Evidence map›Paper›PMID 40364880›Full record

ArticleCureus2025

Biomarkers of Inflammation, Oxidative Stress, and Endothelial Dysfunction in Early Detection of Diabetic Foot Ulcers.

S Sangeeta, Chandu Siripuram, Srujana Konka, Krishnakumar Vaithilingam, Panneerselvam Periasamy, Rajesh Kannan Velu, Ramesh Kandimalla

Abstract read
In one paragraph

Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

  1. Article
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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

7 authors.

S SangeetaBiochemistry, Government Medical College, Karimnagar, Karimnagar, IND.
Chandu SiripuramDepartment of Hospital Medicine, Geisinger Community Medical Center, Scranton, USA.
Srujana KonkaInternal Medicine, Geisinger Wyoming Valley Medical Center, Wilkes-Barre, USA.
Krishnakumar VaithilingamMicrobiology, Bharathidasan University, Tiruchirappalli, IND.
Panneerselvam PeriasamyDepartment of Physiology, Government Erode Medical College, Perundurai, IND.
Rajesh Kannan VeluMicrobiology, Bharathidasan University, Tiruchirappalli, IND.
Ramesh KandimallaBiochemistry, Government Medical College, Narsampet, Warangal, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Diabetic foot ulcers (DFUs) represent a severe complication of diabetes, contributing to increased morbidity, escalating healthcare expenses, and a heightened risk of limb amputation. Early detection is crucial for preventing ulcer progression. Biomarkers offer a non-invasive approach to identifying at-risk individuals. This study evaluates emerging serum biomarkers for early DFU detection in the South Indian population, focusing on inflammation, oxidative stress, and endothelial dysfunction markers. Materials and methods A cross-sectional study was carried out at our tertiary care hospital, which is affiliated with Kakatiya Medical College, Telangana, India. The study included 189 diabetic patients, who were classified into three groups: Control (n=63) - individuals with diabetes but no ulcers, Pre-ulcer (n=63) - patients exhibiting pre-ulcerative foot conditions, and ulcer (n=63) - patients with active foot ulcers. Serum biomarkers analyzed included interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), C-reactive protein (CRP) (inflammatory markers), malondialdehyde (MDA) (oxidative stress marker), matrix metalloproteinase (MMP-9) (extracellular matrix degradation), and vascular endothelial growth factor (VEGF), intercellular adhesion molecule (ICAM-1) (endothelial dysfunction markers). Peripheral neuropathy evaluation was conducted using the Semmes-Weinstein monofilament test (10 g) and vibration perception threshold (VPT) measurement with a biothesiometer. Peripheral arterial disease (PAD) was assessed using the ankle-brachial index (ABI) with a Doppler ultrasound device and classified using Wagner's grading system. All the analyses were performed using established statistical methods. Results The serum concentrations of IL-6, TNF-α, CRP, MDA, and MMP-9 were notably higher in DFU patients (p < 0.05). Among the inflammatory markers, IL-6 (F = 319.75, p < 0.001), TNF-α (F = 186.03, p < 0.001), and CRP (F = 326.12, p < 0.001) showed a progressive increase across groups. MDA (F = 290.95, p < 0.001) reflected elevated oxidative stress, while MMP-9 (F = 356.21, p < 0.001) exhibited the strongest association with DFU severity. In addition, fasting plasma glucose and HbA1c levels were significantly higher in pre-ulcer and ulcer groups compared to controls (p < 0.001), with HbA1c showing strong positive correlations with MMP-9, CRP, and other biomarkers. VEGF and ICAM-1 were markedly elevated in pre-ulcer patients, indicating early vascular impairment. Among all parameters, MMP-9 and CRP demonstrated the highest diagnostic potential for DFU detection. Conclusion Findings suggest that systemic inflammation, oxidative stress, and vascular dysfunction play key roles in the pathogenesis of DFUs. Elevated VEGF and ICAM-1 levels in pre-ulcer patients point to early vascular impairment, supporting their potential as early biomarkers. MMP-9 and CRP showed strong correlations with ulcer severity, highlighting their diagnostic utility for early screening. Additionally, HbA1c levels were significantly associated with biomarker elevations, reinforcing the impact of poor glycemic control on DFU progression. However, given the known limitations of HbA1c in anemic individuals, combining it with objective serum biomarkers may enhance diagnostic accuracy and risk stratification. Integrating such a biomarker-based approach into routine diabetes care could enable earlier intervention and reduce DFU-related complications.

Indexed as

biomarkerscrpdiabetic foot ulcerearly detectionendothelial dysfunctioninflammationmmp-9oxidative stresssouth indian population

Identifiers

PMID40364880
PMCPMC12072064

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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 OpenQuestion graph.