Human Wound and Its Burden: Updated 2020 Compendium of Estimates

Chronic wounds have risen to epidemic proportions in the United States and can have an emotional, physical, and financial toll on patients. By leveraging data within the electronic health record (EHR), machine learning models offer the opportunity to facilitate earlier identification of wounds at risk of not healing or healing after an abnormally long time, which may improve treatment decisions and patient outcomes. Machine learning models in this study were built to predict chronic wound healing time. ApproachMachine learning models were developed using EHR data to predict patients at risk of having wounds not heal within 4, 8, and 12 weeks from the start of treatment. The models were trained on three data sets of 1,220,576 wounds, including 187 covariates describing patient demographics, comorbidities, and wound characteristics.

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Introduction: Wounds are associated with ranges of simple to complex disruption or damage to anatomical structure and function. They are also associated with enormous economic and social costs, increasing yearly, resulting in a severe impact on the wellbeing of individuals and society. Technology that might accelerate wound healing is associated with many benefits to injured people. Methods: BALBc mice underwent symmetrical excisional wounds through the panniculus carnosus. They were divided into a treatment group placed on an autonomous ceramic far-field infrared blanket (cIFRB) and a control group maintained under standard conditions. We also expanded and cultured adipose tissue-derived mesenchymal stem cells (MSCs) on cIFRB and compared them to standard conditions subjected to a scratch injury to compare survival, proliferation, and wound healing. Results: The wound healing of the cIRFB treatment group was significantly faster than the control group of mice. The wound-healing effect of mesenchymal stem cells on cIRFB was also increased and associated with significant migration to the wound area. Conclusions: Wound healing is improved in a mouse model exposed to cFIRB. The ceramic blanket also promotes survival, proliferation, increased migration, and wound healing of MSCs without affecting their survival and proliferation. The utilization of cFIRB in cellular biology and medical applications may be promising in many situations currently explored in animal and human models. This technology needs no direct or battery power source and is entirely autonomous and noninvasive, making its application possible in any environment.