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Association between functional performance and hip muscle torque with Patellofemoral Pain: A multicenter prospective study.

Abstract

Patellofemoral Pain (PFP) is a musculoskeletal knee disorder characterized by retropatellar or peripatellar pain, which is exacerbated during functional tasks (e.g., sitting, stair ascent or descent, jumping, and landing). PFP affects approximately one in four young adults, and symptoms may persist for up to 20 years after diagnosis. There is evidence that PFP may precede clinical signs of patellofemoral osteoarthritis in later stages. In the general population, chronic symptoms (¿ 3 months) are associated with deficits in muscle strength, alterations in movement mechanics, and reduced functional capacity. Nevertheless, evidence regarding the factors related to the development of PFP in young adults remains inconclusive. Hip strength has been described both as a cause and a consequence of PFP; given its role in knee biomechanics, clarifying this relationship is crucial for prevention and early treatment strategies. Quadriceps weakness, in turn, emerges as one of the few consistent risk factors, although most findings are based on isokinetic dynamometry, restricted to research settings, which limits the clinical applicability of risk assessment. Low-cost and more accessible alternatives, such as functional tests targeting the knee, may enable the prediction of PFP risk in young adults across different clinical contexts; however, this possibility still requires investigation. In this context, 300 men and women aged 18 to 35 years are being assessed across five research centers in Brazil and the United States. Data on knee-related functional performance and isometric and isokinetic hip torque of both lower limbs are being collected. Participants are being followed for two years to monitor the development of PFP. Subsequently, those who develop PFP will be reassessed within three months of symptom onset for hip muscle torque and compared with matched asymptomatic participants. Predictive modeling analyses (e.g., classification and regression trees) and generalized estimating equations will be conducted. (AU)

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VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)