{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,20]],"date-time":"2026-08-20T23:12:49Z","timestamp":1787267569068,"version":"build-2736575974"},"reference-count":33,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,1,4]],"date-time":"2024-01-04T00:00:00Z","timestamp":1704326400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:sec><jats:title>Introduction<\/jats:title><jats:p>Longitudinal observations of upper limb motor recovery after stroke have suggested that certain subgroups may exhibit distinct recovery patterns. Here we sought to examine whether the predictive ability for post-stroke upper limb motor outcomes could be enhanced by applying conventional stratification strategies.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>For 60 individuals who suffered the first stroke, upper limb motor impairment was assessed with the upper extremity Fugl-Meyer assessment (UE-FMA) at 2 weeks as a baseline and then 3 months post-stroke. Brain structural damage at baseline was assessed by MRI data-derived markers ranging from traditional lesion size to the lesion load and to the disconnectome. Linear regression models for predicting upper limb motor outcomes (UE-FMA score at 3 months post-stroke) based on baseline upper limb motor impairment (UE-FMA score at 2 weeks post-stroke), brain structural damage, and their combinations were generated, and those with the best predictive performance were determined for individual subgroups stratified according to initial impairment (severe and non-severe), lesion location (cortical and non-cortical), and neurophysiological status (motor evoked potential-positive and motor evoked potential-negative).<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The best predictions were made by baseline upper limb motor impairment alone for subgroups with less functional impairment (non-severe) or less structural involvement (non-cortical), but by the combination of baseline upper limb motor impairment and brain structural damage for the other subgroups. The predictive models tailored for subgroups determined according to initial impairment and neurophysiological status yielded a smaller overall error than that for the whole group in upper limb motor outcome predictions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Discussion<\/jats:title><jats:p>The predictive ability for upper limb motor outcomes could be enhanced beyond the one-size-fits-all model for all individuals with stroke by applying specific stratification strategies, with stratification according to initial impairment being the most promising. We expect that predictive models tailored for individual subgroups could lead closer to the personalized prognosis of upper limb motor outcomes after stroke.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fneur.2023.1323529","type":"journal-article","created":{"date-parts":[[2024,1,4]],"date-time":"2024-01-04T05:07:27Z","timestamp":1704344847000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Stratified predictions of upper limb motor outcomes after stroke"],"prefix":"10.3389","volume":"14","author":[{"given":"Chang-hyun","family":"Park","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min-Su","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2024,1,4]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1093\/brain\/awab439","article-title":"Precision medicine in stroke: towards personalized outcome predictions using artificial intelligence","volume":"145","author":"Bonkhoff","year":"2021","journal-title":"Brain"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1039794","DOI":"10.3389\/fneur.2023.1039794","article-title":"Machine learning prediction of motor function in chronic stroke patients: a systematic review and meta-analysis","volume":"14","author":"Li","year":"2023","journal-title":"Front Neurol"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1177\/1545968307305302","article-title":"Inter-individual variability in the capacity for motor recovery after ischemic stroke","volume":"22","author":"Prabhakaran","year":"2008","journal-title":"Neurorehabil Neural Repair"},{"key":"ref4","doi-asserted-by":"publisher","first-page":"614","DOI":"10.1177\/1545968314562115","article-title":"Generalizability of the proportional recovery model for the upper extremity after an ischemic stroke","volume":"29","author":"Winters","year":"2015","journal-title":"Neurorehabil Neural Repair"},{"key":"ref5","doi-asserted-by":"publisher","first-page":"2189","DOI":"10.1093\/brain\/awaa146","article-title":"Bringing proportional recovery into proportion: Bayesian modelling of post-stroke motor impairment","volume":"143","author":"Bonkhoff","year":"2020","journal-title":"Brain"},{"key":"ref6","doi-asserted-by":"publisher","first-page":"3097","DOI":"10.1007\/s10072-021-05600-9","article-title":"The predictive value of lesion and disconnectome loads for upper limb motor impairment after stroke","volume":"43","author":"Park","year":"2022","journal-title":"Neurol Sci"},{"key":"ref7","doi-asserted-by":"publisher","first-page":"860","DOI":"10.1002\/ana.24510","article-title":"Corticospinal tract lesion load: an imaging biomarker for stroke motor outcomes","volume":"78","author":"Feng","year":"2015","journal-title":"Ann Neurol"},{"key":"ref8","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1159\/000047650","article-title":"Recovery of motor functions following hemiparetic stroke: a clinical and magnetic resonance-morphometric study","volume":"11","author":"Binkofski","year":"2001","journal-title":"Cerebrovasc Dis"},{"key":"ref9","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1034\/j.1600-0404.2000.102006371.x","article-title":"Predicting arm recovery following stroke: value of site of lesion","volume":"102","author":"Feys","year":"2000","journal-title":"Acta Neurol Scand"},{"key":"ref10","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1161\/01.str.32.1.107","article-title":"Effect of lesion location on upper limb motor recovery after stroke","volume":"32","author":"FtdN","year":"2001","journal-title":"Stroke"},{"key":"ref11","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1161\/STROKEAHA.116.016020","article-title":"Proportional motor recovery after stroke: implications for trial design","volume":"48","author":"Stinear","year":"2017","journal-title":"Stroke"},{"key":"ref12","doi-asserted-by":"publisher","first-page":"1854","DOI":"10.1161\/01.str.29.9.1854","article-title":"Prognostic value of motor evoked potential obtained by transcranial magnetic brain stimulation in motor function recovery in patients with acute ischemic stroke","volume":"29","author":"JnV","year":"1998","journal-title":"Stroke"},{"key":"ref13","doi-asserted-by":"publisher","first-page":"13","DOI":"10.2340\/1650197771331","article-title":"The post-stroke hemiplegic patient. 1. 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