A new prediction model could change the way chronic wound patients are treated.

Nigam Shah is an associate professor of medicine at Stanford University. Recently, he began to examine just why people experience different rates of wound healing. For instance, younger people heal fairly quickly compared to the elderly. Additionally, some diseases and other health conditions can diminish the body’s natural healing capabilities.

To better understand this phenomenon, Shah and several colleagues launched an exhaustive study of medical records from a myriad of patients the world over. The results – published recently in the journal Wound Repair and Regeneration – have resulted in a new model for better diagnosing chronic or slow-healing wounds

Diving in

Shah, who specializes in biomedical informatics, recruited fellow Stanford research scientist Kenneth Jung for the lengthy study. Together with a group of graduate students and other assistants, the pair pored over a massive database with some 53,000 patients with a total of 150,000-plus wounds. Examining everything from surgical wounds to diabetic ulcers, the research team focused on a wide array of important variables, including the age of each patient and the dimensions – length, depth and breadth – of every wound.

Breaking new ground

Given the sheer amount of data and number of patients, the researchers placed every participant into one of two groups, according to Stanford’s Scope medical blog. The first was centered on a certain kind of control specifically testing previously unseen data sets. The other group, meanwhile, comprised of patients’ raw data, which the researchers then used to create an all-new predictive model for chronic or slow-healing wounds. According to the study itself, having two groups was instrumental in creating a model that would allow for early and accurate prediction across all wound types and patient backgrounds.

A promising future

So, just how successful was this new model of early wound healing detection? Of the 100 or so predictors the wound team identified, which includes patient age and wound dimensions, 95 percent of these were used to determine whether a wound was slow-healing or not. Perhaps one of the biggest predictors of a wound’s healing rate was the level of a patient’s palliative care. Additionally, a patient’s age and the depth of each wound were also especially noteworthy. The researchers also noted that the healing rate in the first week of recovery served as a particularly reliable predictor.

If there is one notable downside to Stanford’s new model, it’s that it can be somewhat limited. As the Scope blog explained, the model was developed to fit a single company of wound care clinics, making it suited for that very specific set of clients. However, as the team pointed out in the study, the model itself is still rather adaptable and flexible, and just needs to be configured to each group of new patients.

A need for change

A new predictive model is desperately needed within the greater wound care industry. A 2008 report from the European Wound Management Association found that doctors were missing vital information when diagnosing and treating wounds. While many physicians understood the biological factors associated with wound healing, there remains a distinct lack of understanding of the psychosocial components – like a patient’s emotions or general activities – that can influence the entire process. A separate report from Wounds International noted that it takes approximately four weeks to determine if a wound is healing. WI suggested using a checklist centered on establishing the presence of persistent inflammation, infection and ischaemia. However, all of those predictors may not be available, and that can complicate the prediction and overall healing approach.

It’s worth noting that many of the Stanford team’s findings echo those released in a 2001 study. However, those results – published in the journal Medical & Biological Engineering & Computing – only utilized 300 patient records. A fuller data set, like the Stanford team had, could indicate a much higher success rate among a larger number of people.

Continued quality

Predictive models have the ability to help millions of patients dealing with chronic or slow-healing wounds. But no matter how early the intervention might occur, every patient is still going to require the best medical care possible, which is why patients turn to Advanced Tissue. As the nation’s leader in the delivery of specialized wound care supplies, Advanced Tissue promptly ships supplies to individuals at home and in long-term care facilities.