Evidence map›Paper›PMID 40697594›Full record

ArticleWorld journal of diabetes2025

Limitations of glycated hemoglobin and emerging biomarkers for diabetes care after bariatric surgery.

Uchenna Esther Okpete, Haewon Byeon

Abstract readLetter
In one paragraph

Article in World journal of diabetes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Uchenna Esther OkpeteDepartment of Digital Anti-aging Healthcare (BK21), Inje University, Gimhae 50834, South Korea.
Haewon ByeonWorker's Care & Digital Health Lab, Department of Future Technology, Korea University of Technology and Education, Cheonan 31253, South Korea. bhwpuma@naver.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bariatric surgery significantly improves glycemic control and can lead to type 2 diabetes remission. However, the reliability of glycated hemoglobin (HbA1c) as a type 2 diabetes biomarker post-surgery can be confounded by conditions such as anemia and gastrointestinal complications. Hence, we explored the use of alternative biomarkers such as glycated albumin (GA), 1,5-anhydroglucitol (1,5-AG), and insulin-like growth factor binding protein-1 (IGFBP-1) to monitor glycemic control more effectively in post-bariatric surgery patients. Measuring GA and 1,5-AG levels can detect glycemic variability more sensitively than HbA1c, especially under non-fasting conditions. GA shows promise for short-term monitoring post-surgery while 1,5-AG could be useful for real-time glucose monitoring. IGFBP-1 can be used to monitor metabolic improvement and to predict HbA1c normalization. However, challenges in assay standardization and cost remain significant barriers to their clinical adoption. Although these biomarkers could offer a more personalized approach to glucose monitoring (thereby addressing the limitations of utilizing HbA1c in this endeavor in post-bariatric surgery patients), this would require overcoming technical, logistical, and cost-related challenges. While using GA, 1,5-AG, and IGFBP-1 shows promise for glycemic monitoring, further research and validation are crucial for their routine clinical implementation, especially in the context of diabetes management post-bariatric surgery.

Indexed as

1,5-anhydroglucitolBariatric surgeryBiological markersDiabetes mellitusDiabetes remissionGlycated albuminGlycated hemoglobinGlycemic controlObesity management

Identifiers

PMID40697594
PMCPMC12278086

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.