Evidence map›Paper›PMID 30623673›Full record

ArticleJournal of diabetes science and technology2019

Comparative Accuracy Evaluation of a Blood Glucose Meter With Novel Hematocrit Correction Technology, With Three Currently Used Commercially Available Blood Glucose Monitoring Systems.

Gareth J Dunseath, Dominic Bright, Stephen D Luzio

Registry-linked trialOpen access · bronzeAbstract readComparative StudyEvaluation StudyTechnical Report
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. It is linked to trial NCT06815081 (A Study to Determine a Capillary Alternative to the Gold Standard Oral Glucose Tolerance Test), which is not on this map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 100% 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.

NCT06815081 recruitingnot on this mapstarted 2024, after this paper: background citation

A Study to Determine a Capillary Alternative to the Gold Standard Oral Glucose Tolerance Test

TypeobservationalSponsorUniversity of OxfordRan2024 to 2027Enrolled135ConditionsType 1 Diabetes (T1D), Type 2 Diabetes
3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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

3 authors at 1 institution in 1 country.

Gareth J Dunseath1 Diabetes Research Unit Cymru, Swansea University, Singleton Park, Swansea, UK.
Dominic Bright1 Diabetes Research Unit Cymru, Swansea University, Singleton Park, Swansea, UK.
Stephen D Luzio1 Diabetes Research Unit Cymru, Swansea University, Singleton Park, Swansea, UK.
Swansea University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hematocrit is known to influence glucose values obtained on some blood glucose meters, with bias observed especially at low and high hematocrit levels. We evaluated the performance of a meter with hematocrit correction technology alongside 3 other commercially available meters. Capillary blood samples from 100 subjects were analyzed in duplicate and compared to the plasma values obtained by reference laboratory analyzer. Bias, error grid, and sensitivity to hematocrit analyses were performed for each meter. Average percentage bias was similar for all meters, however the evaluated meter performed best with respect to error grid analysis, with 100% of values falling within the "no effect on clinical action" and "no risk" categories and did not display any hematocrit associated bias.

Indexed as

ArtifactsBlood GlucoseBlood Glucose Self-MonitoringCommerceDiabetes MellitusHematocritHumansReference StandardsReproducibility of ResultsResearch DesignSensitivity and SpecificityUnited KingdomBlood Glucoseaccuracyblood glucose meterhematocrit

Identifiers

PMID30623673
PMCPMC6501526
OpenAlexW2910287505

What OpenQuestion holds

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Registered trials

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.