ArticleCureus2024
A Clinical Care Algorithm for Detecting Progression in Multiple Sclerosis: RetratEMos Project.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
objectiveThe diagnosis of secondary progressive multiple sclerosis (SPMS) is often established retrospectively leading to a delay in detection. This work presents a clinical care algorithm that aims to facilitate the recognition of the secondary progressive phase of the disease, analyzing its usefulness and the feasibility of its implementation in routine clinical practice.
methodsThe algorithm was developed in four phases: 1) choice of validated diagnostic tools for the detection of progression; 2) assessment of these tools based on experience of use, applicability, time consumed, perceived usefulness and suitability for a profile of a patient in transition to SPMS; 3) framework and final sequence of application; 4) feasibility evaluation through application in clinical practice.
resultsA hierarchical algorithm was developed with an initial screening phase to detect warning signs and establish suspicion of progression (which included the tests "Your Multiple Sclerosis (Your MS)," "MSProDiscuss," and "Nomogram") and a second phase conditional on a positive result in the first, including a functional examination with the Symbol Digit Modalities Test (SDMT), 9-Hole Peg Test (9-HPT), and Timed 25-Foot Walk (T25FW) tools. The algorithm was applied to 373 patients with Expanded Disability Status Scale (EDSS) ≥ 2. The mean time spent per patient in the screening was eight minutes and 20.4 minutes for the complete algorithm. The perceived usefulness of the process by the neurologists was 3.1 (range of 1-4, with 4 being the maximum). In 46% of the cases, the algorithm detected the need for additional functional exploration.
conclusionsFrom our experience, this clinical care algorithm is effective and feasible for detecting progression in MS, although its implementation requires proper organization and can be uneven depending on the resources of each center.
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