Evidence map›Paper›PMID 39803151›Full record

ArticleCureus2024

Matrix Metalloproteinase-9 as a Predictor of Healing in Diabetic Foot Ulcers.

Prathvi Shetty, Rohan Dsouza, Vinoda Kumar B

Abstract read
In one paragraph

Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 1,3,4-Oxadiazole Derivatives of Pyrrolo[3,4-Pharmaceuticals (Basel, Switzerland) · 2025
    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

3 authors.

Prathvi ShettyGeneral Surgery, Father Muller Medical College, Mangalore, IND.
Rohan DsouzaGeneral Surgery, Father Muller Medical College, Mangalore, IND.
Vinoda Kumar BGeneral Surgery, Father Muller Medical College, Mangalore, IND.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background Wound healing in diabetic foot ulcers (DFUs) is hindered by several physiological and biochemical abnormalities, including prolonged inflammation, an imbalance in extracellular matrix (ECM) synthesis and degradation, insufficient neovascularization, and reduced macrophage activity. In DFUs, excessive and uncontrolled matrix metalloproteinases (MMPs) degrade the ECM and impede wound healing. Matrix metalloproteinase-9 (MMP-9) concentration plays a key role in inflammation and ECM degradation. This study explores the relationship between wound type in DFUs and MMP-9 levels, hypothesizing that a high MMP-9 environment may indicate inflammation and impaired wound healing. Materials and methods Forty individuals with type 2 diabetes and foot ulcers were recruited for the study. The participants were divided into two groups: nonhealing and healing, with 20 patients in each group. Biopsy samples were homogenized, and MMP-9 activity was measured using an ELISA. Results The MMP-9 concentration was significantly higher in nonhealing ulcers compared to healing ulcers. Receiver operating characteristic analysis revealed that MMP-9 measurement was the most accurate predictor of wound healing, with an area under the curve value of 0.945 and high sensitivity and specificity. Although there was a weak correlation between MMP-9 concentration and glycosylated hemoglobin, it was not statistically significant. Conclusions MMP-9 expression serves as a marker of poor wound healing. MMP-9 levels in the wound at the time of presentation may predict the healing trajectory and help tailor a specific treatment plan for each DFU patient.

Indexed as

diabetic foot ulcersglycosylated haemoglobin (hba1c)matrix metalloproteinase 9matrix metalloproteinase 9 inhibitor­wound healing

Identifiers

PMID39803151
PMCPMC11723777

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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.