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Abstrato

An Evaluation of the New Step Algorithm for Diagnosing Proximal Orthopedic Conditions Utilizing Plantar Foot Force

Jonathan Rosenblum, Maeve Corcoran, Kwame Doh, Grant Yonemoto, Simran Bains, Milad Kashani, Gia Cat Pham, Samantha Dunn

The authors review a new algorithm relating plantar foot forces with the development of proximal orthopedic maladies. The algorithm divides the foot into a number of discreet areas and the relationship between the forces applied to each area both ipsilaterally as well as contralaterally feed the evaluation. In addition, deviation of the center of gravity plays a role in evaluation of the algorithm. The authors present a blinded study with 200 subjects all presenting with proximal orthopedic complaints including knee pain, low back or hip pain, or upper back or neck pain. The evaluator scored 90% in positively predicting the subject’s complaints, based on their foot scan. The results were independent of age, gender, or number of complaints presented by the subjects. The evaluator utilized strict adherence to the terms of the Newstep algorithm when making his diagnoses, and was encouraged not to overdiagnose. The algorithm is used by Newstep to develop a treatment protocol utilizing their active system. While this study did not evaluate the treatment aspect of the Newstep algorithm, the one to one relationship between the diagnostic aspect and therapeutic aspect, point to the fact that the treatment utilizing Newstep would also be efficacious.