Evidence mapPaperPMID 35306640Full record

ArticleDiabetes therapy : research, treatment and education of diabetes and related disorders2022

Level of Agreement and Correlation Between the Estimated Hemoglobin A1c Results Derived by Continuous or Conventional Glucose Monitoring Systems Compared with the Point-of-Care or Laboratory-Based Measurements: An Observational Study.

Ayman A Al Hayek, Samia H Sobki, Abdulghani H Al-Saeed, Wael M Alzahrani, Mohamed A Al Dawish

Open access · goldAbstract read
In one paragraph

Article in Diabetes therapy : research, treatment and education of diabetes and related disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 33% 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

5 citing papers in PubMed, 5 citations in OpenAlex.

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  5. First Real-World Experience With Bigfoot Unity: A 6-Month Retrospective Analysis.Clinical diabetes : a publication of the American Diabetes Association · 2023
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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

5 authors at 1 institution in 1 country.

Ayman A Al HayekDepartment of Endocrinology and Diabetes, Diabetes Treatment Center, Prince Sultan Military Medical City, P.O. Box 7897, Riyadh, 11159, Saudi Arabia. ayman.alhayek@yahoo.com.ORCID http://orcid.org/0000-0002-3483-3196
Samia H SobkiDepartment of Central Military Laboratory and Blood Bank, Prince Sultan Military Medical City, Riyadh, Saudi Arabia.
Abdulghani H Al-SaeedDepartment of Endocrinology and Diabetes, Diabetes Treatment Center, Prince Sultan Military Medical City, P.O. Box 7897, Riyadh, 11159, Saudi Arabia.
Wael M AlzahraniDepartment of Endocrinology and Diabetes, Diabetes Treatment Center, Prince Sultan Military Medical City, P.O. Box 7897, Riyadh, 11159, Saudi Arabia.
Mohamed A Al DawishDepartment of Endocrinology and Diabetes, Diabetes Treatment Center, Prince Sultan Military Medical City, P.O. Box 7897, Riyadh, 11159, Saudi Arabia.
Riyadh Armed Forces Hospital · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionHemoglobin A1C (HbA1c) is an important marker for diabetes care management. With the increasing use of new technologies such as continuous glucose monitoring (CGM) and point-of-care testing (POCT), patients and their physicians have been able to monitor and continuously check their blood glucose levels in an efficient and timely manner. This study aimed to investigate the level of agreement between the standard laboratory test for HbA1c (Lab-HbA1c) with point-of-care testing (POCT-HbA1c) and glucose monitoring index (GMI) derived by intermittently scanned CGM (isCGM) or estimated average glucose (eAG) derived by conventional self-monitored blood glucose (SMBG) devices.

methodsA cross-sectional study was conducted at the Diabetes Treatment Center, Prince Sultan Military Medical City, Saudi Arabia, between May and December 2020 with 81 patients with diabetes who used the isCGM system (n = 30) or conventional finger-pricking SMBG system (n = 51). At the same visit, venous and capillary blood samples were taken for routine HbA1c analysis by the standard laboratory and POCT methods, respectively. Also, for isCGM users, the GMI data for 28 days (GMI-28) and 90 days (GMI-90) were obtained, while for SMBG users, eAG data for 30 days (eAG-30) and 90 days (eAG-90) were calculated. The limits of agreement in different HbA1c measurements were evaluated using a Bland-Altman analysis. Pearson correlation and multivariate linear regression analyses were also performed.

resultsBased on the Bland-Altman analysis, HbA1c levels for 96.7% and 96.1% of the patients analyzed by the POCT and the standard laboratory methods were within the range of the 95% limit of agreement in both isCGM and conventional SMBG users, respectively. About 93.3% of the GMI measurements were within the 95% limit of agreement. Also, about 94.12% of the eAG-30 and 90.2% of the eAG-90 measurements were within the 95% limit of agreement. Moreover, the correlation analysis revealed a statistically significant positive correlation and linear regression among Lab-HbA1c, POCT-HbA1c, GMI, and eAG in both conventional SMBG and isCGM users (all p < 0.001). These positive results persisted significantly after adjusting for different factors (all p < 0.001).

conclusionGMI derived by isCGM or eAG derived by conventional SMBG systems, as well as the POCT-HbA1c measurements, showed a high level of agreement; therefore, we recommend them as potential methods for diabetes monitoring, especially when a rapid result is needed or with patients with uncontrolled diabetes or on intensive insulin therapy.

Indexed as

DiabetesHbA1cisCGMPOCTSaudi Arabia

Identifiers

PMID35306640
PMCPMC9076797
OpenAlexW4221027637

What Socratic holds

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LicenceCC BY-NC
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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 Socratic graph.