Comparative Analysis of Infrared Dermal Thermography and Leukocyte Count for Diabetic Foot Infection Diagnosis
Infrared Dermal Thermography and Leukocyte Count in Diabetic Foot Infection Diagnosis
DOI:
https://doi.org/10.60787/tnhj.v24i3.850Keywords:
Temperature, Leukocyte Count, Infrared Dermal Thermography, Diagnosis, Diabetic Foot InfectionAbstract
Background: Diabetic foot infections (DFIs) are a major complication of diabetes, often leading to severe outcomes like amputation. Accurate and timely diagnosis is crucial for effective management. This study compares two diagnostic methods—Infrared Dermal Thermography (IDT) and leukocyte count (LC)—with the gold standard of clinical assessment for detecting DFIs.
Method: A total of 100 patients with suspected diabetic foot infections (DFIs) were evaluated using both Infrared Dermal Thermography (IDT) and leukocyte count (LC). This study employed a quasi-experimental cross-over design, allowing each participant to serve as their own control by undergoing both diagnostic methods in different sequences. Diagnostic accuracy was determined by calculating sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), using clinical confirmation of infection as the gold standard. Foot temperatures were measured using a thermal camera, while leukocyte counts were obtained from blood samples. Data were analyzed using logistic regression to assess the predictive power of both IDT and LC. Prior to logistic regression, multicollinearity was evaluated using the variance inflation factor (VIF), and the goodness-of-fit was assessed with the Hosmer-Lemeshow test. The Box-Tidwell procedure was applied to test the assumption of linearity between continuous independent variables and the logit. Both methods showed significant predictive power for DFI diagnosis, with a significance level set at 0.05.
Result: IDT showed a sensitivity of 90%, specificity of 80%, PPV of 82%, and NPV of 89%. LC had a sensitivity of 80%, specificity of 70%, PPV of 73%, and NPV of 78%. Regression analysis indicated that while both methods were significant, LC demonstrated a higher predictive strength (regression coefficient: 0.60) compared to IDT (0.45).
Conclusion: IDT is a valuable tool for early DFI detection, complementing LC. Integrating both methods could improve diagnostic accuracy, although further research with larger sample sizes is necessary to refine these findings and their clinical applications.
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