Cited by 139Diabetes Management and ResearchDiabetes Management and EducationDiabetes Treatment and Management

Continuous Glucose Monitoring: Review of an Innovation in Diabetes Management

Mian, Zainab, Hermayer, Kathie L., Jenkins, Alicia·2019·The American Journal of the Medical Sciences

Abstract

Most continuous glucose monitors (CGM) provide interstitial fluid glucose trends, which reflect blood glucose trends with alarms and alerts to prevent hypoglycemia and provide better glycemic control. CGM used in conjunction with insulin pumps has changed the management of patients with insulin-dependent diabetes, mainly type 1 diabetes. CGM technology prevents the need for frequent blood glucose testing, which is often cumbersome for patients, providing them with a better alternative. CGM technology is underprescribed and therefore advantage should be taken of this technology to provide better hemoglobin A1c (HbA1c) control and decrease incidence of diabetic complications. CGM is particularly useful in patients with hypoglycemia unawareness and nocturnal hypoglycemia. CGM is currently not approved in pregnant patients, in critically ill patients and patients on dialysis. Research suggests that the benefits certainly outweigh the limitations of this technology. This review article focuses on the technical and clinical use of continuous glucose monitoring and sensor-integrated pump technology.

Integrity signals

Registry

Crossref · 10.1016/j.amjms.2019.07.003

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Continuous glucose monitors such as Dexcom G6 and Abbott FreeStyle Libre continuously measure interstitial glucose levels and use AI algorithms to predict blood sugar trends, allowing users to take preventative action to avoid hypo- or hyperglycemia.

    “For example, CGMs such as the Dexcom G6 and Abbott FreeStyle Libre continuously measured interstitial glucose levels and use AI algorithms to predict blood sugar trends, allowing users to take preventative action to avoid hypo- or hyperglycemia (39,40).”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Mian, Z., Hermayer, K. L., & Jenkins, A.
Affiliations
  • Medical University of South Carolina (US)
  • The University of Sydney (AU)
Corresponding author
Hermayer, Kathie L.
Venue
The American Journal of the Medical Sciences
Publisher
Elsevier BV
Published
2019-11
Volume
358
Issue
5
Pages
332-339
ISSN
0002-9629 (ISSN-L)
OpenAlex
W2959616026
Cited by
139
References
1
Citations by year
2026: 13 · 2025: 17 · 2024: 27 · 2023: 26 · 2022: 16 · 2021: 19 · 2020: 19 · 2019: 2
FWCI
11.36
Type
journal article
Language
en
Open access
closed
Locations
  • The American Journal of the Medical Sciences (publishedVersion)
  • PubMed (publishedVersion)
Funders
Medical University of South Carolina
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
Keywords
continuous glucose monitoring, type 1 diabetes, insulin pump therapy, sensor-augmented pump, hypoglycemia prevention, hypoglycemia unawareness, nocturnal hypoglycemia, glycemic control, HbA1c, diabetes complications
MeSH terms
Blood Glucose, Diabetes Mellitus, Humans, Hypoglycemic Agents, Insulin, Patient Care Management, Infusion Pumps, Implantable, Risk Assessment

About these checks

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.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review