Aplicação de rede neural auto-organizada na análise cinemática da marcha e sua associação com a intensidade da dor em mulheres com dor femoropatelar

Abstract

Introduction: Patellofemoral pain (PFP) is a prevalent musculoskeletal disorder, particularly among women, with an estimated incidence rate of 29.2%. PFP is associated with motor adaptations during gait. However, the relationship between movement deviations and pain intensity remains not fully understood. The Movement Deviation Profile (MDP) has proven to be an effective tool for identifying kinematic differences between women with and without PFP, offering an innovative approach to simplify complex kinematic data. Using the MDP to assess gait changes and correlate them with pain intensity could represent an important strategy in the rehabilitation of patients with PFP. Objective: Investigate the association between the MDP and pain intensity in women with PFP during gait. Methods: This retrospective study included data from 571 women with PFP and 571 asymptomatic women matched by age, year, and height, collected between 2012 and 2020. Participants with PFP reported retro or peripatellar pain for at least three months, with a minimum intensity of 3 on the Visual Analog Scale (VAS). Gait was assessed using eight cameras Vicon capture system, with data processed through the Plug-in Gait model and Vicon Nexus 2.14 software. The MDP was used to quantify gait deviations in the PFP group compared to the pain free group. The mean and confidence interval of the VAS was 6.03 (5.91–6.15), while the mean and confidence interval of the MDP (MDPmean) was 13.17 (12.73°–13.61°). Results: A strong positive correlation (r = 0.959, p < 0.001) was observed between pain intensity and MDPmean, suggesting that higher levels of pain are associated with greater gait deviations. Discussion: Pain can alter movement, and tools such as the MDP are crucial for assessing gait deviations and correlating them with pain intensity in patients with PFP. The findings suggest that reported pain intensity is associated with different levels of gait alterations. These changes may be a natural response to chronic pain but could also contribute to the worsening of function and quality of life in patients with PFP. Detailed analysis of movement deviations, as conducted with the MDP, provides valuable information for developing more precise and effective clinical interventions aimed at improving mobility and reducing pain. Clinically, PFP involves various adaptations that affect motor function and quality of life, emphasizing the need for quantitative methods such as the MDP to better understand the magnitude of these changes and their implications. Conclusion: This study highlights the importance of integrating movement analysis into clinical evaluations, providing a solid foundation for implementing targeted therapeutic strategies that can restore function and improve long-term outcomes. The use of the MDP can be a significant differentiator in personalizing treatments and optimizing rehabilitation, allowing for more precise monitoring of pain progression and motor adaptations during the treatment of PFP.