A Model to Predict Outcome of The Diabetic Foot? A Nine State Solution.

Superb work from our SALSAmigos in Soest and Duesseldorf.

Understanding that diabetic foot complications are lifetime conditions– and not just individual events fundamentally changes how we might model outcomes and care.

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Study of Disease Progression and Relevant
Risk Factors in Diabetic Foot Patients Using a
Multistate Continuous-Time Markov Chain


Alexander Begun1*, Stephan Morbach1,2, Gerhard Rümenapf3, Andrea Icks1,4

The diabetic foot is a lifelong disease. The longer patients with diabetes and foot ulcers are observed, the higher the likelihood that they will develop comorbidities that adversely influence ulcer recurrence, amputation and survival (for example peripheral arterial disease, renal failure or ischaemic heart disease). The purpose of our study was to quantify person and limb-related disease progression and the time-dependent influence of any associated factors (present at baseline or appearing during observation) based on which effective prevention and/or treatment strategies could be developed. Using a nine-state continuous-time Markov chain model with time-dependent risk factors, all living patients were divided into eight groups based on their ulceration (previous or current) and previous amputation (none, minor or major) status. State nine is an absorbing state (death). If all transitions are fully observable, this model can be decomposed into eight submodels, which can be analyzed using the methods of survival analysis for competing risks. The dependencies of the risk factors (covariates) were included in the submodels using Cox-like regression. The transition intensities and relative risks for covariates were calculated from long-term data of patients with diabetic foot ulcers collected in a single specialized center in North-Rhine Westphalia (Germany). The detected estimates were in line with previously published, but scarce, data. Together with the interesting new results obtained, this indicates that the proposed model may be useful for studying disease progression in larger samples of patients with diabetic foot ulcers.


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