{"title":"慢性中风的超臂能力:通过臂效率评估麻痹性臂不使用-一项横断面研究。","authors":"Gaël Le Perf, Germain Faity, Denis Mottet, Makii Muthalib, Isabelle Laffont, Karima Bakhti","doi":"10.1177/15459683241303691","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>After a stroke, the use of the paretic arm is determined by its capacity (what it can or cannot do). When both arms have capacity to perform a task, the choice of which arm to use must be based on another criterion, probably by comparing the efficiency of each arm. Two numerical models account for this: the capacity model (the paretic arm is chosen in preference) and the efficiency model (the most efficient arm is chosen).</p><p><strong>Objective: </strong>To numerically determine whether capacity or efficiency best predict the use of the paretic arm in activities of daily living.</p><p><strong>Methods: </strong>We performed numerical simulations to predict paretic arm use with either the capacity model or the efficiency model. We used the Bayesian Information Criterion (BIC) to compare the adequacy of the 2 models in predicting clinical and accelerometric data collected from 30 patients with chronic stroke.</p><p><strong>Results: </strong>The efficiency model predicted arm use in activities of daily living better than the capacity model (BIC = -66.95 vs -5.89; root mean square error = 0.26 vs 0.72).</p><p><strong>Conclusions: </strong>The study highlights the importance of considering efficiency when assessing paretic arm non-use. Assessing individuals' arm efficiency should help personalize rehabilitation strategies after stroke.</p>","PeriodicalId":94158,"journal":{"name":"Neurorehabilitation and neural repair","volume":" ","pages":"15459683241303691"},"PeriodicalIF":0.0000,"publicationDate":"2024-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Beyond Arm Capacity in Chronic Stroke: Evaluating Paretic Arm Non-Use Through Arm Efficiency-A Cross-Sectional Study.\",\"authors\":\"Gaël Le Perf, Germain Faity, Denis Mottet, Makii Muthalib, Isabelle Laffont, Karima Bakhti\",\"doi\":\"10.1177/15459683241303691\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>After a stroke, the use of the paretic arm is determined by its capacity (what it can or cannot do). When both arms have capacity to perform a task, the choice of which arm to use must be based on another criterion, probably by comparing the efficiency of each arm. Two numerical models account for this: the capacity model (the paretic arm is chosen in preference) and the efficiency model (the most efficient arm is chosen).</p><p><strong>Objective: </strong>To numerically determine whether capacity or efficiency best predict the use of the paretic arm in activities of daily living.</p><p><strong>Methods: </strong>We performed numerical simulations to predict paretic arm use with either the capacity model or the efficiency model. We used the Bayesian Information Criterion (BIC) to compare the adequacy of the 2 models in predicting clinical and accelerometric data collected from 30 patients with chronic stroke.</p><p><strong>Results: </strong>The efficiency model predicted arm use in activities of daily living better than the capacity model (BIC = -66.95 vs -5.89; root mean square error = 0.26 vs 0.72).</p><p><strong>Conclusions: </strong>The study highlights the importance of considering efficiency when assessing paretic arm non-use. Assessing individuals' arm efficiency should help personalize rehabilitation strategies after stroke.</p>\",\"PeriodicalId\":94158,\"journal\":{\"name\":\"Neurorehabilitation and neural repair\",\"volume\":\" \",\"pages\":\"15459683241303691\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-12-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neurorehabilitation and neural repair\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/15459683241303691\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Neurorehabilitation and neural repair","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/15459683241303691","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
背景:中风后,瘫痪手臂的使用取决于其能力(能做什么或不能做什么)。当两只手臂都有能力完成某项任务时,选择使用哪只手臂必须基于另一个标准,可能是比较每只手臂的效率。对此有两种数字模型:能力模型(优先选择瘫痪的手臂)和效率模型(选择效率最高的手臂):目的:通过数值计算确定是能力还是效率最能预测日常生活中使用瘫痪手臂的情况:我们进行了数值模拟,用能力模型或效率模型预测瘫痪手臂的使用情况。我们使用贝叶斯信息标准(BIC)比较了两种模型在预测 30 名慢性中风患者的临床和加速度数据方面的充分性:结果:效率模型对日常生活中手臂使用情况的预测优于能力模型(BIC = -66.95 vs -5.89;均方根误差 = 0.26 vs 0.72):该研究强调了在评估瘫痪患者手臂不使用情况时考虑效率的重要性。结论:该研究强调了在评估瘫痪者手臂不使用情况时考虑效率的重要性,评估个人的手臂效率应有助于制定中风后的个性化康复策略。
Beyond Arm Capacity in Chronic Stroke: Evaluating Paretic Arm Non-Use Through Arm Efficiency-A Cross-Sectional Study.
Background: After a stroke, the use of the paretic arm is determined by its capacity (what it can or cannot do). When both arms have capacity to perform a task, the choice of which arm to use must be based on another criterion, probably by comparing the efficiency of each arm. Two numerical models account for this: the capacity model (the paretic arm is chosen in preference) and the efficiency model (the most efficient arm is chosen).
Objective: To numerically determine whether capacity or efficiency best predict the use of the paretic arm in activities of daily living.
Methods: We performed numerical simulations to predict paretic arm use with either the capacity model or the efficiency model. We used the Bayesian Information Criterion (BIC) to compare the adequacy of the 2 models in predicting clinical and accelerometric data collected from 30 patients with chronic stroke.
Results: The efficiency model predicted arm use in activities of daily living better than the capacity model (BIC = -66.95 vs -5.89; root mean square error = 0.26 vs 0.72).
Conclusions: The study highlights the importance of considering efficiency when assessing paretic arm non-use. Assessing individuals' arm efficiency should help personalize rehabilitation strategies after stroke.