# Analysis of Clinical Profiles, Deformities, and Plantar Pressure Patterns in Diabetic Foot Syndrome
## 4 Discussion  
Diabetic foot syndrome has long been investigated, since it represents a major complication of diabetes mellitus [21; 22]. The disease is associated with very high clinical and economic burden [23], a strong negative impact on quality of life [24], and high rates of hospitalization in type 2 diabetes [25]. The International Working Group on Diabetic Foot (IWGDF) defined this syndrome as \"infection, ulceration, or destruction of tissues of the foot of a person with currently or previously diagnosed diabetes mellitus, usually accompanied by neuropathy and/or peripheral arterial disease in the lower extremity\" [26]. Besides neuropathy [25; 27] and different manifestations of vascular diseases [28; 29], many complex alterations occur at the clinical, biological, or behavioral level, which contribute to the development of these foot complications [30; 31; 32]. Up to 79 risk factors have been retrieved and reported by [PERSON] et al. [27]. Despite the huge progresses in clinical and biomechanical research and relevant technology [21; 33; 34; 35; 36; 37], deeper knowledge, more evidence and general validity, and a larger consensus are needed to effectively model as many risk factors as possible, and to predict the many alterations observed in patients, both in the foot structure and function [4; 5; 6; 7; 8; 9; 10; 12]. Figure 7: Weight-bearing CT parameters in three patients with lesions: % of parameters outside the 95% confidence interval of each parameter, for the DNT1 (7 patients) and the DNNT1 (8 patients) subgroups. For each parameter and patient with lesion, the number of values above and below the interval have been counted separately. The count is reported for each anatomical plane and for the 3D parameters. The present study focused on a small part of this complex process of correlation and modeling. Namely, the core of the study was the hypothesis that an appropriate stratification of patients with diabetes prior to implementing a predictive model might help reduce the variability of the most relevant parameters and improve intra-group correlations. In particular, it was hypothesized that subgroups defined according to type of diabetes, presence or absence of neuropathy, and presence or absence of obesity may support a better identification of relevant clinical, biological, structural, functional, and biomechanical profiles and patterns. The study was observational, with a thorough clinical, functional, and biomechanical assessment conducted in 2016. However, a 48-month follow-up made it possible to address two additional relevant questions, namely whether baseline profiles and patterns could at least partially explain the onset of plantar lesions, whether two important clinical aspects--peripheral neuropathy level at baseline and the trend of glycated hemoglobin during follow-up--might have a concurrent role in the ulceration process. The study showed that patients with diabetes should be stratified for both presence of neuropathy and diabetes type. Six groups of patients were analyzed, and their profiles and patterns were remarkably different (Table 3, Figures 2-6). Differences occurred not only with respect to a number of largely expected variables, for example age and gait performance between T1 and T2, but also with respect to clinical variables among the neuropathic groups, or biomechanical variables in corresponding (i.e., non-obese) groups. It is worth mentioning that type 2 subgroups showed peculiarities related to the presence of neuropathy and/or obesity, but they still showed high intra-group variability of the parameters, greater than in type 1 groups. The only exception was for the non-obese and non-neuropathic type 2 patients. This group, however, consisted of seven patients only, thus requiring confirmation in wider studies. While these specific profiles allow for modeling of foot alterations within each group, the high variability definitely calls for more studies and a more inclusive set of variables.