somewhat from the COVID-19 protocol currently at use in the MICU. Given that, nurses will 
receive training on distinctions between the two protocols including changes to the frequency of POC testing, the 
addition of clinical status events that would warrant more frequent POC testing and validation (Q1 or Q2 hours 
depending on number of events present for a duration of 6 hours). New criteria to stop clinical use (i.e., no use of 
CGM for glucose monitoring, no use of CGM for insulin titration) will be reviewed in detail with nursing along 
with plans for the sensor to remain in place only for data collection. Nursing trainings will be conducted by PI 
(Faulds), Co-I (Jones), and study coordinator during staff meetings and nursing huddles conducted on all shifts. All 
nurses will receive training on the new protocol prior to patient recruitment. The study protocol, along with 
currently available training materials, will be kept at the bedside of all patient participants.  
Staggered enrollment and initial pilot: We will stagger enrollment with just 20 patient participants over a 4-week 
period (target 5 participants/week with a respite between enrollment to allow analysis of safety and fidelity data 
prior to the next round. A robust analysis would be conducted after this first “pilot” round of enrollment. Accuracy 
analysis would include MARD and Clark Error Grid. A full assessment of protocol adherence and evaluate 
adherence to standard insulin dosing guidelines will be completed. The pilot analysis will include evaluation of 

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benchmarks for accuracy, safety, and adverse event monitoring with benchmarks that must met prior to subsequent 
enrollment. Pilot benchmarks for study continuation are as follows:  
• 
Successful initial validation criteria within 24 hours in 80% of participants (16/20) 
• 
Clark error grid analysis demonstrating >95% points in zone A (within 20% of reference glucose value) or 
zone B (outside of 20% but would not lead to inappropriate treatment) following initial validation. 
• 
No more than 1 episode of inappropriate insulin dose resulting in severe hypoglycemia (glucose <55mg/dl) 
after initial sensor validation  
• 
No more than 1 episodes of iatrogenic DKA (pH <7.3 or serum bicarbonate <15 mEq/L in the setting of 
elevated ketones) or hyperosmolar nonketotic state (osmolality 320mOsm/kg with BG >600mg/dl and 
pH >7.3 or serum bicarbonate >15 mEq/L)  
• 
No episodes of severe adverse events resulting in prolonged hospitalization, or other life-threatening 
complication that attributed to the study intervention 
• 
No severe adverse events resulting in death, or other life-threatening complication that is attributed to the 
study intervention  
• 
No severe adverse event resulting in prolonged hospitalization, or other life-threatening complication that 
attributed to the study intervention and is expected to recur 
 
Oversight and monitoring. Study team oversight of nursing use of the CGM system will be performed through a 
combination of (1) daily evaluation of EHR and CGM Clarity data and (2) through rounding on CGM patients 
(mon-Friday by PI (Faulds), Co-I (Jones) and/or study coordinator (to be named) (Saturday, Sunday and holidays 
by the MICU charge nurse who will communicate that day with study team members. Daily rounds will allow the 
study team to continuously evaluate protocol fidelity and identify any safety concerns. The study staff will evaluate 
CGM use daily through Clarity CGM and EHR data to determine the following:  
3. Was initial validation criteria achieved correctly and at what frequency  
4. Is ongoing validations performed Q4 hours and according to validation criteria 
5. If validation is met did the nurse begin hybrid use with non-adjunctive CGM use  
6. Using clarity reports study staff will assess the presence of alarms (e.g., <100mg/dl, >300mg/dl, predictive 
hypoglycemia) Alarms will be reviewed daily by research staff to ensure hypoglycemia and hyperglycemia 
are being treated in accordance with OSUWMC guidelines.  
7. Those patterns of hyperglycemia or hypoglycemia assessed every 24 hours, will be reported to primary 
team via pager/direct message to allow changes to insulin dosing as needed (e.g., max drip rate for IV 
insulin titration).  
8. Assessment of change in clinical status criteria (Table 1) in which per protocol the nurse would increase 
frequency of POC testing and validation.  
9. Assessment of Stop CGM use criteria (Table 1) in which per protocol the nurse would no longer use the 
CGM for glucose monitoring or insulin titration. 
 
RQ 1: Establish the clinical utility, fidelity, and adoption of Dexcom G6 CGM as a tool for making dosing 
decisions within a CGM+POC protocol among medical intensive care unit (MICU) patients.  
Rationale/Approach. We will conduct a prospective cohort observational analysis among critically ill patients on 
IV insulin or those with hyperglycemia (>250mg/dl) in OSUWMC MICU. The research will allow us to examine 
the clinical utility and implementation of CGM as the standard of care in a critical care environment. We 
hypothesis that the majority of insulin dosing decisions will be made using non-adjunctive CGM and CGM, with 
the availability of trend and alarm data, will alter nursing dosing decisions from standard guidelines.  

10
 
 
Procedures. Once consent is obtained, the MICU staff nurse will insert the Dexcom G6 sensor, set up the system, 
pair the transmitter on patients, and connect patient data to a centralized nurse’s station CGM Dashboard in the 
MICU (N=100). The CGM + POC protocol will be used to validate at which time the CGM will be used for non-
adjunctive insulin dosing decisions. POC testing will be performed Q4 hours for continued validation of the CGM 
with more frequent sustained POC validation during periods of rapid clinical change (Table 1).  
The Android phone, which will receive glucose data from the CGM transmitter, will be kept outside of the 
patient room allowing the staff nurse to visualize discrete values, trends and hear alarms without entering the 
patient’s room. OSUWMC MICU employs a staffing ratio maximum of 1 nurse for 2 patients. MICU staff nurses 
will only care for 1 patient using CGM at a time. Alarms are visually displayed and audible from both the 
dashboard and receiver (Android phone); however nurses are instructed to confirm all glucose values and the 
presence of alarms on the receiver devices at the bedside prior to treatment. All nurses in the MICU are trained on 
CGM alarm recognition and response. In a  previous analysis, nurses reported alarms were audible throughout the 
MICU unit.2  If the nurse assigned to the CGM patient participant is not immediately available when an alarm is 
sounding, another nurse or the charge nurse is expected to respond to the alarm and provide appropriate treatment. 
This same alarm response delegation is employed for other MICU systems including cardiac telemetry, Pulse 
oximetry, and ventilator alerts. Nurses will follow standard approved OSUWMC guidelines, policies and provider 
dosing orders for treatment of hyperglycemia and hypoglycemic events. Episodes of hypoglycemia and 
hyperglycemia will be responded to in real time by nursing staff. Our hypoglycemia guideline (Table 3) treats 
glucose <80mg/dl with Dextrose D50% for critically ill patients. Dosing is stratified based on degree of 
hypoglycemia with follow-up required within 15 minutes. For hypoglycemia <60mg/dl nurses are instructed to 
inform the provider via pager/direct chat. Nurses in the MICU are experienced in administration dextrose D50% 
using the described hypoglycemia protocol. If the patient is ordered to undergo magnetic resonance imaging 
(MRI), computerized tomography (CT) radiographic procedures, or diathermy than the sensor/transmitter will be 
removed prior to the procedure as these procedures could potentially interfere with sensor accuracy.29 A new 
sensor will be inserted after procedure is completed and will undergo initial validation prior to use.  
The patient will remain on CGM for the duration of their hospital stay and if discharged to home may 
transition to personal use of the Dexcom G6. The Dexcom G6 sensor is replaced every 10 days and will be 
removed and then replaced for some radiographic procedures or sensor failure. CGM data is automatically 
transferred to Dexcom’s cloud-based Clarity system.  
 
Table 3. OSUWMC Hypoglycemia Guideline, Patients Who are Not Alert, Are NPO, or on IV Insulin 
Infusion 
Blood Glucose 
(BG) Level* 
Action 
Follow-Up 
60-79 mg/dL 
• 
Administer 7.5 g Dextrose D50% (15 ml) IV* 
• 
Consider calling House Officer if patient 
experiencing recurrent BG <70 mg/dL in past 12 h 
• 
Recheck BG q 15 min following treatment 
and treat accordingly until  80mg/dl 
• 
Once  80mg/dl, recheck BG q1h x2 (x4 if 
<45mg/dL at onset), then resume POC 
glucose as previously ordered, Patients 
who are admitted with hypoglycemia 
should be monitored at least q 4h for a 
minimum of 24h 
• 
If > 4h from initial event and BG  
80mg/dl for two consecutive readings, 
may consider reducing IV dextrose 
45-59 mg/dL 
• 
Administer 12.5 g Dextrose D50% (15 ml) IV* 
• 
Call House Officer to report BG and action taken 
<45 mg/dL 
• 
Administer 25 g Dextrose D50% (15 ml) IV* 
• 
Call House Officer to report BG and action taken 
ALL 
• 
Consider adding Dextrose 5% to maintenance IV 
fluids at a rate of 50ml/hr or increase rate of 
existing maintenance IV if dextrose source 
already present  
 
Variables and measures. Clinical utility criteria: Time to CGM validation within hybrid protocol parameters, 
mean percent of dosing decisions determined by CGM, changes in insulin dosing from standard guideline or 
outside standard times in response to alarm and/or trend data (as measured by manufacturer download data and 
corresponding EHR documentation). Fidelity criteria: Proportion of times CGM used non-adjunctively/number of 

11
 
 
times non-adjunctive use indicated per protocol. Adoption criteria: Proportion of patients approached to received 
GCM monitoring/number of patients eligible to receive initial CGM monitoring.  
 
RQ 2: To assess the degree to which CGM implementation within the ICU environment effects nursing 
workload and care delivery.  
Rational/Approach. We will conduct a mixed method analysis to evaluate nursing workload and care delivery 
factors. Nursing care delivery factors including evaluation of CGM support, acceptance of CGM, perceived 
feasibility, and CGM knowledge, will be evaluated using a combination of questionaries and focus groups.  
Procedures/Variables and Measures. We will evaluate nursing care delivery factors related to CGM 
implementation support, acceptance of CGM, feasibility, appropriateness, CGM knowledge and satisfaction with 
CGM as measured by Acceptability of Intervention Measure (AIM), Intervention Appropriateness Measure (IAM), 
and Feasibility of Intervention Measure (FIM), CGM Satisfaction Questionnaire (modified for healthcare workers) 
and focus group conducted among nurses in the CGM-enabled MICU. The AIM, IAM, and FIM are brief 5 item 
Likert-scale questionaries with each showing a high degree of content validity with alphas for the 3 questionnaires 
between 0.87 and 0.89.30 CGM Satisfaction Questionnaire (CGM-SAT) is a 44-item measuring satisfaction with 
CGM over the previous 6 months. The survey has a high degree of validity (a≥0.94) in adults with type 1 diabetes 
using CGM.31 Several items will be modified for application in healthcare workers. All MICU staff nurses (N=152) 
will be informed of the study and invited to participate via email. Upon e-consent, the questionnaires will be 
administered via a REDCap survey. A focus group will be conducted among MICU staff nurses (N=10) to gage 
their experience using CGM. A semi-structured interview guide will focus on areas of perceived CGM 
implementation support and education, CGM knowledge, and recommendations for future best practice. All Aim 2 
variables and measures appear in Table 2.  
RQ 3: To assess glycemic control among patients receiving CGM in the CGM enabled MICU compared to 
historical control patients who received POC glucose monitoring in the MICU.  
Rational/Approach. We will analyze glycemic control factors among MICU patients on CGM compared to 100 
historical control patients from the same MICU who receiving only POC glucose monitoring. We hypothesis that 
patients with CGM will exhibit greater time in range (100-180 mg/dl, 70-180mg/dl, 140-180mg/dl) and experience 
less frequent time in hypoglycemia than patients on fingerstick POC.  
Procedures. Glucose data will be directly transferred from the MICU patients (N=100) to Android mobile 
phones/Dexcom G6 app which captures and stores glucose values every 5 minutes (up to 288 values/day for 100% 
CGM wear). CGM data is automatically transferred from phones/Dexcom G6 app to Dexcom Clarity. Individual 
patient discrete data will be downloads directly from the Clarity site. Historical controls meeting the gateway 
criteria (glucose >250mg/dl or on IV insulin during admission) from the same MICU will be matched on the 
following factors: Diagnosis and type of diabetes, home insulin use, steroid use during hospitalization, vasopressor 
use, North vs. South MICU wings (NP team floor vs. resident team floor, respectively), and diabetic ketoacidosis 
(DKA)/hyperosmolar hyperglycemic syndrome (HHS) status. POC glucose values for historical controls (N=100) 
will be obtained directly from OSUWMC EHR. EHR data will be obtained through an information warehouse 
request providing time stamped, POC glucose value for each match patient. All data will be uploaded into STATA 
15.0 where it will be cleaned and merged prior to analysis. 
Variables and Measures. Demographic, admission, and diabetes specific variables of interest appear in Table 2 
and will be collected from the EHR for MICU participants and for historical controls. Clinical condition variables 
will include presence of renal replacement, mechanical ventilation, ECMO, associated cardiac arrest or 
cerebrovascular accident and SOFA score. SOFA score was calculated, though noted to have limited discriminant 
function for predicting mortality.32 The SOFA score has been validated in critically ill patients33, and is currently 
the scoring system recommended by the Sepsis 3 definition.34 CGM and POC glucose data will be aggregated into 
glucose ranges and thresholds as described in Table 2.  

12
 
 
Exploratory aim:  
RQ 4: To assess hospitalization outcomes and conduct economic evaluation of the costs to deliver CGM 
implementation in the MICU.  
Rational/Approach. We will explore the impact of CGM therapy using a CGM + POC protocol on patient 
hospital outcomes and costs. Analyzes the economic aspects inpatient CGM on patient health and healthcare 
interactions, with a focus on the costs (inputs) and consequences (outcomes) of CGM will enable full 
understanding of implementation effects. We hypothesize that patients with CGM will experience shorter length of 
stay, lower cost of stay, will be more likely to discharge to home vs. SNF, have a lower 30-day readmission rate, 
and experience lower mortality/morbidity than matched patients receiving fingerstick POC.  
Procedures. Data will be retrospectively extracted from the EHR for patients using CGM in the MICU (N=100) 
along with 100 historical controls. Data will be obtained from the EHR and billing department through an 
information warehouse request. Data from the time in motion study will be evaluated to extrapolate the economic 
impact of nursing personnel time spent for CGM vs. POC glucose monitoring and resources used in POC vs. CGM 
glucose monitoring.   
Variables and Measures. Hospital outcomes criteria include the following: Length of stay [ICU, total stay], cost 
of stay, discharge level of care [home, SNF], morbidity, mortality and readmission rate at 30 days. We will conduct 
economic evaluation of the costs to deliver CGM implementation in the MICU. We will track resources needed for 
CGM implementation including personnel, training, facilities, materials, equipment, and other necessary inputs. In 
addition to resources used, we will expand analysis to evaluate nursing productivity and burden. Resource 
outcomes criteria include: nursing time spent in CGM vs. POC glucose monitoring and cost of CGM vs. standard 
POC glucose monitoring materials.  
Table 2. Patient Participant Schedule of Activities  
Aim  
Concept  
Variable  
Frequency 
Measure 
Aim 
1  
Clinical utility 
criteria 
Time to CGM validation (Aim 1 only)  
Sensor placement 
(Q10 days) 
• 
EHR 
• 
Clarity 
download 
Mean percent of dosing decisions determined by CGM 
Daily 
Changes in insulin dosing from guideline or outside 
standard times in response to alarm and/or trend data 
Daily 
Aim 
1 
Fidelity & 
Adoption 
Implementation 
criteria 
Proportion of times CGM initiated or patient 
approached for study inclusion according to 
protocol/total number of initiations 
Admission 
• 
EHR 
• 
Study 
recruitment 
log 
Proportion of patients approached to received GCM 
monitoring/number of patients eligible to receive 
initial CGM monitoring 
Admission 
Acceptability of CGM 
 
Appropriateness of CGM 
Feasibility of CGM 
CGM knowledge 
Aim 
3 
Patient 
condition 
Demographic data: Age, race/ethnicity, gender 
Admission 
• 
EHR 
Height, weight, and BMI 
Admission 
Diagnosis and type of diabetes 
Admission 
Home diabetes regimen 
Admission 
Total daily insulin dose   
Daily 
Past medical history: tobacco use, COPD, 
hypertension, heart failure, coronary artery disease 
Admission 
Clinical condition: Admission/inpatient glucose, 
HbA1c, admission diagnosis, admitting service, MICU 
Admission 

13
 
 
location (North vs. South), DKA/HHS, sepsis, acute 
liver failure, acute heart failure 
Clinical condition:  SOFA score, dialysis, 
thromboembolic events, ECMO mechanical 
ventilation, ICU/hospital length of stay, cardiac arrest, 
cerebrovascular accident, mortality 
Daily 
Medications:  vasopressor use, steroids, 
anticoagulants, acetaminophen dose 
Daily 
Creatinine, eGFR, ALT, AST, TBR, WBC, 
procalcitonin, ferritin, CRP, IL6, D-dimer, PTT, INR, 
troponin, pH, BHB, bicarbonate 
Daily  
Enteral or parenteral nutrition  
Daily 
O2 sat, pAO2, blood pressure 
Daily  
Aim 
3 
Glycemic 
control 
Time in target for CGM patients (70-180mg/dl)  
Daily 
• 
Clarity 
• 
EHR 
Time 100-180mg/dl for CGM patients  
Daily 
Time 140-180mg/dl for CGM patients  
Daily 
Time above range for CGM patients (>180mg/d & 
>250mg/dl)  
Daily 
Time in hypoglycemia for CGM patients (<70mg/dl & 
<55mg/dl) 
Daily 
Percent POC in target (70-180mg/dl) (matched 
controls) 
Daily 
Percent POC 100-180mg/dl (matched controls) 
Daily 
Percent POC 140-180mg/dl (matched controls) 
Daily 
Percent POC above range (>180mg/dl & >250mg/dl) 
(matched controls) 
Daily 
Percent POC in hypoglycemia (<70mg/dl & <55mg/dl) 
(matched controls) 
Daily 
Glucose standard deviation  
Daily 
Glucose coefficient of variation  
Daily 
Aim 
4  
Hospitalization 
outcomes and 
costs 
Length of stay [ICU, total stay] 
Discharge 
• 
EHR 
• 
Clarity 
download 
 
Cost of stay 
Discharge 
Discharge level of care [home, SNF] 
Discharge 
Morbidity 
Discharge 
Mortality 
Discharge 
Readmission rate [30 days] 
30d s/p discharge 
Cost of CGM vs. standard POC glucose monitoring 
materials.  
Discharge 
Table 3. Nurse Participant Schedule of Activities  
Aim  
Concept  
Variables 
Frequency 
Measure 
Aim 
2 
Nursing care 
delivery factors 
Evaluation of CGM support 
Once  
• 
Acceptability of Intervention Measure (AIM), 
Intervention Appropriateness Measure (IAM), 
and Feasibility of Intervention Measure (FIM) 
• 
CGM Satisfaction Questionnaire  
• 
Focus groups 
 
 
Data Management. All data will be labeled with unique identifiers for subject and study, date and time-stamped, 
and secured in locked filing cabinets in the project office, if hardcopy, on a server housed in a 24/7 offsite 
university-run networking facility, via web-based data capture, REDCap. To facilitate the HIPAA compliant remote 
monitoring of CGM data, dummy clinical Clarity accounts will be created for each device/patient. Android phone 
set-up requires entry of individual Dexcom Clarity account information on each phone.  

14
 
 
D. Data Analysis 
 
Descriptive statistics of central tendency (range, mean, median, and standard deviation) will describe variable 
characteristics and examine data distribution for normality and outliers. Descriptive statistics will summarize the 
sample characteristics and distribution of each variable. Data will be screened for normality, outliers, and 
homogeneity. Continuous variables with normal distribution will be reported as mean (standard deviation) while 
non-normal distribution will be reported as median (interquartile range). For RQ1, multivariate linear models will 
be used to evaluate clinical utility and implementation variables while examining the effects of patient condition 
(i.e., sequential organ failure assessment (SOFA) score, renal replacement, ventilator support, pH) as covaries. For 
RQ 2, For qualitative analysis of focus group data, a code book will be developed a priori based on the semi-
structured interview questions. Interview data, fieldnotes and memos were imported into NVivo 12.0 (Doncaster, 
Australia) for data management and analyzed using a qualitative descriptive approach.35,36 Two researchers (Faulds 
and McNett) will perform qualitative analysis. Portions of text will be coded with terms that were low inference 
(“data close”); then grouped into thematic categories and subthemes.35 For RQ3, hyperglycemic and hypoglycemic 
events will be identified for CGM and non-CGM users. Discrete CGM glucose values will be used to aggregate 
derived measures of glucose variability, including time in target (blood glucose value of 70-180mg/dl), time 100-
180mg/dl (representing a more conservative target used inpatient), time 140-180mg/dl (representing institutions IV 
insulin guideline glycemic target), time above target (>180mg/dl & >250mg/dl), time in hypoglycemia (<70mg/dl 
& <55mg/dl), glucose standard deviation, and coefficient of variation. Daily percent time in target as well as 
cumulative time in target will be assessed. Time in target will be derived from ADA glucose targets defining 
hypoglycemia as a blood glucose less than 70mg/dl and peak post-prandial glucose as <180mg/dl 37. The blood 
glucose range of 70-180mg/dl is consistent with other studies examining time in target.38-41 Measures of 
hypoglycemia will be in accordance with ADA recommendations for measurement at <70mg/dl and <55mg/dl 
which is a marker of severe hypoglycemia.42 Days with ≥70% CGM percent wear, as recommended by ADA, will 
be included in daily time in target analysis.42 For matched historical control patients, percent POC in target (70-
180mg/dl), 100-180mg/dl, 140-180mg/dl, percent POC >180mg/dl and percent POC >250mg/dl, percent POC 
<70mg/dl and percent POC <55mg/dl will be evaluated consistent with other recent studies.43,44 For CGM daily 
glycemic control (i.e., time in range [70-180mg/dl], time 100-180mg/dl, time 140-180mg/dl), linear mixed effect 
modeling (LMM) for repeated measures will be used to adjust for between subject and within subject variance. A 
3-tiered LMM will be used to control for patient, unit, and nurse specific variability. LMM will be repeated for 
analysis of daily POC glucose control for matched historical control patients for days with ≥3 POC fingersticks 
performed.  Two-sided significance level of 0.05 was used for all the statistical tests. For RQ4, the cost analysis for 
the proposed study will be conducted from the provider perspective. Cost estimation involves three major steps: (1) 
identify the relevant cost items; (2) measure the use of resources; and (3) place a value on the resources used. We 
will obtain estimated costs for proposed CGM implementation. Direct benefits and savings tend to fall into one of 
two categories: either savings from enhanced efficiency and productivity, or savings from outcomes improvement 
(e.g., reducing length of stay, lower 30 day readmissions). Costs that do not vary with the number of patients will 
be categorized as fixed costs, whereas those that vary by the number of patients will be defined as variable costs. 
The costs of the CGM implementation will be compared to costs under a control scenario. We will estimate the 
potential costs and cost savings resulting from the CGM implementation.  
IV. Regulatory and Safety Monitoring 
A. OSU Center for Clinical and Translational Science Regulatory Oversight.  
The OSU Center for Clinical and Translational Science (CCTS)-Regulatory Knowledge and Support Core assigned 
Data Safety Monitoring Board (DSMB) will oversee safety activity of the study. The DSMB will have expertise in 
either the scientific field of study, clinical trials, statistics, research ethics and/or epidemiology as is required of the 
study. The DSMB will review protocol-specific reports (Enrollment logs; device accountability logs; adverse event 
logs) created by the research team. These standard reports will include an overview of study objectives, a review of 
actual and projected accrual rates, an evaluation of patient demographics for balance of randomization, and a 
summary of the type, frequency, attribution, severity, seriousness and expectedness of adverse events. An interim 

15
 
 
analysis of study results may be performed and source documents void of any identifiers, may be reviewed to allow 
the DSMB to independently judge whether the overall integrity and conduct of the protocol remain acceptable. The 
DSMB will make recommendations to the Principal Investigator that could include actions of continuation, 
modification, suspension, or termination. 
In providing oversight for the conduct of this study, the DSMB will meet at a minimum of every 6 (six) months 
during the 2 (two) -year study to review all salient study information. Additional meetings may be scheduled as 
determined by the DSMB. The boundary for excess harm will equal  an observed excess harm which in the 
judgment of the DSMB, is excessive. All serious adverse events regardless of severity, attribution and/or 
expectedness will be reported to the DSMB  and the OSU Institutional Review Board(IRB) in accordance with 
their reporting guidelines. The DSMB recommended actions and all pertinent regulatory information will be 
forwarded to the Food and Drug Administration (FDA) appropriate Institutional Review Board(s), and Sponsor as 
appropriate. 
 
B. Medical Device Accountability 
The devices will be provided to OSU with permission to be used in this study by Dexcom LLC.  They are 
stored at OSU College of Nursing in a locked office dedicated to the study research team. Accountability of 
devices used will be maintained in a device accountability log that includes device identification (transmitter 
serial number, sensor serial number, android phone serial number), patient ID; date of initial CGM device 
placement, date of sensor replacement (if applicable), date range for use. Transmitter, sensor, and phone 
serial numbers will be linked to participant/patient in the study. Dummy clinical Clarity accounts will be 
created for each device/patient. Android phone set-up requires entry of individual Dexcom Clarity account 
information on each phone. The patient’s hospital identification label will be placed on the back of the 
Android phones once the device is placed to correctly match CGM device to the correct patient participant. 
CGM device orders from the manufacturer (Dexcom, LLC) will be tacked with date of receipt and shipping 
logs. Dexcom Expiration dates will be checked on initial receipt of items, monthly, prior to delivery to 
MICU, and prior to patient placement.  
 
C. Adverse Events and Serious Adverse Events 
 
Definition of Serious Adverse Events (SAE)  
All temporal medical events will be tracked by the study team. An adverse event (AE) or suspected adverse 
reaction is considered "serious" if, in the view of either the investigator or sponsor, it results in any of the following 
outcomes: death, a life-threatening adverse event, prolongation of existing hospitalization or transfer to a more 
acute care environment, a persistent or significant incapacity or substantial disruption of the ability to conduct 
normal life functions. Important medical events that may not result in death, be life-threatening, or prolong 
hospitalization may be considered serious when, based upon appropriate medical judgment, they may jeopardize 
the participant and may require medical intervention to prevent one of the outcomes listed in this definition.  
Severity of Event 
 
• 
Mild – Events require minimal or no treatment and do not interfere with the participant’s daily activities.  
• 
Moderate – Events result in a low level of inconvenience or concern with the therapeutic measures. 
Moderate events may cause some interference with functioning. 
• 
Severe – Events interrupt a participant’s usual daily activity and may require systemic drug therapy or 
other treatment. Severe events are usually potentially life-threatening or incapacitating.  Of note, the term 
“severe” does not necessarily equate to “serious”.] 
Relationship to Study CGM 
Potential adverse events (AEs) will be evaluated to determine their relationship to study intervention assessed by 
the clinician who examines and evaluates the participant based on temporal relationship and his/her clinical 

16
 
 
judgment. The degree of certainty about causality will be graded using the categories below. In a clinical trial, the 
study product must always be suspect.  
 
• 
Related – The AE is known to occur with the study intervention, there is a reasonable possibility that the 
study intervention caused the AE, or there is a temporal relationship between the study intervention and 
event. Reasonable possibility means that there is evidence to suggest a causal relationship between the 
study intervention and the AE. 
• 
Not Related – There is not a reasonable possibility that the administration of the study intervention caused 
the event, there is no temporal relationship between the study intervention and event onset, or an alternate 
etiology has been established. 
 
All AEs including local and systemic reactions not meeting the criteria for SAEs will be captured on the 
appropriate case report form (CRF). Information to be collected includes event description, time of onset, 
clinician’s assessment of severity, relationship to study product (assessed only by those with the training and 
authority to make a diagnosis), and time of resolution/stabilization of the event. All AEs occurring while on study 
must be documented appropriately regardless of relationship. All AEs will be followed to adequate resolution. 
 
Historically, few adverse events have been reported with Dexcom G6 CGM systems and have been isolated to mild 
skin irritation associated with the manufactures adhesive.45 
 
Any medical condition that is present at the time that the participant is screened will be considered as baseline and 
not reported as an AE. Participants are recruited from the MICU and are critically ill. Participants are not excluded 
based on the severity of critical illness and it is not uncommon for patients to deteriorate in the natural course of 
treatment or illness. If the study participant’s condition deteriorates for reasons related to the study intervention 
(e.g., hypoglycemia) at any time during the study, it will be recorded as an AE.  
 
Changes in the severity of an AE will be documented to allow an assessment of the duration of the event at each 
level of severity to be performed. AEs characterized as intermittent require documentation of onset and duration of 
each episode. 
Adverse Event Reporting  
Serious Adverse Event Reporting  
The study investigator shall complete an Unanticipated Adverse Device Effect Form and submit to the reviewing 
Institutional Review Board (IRB) and the manufacturer as soon as possible, but in no event later than 10 working 
days after the investigator first learns of the effect.  The study sponsor is responsible for conducting an evaluation 
of an unanticipated adverse device effect and shall report the results of such evaluation to the FDA and to all 
reviewing IRBs and participating investigators within 10 working days after the sponsor first receives notice of the 
effect. Thereafter, the sponsor shall submit such additional reports concerning the effect as FDA requests. 
D. Unanticipated Problems 
 
Definition of Unanticipated Problems (UP) 
This definition could include an unanticipated adverse device effect, any serious adverse effect on health or safety 
or any life-threatening problem or death caused by, or associated with, the CGM intervention, if that effect, 
problem, or death was not previously identified in nature, severity, or degree of incidence in the investigational 
plan or application (including a supplementary plan or application), or any other unanticipated serious problem 
associated with a device that relates to the rights, safety, or welfare of subjects (21 CFR 812.3(s)).] 

17
 
 
Unanticipated Problem Reporting  
The investigator will report unanticipated problems (UPs) to the reviewing Institutional Review Board (IRB) and 
to the Data Coordinating Center (DCC)/lead principal investigator (PI). The UP report will include the following 
information: 
 
An investigator shall submit to the sponsor and to the reviewing IRB a report of any unanticipated adverse device 
effect occurring during an investigation as soon as possible, but in no event later than 10 working days after the 
investigator first learns of the effect (21 CFR 812.150(a)(1)), A sponsor who conducts an evaluation of an 
unanticipated adverse device effect under 812.46(b) shall report the results of such evaluation to the FDA and to all 
reviewing IRB's and participating investigators within 10 working days after the sponsor first receives notice of the 
effect. Thereafter the sponsor shall submit such additional reports concerning the effect as FDA requests (21 CFR 
812.150(b)(1)).    
 
E. Study and individual participant stopping criteria:  
 
We plan to enroll participants in waves of 20 with ongoing analysis between waves. We plan to stop the study for 
the following conditions in consultation with the data safety monitoring board assigned to oversee safety activities 
and the study:  
• 
Failure to meet initial validation criteria within 24 hours in 20% of participants 
• 
CGM-meter pairs obtained during routine monitoring  following initial validation without a change in 
clinical status prompting hourly monitoring meeting the following criteria: 
o Failure to detect clinically significant hypoglycemia ( 2 episodes):  CGM value >100 mg/dl with 
no Urgent Low Soon alert while POC BG <70 mg/dl 
o Failure to detect severe hyperglycemia ( 2 episodes):  CGM value <180 mg/dl when POC 
BG >400 mg/dl 
o Inappropriate treatment ( 2 episodes):  CGM value triggers the opposite action than the POC BG 
value (CGM >180 mg/dl while POC BG <70 mg/dl or vice versa). 
• 
 2 episodes of inappropriate insulin dose resulting in clinically significant hypoglycemia (glucose 
<55mg/dl) after initial sensor validation  
• 
 2 episodes of iatrogenic DKA (pH <7.3 or serum bicarbonate <15 mEq/L in the setting of elevated 
ketones) or hyperosmolar nonketotic state (osmolality 320mOsm/kg with BG >600mg/dl and pH >7.3 or 
serum bicarbonate >15 mEq/L)  
• 
 2 episodes severe adverse events resulting in prolonged hospitalization, or other life-threatening 
complication that are attributed to the study intervention 
• 
Any severe adverse event resulting in death, or other life-threatening complication that is attributed to the 
study intervention  
• 
Any severe adverse event resulting in prolonged hospitalization, or other life-threatening complication that 
attributed to the study intervention and is expected to recur 
 
Patient participation in the study will stop if any of the following occur:  
• 
Failed sensor validation x 2 sensors (48 hours) 
• 
Transitioned to hospice care 
• 
Patient participant or patient’s legally authorized representative withdraw consent  
 
 
 
 

18
 
 
Appendix A. Device label  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
CAUTION Investigational Device. Limited by United States Federal law to investigational 
use 
Dexcom G6 Continuous Glucose Monitoring System (CGM) 
Manufacturer: Dexcom LLC, 6340 Sequence Drive 
San Diego, CA 92121, USA 
Package contains: 1 sensor, 1 transmitter, 1 android phone 
 
Dexcom G6 CGM may fail to adequately detect high (hyperglycemia) or low (hypoglycemia) glucoses which could 
result in adverse events including death. High dose acetaminophen (>1 gram Q6 hours) or treatment with 
hydroxyurea may interfere with device accuracy. May not be worn during magnetic resonance imaging (MRI), 
computerized tomography (CT) radiographic procedures, or diathermy. 

19
 
 
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Faulds ER, Jones L, McNett M, et al. Facilitators and Barriers to Nursing Implementation of 
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3. 
Faulds ER, Boutsicaris A, Sumner L, et al. Use of Continuous Glucose Monitor in Critically Ill 
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Monitoring in Non-Critically Ill Hospitalized Patients With Diabetes. Diabetes Care 2021;44:1641-6. 
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Boom DT, Sechterberger MK, Rijkenberg S, et al. Insulin treatment guided by subcutaneous 
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a randomized controlled trial. Crit Care 2014;18:453. 
14. 
De Block CE, Gios J, Verheyen N, et al. Randomized Evaluation of Glycemic Control in the 
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Diabetes Technol Ther 2015;17:889-98. 
15. 
Kosiborod M, Gottlieb RK, Sekella JA, et al. Performance of the Medtronic Sentrino continuous 
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