Surgical Treatment of Diabetic Foot and Ankle Osteomyelitis

Lower extremity infections: Essential anatomy and multimodality imaging findings

In modern practice, imaging plays an integral role in the diagnosis, evaluation of extent, and treatment planning for lower extremity infections. This review will illustrate the relevant compartment anatomy of the lower extremities and highlight the role of plain radiographs, CT, US, MRI, and nuclear medicine in the diagnostic workup. The imaging features of cellulitis, abscess and phlegmon, necrotizing soft tissue infection, pyomyositis, infectious tenosynovitis, septic arthritis, and osteomyelitis are reviewed. Differentiating features from noninfectious causes of swelling and edema are discussed.

Racial and Ethnic Disparities in the Management of Diabetic Feet

PURPOSE OF REVIEW

Diabetes mellitus is a chronic medical condition affecting many individuals worldwide and leads to billions of dollars spent within the healthcare system for its treatment and complications. Complications from diabetes include diabetic foot conditions that can have a devasting impact on quality of life. Diabetic foot ulcers and amputations occur in minority individuals at an increased rate compared to Caucasian individuals. This review provides an update examining the racial and ethnic disparities in the management of diabetic foot conditions and the differences in rates of amputation.

RECENT FINDINGS

Current research continues to show a disparity as it relates to diabetic foot management. There are novel treatment options for diabetic foot ulcers that are currently being explored. However, there continues to be a lack in racial diversity in new treatment studies conducted in the USA. Individuals from racial and ethnic minority groups have diabetes at higher rates compared to Caucasian individuals, and are also more likely to develop diabetic foot ulcers and receive amputations. Over the last few years, more efforts have been made to improve health disparities. However, there needs to be an improvement in increasing racial diversity when investigating new therapies for diabetic foot ulcers.

State-of-the-art update for diagnosing diabetic foot osteomyelitis: a narrative review

Recently, the International Working Group on the Diabetic Foot and the Infectious Diseases Society of America divided diabetic foot disease into diabetic foot infection (DFI) and diabetic foot osteomyelitis (DFO). DFI is usually diagnosed clinically, while numerous methods exist to diagnose DFO. In this narrative review, the authors aim to summarize the updated data on the diagnosis of DFO. An extensive literature search using "diabetic foot [MeSH]" and "osteomyelitis [MeSH]" or "diagnosis" was performed using PubMed and Google Scholar in July 2023. The possibility of DFO is based on inflammatory clinical signs, including the probe-to-bone (PTB) test. Elevated inflammatory biochemical markers, especially erythrocyte sedimentation rate, are beneficial. Distinguishing abnormal findings of plain radiographs is also a first-line approach. Moreover, sophisticated modalities, including magnetic resonance imaging and nuclear medicine imaging, are helpful if doubt remains after a first-line diagnosis. Transcutaneous bone biopsy, which does not pass through the wound, is necessary to avoid contaminating the sample. This review focuses on the current diagnostic techniques for DFOs with an emphasis on the updates. To obtain the correct therapeutic results, selecting a proper option is necessary. Based on these numerous diagnosis modalities and indications, the proper choice of diagnostic tool can have favorable treatment outcomes.

Predicting the Risk of Diabetic Foot Ulcers From Diabetics With Dysmetabolism: A Retrospective Clinical Trial

BACKGROUND

Diabetic foot ulcer (DFU) in patients with type 2 diabetes mellitus (T2D) often leads to amputation. Early intervention to prevent DFU is urgently necessary. So far, there have been no studies on predictive models associated with DFU risk factors. Our study aimed to quantify the predictive risk value of DFU, promote health education, and further develop behavioral interventions to reduce the incidence of DFU.

METHODS

Data from 973 consecutive patients with T2D was collected from two hospitals. Patients from the Guangxi Medical University First Affiliated Hospital formed the training cohort (n = 853), and those from the Wuming Hospital of Guangxi Medical University formed the validation cohort (n = 120). Independent variable grouping analysis and multivariate logistic regression analysis were used to determine the risk factors of DFUs. The prediction model was established according to the related risk factors. In addition, the accuracy of the model was evaluated by specificity, sensitivity, predictive value, and predictive likelihood ratio.

RESULTS

In total, 369 of the 853 patients (43.3%) and 60 of the 120 (50.0%) were diagnosed with DFUs in the two hospitals. The factors associated with DFU were old age, male gender, lower body mass index (BMI), longer duration of diabetes, history of foot disease, cardiac insufficiency, no use of oral hypoglycemic agent (OHA), high white blood cell count, high platelet count, low hemoglobin level, low lymphocyte absolute value, and high postprandial blood glucose. After incorporating these 12 factors, the nomogram drawn achieved good concordance indexes of 0.89 [95% confidence interval (CI): 0.87 to 0.91] in the training cohort and 0.84 (95% CI: 0.77 to 0.91) in the validation cohort in predicting DFUs and had well-fitted calibration curves. Patients who had a nomogram score of ≥180 were considered to have a low risk of DFU, whereas those having ≥180 were at high risk.

CONCLUSIONS

A nomogram was constructed by combining 12 identified risk factors of DFU. These 12 risk factors are easily available in hospitalized patients, so the prediction of DFU in hospitalized patients with T2D has potential clinical significance. The model provides a reliable prediction of the risk of DFU in patients with T2D.