Evidence map›Paper›PMID 40537139›Full record

ArticleBone & joint research2025

Detection limitations of bacteria in tissue samples.

Tim Holm Jakobsen, Julius Bier Kirkegaard, Mads Lichtenberg, Lasse Andersson Kvich, Hans Gottlieb, Martin McNally, Thomas Bjarnsholt

Abstract read
In one paragraph

Article in Bone & joint research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. 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.

Tim Holm JakobsenCosterton Biofilm Center, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark.
Julius Bier KirkegaardNiels Bohr Institute, Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
Mads LichtenbergCosterton Biofilm Center, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark.
Lasse Andersson KvichCosterton Biofilm Center, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark.
Hans GottliebDepartment of Orthopedic Surgery, Herlev Hospital, Herlev, Denmark.
Martin McNallyThe Bone Infection Unit, Nuffield Orthopaedic Centre, Oxford University Hospitals, Oxford, UK.
Thomas BjarnsholtCosterton Biofilm Center, Department of Immunology and Microbiology, University of Copenhagen, Copenhagen, Denmark.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: Successful identification of bacteria in tissue samples requires careful consideration of multiple factors, including sample type and quality, the type of bacteria being detected, and the sensitivity and specificity of the detection method. Here, we address the issues of detecting a small number of bacteria, often found in biofilms and heterogeneously distributed in a large volume (the surgical site with suspected infection). Specifically, the study seeks to address the difficulties in detecting small numbers of bacteria, and to evaluate the impact of bacterial aggregation on the probability of successful detection. Methods: We present simple formulae for the probability of detecting bacteria in different infection scenarios where the number of bacteria and size of bacterial aggregates are incorporated as variables. We define a critical aggregation parameter, above which the probability of sampling bacteria decreases dramatically. Results: Our calculations demonstrate that aggregation of bacteria in tissues can strongly impact the probability of detection, where an increase in aggregate size results in a reduced probability of obtaining a positive biopsy. Our calculations underscore the challenges in effectively sampling tissue for diagnostic purposes, particularly in low-grade infections characterized by small bacterial quantities within aggregates. Below the critical aggregation parameter, obtaining five tissue specimens is associated with a high probability of detecting infection, but at a higher aggregation level, increasing the number of specimens is rendered ineffective, resulting in culture-negative diagnoses. Conclusion: We hypothesize that the high false-negative rate in diagnosing orthopaedic surgical site infections, such as periprosthetic joint infections, could be partly influenced by the heterogeneous bacterial distribution and the sampling complexities of such populations outlined here. Homogenization of tissue specimens is a technique to enhance the surface area which potentially could increase the detection of heterogeneously distributed bacteria.

Identifiers

PMID40537139
PMCPMC12178716

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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.