Biomarkers of chronic kidney disease-mineral bone disorder (CKD-MBD) in the diabetic foot: A medical record review

Jones, Michael A.; George, Tyler S.; Bullock, Garrett S.; Sikora, Rebecca R.; Vesely, Bryanna D.; Sinacore, David R.

doi:10.1016/j.diabres.2022.110160

Cited by 2 publications

(3 citation statements)

References 22 publications

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Section: Discussionmentioning

confidence: 99%

“…Diabetic chronic kidney disease (CKD) leads to gradual injuries of the skeletal and vascular systems, giving rise to a complex condition referred to as chronic kidney disease-mineral bone disorder (CKD-MBD) [ 23 , 24 ]. The development of these features may begin as early as stage 2 chronic kidney disease (CKD) and often becomes apparent once the estimated glomerular filtration rate (eGFR) drops below 60 mL/min/1.73 m 2 , which corresponds to stage 3 CKD [ 23 ]. In a study on patients with diabetic neuropathic feet, specific biomarkers, such as the presence of peripheral neuropathy, the calcification of pedal vessels, and a decrease in the metatarsals’ capacity to withstand bending forces, supported the presence of CKD-MBD syndrome.…”

Section: Discussionmentioning

confidence: 99%

“…In a study on patients with diabetic neuropathic feet, specific biomarkers, such as the presence of peripheral neuropathy, the calcification of pedal vessels, and a decrease in the metatarsals’ capacity to withstand bending forces, supported the presence of CKD-MBD syndrome. Furthermore, the frequency of single-foot biomarkers, as well as combinations of two- and three-foot biomarkers, exhibits an upward trend as chronic kidney disease (CKD) advances through its stages [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

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Survival Prediction in Diabetic Foot Ulcers: A Machine Learning Approach

Popa,

Gavril,

Popa

et al. 2023

JCM

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Our paper proposes the first machine learning model to predict long-term mortality in patients with diabetic foot ulcers (DFUs). The study includes 635 patients with DFUs admitted from January 2007 to December 2017, with a follow-up period extending until December 2020. Two multilayer perceptron (MLP) classifiers were developed. The first MLP model was developed to predict whether the patient will die in the next 5 years after the current hospitalization. The second MLP classifier was built to estimate whether the patient will die in the following 10 years. The 5-year and 10-year mortality models were based on the following predictors: age; the University of Texas Staging System for Diabetic Foot Ulcers score; the Wagner–Meggitt classification; the Saint Elian Wound Score System; glomerular filtration rate; topographic aspects and the depth of the lesion; and the presence of foot ischemia, cardiovascular disease, diabetic nephropathy, and hypertension. The accuracy for the 5-year and 10-year models was 0.7717 and 0.7598, respectively (for the training set) and 0.7244 and 0.7087, respectively (for the test set). Our findings indicate that it is possible to predict with good accuracy the risk of death in patients with DFUs using non-invasive and low-cost predictors.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Survival Prediction in Diabetic Foot Ulcers: A Machine Learning Approach

Popa,

Gavril,

Popa

et al. 2023

JCM

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Major adverse foot events and functional mobility deficits associated with diabetic neuropathy and nephropathy

Sinacore,

Jones,

Kline

2024

Metab Target Organ Damage

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Aim: The purpose is to determine the risk ratios (RR) for both major adverse foot events (MAFEs) and the presence of moderate and severe functional mobility deficits in participants with diabetic peripheral neuropathy across the stages of chronic kidney disease (CKD). Methods: We studied 284 participants with diabetes mellitus, peripheral neuropathy, and CKD. MAFEs including foot fracture, ulcerations, Charcot neuropathic arthropathy (CN), osteomyelitis, and minor foot amputations were collected from foot x-ray reports in the medical records of 152 participants; functional mobility deficits were assessed in 132 participants using the modified physical performance test (mPPT). Moderate mobility deficit was categorized as mPPT scores 22-29 and severe mobility deficit as < 22. Unadjusted and adjusted (age, body weight, race, HbA1c) RR were calculated across each stage of CKD, with stage 1 CKD used as the reference group. Results: The RR for neuropathic foot fracture, CN, and diabetic foot ulceration remained consistent across CKD stages. The RR of minor amputation is greater in CKD stages 4 and 5. The RR of moderate or severe mobility deficit is greater in CKD stages 3 and 5 and in CKD stages 3, 4, and 5, respectively. An inverse association was observed between MAFE prevalence and mPPT scores across CKD stages. Conclusion: Major adverse foot events and functional mobility deficits are prevalent in individuals with DPN and diabetic kidney disease. The risks for minor foot amputation and functional mobility deficits increase as early as stage 3 CKD and increase further in stages 4 and 5.

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Biomarkers of chronic kidney disease-mineral bone disorder (CKD-MBD) in the diabetic foot: A medical record review

Cited by 2 publications

References 22 publications

Survival Prediction in Diabetic Foot Ulcers: A Machine Learning Approach

Survival Prediction in Diabetic Foot Ulcers: A Machine Learning Approach

Major adverse foot events and functional mobility deficits associated with diabetic neuropathy and nephropathy

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