Evidence map›Paper›PMID 30198331›Full record

ArticleJournal of diabetes science and technology2019

Performance of a Factory-Calibrated, Real-Time Continuous Glucose Monitoring System in Pediatric Participants With Type 1 Diabetes.

John B Welsh, Xiaohe Zhang, Sarah A Puhr, Terri Kang Johnson, Tomas C Walker, Andrew K Balo, David Price

Open access · hybridAbstract read
In one paragraph

Article in Journal of diabetes science and technology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
2.0field-weighted citation impact, top 13% 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

20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

John B Welsh1 Dexcom, Inc, San Diego, CA, USA.
Xiaohe Zhang1 Dexcom, Inc, San Diego, CA, USA.
Sarah A Puhr1 Dexcom, Inc, San Diego, CA, USA.ORCID 0000-0003-1564-7563
Terri Kang Johnson1 Dexcom, Inc, San Diego, CA, USA.
Tomas C Walker1 Dexcom, Inc, San Diego, CA, USA.
Andrew K Balo1 Dexcom, Inc, San Diego, CA, USA.
David Price1 Dexcom, Inc, San Diego, CA, USA.
Dexcom (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe perceived value and consistent use of continuous glucose monitoring (CGM) systems depends in part on their accuracy. We assessed the performance of a sixth-generation CGM system (Dexcom G6) in children and adolescents.

methodsForty-nine participants (6-17 years of age, mean ± SD of 13.5 ± 3.3 years), all with type 1 diabetes, enrolled and data were available from 37. Each participant wore 1 sensor for up to 10 days and was asked to undergo an in-clinic visit lasting 6-12 hours for frequent blood glucose (BG) sample testing on one of the sensor wear days. Estimated glucose values (EGVs) from the G6 system were compared with venous BG values measured with a laboratory reference instrument (YSI).

resultsThe overall mean absolute relative difference (MARD) for 1387 EGV-YSI pairs was 7.7%, and the overall percentage of EGVs within 20% or 20 mg/dL of the YSI reference value (for YSI > or ⩽100 mg/dL, respectively, the "%20/20") was 96.2%. The %20/20 was 92.1% on Day 1 and 91.0% on Day 10 of sensor wear. For EGVs <70 mg/dL, 92.6% of the YSI values were within 20 mg/dL and for EGVs >250 mg/dL, 100% of the YSI values were within 20%. Differences between EGVs and YSI values in over 99.9% of the pairs posed no or only slight clinical risk as evaluated by surveillance error grid analysis.

conclusionsThe accuracy of the G6 CGM system in pediatrics may encourage consistent use of the system and contribute to improved glycemic outcomes in this population.

Indexed as

Wearable Electronic DevicesAdolescentAge FactorsAlgorithmsBiomarkersBlood GlucoseBlood Glucose Self-MonitoringCalibrationChildDiabetes Mellitus, Type 1FemaleHumansMalePredictive Value of TestsReproducibility of ResultsRetrospective StudiesBiomarkersBlood Glucoseadvanced algorithmclinical accuracycontinuous glucose monitoringfactory-calibratedglucose sensor performanceMARD

Identifiers

PMID30198331
PMCPMC6399785
OpenAlexW2889768647

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.