Diagnostic accuracy of C-reactive protein for diabetic foot osteomyelitis: a retrospective study and meta-analysis of composite cut-off values

OBJECTIVE: To determine the composite cut-off value and diagnostic accuracy of C-reactive protein (CRP) for diabetic foot osteomyelitis (DFO). METHOD: A retrospective study of patients was combined with a meta-analysis. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity and area under the curve (AUC) were calculated via forest plots and summary receiver operating characteristic curves. A composite cut-off model was developed using R 4.4.3 (R Foundation for Statistical Computing, Austria). RESULTS: The experimental cohort comprised 265 patients (204 with DFO and 61 without). The meta-analysis comprised 12 studies, including a total of 1828 patients. The retrospective cohort demonstrated that CRP achieved an AUC of 0.63 (95% confidence interval (CI): 0.55, 0.71) for diagnosing DFO, with an optimal cut-off value of 9.57mg/l (sensitivity 74%, specificity 53%). Meta-analysis revealed pooled sensitivity of 74% (63-83%) and specificity of 73% (65-79%) (AUC=0.79; 95%CI: 0.75, 0.82). The composite model suggested a CRP cut-off of 15.20mg/l (sensitivity 80%, specificity 53%). CONCLUSION: In this study, CRP demonstrated moderate diagnostic utility for DFO and could function as a screening adjunct.

Authors

Institutions

Publication Details

Journal
Journal of Wound Care
Published
2026-04-01
DOI
https://doi.org/10.12968/jowc.2025.0340
Citations
1
Primary Topic
Diabetic Foot Ulcer Assessment and Management
Type
article
Field-Weighted Citation Impact
18.34
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnostic accuracy of C-reactive protein for diabetic foot osteomyelitis: a retrospective study and meta-analysis of composite cut-off values

Qingzhu Zhang, S. Quan, Jing Li, Jinzheng Hou et al.
1 citations
Journal of Wound Care
Diabetic Foot Ulcer Assessment and Management
18.34
article

Diagnostic accuracy of C-reactive protein for diabetic foot osteomyelitis: a retrospective study and meta-analysis of composite cut-off values

Qingzhu Zhang, S. Quan, Jing Li, Jinzheng Hou, Li Xiao, Lulu Liu, Yukun Tao, Fang Liu, Guangxin Zhou, Da Zhang
article en
1 citations

Abstract

OBJECTIVE: To determine the composite cut-off value and diagnostic accuracy of C-reactive protein (CRP) for diabetic foot osteomyelitis (DFO). METHOD: A retrospective study of patients was combined with a meta-analysis. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Pooled sensitivity, specificity and area under the curve (AUC) were calculated via forest plots and summary receiver operating characteristic curves. A composite cut-off model was developed using R 4.4.3 (R Foundation for Statistical Computing, Austria). RESULTS: The experimental cohort comprised 265 patients (204 with DFO and 61 without). The meta-analysis comprised 12 studies, including a total of 1828 patients. The retrospective cohort demonstrated that CRP achieved an AUC of 0.63 (95% confidence interval (CI): 0.55, 0.71) for diagnosing DFO, with an optimal cut-off value of 9.57mg/l (sensitivity 74%, specificity 53%). Meta-analysis revealed pooled sensitivity of 74% (63-83%) and specificity of 73% (65-79%) (AUC=0.79; 95%CI: 0.75, 0.82). The composite model suggested a CRP cut-off of 15.20mg/l (sensitivity 80%, specificity 53%). CONCLUSION: In this study, CRP demonstrated moderate diagnostic utility for DFO and could function as a screening adjunct.

Journal of Wound CareVol. 35(Sup4a)
Hebei North University (CN), United States Air Force (US), Air Force General Hospital PLA (CN)
Openalex Percentile: Top 1%
Diabetic Foot Ulcer Assessment and Management
18.34
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.