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Usefulness of the Delta Neutrophil Index in Predicting Surgery in Patients with Foot and Ankle Infection

Overview
Journal PLoS One
Date 2022 Aug 4
PMID 35926065
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Abstract

Background: In foot and ankle infections, cases with apparent soft-tissue necrosis or purulent fluid collections definitely require surgical treatments. However, clinicians often have difficulty in determining whether to perform surgery in ambiguous cases without these findings. This study aimed to investigate the impact of the delta neutrophil index as a predictor of surgical treatment in patients with foot and ankle infections.

Methods: In total, 66 patients diagnosed with foot and ankle infections who underwent the delta neutrophil index test were retrospectively investigated. Medical records, including data on diabetes mellitus status, delta neutrophil index values, white blood cell count, polymorphonuclear leukocyte count, erythrocyte sedimentation rate, and C-reactive protein level, were retrospectively investigated. Logistic regression models were analyzed for the correlation between biomarkers, such as the delta neutrophil index and surgical treatment. The area under the curve was investigated to evaluate the cut-off value of the logistic model in predicting surgery.

Results: The relationship between the delta neutrophil index and surgical treatment was analyzed. The delta neutrophil index, adjusted for diabetes mellitus, was the best predictor of future surgical intervention. Based on the Youden index, the cutoff point (the equation's adjusted by diabetes mellitus) for the prediction of surgical treatment was defined as a probability of 0.3, with sensitivity and specificity of 82.4% and 77.6%, respectively.

Conclusions: Based on the present study, the delta neutrophil index can help clinicians decide the appropriate surgical treatment for foot and ankle infections at the right time.

Citing Articles

Prognostic and Diagnostic Power of Delta Neutrophil Index and Mean Platelet Component in Febrile Patients with Suspected Sepsis.

Lee T, Lee J, Shin D, Lee H, Kim S Biomedicines. 2023; 11(12).

PMID: 38137411 PMC: 10740452. DOI: 10.3390/biomedicines11123190.

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