Evidence map›Paper›PMID 32116024›Full record

ArticleJournal of diabetes science and technology2020

Diabetes Healthcare Professionals Use Multiple Continuous Glucose Monitoring Data Indicators to Assess Glucose Management.

Tong Sheng, Reid Offringa, David Kerr, Mark Clements, Jerome Fischer, Linda Parks, Michael Greenfield

Open access · bronzeAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 31% 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

1 citing paper in PubMed, 7 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Tong ShengGlooko, Inc., Mountain View, CA, USA.ORCID 0000-0003-1067-7608
Reid OffringaGlooko, Inc., Mountain View, CA, USA.
David KerrSansum Diabetes Research Institute, Santa Barbara, CA, USA.
Mark ClementsChildren's Mercy Kansas City, MO, USA.
Jerome FischerMDREQUEST, San Antonio, TX, USA.
Linda ParksGlooko, Inc., Mountain View, CA, USA.
Michael GreenfieldGlooko, Inc., Mountain View, CA, USA.
Children's Mercy Hospital · USSansum Diabetes Research Institute · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundContinuous glucose monitoring (CGM) offers multiple data features that can be leveraged to assess glucose management. However, how diabetes healthcare professionals (HCPs) actually assess CGM data and the extent to which they agree in assessing glycemic management are not well understood.

methodsWe asked HCPs to assess ten de-identified CGM datasets (each spanning seven days) and rank order each day by relative glycemic management (from "best" to "worst"). We also asked HCPs to endorse features of CGM data that were important in making such assessments.

resultsIn the study, 57 HCPs (29 endocrinologists; 28 diabetes educators) participated. Hypoglycemia and glycemic variance were endorsed by nearly all HCPs to be important (91% and 88%, respectively). Time in range and daily lows and highs were endorsed more frequently by educators (all

conclusionsConsensus in the endorsement of certain data features and agreement in assessing glycemic management were observed. While some practice-specific differences in feature endorsement were found, no differences between educators and endocrinologists were observed in assessing glycemic management. Overall, HCPs tended to consider CGM data holistically, in alignment with published recommendations, and made converging assessments regardless of practice.

Indexed as

Datasets as TopicGlycemic ControlBlood GlucoseBlood Glucose Self-MonitoringData AnalysisDelivery of Health CareDiabetes Mellitus, Type 1Diabetes Mellitus, Type 2EndocrinologistsHealth EducatorsHealth PersonnelHumansHypoglycemiaMonitoring, PhysiologicProfessional PracticeUnited StatesBlood GlucoseAGPCGMclinical careglucose dataoutcomes

Identifiers

PMID32116024
PMCPMC7196866
OpenAlexW2971698704

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.