BACKGROUND: The design and manufacturing of effective foot orthoses is a complex multidisciplinary problem involving biomedical and gait pattern aspects, technical material and geometric design elements as well as psychological and social contexts. This complexity contributes to the current trial-and-error and experience-based orthopedic footwear practice in which a major part of the expertise is implicit. This hampers knowledge transfer, reproducibility and innovation. OBJECTIVE/METHODS: A systematic review of literature has been performed to find evidence of explicit knowledge, quantitative guidelines and design motivations of pedorthists. RESULTS: 17 studies have been included. No consensus is found on which measurable parameters ensure proper foot and ankle functioning. Parameters suggested are: neutral foot positioning and control of rearfoot motion, maximum arch, but also tibial internal/external rotation as well as a three point force system. Also studies evaluating foot orthoses centering on the diagnosis or orthosis type find no clear guidelines for treatment or for measuring the effectiveness. CONCLUSIONS: A gap in the translation from diagnosis to a specific, customized and quantified effective orthosis design is identified. Suggested solutions are both top-down, fitting of patient data in simulations, as well as bottom-up, quantifying current practices of pedorthists in order to develop new practical guidelines and evidence-based procedures.
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Ankle Foot Orthoses (AFOs) to promote walking ability are a common treatment in patients with neurological or muscular diseases. However, guidelines on the prescription of AFOs are currently based on a low level of evidence regarding their efficacy. Recent studies aiming to demonstrate the efficacy of wearing an AFO in respect to walking ability are not always conclusive. In this paper it is argued to recognize two levels of evidence related to the ICF levels. Activity level evidence expresses the gain in walking ability for the patient, while mechanical evidence expresses the correct functioning of the AFO. Used in combination for the purpose of evaluating the efficacy of orthotic treatment, a conjunct improvement at both levels reinforces the treatment algorithm that is used. Conversely, conflicting outcomes will challenge current treatment algorithms and the supposed working mechanism of the AFO. A treatment algorithm must use relevant information as an input, derived from measurements with a high precision. Its result will be a specific AFO that matches the patient's needs, specified by the mechanical characterization of the AFO footwear combination. It is concluded that research on the efficacy of AFOs should use parameters from two levels of evidence, to prove the efficacy of a treatment algorithm, i.e., how to prescribe a well-matched AFO.
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Background: Impaired upper extremity function due to muscle paresis or paralysis has a major impact on independent living and quality of life (QoL). Assistive technology (AT) for upper extremity function (i.e. dynamic arm supports and robotic arms) can increase a client’s independence. Previous studies revealed that clients often use AT not to their full potential, due to suboptimal provision of these devices in usual care. Objective: To optimize the process of providing AT for impaired upper extremity function and to evaluate its (cost-)effectiveness compared with care as usual. Methods: Development of a protocol to guide the AT provision process in an optimized way according to generic Dutch guidelines; a quasi-experimental study with non-randomized, consecutive inclusion of a control group (n = 48) receiving care as usual and of an intervention group (optimized provision process) (n = 48); and a cost-effectiveness and cost-utility analysis from societal perspective will be performed. The primary outcome is clients’ satisfaction with the AT and related services, measured with the Quebec User Evaluation of Satisfaction with AT (Dutch version; D-QUEST). Secondary outcomes comprise complaints of the upper extremity, restrictions in activities, QoL, medical consumption and societal cost. Measurements are taken at baseline and at 3, 6 and 9 months follow-up.
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