Evidence map›Paper›PMID 40873802›Full record

ArticleFrontiers in medicine2025

A proposed model using glycation metrics and circulating biomarkers for the prevention of cardiovascular disease.

Timothy Valk, Carol McMorrow

Abstract read
In one paragraph

Article in Frontiers in medicine, 2025. 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

2 authors.

Timothy ValkCardiacData Analytics, Winter Park, FL, United States.
Carol McMorrowCardiacData Analytics, Winter Park, FL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Cardiovascular aging starts early in life due to the glycation of critical proteins, though its progression remains undetected in the formative years. The glycation reaction affects all tissues by the same non enzymatic irreversible reaction. The variables are the pH, temperature, glucose concentration, and the specific protein. This relationship implies that glycated blood biomarkers could potentially be used as a proxy for assessing Methods: Laboratory tests for troponin I (cTnI), hemoglobin A1c (A1c), fructosamine, and low-density lipoprotein (LDL), were chosen to calculate the proxy for Results: Modeling of glycation was determined for each variable. Using metrics from multiple studies, theoretical rates of glycation of LDL and troponin I were calculated. The glycated changes in LDL and troponin I were used to determine the increases above optimal physiological rates. Conclusion: Laboratory results of LDL, cTnI, A1c and fructosamine could be used sequentially to derive a cost-effective proxy for assessing

Indexed as

algorithmbiomarkerscardiovascular diseaseglycationprevention

Identifiers

PMID40873802
PMCPMC12378529

What Socratic holds

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LicenceCC BY
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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 Socratic graph.