
==== Front
Int Wound J
Int Wound J
10.1111/(ISSN)1742-481X
IWJ
International Wound Journal
1742-4801
1742-481X
Blackwell Publishing Ltd Oxford, UK

10.1111/iwj.70063
IWJ70063
Original Article
Original Article
Systematic review and meta‐analysis of diagnostic test accuracy in chronic wound's microbiology
Berenguer‐Pérez et al.
Berenguer‐Pérez Miriam 1 2
Manzanaro‐García Nerea 3
González‐de la Torre Héctor 2 4 5
Durán‐Sáenz Iván 6
Hernández Martínez‐Esparza Elvira 7
Diaz Herrera Miguel Ángel 8 9
González Suárez Borja 1 2
Verdú‐Soriano José https://orcid.org/0000-0002-8307-7323
1 2 pepe.verdu@ua.es

1 Department of Community Nursing, Preventive Medicine, Public Health and History of Science University of Alicante Alicante Spain
2 WINTER: Wounds, Innovation, ThErapeutics and Research Group, University of Alicante Alicante Spain
3 General University Hospital Doctor Balmis Alicante Spain
4 Research Support Unit, Insular Maternal and Child University Hospital Complex, Canary Health Service Las Palmas de Gran Canaria Spain
5 Nursing Department, Faculty of Healthcare Science Universidad de Las Palmas de Gran Canaria Las Palmas de Gran Canaria Spain
6 Bioaraba, Basque Nurse Education Research Group, Osakidetza Basque Health Service, Araba University Hospital, Vitoria‐Gasteiz School of Nursing Vitoria‐Gasteiz Spain
7 Escola Universitària d'Infermeria de l'Hospital de la Santa Creu i Sant Pau Barcelona Spain
8 Unidad de Heridas Complejas Atención Primaria Metropolitana Sur, ICS, Hospitalet de Llobregat Barcelona Spain
9 Grupo de Investigación en Heridas Complejas GReFeC, Unitat Suport a la Recerca (USR) Costa Ponent Jordi Gol Barcelona Spain
* Correspondence
José Verdú‐Soriano, University of Alicante, Carretera de San Vicente del Raspeig, s/n. 03690, San Vicente del Raspeig, Alicante. Spain.
Email: pepe.verdu@ua.es

23 9 2024
9 2024
21 9 10.1111/iwj.v21.9 e7006305 9 2024
15 7 2024
06 9 2024
© 2024 The Author(s). International Wound Journal published by Medicalhelplines.com Inc and John Wiley & Sons Ltd.
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Abstract

Purpose

This study aims to assess the diagnostic accuracy of non‐culture‐based methodologies for detecting microorganisms in chronic wounds.

Methods

We systematically reviewed studies that evaluated the diagnostic accuracy of alternative tests in chronic wound samples, excluding studies focused on animal samples or unrelated conditions. The search encompassed PubMed, CINAHL, Scopus and Web of Science databases, employing the QUADAS‐2 tool for risk of bias assessment. Our search included the PubMed, CINAHL, Scopus and Web of Science databases, and we assessed the risk of bias using the QUADAS‐2 tool. A meta‐analysis was conducted on polymerase chain reaction (PCR) and colorimetric methods to determine sensitivity, specificity, diagnostic odds ratio, and summary receiver‐operating characteristic (sROC) curves using a random‐effects model. For methods not suitable for quantitative synthesis, a narrative synthesis was performed.

Results

Nineteen studies involving various types of chronic wounds were analysed, revealing diverse diagnostic methods including fluorescence, PCR, colorimetry, voltammetry, electronic nose, biosensors, enzymatic methods, staining and microscopy. Combining fluorescence with clinical signs and symptoms (CSS) versus culture showed significant accuracy. Colorimetry demonstrated low sensitivity but high specificity, with a diagnostic odds ratio of 6.3. PCR generally exhibited good accuracy, although significant heterogeneity was noted, even in subgroup analyses.

Conclusions

This study identified a broad spectrum of diagnostic approaches, highlighting the superior diagnostic accuracy achieved when microbiological analysis is combined with clinical assessments. However, the heterogeneity and methodological variations across studies present challenges in meta‐analysis. Future research should aim for standardized and homogeneous study designs to enhance the assessment of diagnostic accuracy for alternative methods.

chronic wounds
diagnostic accuracy
meta‐analysis
microbiological diagnosis
systematic review
source-schema-version-number2.0
cover-dateSeptember 2024
details-of-publishers-convertorConverter:WILEY_ML3GV2_TO_JATSPMC version:6.4.8 mode:remove_FC converted:23.09.2024
Berenguer‐Pérez M , Manzanaro‐García N , González‐de la Torre H , et al. Systematic review and meta‐analysis of diagnostic test accuracy in chronic wound's microbiology. Int Wound J. 2024;21 (9 ):e70063. doi:10.1111/iwj.70063
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pmc1 INTRODUCTION

Chronic wounds pose a significant challenge to healthcare systems worldwide, affecting an estimated 1%–5% of the population in developed countries. These wounds are characterized by their failure to progress through the normal stages of healing, remaining open for more than a month, which results in prolonged discomfort and considerable healthcare costs. 1 The complexity of managing chronic wounds is further complicated by their diverse aetiologies, including but not limited to diabetes mellitus, vascular insufficiencies and pressure injuries, all contributing to the stagnation of wound repair processes. The psychosocial and economic impacts on affected individuals are also profound, with decreased quality of life and increased healthcare expenditures. 2 , 3

The role of microorganisms in wound healing has been a subject of debate for years, with emerging insights into the various phenotypes of microorganisms, especially biofilm phenotypes, and their roles in wound healing being of utmost importance. Diagnosis of infection in chronic wounds typically relies on clinical assessments based on signs and symptoms of low‐level inflammation; however, precise microbial identification becomes critical when conventional treatments fail. 4 , 5 In such cases, laboratory analyses, particularly microbiological cultures, are the gold standard, although they have notable limitations, particularly when diagnosing biofilms. The specific growth requirements of certain pathogens and the time‐consuming nature of cultures necessitate the exploration of rapid, accurate and non‐invasive diagnostic alternatives. 6 , 7 , 8 , 9 , 10 Additionally, the rise of antibiotic resistance, largely due to antibiotic misuse, exacerbates these challenges, highlighting the urgency for precise pathogen identification to guide targeted treatment strategies. 6 , 8 , 10

This study aims to evaluate the diagnostic accuracy of non‐culture‐based methods for microbial detection in chronic wounds, without attempting to diagnose infection, as infection is currently diagnosed by clinical signs and symptoms. The potential of molecular techniques, such as polymerase chain reaction (PCR) and fluorescence, to provide timely and precise results is explored. By comparing these novel methods to traditional cultures, this review seeks to elucidate their efficacy and accuracy in identifying wound pathogens, irrespective of their phenotype, thereby contributing to the optimization of chronic wound management practices.

2 METHODS

2.1 Design

A systematic review and meta‐analysis were performed following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses of Diagnostic Test Accuracy Studies (PRISMA‐DTA) guidelines. 11 Although the study protocol was not pre‐registered, the review was systematically structured to ensure comprehensive coverage and analysis of the relevant literature.

2.2 Inclusion criteria

We included peer‐reviewed articles that evaluated the diagnostic accuracy (sensitivity and specificity) of non‐culture‐based methods for detecting microorganisms in chronic wound samples. Eligible studies provided detailed results, including true positives, true negatives, false positives and false negatives, comparing the index test with either microbiological culture or clinical signs and symptoms (CSS) as reference standards. We focused on studies involving chronic wound samples from hospitalized patients, primary care settings or specialized chronic wound care units.

2.3 Exclusion criteria

We excluded review articles, studies without diagnostic accuracy estimates, studies that did not use human samples or studies unrelated to chronic wounds. This approach ensured that the focus remained on the most relevant and high‐quality data available for analysis.

2.4 Information sources and search strategy

A comprehensive search was conducted across MEDLINE (via PubMed), CINAHL, Web of Science and SCOPUS databases from December 2022 to mid‐February 2023, without temporal restrictions. An inverse search was also performed on the references of the retrieved studies. We utilized Medical Subject Headings (MeSH) and relevant keywords, combined with Boolean operators AND/OR, to maximize the search scope. The search strategy was meticulously designed to include a broad range of terms related to chronic wounds and diagnostic methods, ensuring thorough literature coverage (Table 1).

TABLE 1 Search strategy.

Data bases	Search strategy	Date until…	
Web of Science	TS = (“accuracy”) OR TS = (“sensitivity and specificity”) AND TS = (“chronic wound”) OR TS = (“wound infection”) AND TS = (diagnostic test)	15 February 2023	
SCOPUS	(TITLE‐ABS‐KEY (“diagnostic test”)) AND ((TITLE‐ABS‐KEY (“chronic wound”)) OR (TITLE‐ABS‐KEY (“wound infection”))) AND ((TITLE‐ABS‐KEY (“sensitivity and specificity”)) OR (TITLE‐ABS‐KEY (accuracy)))	17 February 2023	
PUBMED	(“skin ulcer”[MeSH Terms] OR “wound infection”[Title/Abstract] OR “chronic wound”[Title/Abstract]) AND (“diagnostic tests, routine” [MeSH Terms] OR “Diagnostic Imaging” [MeSH Terms] OR “molecular diagnostic techniques” [MeSH Terms] OR “microbiological techniques” [MeSH Terms]) AND (“data accuracy” [MeSH Terms] OR “sensitivity and specificity” [MeSH Terms] OR “reproducibility of results” [MeSH Terms] OR (“sensitivity”[Title/Abstract] AND “specificity”[Title/Abstract]) OR “accuracy”[Title/Abstract])	16 February 2023	
CINAHL	(MH “Wound infection”) AND (MH “Molecular Diagnostic Techniques”) OR (MH “Microbial Culture and Sensitivity Tests”) OR (MH “diagnostic Tests, Routine”) AND (MH “Wound Infection”) AND (MH “Sensitivity and Specificity”) OR (MH “Validity”)	15 February 2023	

2.5 Study selection

The study selection process involved an initial screening of titles and abstracts to remove irrelevant articles and duplicates. The remaining studies underwent full‐text review to assess eligibility based on the predefined inclusion and exclusion criteria. This selection process was conducted by two independent reviewers, with discrepancies resolved through consultation with a third reviewer to reach consensus.

2.6 Data extraction and quality assessment

Data extraction was performed independently by two researchers, focusing on publication year, geographic location, sample size, wound type and diagnostic accuracy metrics (true positive, true negative, false positive, false negative rates, sensitivity and specificity). 12 The QUADAS‐2 tool 13 was used to assess the risk of bias and the quality of included studies, providing a critical appraisal of the evidence base.

2.7 Statistical analysis

Meta‐analysis was conducted using the DerSimonian and Laird random‐effects model, chosen due to anticipated high heterogeneity among studies. We assessed statistical heterogeneity using the I2 index. Diagnostic odds ratio, sensitivity, specificity and summary receiver‐operating characteristic (sROC) curves were calculated with 95% confidence intervals to synthesize diagnostic accuracy data comprehensively. Subgroup analyses were performed based on the type of microorganisms detected by the diagnostic tests, employing MetaDisc software for statistical calculations. 14

3 RESULTS

3.1 Study selection

The comprehensive search yielded 1369 records, with 175 duplicates removed. After screening titles and abstracts, 21 articles were selected for full‐text review. Due to access issues, one article was unreachable and three were excluded based on our selection criteria (two did not provide data on accuracy, and one involved a different sample type), leaving 17 studies included from databases. Two additional articles were included from inverse searching, resulting in a final sample of 19 studies (Figure 1).

FIGURE 1 PRISMA flow diagram on studies selection.

3.2 Study characteristics

The final cohort consisted of various research designs: five cohort studies, 13 cross‐sectional studies and one retrospective study, primarily from the United States, followed by Canada, England and the Netherlands. All studies were in English and compared index diagnostic tests against a ‘gold standard’, predominantly microbiological culture (Table 2).

TABLE 2 Summary of the characteristics and results of the primary studies.

Author/Year	Country	Objective	Design	Population/Sample	Results	Comments	
Clay et al., 2021 15	USA	To validate the clinical correlation of PCR for MRSA detection	Retrospective	251 samples of diabetic foot wounds collected by swab.	PCR versus Culture (gold standard)

Sensitivity: 95.3% (95% CI 92.3–97.7)

Specificity: 88.5% (95% CI 85.1–92.9)

Accuracy: 90.8% (95% CI 86.6–93.8)

	Limitations of the gold standard. Possible interferences with other substances.	
Melendez et al., 2010 16	USA	Comparing PCR analysis versus quantitative and qualitative microbiological culture for identifying aerobic bacteria in chronic wounds	Cross‐sectional	39 biopsy‐collected chronic wound samples	PCR versus qualitative culture (gold standard)

Sensitivity: 90.0% (54/60) (95% CI 79.5–96.2)

Specificity 96.5% (469/486) (95% CI 94.5–98.0)

PCR versus quantitative culture (gold standard)

Sensitivity:100% (55/55) (95% CI 93.5–100)

Specificity: 96.7% (475/491) (95% CI 94.8–98.1)

	A panel that can be used with more microorganisms to identify them needs to be designed.	
Haalboom et al., 2019 17	Netherlands	To explore whether the electronic nose ‘Aetholab’ can discriminate between an infected wound or not.	Cross‐sectional	77 samples of open wounds collected by Levine technique	Electronic nose versus culture (gold standard)

Sensitivity: 81% (95% CI 64–91)

Specificity: 63% (95% CI 46–77)

PPV: 67% (95% IC 51–80)

NPV: 78% (95% IC 60–90)

Electronic nose versus CSS (gold standard)

Sensitivity: 91% (95% CI 76–98)

Specificity: 71% (95% CI 55–84)

PPV: 73% (95% IC 57–85)

NPV: 91% (95% IC 75–98)

	Microbiological culture is necessary to perform antibiogram.	
Le et al., 2021 18	USA	To demonstrate that fluorescence (FL) imaging improves the identification of high bacterial loads in wounds.	Cohort	350 wounds collected by biopsy: diabetic foot, pressure ulcers, venous ulcers, surgical wounds between May 2018 and April 2019.	CSS versus culture (gold standard)

Accuracy 29.43% (95% CI 24.90–34.41)

Sensitivity 15.33% (95% CI 11.16–19.5)

FL + CSS versus culture (gold standard)

Accuracy 65.14 (95% CI 60.01–69.95)

Sensitivity 61% (95% CI 55.3–66.6)

Specificity 84.1% (95% CI 75.1–93.2)

FL versus culture (gold standard)

Accuracy 64.00% (95% CI 58.84–68.85)

	The information provided by FL modified treatments and improved patient care. FL also detects biofilms but does not distinguish the planktonic form of biofilm. Fastidious bacteria may have been under‐diagnosed. Limitations of biopsy processing technique. Some patients were under antibiotic therapy. Conflicts of interest.	
Hill et al., 2020 19	USA	To evaluate the usefulness of incorporating real‐time FL imaging in combination with UPPER/LOWER checklist for the identification of wound infection.	Cohort	27 wounds collected using the Levine (swab) technique: diabetic foot, pressure ulcers, venous ulcers and surgical wounds.	UPPER/LOWER checklist versus culture (gold standard)

Accuracy 85.2%.

Sensitivity of 81.8%.

100% specificity

FL+ UPPER/LOWER vs. culture (gold standard)

100% accuracy

100% sensitivity

100% specificity

	FL imaging does not provide information on bacterial species. It is necessary to obtain a sample for culture. Small sample, specificity data should be interpreted with caution. Some patients were under antibiotic therapy. Conflicts of interest.	
Ottolino‐Perry et al., 2017 20	Canada	To evaluate real‐time FL imaging to visualize bacteria and guide sampling compared with assessing CSS on the same wound.	Cross‐sectional	27 samples of diabetic foot wounds collected by Levine technique (swab)	CSS versus Culture (gold standard)

Accuracy 52% (95% CI 34–70)

Sensitivity 73% (95% CI 41–94)

Specificity 38% (95% CI 18–62)

FL versus Culture (gold standard)

Accuracy 78% (95% CI 59–90)

Sensitivity 78% (95% 42–94)

Specificity 78% (95% CI 54–91)

	Swab sampling has limitations. Results should be interpreted with caution. Surface microorganisms. Small sample size. Patients under antibiotic therapy. Conflicts of interest.	
Serena et al., 2023 21	USA	To investigate wound microorganisms using FL imaging and compare results with standard biopsy sampling without FL.	Cross‐sectional	350 biopsy‐collected hard‐to‐heal wounds	Standard collection (wound centre) versus Culture (gold standard)

Sensitivity 87.2% (95% CI 77.7–93.7)

FL versus Culture (gold standard)

Sensitivity 98.7% (95% CI 58.7–99.8)

	Specificity was not calculated because all samples were positive for microorganisms. Patients under antibiotic therapy. Conflicts of interest.	
Jonker et al., 2020 22	UK	To evaluate a point‐of‐care colorimetric wound infection detection kit for diabetic foot ulcers.	Cohort	383 samples of diabetic foot wounds collected by swab.	Colorimetric kit versus CSS (Gold standard)

Sensitivity: 26% (95% CI: 16–36)

Specificity: 95% (95% CI: 93–97)

PPV: 59% (95% IC: 42–75)

NVP: 84% (95% IC: 82–85)

Accuracy: 81.7% (95% CI: 77–85)

	It is necessary to check the brush for blood. Patients under antibiotic therapy. Limitations of the gold standard. Only indicates presence or absence.	
Serena et al., 2019 23	USA	To assess the diagnostic accuracy when using FL imaging in combination with CSS to identify wounds with high bacterial burden.	Cross‐sectional	19 wound samples collected by biopsy: diabetic foot, pressure ulcers, venous ulcers and surgical wounds.	Checklist NERDS/STONES versus PCR (gold standard)

Accuracy 26.3%.

Sensitivity 22.2% Sensitivity 22.2% Sensitivity 22.2% Sensitivity 22.2% Sensitivity 22.2% Sensitivity

FL+ NERDS/STONES versus PCR (gold standard)

Accuracy 73.7%.

Sensitivity 72.2%.

	Small sample size. Low proportion of true negatives (<104 CFU/g) so did not test specificity. Studies with larger sample needed. Excluded patients taking antibiotics. Conflicts of interest.	
DaCosta., 2015 24	Canada	To establish the safety and feasibility of FL imaging and its accuracy in detecting significant levels of bacterial load in chronic wounds.	Cross‐sectional	28 wound samples collected by Levine technique (swab)	FL versus Culture (gold standard)

Accuracy 74.5% Accuracy 74.5% Accuracy 74.5% Accuracy 74.5% Accuracy

CSS versus Culture (gold standard)

Accuracy 35.5%.

	Does not distinguish bacterial species. Small sample. Sample collection by swab has limitations.	
Lelli et al., 2018 27	Italy	Determine the performance of voltametric analysis on ulcer exudates	Cohort	42 lower limb ulcer exudates	Voltammetry versus Culture + CSS (gold standard)

100% sensitivity

Specificity: 88.9%.

Accuracy: 97.6% (95% CI 87–100)

	It only determines infection or non‐infection. A culture with a count of >105 CFU/mL and two or more signs of infection is considered as infection. Small sample.	
Sismaet et al., 2016 28	USA	To evaluate the use of a biosensor to detect P. aeruginosa pyocyanin in chronic wound exudates against 16 s rRNA sequencing.	Cross‐sectional	12 open wound samples collected by Levine technique.	Pyocyanin sensor versus PCR (gold standard)

Sensitivity: 71% (95% CI: 0.29–0.96)

Specificity: 57% (95% CI: 0.18–0.90).

PPV:63% (95% CI 0.24–0.91)

NPV: 67% (95% CI 0.22–0.96)

	Small sample size. Pilot study. False negatives and positives due to low concentration of Pseudomonas spp. Results quickly.	
Elsayed et al., 2003 29	Canada	To determine the degree of correlation of Gram staining with microbiological culture in burns.	Cross‐sectional	375 burn samples collected by swabbing	Gram stain versus culture (gold standard)

Sensitivity: 31% (95% CI 23.7–39.4)

Specificity: 97.2 (95% CI 94.2–98.6)

Accuracy: 74.4% (95% CI 69.8–78.6)

	Technical limitations. Limitations of the gold standard: not suitable for microbiological analysis.	
Wu et al., 2020 30	Thailand	Improving the method of wound biofilm diagnosis with the modified alcian blue stain.	Cohort	31 chronic wound samples collected by swab.	Alcian blue staining + Scanning electron microscopy (SEM) versus Culture (gold standard)

Sensitivity: 83.3% (95% CI: 64.1–93.3)

Specificity: 85.7% (95% CI: 48.7–97.4)

Accuracy: 83.9% (95%CI: 67.4–92.9)

	Very small number of cases. Possible misleading results with culture due to poor diagnosis in polymicrobial infections. Used to detect S. aureus and P. aeruginosa.	
BLokhuis‐Arkes et al., 2015 31	Netherlands	To evaluate the diagnostic properties of MPO, HNE, lysozyme and CatG enzymes in comparison with swab culture.	Cross‐sectional	81 samples of chronic and acute wounds collected by swab.	CSS versus Culture (gold standard)

Sensitivity: 38.7% (95% CI 23.7–56.2)

Specificity: 66% (95% CI 52.2–77.6)

Accuracy: 55.6% (95% CI 44.7–65.9)

Model 1. (at least 1 positive enzyme) versus Culture (gold standard)

Sensitivity: 90.3% (95% CI 75.1–96.7)

Specificity: 58% (95% CI 44.2–70.6)

Accuracy: 70.4% (95% CI 59.7–79.2)

Model 2. human neutrophil elastase (HNE) and lysozyme positive after 30 min versus Culture (gold standard)

Sensitivity: 54.8% (95% CI 37.8–70.8)

Specificity: 80% (95% CI 67–88.8)

Accuracy: 70.4% (95% CI 59.7–79.2)

Model 3. Myeloperoxidase (MPO) positive after 5 min and HNE or lysozyme positive after 30 min versus Culture (gold standard)

Sensitivity: 87.1% (95% CI 71.1–94.9)

Specificity: 60% (95% CI 46.2–72.4)

Accuracy: 70.4% (95% CI 59.7–79.2)

	Limitations of the gold standard. Does not provide information on the microorganisms involved. Rapid results. Small sample size.	
Young et al., 2020 32	UK	To evaluate the accuracy of the SPaCE (point‐of‐care) colorimetric method for the clinical diagnosis of infections in burns.	Cross‐sectional	31 burn wound samples collected by swab.	Colorimetric kit versus CSS (gold standard)

PPV: 66.7% (95% CI 43.7–83.7)

NPV: 61.5% (95% CI 35.5–82.3)

Sensitivity: 71% (95% CI 44–90)

Specificity: 57% (95% CI 29–82)

Accuracy: 64.5% (95% CI 46.9–78.9)

	Only indicates presence or absence of microorganisms. Lack of objectivity of clinical opinion.	
Stappers et al., 2015 33	Netherlands, Germany and Belgium.	To assess the potential benefit of using PCR in the identification of microorganisms causing infection in complicated wounds.	Cross‐sectional	128 diabetic foot wound samples collected by biopsy, curettage, aspiration.	PCR versus culture (gold standard) for different microorganisms (in brief)

Sensitivity ≥64.3%.

Specificity ≥25.5%.

Accuracy ≥67.2%.

	Possible contamination or cross‐reactivity. Technical limitations. Limitations of the gold standard Conflicts of interest.	
Stappers et al., 2015 34	USA	To assess the potential benefit of using PCR in the identification of Bacteroides fragilis in wounds.	Cross‐sectional	128 samples of diabetic foot wounds collected by biopsy, curettage, aspiration	PCR versus Culture (gold standard)

Sensitivity: 100% (95% CI 56.6–100)

Specificity: 93.5% (95% CI 87.7–96.7)

Accuracy: 93.8% (95% CI 88.2–96.8)

	Possible contamination or cross‐reactivity. Technical limitations. Limitations of the gold standard Conflicts of interest.	
Close et al., 2022 35	USA	To assess the reliability of a point‐of‐care PCR to detect group A streptococci.	Cross‐sectional	399 samples of soft tissue wounds (lower limbs, cellulitis or impetigo) collected by swab.	PCR versus Culture (gold standard)

Sensitivity: 100% (95% CI 98.2–100)

Specificity: 99.5% (95% CI 97.1–100)

Accuracy: 99.7% (95% CI 98.6–100)

	Limitations of the gold standard. 30% of pre‐prescribed antibiotics could have been avoided.	

3.3 Risk of bias

Bias assessment using QUADAS‐2 identified the main sources of bias as the use of microbiological cultures or CSS as gold standards, which may skew the accuracy of index tests. Additional biases arose from retrospective study designs, 15 antibiotic treatments at sampling 16 , 17 , 18 , 19 , 20 , 21 and lack of control in test interpretation, 22 which could lead to potential misinterpretations (Table 3).

TABLE 3 Tabular presentation for QUADAS‐2 risks of bias assessment results.

Study	Risk of bias	Applicability concerns	
Patient selection	Index test	Reference standard	Flow and timing	Patient selection	Index test	Reference standard	
Clay et al., 2021 15		☺		☺	☺	☺	☺	
Melendez et al., 2010 16		☺		☺	☺	☺	☺	
Haalboom et al., 2019 17		☺	☺	☺	☺	☺	☺	
Le et al., 2021 18		☺		☺	☺	☺	☺	
Hill et al., 2020 19		☺		☺	☺	☺	☺	
Ottolino‐Perry et al., 2017 20		☺		☺	☺	☺	☺	
Serena et al., 2023 21		☺		☺	☺	☺	☺	
Jonker et al., 2020 22				☺	☺	☺	☺	
Serena et al., 2019 23	☺	☺	☺	☺	☺	☺	☺	
Dacosta., 2015 24	☺	☺		☺	☺	☺	☺	
Lelli et al., 2018 25	☺	☺		☺	☺	☺	☺	
Sismaet et al., 2016 26	☺	☺	☺	☺	☺	☺	☺	
Elsayed et al., 2003 27	☺	☺		☺	☺	☺	☺	
Wu et al., 2020 28	☺	☺		☺	☺	☺	☺	
Blokhuis‐arkes et al., 2015 29	☺	☺		☺	☺	☺	☺	
Young et al., 2020 30	☺	☺		☺	☺	☺	☺	
Stappers et al., 2015 31	☺	☺		☺	☺	☺	☺	
Stappers et al., 2015 32	☺	☺		☺	☺	☺	☺	
Close et al., 2022 33	☺	☺		☺	☺	☺	☺	

3.4 Synthesis of results

Diagnostic methods were categorized by index test versus reference test, leading to various combinations such as fluorescence versus culture/PCR, colorimetry versus CSS and PCR versus culture, biosensors (voltammetry vs. culture/CSS, pyocyanin biosensor vs. PCR, electronic nose vs. culture/CSS), stains versus culture and enzymatic methods versus culture. Meta‐analysis was feasible for PCR versus culture and colorimetric kits versus CSS due to complete data, while other comparisons were narratively synthesized: Fluorescence Imaging: Fluorescence imaging in wound care offers various approaches, including laboratory‐based methods and point‐of‐care devices that detect photophores within microorganisms. Laboratory‐based methods typically use fluorescent dyes or markers that bind to microorganisms, while point‐of‐care devices detect specific intrinsic molecules (photophores) of certain microorganisms in real time. 23 When exposed to specific light wavelengths, these compounds emit light, allowing healthcare professionals to visualize and identify the presence, location and type of microorganisms. Utilized in six studies, 18 , 19 , 20 , 21 , 24 , 25 fluorescence imaging, combined with CSS, showed improved diagnostic accuracy, particularly in differentiating bacterial loads and guiding treatment modifications. However, species distinction required supplementary microbiological analysis. Accuracy varied across studies, with Hill et al 19 reporting 100% accuracy when combined with UPPER/LOWER checklist, Ottolino‐Perry et al 20 reporting 78% accuracy in identifying microorganisms on the wound surface, and Le et al 18 reporting 65.14% accuracy when used alongside CSS. However, data limitations prevented a full meta‐analysis.

Biosensor‐based analysis: These sensors are often arranged in multidimensional arrays designed to create artificial sensory systems that mimic human sensory mechanisms. 26 These methods include various techniques based on voltammetry and electrochemical reactions. Voltammetry identifies microorganisms by detecting electrochemical signals generated from their metabolic byproducts. By applying variable voltage, this technique measures changes in current to identify the microbial species present. It is a rapid, non‐invasive method that provides real‐time analysis. 26 One study 27 utilizing voltammetry demonstrates high sensitivity (100%) and specificity (88.9%) for microorganisms' detection, highlighting its potential for rapid diagnostics and differentiating the aetiology of wounds. The study emphasized the significance of ulcer aetiology in guiding management decisions. A biosensor designed to detect Pseudomonas spp. by measuring pyocyanin, 28 a bacterial metabolite, was evaluated in a pilot study. Despite the limited sample size, the biosensor exhibited a sensitivity of 71% and specificity of 57%, indicating potential but also underscoring the need for further research to address challenges such as low sample concentrations and potential false results. Additionally, an Electronic Nose was tested, an innovative method 17 that detects volatile organic compounds to identify wound microorganisms. The sensitivity and specificity varied depending on the reference standard used (CSS or microbiological culture), but one study reported promising results, with sensitivity reaching up to 91% and specificity at 71%.

Staining Techniques: GRAM staining showed low sensitivity but high specificity while an enhanced alcian blue staining protocol demonstrated good consistency in detecting S. aureus and P. aeruginosa biofilms. 29 , 30

Enzymatic Methods: Enzymatic methods, such as those involving myeloperoxidase and human neutrophil elastase, offered alternative perspectives on diagnostic properties in chronic wound samples. 31

Colorimetric Kits versus CSS: Colorimetric kits for identifying microorganisms in wounds are diagnostic tools that detect the presence of specific bacteria or fungi through colour changes. These kits typically function by facilitating a reaction between the metabolic byproducts of the microorganisms and a reagent, resulting in a distinct colour change. This visual indicator enables the rapid identification of microorganisms, making these kits a practical option for quick diagnostics. Two studies 22 , 32 included in the meta‐analysis revealed a pooled sensitivity of 34.4% (95% CI: 24.9%–45.0%) for colorimetric tests, indicating a limitation in accurately identifying true positive cases. The high level of inconsistency, marked by an I2 value of 91.3%, suggests significant heterogeneity in the sensitivity outcomes among the included studies. By contrast, the pooled specificity of colorimetric tests was substantially higher at 93.8% (95% CI: 90.5%–96.2%), indicating a strong likelihood of correctly identifying true negative cases. However, the specificity also exhibited notable inconsistency (I2 = 94.1%), which suggests variations in specificity measurements or participant demographics across the studies.

Forest plots for both sensitivity and specificity (Figure 2) visually represent the variability across studies, showing individual study estimates alongside the aggregated results. Although the high specificity is commendable, the compromised sensitivity and significant heterogeneity raise concerns about the reliability of colorimetric tests for confirming infections. This highlights the need for complementary diagnostic techniques to confirm positive outcomes, pointing out the limitations of relying solely on colorimetric tests as diagnostic tools.

The diagnostic odds ratio (Figure 3) was 6.29 (95% CI: 3.21–12.32), reflecting moderate diagnostic accuracy of colorimetric tests compared with microbiological cultures. Notably, the minimal inconsistency (I2 = 1.3%) and the Cochran‐Q statistic (Q = 1.01, df = 1, p = 0.314) indicate negligible heterogeneity, suggesting a consistent effect size and reinforcing the reliability of the reported diagnostic odds ratios. The very low between‐study variance (Tau‐squared = 0.005) further supports the consistency in diagnostic performance reported by the studies.

Despite these findings, the limited number of studies and wide confidence intervals necessitate cautious interpretation of the results, emphasizing the need for further research to validate these preliminary conclusions. While colorimetric tests demonstrate high specificity, their reduced sensitivity and significant heterogeneity among studies limit their effectiveness as standalone diagnostic tools. Therefore, integrating colorimetric tests with other diagnostic methods could enhance accuracy and reliability. These findings underscore the necessity for additional research to solidify the diagnostic utility of colorimetric tests compared with traditional microbiological cultures.

6 PCR versus Culture: PCR (polymerase chain reaction) is a molecular technique used to amplify and detect specific DNA or RNA sequences in wound samples. This method enables the identification of pathogens, quantification of bacterial load and detection of antibiotic resistance genes, providing valuable insights for targeted treatment and effective wound management. Five studies 15 , 16 , 33 , 34 , 35 demonstrated that PCR has high sensitivity, specificity and diagnostic odds ratio, though with substantial heterogeneity observed across studies (Figures 4 and 5). The meta‐analysis revealed a pooled sensitivity of 95.7% (95% CI: 93.6% to 97.3%), underscoring PCR's exceptional ability to accurately identify true positive cases. Similarly, the pooled specificity was 91.6% (95% CI: 90.3% to 92.8%), demonstrating PCR's effectiveness in correctly ruling out false negatives. The pooled diagnostic odds ratio, which combines sensitivity and specificity to reflect overall diagnostic performance, was 140.6 (95% CI: 33.5 to 589.3), indicating that PCR substantially outperforms traditional microbiological cultures as a diagnostic tool

However, significant heterogeneity was observed across the studies, as indicated by I2 values of 85.4% for the diagnostic odds ratio, 84.5% for sensitivity and 96.1% for specificity, highlighting considerable variability that must be taken into account when interpreting these results. Despite the high sensitivity and specificity rates, the pronounced heterogeneity suggests that study‐specific factors significantly influence diagnostic precision, necessitating caution when generalizing these findings.

The sROC curve (Figure 6) illustrates the balance between sensitivity and specificity across the included studies, with an area under the curve (AUC) of 0.97 (SE = 0.02). This high AUC value confirms PCR's superior ability to distinguish between true positive and negative cases compared with microbiological cultures. Additionally, the Q* index, a global measure of diagnostic accuracy where sensitivity and specificity are optimally balanced, was reported at 0.92 (SE = 0.03). A Q* index close to 1 indicates high diagnostic precision, further validating the robust diagnostic accuracy of PCR in this meta‐analysis.

Overall, the sROC curve, combined with the pooled sensitivity and specificity estimates from individual studies, supports the reliability of PCR as a diagnostic tool across diverse clinical settings and populations. The high AUC and Q* indices underscore PCR's robustness for clinical diagnosis within the evaluated context. Due to the pronounced heterogeneity, a subgroup analysis by microorganism type (Staphylococci and Streptococci) was performed, revealing variations in diagnostic accuracy (Supplementary File S1).

FIGURE 2 Summary results of sensitivity and specificity for colorimetric tests.

FIGURE 3 Summary results of diagnostic odds ratio for colorimetric tests.

FIGURE 4 Summary results of sensitivity and specificity for polymerase chain reaction (PCR) tests.

FIGURE 5 Summary results of diagnostic odds ratio for polymerase chain reaction (PCR) tests.

FIGURE 6 Summary results of summary receiver operating characteristic (sROC) curve for polymerase chain reaction (PCR) tests.

These findings highlight the diverse range of diagnostic methods that are emerging as potential alternatives to traditional microbiological cultures in chronic wound management. Each method offers distinct advantages and limitations, emphasizing the need for further research to validate their effectiveness and facilitate their integration into clinical practice.

4 DISCUSSION

This systematic review identifies a diverse array of diagnostic techniques for chronic wound's microbiology, primarily compared with traditional cultures or CSS. The findings highlight PCR's superior sensitivity for detecting Staphylococcus spp., consistent with studies by Noor et al. 36 and Rhoads et al., 37 which emphasized PCR's effectiveness in identifying polymicrobial growth compared with standard culture. This underscores PCR's utility in revealing the broader microbial diversity within wounds, crucial given the increasing challenge of antibiotic resistance.

The observed heterogeneity, especially in studies involving colorimetric kits, reflects the complexities of diagnosing wound microorganisms. Despite this, the diagnostic odds ratio suggests these kits can effectively discriminate between positive and negative samples, potentially complementing PCR in identifying antibiotic‐resistant pathogens such as MRSA. 38

Fluorescence‐based diagnostics also show promise for enhancing microbial detection accuracy, though data limitations necessitate cautious interpretation. The integration of fluorescence with molecular techniques like PNA‐FISH represents a significant advance, with potential in vivo applications that could offer a more nuanced understanding of wound microbiology. 39 , 40

While traditional cultures remain essential, the advent of rapid diagnostic technologies—such as voltammetry, biosensors, electronic noses and enzymatic methods—offers enhanced microbial recovery and species differentiation. These technologies do not aim to replace cultures but rather to enrich the diagnostic toolkit, providing clinicians with a more comprehensive microbial profile of chronic wounds.

The integration of microbiological studies with clinical assessments is emerging as a crucial factor in the accurate diagnosis of infections, highlighting the importance of developing bedside diagnostic tools that complement clinical observations. The potential of fluorescence imaging devices, along with the validation of wound infection assessment tools such as the Therapeutic Index for Local Infections (TILI) score, points to promising directions for future research and clinical practice. 41 , 42 Consequently, precise microbial identification may be less critical for managing chronic infections compared with acute infections. Methods that can pinpoint the location of microorganisms within the wound bed could facilitate targeted treatments, such as sharp debridement or other techniques aimed at eliminating bioburden. However, the widespread adoption of these advanced diagnostic methods faces significant challenges, primarily due to their higher costs compared with traditional cultures, which limits their clinical implementation.

4.1 Limitations

The heterogeneity of wound types, patient selection, sample collection and processing methodologies introduces significant variability across studies, complicating result synthesis. Additionally, the studies examined varied microbiology outcomes, with some focusing on bioburden and bacterial load levels, while others targeted specific pathogens. Non‐culture methods often detect specific genes or enzymes, contrasting with culture methods that use selective media for a broader spectrum of microorganisms. These factors highlight the challenge of identifying a definitive ‘gold standard’ for comparison, as cultures and CSS each have their limitations.

Further complicating the analysis, conflicts of interest and reliance on variable ‘gold standards’ add layers of complexity to understanding diagnostic accuracy. Publication bias may further skew the data landscape.

4.2 Implications for practice

This study underscores the potential of alternative diagnostic methods to complement traditional culture techniques in chronic wound management. Integrating microbiological analysis with clinical evaluation provides a holistic approach to diagnosing chronic wound's infections, though variability in diagnostic accuracy and high heterogeneity among studies necessitate careful interpretation. As the field evolves, standardized and reliable diagnostic techniques will be critical for clinical application, requiring further research to solidify these methodologies.

5 CONCLUSIONS

Our review highlights the varied diagnostic approaches for chronic wound's microbiology, with no single method demonstrating universal superiority. The introduction of rapid diagnostic technologies like PCR and colorimetric kits, particularly for detecting drug‐resistant microorganisms, marks a significant progress. The integration of these methods with clinical assessments appears to enhance diagnostic accuracy, suggesting a promising future for bedside diagnostic tools. Future research should prioritize standardization and methodological homogeneity to refine our understanding of these innovative diagnostics.

CONFLICT OF INTEREST STATEMENT

The author(s) declared no conflict of interest regarding this manuscript.

Supporting information

Data S1. Complementary material for subanalysis made.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.
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