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Cited by 315Diabetes Management and ResearchClinical Laboratory Practices and Quality ControlDiabetes, Cardiovascular Risks, and Lipoproteins

Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study

Open access
Shah, Viral N, DuBose, Stephanie N, Li, Zoey, Beck, Roy W, Peters, Anne L, Weinstock, Ruth S, Kruger, Davida, Tansey, Michael +7 more·2019·The Journal of Clinical Endocrinology & Metabolism
DOI 10.1210/jc.2018-02763PMC PMC7296129
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Abstract

Context: Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes. Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking. Objective: To establish reference sensor glucose ranges in healthy, nondiabetic individuals across different age groups using a current generation CGM sensor. Design: Multicenter, prospective study. Setting: Twelve centers within the T1D Exchange Clinic Network. Patients or Participants: Nonpregnant, healthy, nondiabetic children and adults (age ≥6 years) with nonobese body mass index. Intervention: Each participant wore a blinded Dexcom G6 CGM, with once-daily calibration, for up to 10 days. Main Outcome Measures: CGM metrics of mean glucose, hyperglycemia, hypoglycemia, and glycemic variability. Results: A total of 153 participants (age 7 to 80 years) were included in the analyses. Mean average glucose was 98 to 99 mg/dL (5.4 to 5.5 mmol/L) for all age groups except those over 60 years, in whom mean average glucose was 104 mg/dL (5.8 mmol/L). The median time between 70 to 140 mg/dL (3.9 to 7.8 mmol/L) was 96% (interquartile range, 93 to 98). Mean within-individual coefficient of variation was 17 ± 3%. Median time spent with glucose levels >140 mg/dL was 2.1% (30 min/d), and median time spent with glucose levels <70 mg/dL (3.9 mmol/L) was 1.1% (15 min/d). Conclusion: By assessing across age groups in a healthy, nondiabetic population, normative sensor glucose data have been derived and will be useful as a benchmark for future research studies.

AI snapshot

Written from the paper’s full text.

TL;DR

In 153 healthy nondiabetic children and adults aged 7 to 80 years, blinded Dexcom G6 CGM showed a mean 24-hour glucose of 99 ± 7 mg/dL and median 96% time in 70 to 140 mg/dL. Adults ≥60 years had higher mean glucose and less time in range than younger participants.

Key findings

  • Overall mean 24-hour CGM glucose was 99 ± 7 mg/dL, mean within-individual coefficient of variation was 17 ± 3%, and median time between 70 and 140 mg/dL was 96% (IQR 93–98).
  • Mean average glucose was 98–99 mg/dL for all age groups except those ≥60 years, in whom it was 104 mg/dL (P < 0.001); median time in 70–140 mg/dL was lowest at 93% in adults ≥60 years (P < 0.001).
  • Median time >140 mg/dL was 2.1% (30 min/d) and <70 mg/dL was 1.1% (15 min/d); values >180 mg/dL and <54 mg/dL were uncommon, but 28% of participants had at least one hypoglycemic event overall and 14% had an overnight event.
  • The correlation between mean glucose and HbA1c was weak (r = 0.27; 95% CI, 0.12–0.41).

Methods

  • Multicenter, prospective study at 12 T1D Exchange Clinic Network centers; participants were healthy, nondiabetic, nonpregnant children and adults age ≥6 years with nonobese BMI, HbA1c <5.7%, and no islet autoantibodies. Of 201 screened, 153 were analyzed (age 7–80 years; mean 31 years).
  • Participants wore a blinded Dexcom G6 CGM for up to 10 days with once-daily calibration; ≥72 total hours of CGM data with ≥24 overnight hours were required. Mean CGM use was 192 hours (8 days), and MARD versus blood glucose meter was 6.0% (n = 1555 paired measurements).
  • Glucose outcomes were summarized overall and by age group and by daytime/nighttime; analyses included t tests for ≥60 vs <60 years, Pearson correlation for mean glucose and HbA1c, and sensitivity analyses removing implausible values.

Limitations

  • The paper states that 93% of participants were white, so it could not evaluate whether results were consistent across races; possible sensor pressure during sleep may have caused inaccurate CGM readings, and the study could not determine how many nocturnal hypoglycemic events were due to pressure on the sensor.
  • The paper states that after removing implausible data, mean glucose, time in 70–140 mg/dL, and CV were unchanged, but the percentage of participants with a hypoglycemic event was much lower; results may not be generalizable to capillary or laboratory-measured glucose profiles.
  • The paper notes the weak HbA1c–glucose correlation may relate to HbA1c being obtained before CGM data collection and to having at most 10 days of CGM data. Evident from the text: participants were primarily recruited from family, friends, and neighbors of patients seen in diabetes clinics, which may limit generalizability to the broader nondiabetic population.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1210/jc.2018-02763

Cites

20 of 20 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

13 of 17 cited sources checked · 7 supported · 0 flagged · accuracy not yet measured

  • Interpretationnone given

    The overall results of this study are in agreement with previous studies despite the different generations of CGM systems used in most of the studies.

    “The overall results of our study are in agreement with previous studies (3)(4)(5)(6)(7)17) despite the different generations of CGM systems used in most of the studies.”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [3] Borg, 2010, Real-life glycaemic profiles in non-diabetic individuals with low fasting glucose and normal HbA1c: the A1C-Derived Average Glucose (ADAG) study, Diabetologia source

      The Discussion says previous smaller CGM studies found similar glucose patterns, supporting the claim of overall agreement. The cited paper does not compare generations of CGM systems, so it does not support that qualification. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
    • cites [4] Freckmann, 2007, Continuous glucose profiles in healthy subjects under everyday life conditions and after different meals, J Diabetes Sci Technol source
    • cites [5] Fox, 2010, Variation of interstitial glucose measurements assessed by continuous glucose monitors in healthy, nondiabetic individuals, Diabetes Care source
  • Interpretationcitation

    The correlation between HbA1c and glucose is lower than what others have found.

    “However, the correlation between HbA1c and glucose is lower than what others have found (15).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [15] Nathan, 2008, Translating the A1C assay into estimated average glucose values, Diabetes Care source
  • Findingown data

    Overall, median time spent with glucose levels >140 mg/dL was 2.1% (30 min/d).

    “Overall, median time spent with glucose levels .140mg/dL was 2.1% (30 min/d)”
    Quote in the paperNot a substantial claim
  • Findingown data

    Overall, median time spent with glucose levels <70 mg/dL was 1.1% (15 min/d).

    “and ,70 mg/dL was 1.1% (15 min/d).”
    Quote in the paperNot a substantial claim
  • Findingown data

    Median sensor glucose between 70 and 140 mg/dL during nighttime was 99% (IQR, 95 to 100).

    “and 99% (IQR, 95 to 100), respectively”
    Quote in the paperNot a substantial claim
  • Classified as probably not a substantial claim. 21
  • May combine two claims. 16
  • The quote only partly states this claim. 3

  • Classified as probably not a substantial claim.

    Interpretationown data

    The findings support the recent consensus conference recommendation that sensor glucose values <54 mg/dL represent a more meaningful cut-off than 70 mg/dL to define clinically important hypoglycemia.

    “Our findings support the recent consensus conference recommendation (12, 13) that sensor glucose values ,54 mg/dL represent a more meaningful cut-off than 70 mg/dL to define clinically important hypoglycemia because CGM glucose levels below 54 mg/dL were uncommon, whereas most participants had some glucose levels of 55 to 69 mg/dL.”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [12] Danne, 2017, International consensus on use of continuous glucose monitoring, Diabetes Care source
    • cites [13] Maahs, 2016, Outcome measures for artificial pancreas clinical trials: a consensus report, Diabetes Care source

      In Additional Recommendations and Limitations (page unavailable), the consensus report suggests reporting CGM excursions below either 70 or 55 mg/dL as possible measures of hypoglycemia. It does not recommend a cutoff below 54 mg/dL or say that cutoff is more clinically meaningful than 70 mg/dL. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Most studies of CGM profiles in healthy, nondiabetic individuals have had small sample sizes or used early-generation CGM systems, which were less accurate than current devices.

    “Most studies of CGM profiles in healthy, nondiabetic individuals have had small sample sizes or used early-generation CGM systems, which were less accurate than current devices (3)(4)(5)(6)(7).”
    Quote in the paperSubstantial claim3 of 3 sources checked
    • cites [3] Borg, 2010, Real-life glycaemic profiles in non-diabetic individuals with low fasting glucose and normal HbA1c: the A1C-Derived Average Glucose (ADAG) study, Diabetologia source

      The Discussion describes earlier CGM studies of 32 and 15 people, supporting the small-sample part of the claim; Methods reports that this study used CGM in 80 nondiabetic participants. Neither section says the systems were early-generation or compares their accuracy with current devices. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [4] Freckmann, 2007, Continuous glucose profiles in healthy subjects under everyday life conditions and after different meals, J Diabetes Sci Technol source

      The Methods report CGM profiles from 24 healthy volunteers using SCGM1 devices, supporting this paper as an example of a small study using an older system. The paper reports the SCGM1’s measurement error but does not compare its accuracy with current devices or establish that most such studies share these limitations. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [5] Fox, 2010, Variation of interstitial glucose measurements assessed by continuous glucose monitors in healthy, nondiabetic individuals, Diabetes Care source

      The Abstract’s Research Design and Methods describes a CGM study of 74 healthy participants. Research Design and Methods identifies the devices used and reports missing or implausible readings from one sensor, noting that a commercially available version had newer software. The paper does not establish that most such studies had small samples or that earlier devices were less accurate than current devices. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisecitation

    As assessment of diabetes treatment outcomes moves beyond HbA1c to include sensor glucose profiles, there is an increased need for a repository of normative CGM data with up-to-date and widely used devices.

    “As the assessment of outcomes of treatment of T1D and type 2 diabetes in clinical practice and research trials moves beyond the narrow focus of HbA1c levels to include the results of sensor glucose profiles (14), there is an increased need for a repository of”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [14] Beck, 2017, The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading, Diabetes Care source

  • May combine two claims.

    Interpretationcitation

    The variability of mean glucose at the same HbA1c is similar to what has been observed in the T1D population and highlights the limitation of HbA1c to reflect true glycemic status for some individuals.

    “This is similar to what has been observed in the T1D population and highlights the limitation of HbA1c to reflect true glycemic status for some individuals (14).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [14] Beck, 2017, The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading, Diabetes Care source

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Current consensus conferences have somewhat arbitrarily set time in ranges for CGM sensor glucose levels for patients with T1D, with time in target identified as being between 70 to 180 mg/dL.

    “The current consensus conferences have somewhat arbitrarily set time in ranges for CGM sensor glucose levels for patients with T1D, with time in target identified as being between 70 to 180 mg/dL (12,13).”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [12] Danne, 2017, International consensus on use of continuous glucose monitoring, Diabetes Care source
    • cites [13] Maahs, 2016, Outcome measures for artificial pancreas clinical trials: a consensus report, Diabetes Care source

      The Objective and Rationale section advocates standardized CGM glucose metrics for artificial-pancreas studies and says they are broadly applicable to type 1 diabetes studies. Additional Recommendations and Limitations mentions arbitrary glycemic ranges, but the retrieved passages do not identify 70–180 mg/dL as the target range or say that consensus conferences set that range somewhat arbitrarily. Page numbers were not available in our copy. (LLM, conf=0.80)

      Experimental — accuracy not yet measured

  • Classified as probably not a substantial claim.

    Findingown data

    A total of 153 participants aged 7 to 80 years were included in the analyses.

    “A total of 153 participants (age 7 to 80 years) were included in the analyses.”
    • Also stated in: § Results · plain
      “Therefore, 153 participants were included in the analyses, ranging from 7 to 80 years (mean, 31 years).”
    Quote in the paperSubstantial claim

  • The quote only partly states this claim.

    Findingown data

    Median sensor glucose between 70 and 140 mg/dL during the daytime was 96% (IQR, 92 to 97%).

    “Median sensor glucose between 70 and 140 mg/dL during the daytime and nighttime was 96% (IQR, 92 to 97%)”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Sensor glucose values >180 mg/dL and <54 mg/dL were uncommon.

    “Sensor glucose values .180mg/dL (10.0 mmol/L) and ,54 mg/dL (3.0 mmol/L) were uncommon.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In a sensitivity analysis after removing participants with first-degree family members with T1D (n = 101), mean CGM glucose, time spent in the 70 to 140 mg/dL range, and glycemic variability as measured by CV were not different from the main analysis.

    “In a sensitivity analysis after removing participants with first-degree family members with T1D (n 5 101), mean CGM glucose, time spent in the 70 to 140 mg/dL range, and glycemic variability as measured by CV were not different from the main analysis (data not shown).”
    Quote in the paperNot a substantial claim

  • May combine two claims. The quote only partly states this claim.

    Findingown data

    Mean average glucose was 98 to 99 mg/dL for all age groups except those over 60 years, in whom mean average glucose was 104 mg/dL (P < 0.001 comparing those ≥60 years old with those younger).

    “Mean average glucose was 98 to 99 mg/dL (5.4 to 5.5 mmol/L) for all age groups except those over 60 years, in whom mean average glucose was 104 mg/dL (5.8 mmol/L).”
    • Also stated in: § Results · plain
      “The mean average glucose level was 98 to 99 mg/dL (5.4 to 5.5 mmol/L) for all age groups except those $60 years old in whom mean average glucose a The underweight, normal weight, and overweight BMI categories for participants aged $18 years are ,18.5, 18.5 to ,24.9, and $24.9, respectively.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In a sensitivity analysis after removing implausible data, mean glucose, time spent in the 70 to 140 mg/dL range, and CV were not different from the main analysis.

    “Similarly, in a sensitivity analysis after removing implausible data, mean glucose, time spent in the 70 to 140 mg/dL range, and CV were not different from the main analysis”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    Mean glycemic variability measured by CV during the daytime was 17% ± 3%.

    “mean glycemic variability measured by CV during the daytime and nighttime was 17% 6 3%”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Mean CGM use by participants was 192 hours (8 days).

    “Mean CGM use by the participants was 192 hours (8 days)”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Participants 6 to 11 years old had a median of 90% of their readings in the 70 to 120 mg/dL range, as compared with only 81% in the cohort over age 60 years.

    “with participants 6 to 11 years old having a median of 90% of their readings in this range, as compared with only 81% in the cohort over age 60 years.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    Two possible factors may have contributed to the weaker-than-expected correlation: HbA1c was obtained prior to collection of CGM glucose data, and there are at most 10 days of CGM data.

    “There are two possible factors that may have contributed to this weaker-than-expected correlation: (1) HbA1c was obtained prior to collection of CGM glucose data and ( 2) there are at most 10 days of CGM data (16).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [16] Riddlesworth, 2018, Optimal sampling duration for continuous glucose monitoring to determine long-term glycemic control, Diabetes Technol Ther source

  • Probably not a substantial claim: may not pass S2 (checkable).

    Premisenone given

    Understanding CGM metrics in healthy participants without diabetes is needed to serve as a benchmark for research studies to define impaired glycemic status and for future technologies aiming to help individuals achieve near-normal glycemic profiles.

    “Understanding CGM metrics in healthy participants without diabetes is needed to serve as a benchmark for research studies to define impaired glycemic status and for future technologies aiming to help individuals achieve near-normal glycemic profiles.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Strengths of the study include the large sample size crossing the lifespan, multiple centers conducting the study, use of the latest generation technology, and up to 10 days of CGM wear time.

    “Strengths of our study include the large sample size crossing the lifespan, multiple centers conducting the study, use of the latest generation technology, and up to 10 days of CGM wear time.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationnone given

    This study fills the current gap in normative CGM data.

    “Although our study fills the current gap in the data”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The reported mean absolute relative difference (MARD) for the Dexcom G6 in accuracy studies comparing sensor glucose values with reference blood glucose values is 9.0%.

    “The reported mean absolute relative difference (MARD) for the Dexcom G6 in accuracy studies comparing sensor glucose values with reference blood glucose values is 9.0% (9).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [9] Shah, 2018, Performance of a factory-calibrated real-time continuous glucose monitoring system utilizing an automated sensor applicator, Diabetes Technol Ther source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Pressure on the sensor during sleep may have resulted in inaccuracy of some CGM readings.

    “Although pressure on the sensor during sleep may have resulted in inaccuracy of some CGM readings”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationnone given

    CGM profiles provide the best window available to date to evaluate the frequency of biochemical hypoglycemia in clinical trials of new drugs and devices for the treatment of diabetes.

    “CGM profiles also provide the best window available to date to evaluate the frequency of biochemical hypoglycemia in clinical trials of new drugs and devices for the treatment of diabetes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Premisereasoning

    HbA1c does not capture clinically relevant hyperglycemic and hypoglycemic patterns, which limits its utility in personalizing insulin-dosing decisions.

    “However, HbA1c does not capture clinically relevant hyperglycemic and hypoglycemic patterns, which limits its utility in personalizing insulin-dosing decisions.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Premisenone given

    Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking.

    “Although data on glycemic profiles of healthy, nondiabetic individuals exist for older sensors, assessment of glycemic metrics with new-generation CGM devices is lacking.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    HbA1c reflects overall glycemic control from the prior 60-90 days and is a surrogate marker for diabetes microvascular complications risk.

    “This is due to the fact that HbA1c is a reflection of overall glycemic control from the prior 60-90 days, as well as clear evidence from the DCCT establishing it as a surrogate marker for diabetes microvascular complications risk (1).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [1] Nathan, 1993, The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus, N Engl J Med source

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes.

    “Use of continuous glucose monitoring (CGM) is increasing for insulin-requiring patients with diabetes.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Participants were healthy, nondiabetic children and adults, primarily recruited from family, friends, and neighbors of patients seen in the diabetes clinics.

    “Participants were healthy, nondiabetic children and adults, primarily recruited from family, friends, and neighbors of patients seen in the diabetes clinics.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given

    CGM metrics are being used to examine and compare the relative effectiveness and safety of new therapeutic agents and modern technologies in clinical diabetes research.

    “Moreover, CGM metrics are being used to examine and compare the relative effectiveness and safety of new therapeutic agents and modern technologies in clinical diabetes research.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based). May combine two claims.

    Premisenone given

    CGM provides information on trends for hypoglycemia, hyperglycemia, and glycemic variability that helps patients and providers optimize glycemic control without increasing the risk for hypoglycemia.

    “Continuous glucose monitoring (CGM) provides information on trends for hypoglycemia, hyperglycemia, and glycemic variability that helps patients and providers optimize glycemic control without increasing the risk for hypoglycemia.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Study participants provided written informed consent prior to study participation.

    “Study participants provided written informed consent prior to study participation.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Only participants with ≥72 total hours of CGM data (with at least 24 hours overnight) were included in the analysis.

    “Only participants with $72 total hours of CGM data (with at least 24 hours overnight) were included in the analysis.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    Only participants with no islet autoantibodies and a central laboratory HbA1c level <5.7% were included in the analysis.

    “Only participants with no islet autoantibodies and a central laboratory HbA1c level ,5.7% were included in the analysis.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductcitation

    The study was conducted at 12 diabetes centers within the T1D Exchange Clinic Network after approval by institutional review boards.

    “The study was conducted at 12 diabetes centers within the T1D Exchange Clinic Network after approval by institutional review boards (8).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [8] Beck, 2012, The T1D Exchange clinic registry, J Clin Endocrinol Metab source
32 of 32

  • The paper relies on this without support.

    The 153 participants are representative of healthy nondiabetic individuals across age groups.

    “Participants were healthy, nondiabetic children and adults, primarily recruited from family, friends, and neighbors of patients seen in the diabetes clinics.”
    “Because the majority of our participants were white (93%), we were unable to evaluate whether results were consistent across races.”

  • The paper relies on this without support.

    CGM profiles over up to 10 days reflect usual glucose profiles in healthy nondiabetic individuals.

    “An early-generation Dexcom G6 CGM (Dexcom, Inc., San Diego, CA) in blinded mode (i.e., the participant was unable to see the glucose values) was worn for up to 10 days with one daily calibration using a study-provided blood glucose meter (Contour Next EZ; Ascensia Diabetes Care, Parsippany, NJ).”
    “there are at most 10 days of CGM data (16).”

  • The authors state this as an assumption.

    Low CGM readings <50 mg/dL during sleep are likely due to the participant lying on the CGM sensor.

    “any low CGM readings ,50 mg/dL (2.8 mmol/L) during sleep time as defined by logs (in which case the participant was likely to be lying on the CGM sensor)”

  • The paper relies on this without support.

    Participants' daily logs accurately recorded sleep and wake times.

    “Participants completed a daily log indicating times and intensity of any exercise, start times of meals and snacks, and sleep and wake times.”
4 of 4

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Authors
Shah, V. N., DuBose, S. N., Li, Z., Beck, R. W., Peters, A. L., Weinstock, R. S., Kruger, D., Tansey, M., Sparling, D., Woerner, S., Vendrame, F., Bergenstal, R., Tamborlane, W. V., Watson, S. E., & Sherr, J.
Affiliations
  • Barbara Davis Center for Diabetes, Aurora, Colorado
  • Jaeb Center for Health Research (US)
  • University of Southern California (US)
  • SUNY Upstate Medical University (US)
  • Henry Ford Health (US)
  • University of Iowa (US)
  • University of Oklahoma Health Sciences Center (US)
  • Indiana University School of Medicine
  • University of Miami (US)
  • Park Nicollet Clinic (US)
  • Yale University (US)
  • University of Louisville (US)
Corresponding author
DuBose, Stephanie N
ORCID
Venue
The Journal of Clinical Endocrinology & Metabolism
Publisher
The Endocrine Society
Published
2019-04-25
Volume
104
Issue
10
Pages
4356-4364
ISSN
  • 0021-972X (ISSN-L)
  • 1945-7197
DOI
10.1210/jc.2018-02763
PMC
PMC7296129
OpenAlex
W2941246007
Semantic Scholar
22170f815dcf3fd4385ff1485a7902d3413b5ae7
Cited by
315
References
17
Citations by year
2026: 57 · 2025: 71 · 2024: 63 · 2023: 41 · 2022: 38 · 2021: 26 · 2020: 15 · 2019: 4
FWCI
14.29
Type
journal article
Language
en
Open access
Locations
  • The Journal of Clinical Endocrinology & Metabolism (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (submittedVersion)
Funders
  • Leona M. and Harry B. Helmsley Charitable Trust
  • National Institutes of Health
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Health Sciences › Medicine › Physiology › Clinical Laboratory Practices and Quality Control
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
Keywords
continuous glucose monitoring, glycemic variability, hypoglycemia, hyperglycemia, Dexcom G6, reference values
MeSH terms
Adolescent, Adult, Age Factors, Aged, Blood Glucose, Child, Circadian Rhythm, Female, Humans, Hyperglycemia, Hypoglycemia, Male, Middle Aged, Monitoring, Physiologic, Prospective Studies, Reference Values, Sex Factors, Blood Glucose Self-Monitoring, Benchmarking, Young Adult, Healthy Volunteers

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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-14.

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