Evidence map›Paper›PMID 30616388›Full record

ArticleJournal of diabetes science and technology2019

New Paradigm of Personalized Glycemic Control Using Glucose Temporal Density Histograms.

Uriel Trahtemberg, Tova Hallas, Yehonatan Segman, Ella Sheiman, Michal Shasha, Kobi Nissim, Yosef Joseph Segman

Abstract 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. 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
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

0 citing papers in PubMed.

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

7 authors.

Uriel Trahtemberg1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.ORCID 0000-0001-9103-2494
Tova Hallas1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.
Yehonatan Segman1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.
Ella Sheiman1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.
Michal Shasha1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.
Kobi Nissim1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.
Yosef Joseph Segman1 Cnoga Medical Ltd, Caesarea North industrial Park, Caesarea, Israel.ORCID 0000-0002-6523-8314

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrent methods used to assess glycemic control use averaged measures and provide little information on the glycemic pathology of the patients. In this article we propose visual tools and their related mathematical formulas that allow for improved characterization of the glycemic behavior and achieve better glycemic control.

methodsWe present a reanalysis of published data, based on SMBG measurements from clinical trials of both men and women older than 18 years who were either healthy volunteers, prediabetes, or type 1 or type 2 diabetes. New graphic visualizations of glycemia as well as mathematical formulas that describe the glycemic behavior are presented and described, as well as suggested methods for their use to improve glycemic control.

resultsPatients with different problems in their glycemic control had different histogram shapes. In addition, patients who had the same HbA1c level at the time of the trial revealed significantly different glucose histograms with different shapes, variability and glycemic burden. The derived graphic visualizations provided information about the temporal evolution of the glycemic control.

conclusionsA paradigm change of the existing model of diabetes control is proposed, shifting from standardized treatment algorithms based on HbA1c follow-up to a new controlling approach that is based on the personal glucose density histogram. The histogram is an informative, detailed tool for the current patient glycemic behavior, and a future histogram can be targeted for a successful treatment. In addition, the glucose burden and the glucose severity index are proposed as informative markers for successful treatment. This is applicable to any glycemic data, by means of invasive and noninvasive glucometers.

Indexed as

Models, TheoreticalAdultBlood GlucoseDiabetes MellitusFemaleHumansMaleBlood Glucosediabetes careglucose histogramsglycemic burdenglycemic severity indexHb-A1cpersonalized medicine

Identifiers

PMID30616388
PMCPMC6610592

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.