Effect of Continuous Glucose Monitoring on Hypoglycemia in Older Adults With Type 1 Diabetes: A Randomized Clinical Trial | Diabetes | JAMA | JAMA Network
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Visual Abstract. Continuous Glucose Monitoring and Hypoglycemia in Older Adults With Type 1 Diabetes
Continuous Glucose Monitoring and Hypoglycemia in Older Adults With Type 1 Diabetes
Figure 1.  Flow of Participants in the Wireless Innovation for Seniors With Diabetes Mellitus (WISDM) Study
Flow of Participants in the Wireless Innovation for Seniors With Diabetes Mellitus (WISDM) Study

Enrollment took place from September 2017 to May 2018, and study follow-up for the randomized trial continued through December 2018. BGM indicates blood glucose monitoring; CGM, continuous glucose monitoring.

aInformation on patients screened but not enrolled was not collected.

bOne patient was excluded for having both a history of at least 1 severe hypoglycemia event in the past 6 months and spending more than 10% of time with CGM glucose levels less than 54 mg/dL during the blinded prerandomization phase.

cTwo participants in the standard BGM group initiated real-time CGM before completing the 26-week visit.

dOne participant in the CGM group and 6 participants in the standard BGM group were missing CGM data at follow-up. Missing data were handled using direct likelihood. Baseline data for these participants were included in the model.

Figure 2.  Percentage of Time Spent With Less Than 70 mg/dL by Study Visit and Time of Day
Percentage of Time Spent With Less Than 70 mg/dL by Study Visit and Time of Day

To convert glucose values to millimoles per liter, multiply by 0.0555. A, By study visit: tops and bottoms of boxes indicate 25th and 75th percentiles; lines, medians; solid cirles, means; whiskers, minimums and maximums after removing outliers; and open circles, outliers. B, By time of day: thinner lines indicate 25th and 75th percentiles and thicker lines, medians. Participants with follow-up continuous glucose monitoring data had a minimum of 48 readings and maximum of 420 readings used to calculate percentage of time spent with glucose levels less than 70 mg/dL for each hour of the day.

Table 1.  Baseline Characteristics of Study Participants
Baseline Characteristics of Study Participants
Table 2.  Glycemic Outcomes
Glycemic Outcomes
Table 3.  Safety Outcomes: Severe Hypoglycemia and Other Adverse Events
Safety Outcomes: Severe Hypoglycemia and Other Adverse Events
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Original Investigation
June 16, 2020

Effect of Continuous Glucose Monitoring on Hypoglycemia in Older Adults With Type 1 Diabetes: A Randomized Clinical Trial

Author Affiliations
  • 1AdventHealth Translational Research Institute, Orlando, Florida
  • 2Jaeb Center for Health Research, Tampa, Florida
  • 3Rodebaugh Diabetes Center, University of Pennsylvania Perelman School of Medicine, Philadelphia
  • 4Oregon Health and Science University, Portland
  • 5Feinberg School of Medicine, Northwestern University, Chicago, Illinois
  • 6Iowa Diabetes and Endocrinology Research Center, Des Moines
  • 7Atlanta Diabetes Associates, Atlanta, Georgia
  • 8Park Nicollet International Diabetes Center, Minneapolis, Minnesota
  • 9Elson S. Floyd College of Medicine, Washington State University, Spokane
  • 10University of South California, School of Pharmacy, Los Angeles
  • 11Naomi Berri Diabetes Center, Columbia University, New York, New York
  • 12University of Washington, Seattle
  • 13Henry Ford Health System, Detroit, Michigan
  • 14Mayo Clinic, Rochester, Minnesota
  • 15Icahn School of Medicine at Mount Sinai, New York, New York
  • 16Washington University School of Medicine in St Louis, St Louis, Missouri
  • 17Keck School of Medicine, University of Southern California, Los Angeles
  • 18University of Chicago, Chicago, Illinois
  • 19Scripps Whittier Diabetes Institute, La Jolla, California
  • 20University of Michigan, Ann Arbor
  • 21Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora
  • 22University of Massachusetts Medical School, Worcester
  • 23University of Miami, Miami, Florida
  • 24SUNY Upstate Medical University, Syracuse, New York
  • 25University of North Carolina at Chapel Hill, Chapel Hill
JAMA. 2020;323(23):2397-2406. doi:10.1001/jama.2020.6928
Visual Abstract. Continuous Glucose Monitoring and Hypoglycemia in Older Adults With Type 1 Diabetes
Continuous Glucose Monitoring and Hypoglycemia in Older Adults With Type 1 Diabetes
Key Points

Question  Is continuous glucose monitoring effective in reducing hypoglycemia compared with standard blood glucose monitoring in older adults with type 1 diabetes?

Findings  In this randomized clinical trial that included 203 adults aged 60 years or older with type 1 diabetes, treatment for 6 months with continuous glucose monitoring compared with standard blood glucose monitoring resulted in a significantly lower percentage of glucose values less than 70 mg/dL (adjusted difference, 1.9%).

Meaning  Among older adults with type 1 diabetes, continuous glucose monitoring resulted in a small but statistically significant improvement in hypoglycemia over 6 months.

Abstract

Importance  Continuous glucose monitoring (CGM) provides real-time assessment of glucose levels and may be beneficial in reducing hypoglycemia in older adults with type 1 diabetes.

Objective  To determine whether CGM is effective in reducing hypoglycemia compared with standard blood glucose monitoring (BGM) in older adults with type 1 diabetes.

Design, Setting, and Participants  Randomized clinical trial conducted at 22 endocrinology practices in the United States among 203 adults at least 60 years of age with type 1 diabetes.

Interventions  Participants were randomly assigned in a 1:1 ratio to use CGM (n = 103) or standard BGM (n = 100).

Main Outcomes and Measures  The primary outcome was CGM-measured percentage of time that sensor glucose values were less than 70 mg/dL during 6 months of follow-up. There were 31 prespecified secondary outcomes, including additional CGM metrics for hypoglycemia, hyperglycemia, and glucose control; hemoglobin A1c (HbA1c); and cognition and patient-reported outcomes, with adjustment for multiple comparisons to control for false-discovery rate.

Results  Of the 203 participants (median age, 68 [interquartile range {IQR}, 65-71] years; median type 1 diabetes duration, 36 [IQR, 25-48] years; 52% female; 53% insulin pump use; mean HbA1c, 7.5% [SD, 0.9%]), 83% used CGM at least 6 days per week during month 6. Median time with glucose levels less than 70 mg/dL was 5.1% (73 minutes per day) at baseline and 2.7% (39 minutes per day) during follow-up in the CGM group vs 4.7% (68 minutes per day) and 4.9% (70 minutes per day), respectively, in the standard BGM group (adjusted treatment difference, −1.9% (−27 minutes per day); 95% CI, −2.8% to −1.1% [−40 to −16 minutes per day]; P <.001). Of the 31 prespecified secondary end points, there were statistically significant differences for all 9 CGM metrics, 6 of 7 HbA1c outcomes, and none of the 15 cognitive and patient-reported outcomes. Mean HbA1c decreased in the CGM group compared with the standard BGM group (adjusted group difference, −0.3%; 95% CI, −0.4% to −0.1%; P <.001). The most commonly reported adverse events using CGM and standard BGM, respectively, were severe hypoglycemia (1 and 10), fractures (5 and 1), falls (4 and 3), and emergency department visits (6 and 8).

Conclusions and Relevance  Among adults aged 60 years or older with type 1 diabetes, continuous glucose monitoring compared with standard blood glucose monitoring resulted in a small but statistically significant improvement in hypoglycemia over 6 months. Further research is needed to understand the long-term clinical benefit.

Trial Registration  ClinicalTrials.gov Identifier: NCT03240432

Introduction

Quiz Ref IDThe population of older adults with type 1 diabetes is increasing because of advancements in diabetes care leading to longer life expectancy.1 Older adults, particularly those with long-standing type 1 diabetes, are prone to hypoglycemia and hypoglycemia unawareness. In addition to acute changes in mental status, severe hypoglycemia can cause seizures, falls leading to fractures, cognitive impairment, and cardiac arrhythmias resulting in sudden death.2,3 Consequently, treatment guidelines for older adults with type 1 diabetes emphasize minimizing hypoglycemia by having glucose levels less than 70 mg/dL less than 1% of the time, and allow for less stringent hemoglobin A1c (HbA1c) targets.4 Despite this, severe hypoglycemia remains a common complication.5

Quiz Ref IDContinuous glucose monitoring (CGM) measures interstitial glucose concentrations, allowing for near real-time assessment of glucose levels and trends. Continuous glucose monitors can provide alerts when glucose levels exceed low or high thresholds or are changing rapidly, allowing patients to adjust insulin dosing or consume carbohydrates to minimize the risk of hypoglycemia. The US Food and Drug Administration now allows certain continuous glucose monitors to be used in place of standard capillary blood glucose monitoring (BGM) for diabetes treatment decisions.6 Several randomized trials have demonstrated the efficacy of CGM in adults with type 1 diabetes.7-10 However, none have included a substantial number of older individuals,7,11-14 and most have excluded patients with recent severe hypoglycemia or hypoglycemia unawareness. Thus, the benefits of CGM found in prior studies cannot be generalized to older adults with type 1 diabetes, who are at high risk of hypoglycemia and its complications. This trial was conducted with the primary goal of assessing whether CGM was effective in reducing hypoglycemia compared with standard BGM in older adults with type 1 diabetes.

Methods
Trial Design and Oversight

This randomized clinical trial was conducted at 22 endocrinology practices in the United States. The protocol and informed consent forms were approved by institutional review boards. Written informed consent was obtained from each participant prior to enrollment. An independent data and safety monitoring board provided trial oversight reviewing unmasked safety data during the conduct of the study. The final protocol and statistical analysis plan are available in Supplement 1.

Participants

Quiz Ref IDMajor eligibility criteria included a clinical diagnosis of type 1 diabetes, age of at least 60 years, no use of real-time CGM in the 3 months prior to enrollment, and an HbA1c of less than 10.0%. Participants were required to be using either an insulin pump or multiple daily insulin injections, and an enrollment target was set to include at least 40% of participants using each mode of insulin delivery. A complete list of the inclusion and exclusion criteria is available in eTable 1 in Supplement 2.

Each participant completed a 2-week prerandomization period using a masked CGM on which sensor glucose concentrations were not visible to participants. To be eligible for randomization, participants were required to have at least 10 of 14 days (240 hours) of data available with an average of at least 1.8 calibrations per day using the study-provided blood glucose meter (Bayer Contour Next USB; Ascensia Diabetes Care).

Intervention and Procedures

Eligible participants were randomly assigned in a 1:1 ratio via a computer-generated sequence to use of CGM (Dexcom G5, Dexcom) with a study blood glucose meter as needed or to use the study blood glucose meter without CGM, using a permuted block design (block sizes of 2 and 4), stratified by site.

Participants in both groups were provided general diabetes management education, and clinicians were encouraged to review downloaded glucose data at each visit to inform treatment recommendations at their discretion. The standard BGM group was asked to perform home BGM at least 4 times daily. The CGM group was instructed to use the continuous glucose monitor daily, to calibrate the monitor twice daily, and to set the low alert (recommended to be set at 70 mg/dL). The continuous glucose monitor includes an urgent low alert at 55 mg/dL that cannot be turned off. General guidelines were provided to participants about using CGM. Additional instructions were provided on using CGM trend arrows to adjust insulin dosing based on guidelines specific to an at-risk older adult population (eAppendix in Supplement 2).15

Both groups had clinic visits 4, 8, 16, and 26 weeks following randomization. In addition, the standard BGM group was seen in clinic at weeks 7, 15, and 25 for placement of a masked CGM (same algorithm as the CGM group’s real-time CGM), which was worn for 1 week.

Hemoglobin A1c was measured at randomization, 16 weeks, and 26 weeks at the University of Minnesota using the Tosoh A1c 2.2 Plus Glycohemoglobin Analyzer. Participants completed patient-reported outcome and cognitive assessments at the randomization and 26-week clinic visits.

Data Collection and Outcomes

Participant sociodemographic data, including fixed categories for race/ethnicity, were collected from medical records and confirmed by participants to better describe the study cohort and to address generalizability.

The primary outcome was CGM-measured percentage of time spent with a glucose value less than 70 mg/dL during follow-up using data pooled from approximately 7 days prior to the 8, 16, and 26-week visits. (To convert glucose values to millimoles per liter, multiply by 0.0555.) Prespecified secondary hypoglycemia outcomes included percentage of time with a glucose value less than 54 mg/dL, percentage of time with a glucose value less than 60 mg/dL, and rate of hypoglycemia events per week (with an event defined as 15 consecutive minutes with a sensor glucose value <54 mg/dL). Prespecified secondary hyperglycemia outcomes included percentages of time with glucose values greater than 180 mg/dL, greater than 250 mg/dL, and greater than 300 mg/dL. Prespecified glycemic control outcomes included percentage of time with glucose values in the range of 70 to 180 mg/dL, mean glucose, and glycemic variability (coefficient of variation, defined as ratio of the standard deviation to the mean). Prespecified secondary HbA1c outcomes included mean change from baseline, percentage with HbA1c less than 7.0%, percentage with HbA1c less than 7.5%, percentage with relative reduction in HbA1c of at least 10%, percentage with absolute reduction in HbA1c of at least 0.5%, percentage with absolute reduction in HbA1c of at least 1%, and percentage with absolute reduction in HbA1c of at least 0.5% or HbA1c less than 7.0%.

Additional prespecified secondary participant-reported outcomes included general quality of life (PROMIS Global Health Short Form; National Institutes of Health [NIH] Toolbox [http://www.nihtoolbox.org] Emotion Battery), hypoglycemia awareness (Clarke Survey16), hypoglycemia fear (Hypoglycemia Fear Survey II–Worry subscale17), and diabetes distress (Type 1 Diabetes Distress Scale18). Descriptions of these outcomes, scoring, and clinically relevant change (when known) are shown in eTable 2 in Supplement 2. Cognitive performance also was assessed at baseline and 26 weeks using the NIH Toolbox Cognition Battery; specifics on this measure and training of study personnel are also described in eTable 2.

Reportable adverse events included severe hypoglycemia (defined as an event that required assistance from another person because of altered consciousness), hyperglycemia resulting in treatment at a health care facility or that involved diabetic ketoacidosis (as defined by the Diabetes Control and Complications Trial19), device-related events with potential effect on participant safety, falls, fractures, emergency department visits, and all serious adverse events regardless of causality.

Statistical Analysis

A sample size of 200 participants was determined to have at least 90% power to detect a reduction in percentage of time spent with a glucose value less than 70 mg/dL for the overall cohort and a minimum of 80% power for an a priori subgroup analysis by insulin delivery method, assuming a population relative treatment reduction of 50% from a percentage of time spent with a glucose value less than 70 mg/dL of 6%, a standard deviation of 5%, a type I error rate (2-sided) of 5%, and 10% missing follow-up data.

Participants were analyzed according to their randomization group, and all participants were included in the primary analysis. For the primary analysis, the difference in percentage of time spent with a glucose value less than 70 mg/dL at follow-up between the 2 treatment groups was assessed in a longitudinal linear regression model including baseline and follow-up data and clinical center as a random effect. Missing data were handled by direct likelihood, which maximizes the likelihood function integrated over possible values of the missing data.20 The analyses for the secondary continuous outcomes paralleled those for the primary outcome. Binary HbA1c outcomes were compared between treatment groups using available cases only in a logistic regression model adjusting for baseline HbA1c and clinical center as a random effect.

Modification of the treatment effect by baseline variables was assessed by including an interaction term in the primary model. Sensitivity analyses were performed as described in the statistical analysis plan (adjustment for potential confounding of baseline imbalances and including only participants meeting per-protocol criteria) (Supplement 1).

Analysis of all outcomes was repeated separately among insulin pump and injection users and paralleled the overall analysis described above. Additional analyses also were performed for data collected through 16 weeks and data collected separately during daytime (6:00 am to 11:59 pm) and nighttime (12:00 am to 5:59 am) hours for CGM outcomes.

For all secondary analyses, 2-sided P values and 95% confidence intervals were adjusted for multiple comparisons to control the false-discovery rate using the adaptive Benjamini-Hochberg procedure21 (eTable 3 in Supplement 2). Analyses were conducted with SAS software version 9.4 (SAS Institute Inc).

Results

Between October 2017 and June 2018, 203 participants were randomly assigned to the CGM group (n = 103) or the standard BGM group (n = 100). Sixteen patients who provided consent and were screened for the study did not proceed into the randomized clinical trial (Figure 1). Participant characteristics overall and according to randomization group are shown in Table 1 and additionally stratified by insulin delivery method in eTable 4 in Supplement 2. Participant comorbidities and medications are reported in eTables 5 and 6 and in Supplement 2, respectively.

The 26-week visit was completed by 102 participants in the CGM group (99%) and by 96 participants in the standard BGM group (96%) (Figure 1 and eFigure 1 in Supplement 2). Unscheduled visits and contacts are reported in eTable 7 in Supplement 2.

In the CGM group, CGM use was high throughout the study (eTable 8 in Supplement 2). In the 4 weeks prior to the 26-week visit, 81% were wearing the device 7 days per week and 89% 5 or more days per week; 6% had zero use, which included 1 participant who had dropped out. Use of CGM was similar between those who used a pump and those who used injections for insulin delivery (eTable 9 in Supplement 2). Two participants in the standard BGM group initiated real-time CGM use during the trial.

Blood glucose self-monitoring, measured as the median of individuals’ mean number of tests per day, was 5.0 (interquartile range [IQR], 4.0-6.0) in the CGM group and 4.0 (IQR, 3.0-5.5) in the standard BGM group during the baseline period of blinded CGM wear, and was 3.5 (IQR, 2.8-4.5) and 4.3 (IQR, 3.8-5.0), respectively, during follow-up.

Glycemic Control Outcomes

Quiz Ref IDIn the primary analysis, median percentage of time with glucose levels less than 70 mg/dL decreased from 5.1% (73 minutes per day) at baseline to 2.7% (39 minutes per day) during the 6 months of follow-up for the CGM group and remained relatively unchanged from 4.7% (68 minutes per day) at baseline to 4.9% (70 minutes per day) during follow-up for the standard BGM group, for an adjusted treatment group difference of −1.9% (95% CI, −2.8% to −1.1%; P <.001), corresponding to a significant reduction in hypoglycemia of 27 minutes per day (95% CI, −40 to −16 minutes per day; P <.001) (Table 2 and eTable 10 and eFigure 2 in Supplement 2). Results were similar for other CGM hypoglycemia metrics (Table 2 and eTable 10). The significant treatment effect was evident in the first month and remained consistent over 6 months (Figure 2A and eTable 11 in Supplement 2). Results were similar in a sensitivity analyses that adjusted for characteristics with some imbalance at baseline (duration of diabetes, sex, education, severe hypoglycemia in the 12 months prior to the study, and functional activity [questionnaire score]) and in a per-protocol sensitivity analysis (eTable 12 in Supplement 2). A significant benefit of CGM in reducing time with glucose levels less than 70 mg/dL was observed both during daytime and overnight (Figure 2B and eTable 13 in Supplement 2) and was present for both insulin pump and injection users (eTables 14 and 15 in Supplement 2). The treatment effect was significantly greater in participants with higher levels of baseline time with glucose levels less than 70 mg/dL, with a higher coefficient of variation, and with presence of a detectable C-peptide level (P <.001 for interaction for each). There was no significant interaction of the treatment effect on time with glucose levels less than 70 mg/dL with respect to other baseline characteristics, including age (<70 vs ≥70 years), socioeconomic status, presence of cognitive impairment, or HbA1c value (eTable 16 in Supplement 2).

Quiz Ref IDIn addition to the reduction in hypoglycemia with CGM, significant treatment group differences were observed for hyperglycemia (glucose levels >180 mg/dL, >250 mg/dL, and >300 mg/dL), mean glucose concentration, and glycemic variability (Table 2 and eTable 10 in Supplement 2). Time spent in the target range of 70 to 180 mg/dL was 8.8% (2.1 hours per day) higher in the CGM group compared with the standard BGM group (95% CI, 6.0%-11.5% [1.4-2.8 hours per day]; P <.001) (Table 2 and eTable 10). Mean HbA1c was 7.6% (SD, 0.9%) at baseline and 7.2% (SD, 0.9%) at 26 weeks in the CGM group and 7.5% (SD, 0.8%) and 7.4% (SD, 0.9%), respectively, in the standard BGM group (adjusted group difference, −0.3%; 95% CI, 0.4% to −0.1%; P <.001) (Table 2). Additional HbA1c metrics are shown in eTable 17 in Supplement 2.

Severe Hypoglycemia and Other Adverse Events

One participant in the CGM group and 10 participants in the standard BGM group experienced a severe hypoglycemia event during the 6 months of follow-up (Table 3). Five of the 10 participants (50%) in the standard BGM group had an event that involved seizure or loss of consciousness, which did not occur in the 1 CGM participant.

One episode of diabetic ketoacidosis occurred during the study in a participant in the CGM group, unrelated to use of CGM (Table 3). There were no statistically significant treatment group differences in fractures, falls, hospitalizations, or emergency department visits.

There were 22 CGM device issues reported over the 26-week follow-up (eTable 18 in Supplement 2), none of which were related to an adverse event.

Patient-Reported Outcomes and Cognitive Assessments

No significant treatment group differences were observed at 26 weeks for any of the participant-reported questionnaires or cognitive assessments, including measures of hypoglycemia awareness, diabetes-specific quality of life (hypoglycemia fear, diabetes distress, and glucose monitoring satisfaction), general quality of life, and cognition (eTable 19 in Supplement 2).

Discussion

Among adults aged 60 years or older with type 1 diabetes, use of CGM resulted in a small but statistically significant reduction in time spent with hypoglycemia (glucose level less than 70 mg/dL) compared with periodic finger-stick monitoring using standard BGM. A similar degree of hypoglycemia reduction was seen in those using insulin pump therapy and those using multidose insulin injection therapy. Results were consistent across the age range of 60 to 86 years, across the baseline HbA1c range of 5.6% to 10.8%, among those with and without cognitive impairment, and at all education levels. The higher the amount of baseline hypoglycemia and glycemic variability, risk factors for severe hypoglycemia in older adults with type 1 diabetes,22 the greater the treatment effect. In this study, the risk of a severe hypoglycemia event was significantly reduced with use of CGM, but the majority of participants using CGM did not achieve the less-than-1% target for time with a glucose level less than 70 mg/dL recommended for older adults.23

Reducing time with a glucose level less than 70 mg/dL is important, as it has been associated with risk of a subsequent severe hypoglycemia event, demonstrating the potential for clinical importance.4,8 However, further research of longer duration and with clinical outcomes is needed before reaching any conclusions about the clinical value of these findings.

Despite improvements in various measures of hypoglycemia and glycemic control and the high degree of CGM use after 6 months, there were no significant treatment group differences in patient-reported outcomes, including fear of hypoglycemia and diabetes distress. One possible explanation is that the baseline scores on these measures were quite low, indicating already good adjustment to managing diabetes.

The findings in this trial are consistent with a subgroup analysis of the participants in the DIAMOND study, who were aged 60 years or older, with respect to the high degree of CGM use after 6 months and the benefit of CGM on reducing hyperglycemia and HbA1c; however, the DIAMOND cohort had too little baseline hypoglycemia for a meaningful assessment of the effect of CGM on hypoglycemia.9,14

The strengths of this study include random treatment assignment, high participant retention rate, high degree of CGM use by the CGM group, and only 2 treatment crossovers by the standard BGM group. Although treatment group assignment could not be masked, the amount of contact with participants was similar between groups.

Limitations

This study has several limitations. First, the study cohort had relatively high socioeconomic status and consisted of individuals receiving specialized diabetes care. On average, baseline glycemic control was good and the amount of biochemical hypoglycemia was modest. Median age at diagnosis was 30 years, but the treatment effect appeared similar irrespective of age at diagnosis. Second, there was a relatively short intervention period of 6 months. This study included an extension phase during which the CGM group continued using CGM through 12 months and the standard BGM group initiated CGM. Results of the extension phase may provide insight into longer-term use of CGM. Third, the study intervention used an older version of the CGM sensor than what is now commercially available. It is unknown whether the additional features of the newer CGM sensor (such as no calibration requirement, easier insertion process, and a predictive low glucose alert) would have further increased CGM use in this population. Fourth, the study intervention also did not include a system that suspends insulin delivery from a pump when hypoglycemia is predicted based on the CGM glucose readings. Such a system for pump users might have an even greater effect on reducing hypoglycemia than was seen in this study.24,25 Fifth, by chance, the CGM group had a higher frequency of severe hypoglycemia events in the year prior to the study than the standard BGM group; adjusting for this factor did not alter the result.

Conclusions

Among adults aged 60 years or older with type 1 diabetes, CGM compared with standard BGM resulted in a small but statistically significant improvement in hypoglycemia over 6 months. Further research is needed to understand the long-term clinical benefit.

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Article Information

Corresponding Author: Richard E. Pratley, MD, AdventHealth Translational Research Institute, 301 E Princeton St, Orlando, FL 32789 (richard.pratley.md@adventhealth.com).

Accepted for Publication: April 16, 2020.

Author Contributions: Dr Miller had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Pratley, Rickels, Ahmann, Aleppo, Beck, Carlson, Chaytor, Fox, Goland, Hirsch, Kruger, Kudva, Peters, Pop-Busui, Shah, Verdejo, Miller.

Acquisition, analysis, or interpretation of data: Pratley, Kanapka, Rickels, Ahmann, Aleppo, Bhargava, Bode, Carlson, Chaytor, Fox, Goland, Hirsch, Kruger, Kudva, Levy, McGill, Peters, Philipson, Philis-Tsimikas, Pop-Busui, Shah, Thompson, Vendrame, Weinstock, Miller.

Drafting of the manuscript: Pratley, Kanapka, Rickels, Carlson, Kudva, Peters, Philis-Tsimikas, Thompson, Miller.

Critical revision of the manuscript for important intellectual content: Pratley, Kanapka, Rickels, Ahmann, Aleppo, Beck, Bhargava, Bode, Carlson, Chaytor, Fox, Goland, Hirsch, Kruger, Kudva, Levy, McGill, Peters, Philipson, Philis-Tsimikas, Pop-Busui, Shah, Vendrame, Verdejo, Weinstock.

Statistical analysis: Kanapka, Fox.

Obtained funding: Pratley, Miller.

Administrative, technical, or material support: Rickels, Beck, Bode, Carlson, Chaytor, Goland, Philipson, Vendrame, Verdejo, Miller.

Supervision: Pratley, Rickels, Ahmann, Aleppo, Beck, Carlson, Chaytor, Goland, Hirsch, Kudva, Levy, Peters, Philipson, Vendrame, Weinstock, Miller.

Conflict of Interest Disclosures: Dr Pratley reported lecture and/or consultancy fees and/or grants paid to his institution, AdventHealth, from AstraZeneca, Boehringer Ingelheim, Eisai Inc, GlaxoSmithKline, Glytec LLC, Janssen, Lexicon Pharmaceuticals, Ligand Pharmaceuticals Inc, Lilly, Merck, Mundipharma, Novo Nordisk, Pfizer, Sanofi, and Takeda; receipt of grants from Lexicon Pharmaceuticals, Ligand Pharmaceuticals Inc, Lilly, Merck, Novo Nordisk, Sanofi, and Takeda; and receipt of personal fees from Sanofi US Services Inc. Dr Rickels reported receipt of personal fees from Hua Medicine, Xeris Pharmaceuticals, Semma Therapeutics, and Sernova; grants from Xeris Pharmaceuticals; and nonfinancial support from Merck & Co. Dr Ahmann reported contract research payments to his institution from Dexcom and receipt of personal fees from Medtronic. Dr Aleppo reported receipt of grants from Novo Nordisk, Dexcom, AstraZeneca, and Lilly and personal fees from Dexcom, Medtronic, Insulet, and Novo Nordisk. Dr Beck reported consulting fees paint to his institution from Bigfoot Biomedical, Tandem Diabetes Care, Insulet, and Lilly and receipt of grants from Dexcom and Tandem Diabetes Care and nonfinancial support from Dexcom, Tandem Diabetes Care, Roche, and Ascensia. Dr Bhargava reported receipt of grants from Sanofi, AstraZeneca, Lilly, United BioSource Corporation, Dexcom, Teijin America Inc, Bayer Healthcare Pharmaceuticals, Boehringer Ingelheim, Bristol-Meyers Squibb Research and Development, Gan & Lee Pharmaceutical, the Jaeb Center for Health Research, KOWA Research Institute Inc, Medtronic MiniMed, Mylan GmbH, Novo Nordisk, AstraZeneca, Lilly, and Theracos Sub LLC; speaker fees from Sanofi, AstraZeneca, and Lilly; and consultant fees from Sanofi. Dr Carlson reported receipt of grants from Novo Nordisk, Medtronic, Insulet, Sanofi, Dexcom, Abbott, Lilly, and UnitedHealth; he reports contracts as a research investigator and/or consultant through his employer, HealthPartners Institute/International Diabetes Center at Park Nicollet (with no personal income received), with Novo Nordisk, Medtronic, Insulet, Sanofi, Abbott, Sensionics, and Lilly; in addition, Dr Carlson has a patent to US Provisional Patent Application Serial No. 62/443 004 pending. Dr Chaytor reported receipt of personal fees from Lilly. Dr Kruger reported receipt of grants and personal fees from Dexcom. Dr Levy reported receipt of nonfinancial support from Dexcom. Dr McGill reported receipt of personal fees from Aegerion, Bayer, Boehringer Ingelheim, Gilead, Lilly, Metavant, Valeritas, Janssen, Mannkind, the Endocrine Society, the American Association of Clinical Endocrinologists, Culinary Medicine, Novo Nordisk, and Dexcom; grants from Novo Nordisk, Dexcom, Medtronic, Novartis, AstraZeneca, and the NIH; and nonfinancial support from Bayer, Boehringer Ingelheim, the American Association of Clinical Endocrinologists, Mannkind, Culinary Medicine, and the Jaeb Center for Health Research. Dr Peters reported receipt of personal fees from Medscape, Sanofi, Lexicon, Becton Dickinson, Abbot Diabetes Care, Bigfoot, Mannkind, Novo Nordisk, Lilly, and Boehringer Ingelheim; grants from AstraZeneca, vTv Therapeutics, Mannkind, and Dexcom; and stock options for Mellitus Health, Omada Health, Stability Health, Pendulum Therapeutics, and Livongo. Dr Shah reported receipt of consulting fees through the University of Colorado from Dexcom and grants from vTv therapeutics, Novo Nordisk, Mylan GmbH, Sanofi US Services Inc, Insulet, and the NIH. Dr Weinstock reported receipt of grants from the Juvenile Diabetes Research Foundation, Insulet Corporation, Tolerion Inc, Lilly, Medtronic, Diasome Pharmaceuticals, Boehringer Ingelheim, Oramed Ltd, and Mylan GmbH and personal fees from Insulogic. Dr Miller reported receipt of nonfinancial support from Dexcom and Tandem. No other disclosures were reported.

Funding/Support: This study was funded by JDRF and the Leona M. and Harry B. Helmsley Charitable Trust by a grant provided to the Jaeb Center for Health Research. The National Center for Research Resources and the National Center for Advancing Translational Sciences of the NIH (grant UL1TR001878) support the Center for Human Phenomic Science at the University of Pennsylvania. Dexcom provided study CGM devices and sensors.

Role of the Funders/Sponsors: JDRF, the Leona M. and Harry B. Helmsley Charitable Trust, and Dexcom were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; or in writing the original manuscript draft or revision of the manuscript. JDRF, the Leona M. and Harry B. Helmsley Charitable Trust, and Dexcom were sent the manuscript for review, but any revisions made based on their comments were at the discretion of the authors, and permission for submitting content to the journal was not required. There was no approval of JDRF, the Leona M. and Harry B. Helmsley Charitable Trust, or Dexcom required or obtained for manuscript submission.

WISDM Study Group: Participating principal investigators (PIs), coinvestigators (Is), primary coordinator (PCs), and coordinators (Cs) are listed below. All study personnel listed below were involved in data collection. Additional roles beyond data collection are noted. Icahn School of Medicine at Mt Sinai, New York, New York: Carol Levy, MD, CDE (PI); David Lam, MD (I); Grenye O’Malley, MD (I); Camilla Levister, NP, CDE (I); Nirali Shah, MD (I); Selassie Ogyaadu, MD, MPH (PC); Mayo Clinic, Rochester, Minnesota: Yogish Kudva, MD (PI); Vinaya Simha, MD (I); Shelly McCrady Spitzer (PC); Corey Reid (C); International Diabetes Center/Park Nicollet, Minneapolis, Minnesota: Anders Carlson, MD (PI); Richard Bergenstal, MD (I); Marcia Madden, MPH, RN, CNP, CDE (I); Thomas Martens, MD (I); Sean Dunnigan, RN (PC); Kathleen McCann, RN (C); University of Washington Diabetes Care Center, Seattle: Irl Hirsch, MD (PI); Dace Trence, MD, FACE (I); Subbulaxmi Trikudanathan, MD, MRCP, MMSc (I); Lorena Wright, MD (I); Andrea Toulouse, MS (PC); Dori Khakpour, RDN, CD, CDE (C); Lori Sameshima, RN (C); Nancy Sanborn, ND, CDE (C) Naomi Berrie Diabetes Center, Columbia University, New York, New York: Robin Goland, MD (PI); Lauren Golden, MD (I); Sarah Pollak, RN, MSN (PC); Courtney Melrose, MPH, RDN, CDE (C); Analia Alvarez, RN, BSN (C); Elizabeth Robinson (C); Eleanor Zagoren (C); University of North Carolina Diabetes Care Center, Chapel Hill, North Carolina: Laura Young, MD, PhD (PI); Elizabeth Harris, MD, FACE (I); John Buse, MD, PhD (I); Katherine Bergamo, BSN, MSN, FNP-C (I); Marian Sue Kirkman, MD (I); Jean Dostou, MD, FACE (I); Alexander Kass, BSN, RN, CDE (PC); Milana Dezube, BSN, RN, CDE (C); Rahul Kathard (C); Jamie C. Diner, BSN, RN, CDE (C); Henry Ford Health System, Detroit, Michigan: Davida Kruger, NP (PI); Natalie Corker (PC); Heather Remtema (C); Keck School of Medicine, University of Southern California, Los Angeles: Anne Peters, MD (PI); Mark Harmel, MPH, CDE (PC); SUNY Upstate Medical University, Syracuse, New York: Ruth Weinstock, MD, PhD (PI); Suzan Bzdick, RN, CDE (PC); Atlanta Diabetes Associates, Atlanta, Georgia: Bruce Bode, MD (PI); Jennifer Boyd, PA (I); Joseph Johnson, PA (I); Lisa Kiblinger, RN, NP-C, CDE (I); Jonathan Ownby, MD (I); Nitin Rastogi, MBBS (PC); Blake Winslett (C); Tracy Lawrence (C); Harold Schnitzer Diabetes Health Center, Oregon Health and Science University, Portland: Andrew Ahmann, MD (PI); Jessica Castle, MD (I); Farahnaz Joarder, MD (I); Diana Aby-Daniel, PA (I); Victoria Morimoto, PA (I); Kathryn Hanavan, RN, NP (I); Kristin Jahnke (PC); Rebecca Fitch (C); Brianna Moralez-Gomez (C); Washington University, St Louis, Missouri: Janet McGill, MD (PI); Maamoun Salam, MD (I); Stacy Hurst, RN, BSN, CDE (PC); Mary Jane Clifton, CCRP (C); Carol Recklein, RN, MHS, CDE (C); Toni Schweiger, RN (C); Alex Goay, BA (C); Northwestern University, Chicago, Illinois: Grazia Aleppo, MD (PI); Emily Szmuilowicz, MD (I); Elaine Massaro, MS, RN, CDE (PC); Anupam Bansal, MD (C); Division of Endocrinology, Diabetes and Metabolism, University of Miami, Miami, Florida: Francesco Vendrame, MD, PhD (PI); Natalia Sanders-Branca, MD (PC); Della Matheson, RN, CDE (C); University of Michigan, Ann Arbor: Rodica Pop-Busui, MD, PhD (PI); Lynn Ang, MD (I); Kara Mizokami-Stout, MD (I); Cynthia Plunkett, RN (PC); Brittany Plunkett (C); Virginia Leone (C); University of Pennsylvania Perelman School of Medicine/Rodebaugh Diabetes Center, Philadelphia: Michael Rickels, MD, MS (PI); Amy Peleckis, MSN, CRNP (I); Cornelia Dalton-Bakes, MS, CCRC (PC); Eileen Markmann, BSN (C); University of Massachusetts Medical School, Worcester: Michael Thompson, MD (PI); Nina Rosano, MD (I); Celia Hartigan, RN, MPH (PC); Iowa Diabetes and Endocrinology Research Center, West Des Moines: Anuj Bhargava, MD (PI); Kathleen Fitzgerald, RN (I); Kirstie Stifel (PC); Lisa Borg (C); AdventHealth, Translational Research Institute, Orlando, Florida: Richard Pratley, MD (PI); Melissa Rooney, ARNP (I); Heather Richmond, PA (I); Karthik Chivukula, MD (I); Keri Whitaker, RN (PC); Karla Flores Perez (C); University of Chicago, Chicago, Illinois: Louis Phillipson, MD, PhD (PI); Celeste Thomas, MD, MS (I); Gail Gannon, APN, FNP-C (I); Mariko Pusinello, APN, RN (C) (C); Barbara Davis Center for Diabetes, University of Colorado/Denver, Aurora: Viral Shah, MD (PI); Halis Kaan Akturk, MD (I); Hal Joseph, PA-C (I); Lisa Myers (PC); Prakriti Joshee (C); Elizabeth Beck (C); Scripps Whittier Diabetes Institute, San Diego, California: Athena Philis-Tsimikas, MD (PI); George Dailey, MD (I); Amy Chang, MD (I); James McCallum, MD (I); Maria Isabel Garcia, RN (PC); Rosario Rosal (C); Jaeb Center for Health Research, Tampa, Florida: Kellee M. Miller, PhD; Alandra Verdejo, MPH; Nicole Reese, BS; David McNabb, AS; Heidi Strayer, PhD; Kamille Janess, BS; Israel Mahr, MS; Lauren Kanapka, MSc; Craig Kollman, PhD; Roy Beck, MD, PhD; WISDM Operations committee members: Richard Pratley, MD; Michael Rickels, MD, MPH; Naomi Chaytor, PhD; D. Steven Fox, MD; Kellee M. Miller, PhD; Data and Safety Monitoring Board: Mark Espeland, PhD, FASA (chair); Guillermo Umpierrez, MD, CDE; Mary Korytkowski, MD; Matthew Gilbert, DO.

Meeting Presentation: The trial results were presented at the American Diabetes Association meeting in San Francisco, California, on June 9, 2019, and at the European Association for the Study of Diabetes meeting in Barcelona, Spain, on September 17, 2019.

Data Sharing Statement: See Supplement 3.

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