Evidence map›Paper›PMID 41693232›Full record

ArticleDiabetic medicine : a journal of the British Diabetic Association2026

Enhancing diabetic foot osteomyelitis diagnosis with metagenomics next-generation sequencing, proof of concept.

Madjid Morsli, Chloé Magnan, Florian Salipante, Adeline Dubois, Sophie Schuldiner, Nicolas Cellier, Albert Sotto, Jean-Philippe Lavigne, Catherine Dunyach-Remy

Abstract read
In one paragraph

Article in Diabetic medicine : a journal of the British Diabetic Association, 2026. 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

9 authors.

Madjid MorsliVBIC, INSERM U1047, Université Montpellier, Service de Microbiologie et Hygiène Hospitalière, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.ORCID https://orcid.org/0000-0002-8074-1794
Chloé MagnanVBIC, INSERM U1047, Université Montpellier, Service de Microbiologie et Hygiène Hospitalière, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.
Florian SalipanteService de Biostatistique, Épidémiologie, Santé Publique, et Information Médicale, Univ Montpellier, CHU Nîmes, Nîmes, France.
Adeline DuboisVBIC, INSERM U1047, Université Montpellier, Service de Microbiologie et Hygiène Hospitalière, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.
Sophie SchuldinerVBIC, INSERM U1047, Université Montpellier, Service des Maladies Métaboliques et Endocriniennes, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.
Nicolas CellierService d'Orthopédie, Université Montpellier, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.
Albert SottoVBIC, INSERM U1047, Université Montpellier, Service des Maladies Infectieuses et Topicales, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.
Jean-Philippe LavigneVBIC, INSERM U1047, Université Montpellier, Service de Microbiologie et Hygiène Hospitalière, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.
Catherine Dunyach-RemyVBIC, INSERM U1047, Université Montpellier, Service de Microbiologie et Hygiène Hospitalière, Clinique du Pied Diabétique Gard Occitanie, CHU Nîmes, Nîmes, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diabetic foot osteomyelitis (DFOM) is a serious medical condition that necessitates robust diagnostic tools for effective clinical management. Conventional diagnostic methods for DFOM rely heavily on bacterial culture, which is time-consuming and may fail to capture the full microbial diversity present in infections. This pilot study explored the utility of metagenomics next-generation sequencing (mNGS) as a complementary diagnostic tool for DFOM. We retrospectively analysed ten bone biopsies from nine diabetic persons using both routine microbiological culture and mNGS. Routine culture identified 11 bacterial species across seven biopsies, while mNGS detected 84 species, including all those found by culture. High microbial diversity (Shannon index = 1.10) was associated with severe osteomyelitis, leading to amputation in three of seven DFOM cases. Interestingly, one culture-negative biopsy revealed high bacterial diversity by mNGS and progressed to a severe infection within 7 days. mNGS also identified resistance genes, providing additional insights for targeted therapy. Integrating mNGS into routine clinical microbiology may serve as a complementary method to conventional diagnostics, particularly for distinguishing infection from colonization and predicting clinical outcomes. However, challenges such as human DNA contamination and limited sequencing depth must be addressed to optimize its clinical application. These findings support the integration of mNGS into diagnostic workflows for bone biopsies for improved management of DFOM.

Indexed as

Diabetic FootHigh-Throughput Nucleotide SequencingMetagenomicsOsteomyelitisAgedBacteriaBiopsyFemaleHumansMaleMiddle AgedPilot ProjectsProof of Concept StudyRetrospective Studiesbone biopsydiabetic foot osteomyelitismetagenomics next‐generation sequencingmicrobial diversityosteomyelitis management

Identifiers

PMID41693232
PMCPMC12982636

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LicenceCC BY-NC
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Registered trials

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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.