Evidence map›Paper›PMID 27530720›Full record

ReviewJournal of diabetes science and technology2017

Recommendations for Using Real-Time Continuous Glucose Monitoring (rtCGM) Data for Insulin Adjustments in Type 1 Diabetes.

Jeremy Pettus, Steven V Edelman

Open access · bronzeAbstract readReview
In one paragraph

Review in Journal of diabetes science and technology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed
14.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 118 citations in OpenAlex.

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  10. Race Across America: First Athlete With Type 1 Diabetes to Finish Solo With Diabetes Technology Support.Diabetes spectrum : a publication of the American Diabetes Association · 2022
    Article
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  13. Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.Journal of diabetes science and technology · 2021
    Article
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  16. A "Slide Rule" to Adjust Insulin Dose Using Trend Arrows in Adults with Type 1 Diabetes: Test in Silico and in Real Life.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Jeremy Pettus1 University of California, San Diego, San Diego, CA, USA.
Steven V Edelman1 University of California, San Diego, San Diego, CA, USA.
University of California, San Diego · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The clinical benefits of real time continuous glucose monitoring (rtCGM) use have been well demonstrated in both CSII- and MDI-treated individuals in large clinical trials. However, recommendations for patient use of rtCGM in everyday life situations are lacking. This article provides guidance to clinicians and patients with type 1 diabetes (T1D) in effective use of rtCGM data, including glucose rate of change (ROC) arrows, for insulin dosing adjustments and other treatment decisions. The recommendations presented here are based on our own clinical experiences as endocrinologists, our personal experiences living with T1D using rtCGM, and findings from a recent survey of T1D patients who have successfully used rtCGM in their self-management. It is important that both clinicians and people with diabetes understand the utility and limitations of rtCGM. Maintaining a collaborative clinician-user relationship remains an important factor in safe, successful rtCGM use.

Indexed as

Blood Glucose Self-MonitoringBlood GlucoseDiabetes Mellitus, Type 1FemaleHumansHypoglycemic AgentsInsulinMaleSelf CareBlood GlucoseHypoglycemic AgentsInsulincontinuous glucose monitoringCSIIinsulin pumpMDImultiple daily insulin injectionsrate of changetype 1 diabetes

Identifiers

PMID27530720
PMCPMC5375074
OpenAlexW2513029483

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.