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Predicting Upper Limb Motor Impairment Recovery after Stroke: A Mixture Model.
van der Vliet, Rick; Selles, Ruud W; Andrinopoulou, Eleni-Rosalina; Nijland, Rinske; Ribbers, Gerard M; Frens, Maarten A; Meskers, Carel; Kwakkel, Gert.
Afiliação
  • van der Vliet R; Department of Neuroscience, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Selles RW; Department of Rehabilitation Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Andrinopoulou ER; Department of Rehabilitation Medicine, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Nijland R; Department of Plastic and Reconstructive Surgery, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Ribbers GM; Rijndam Rehabilitation Center, Rotterdam, the Netherlands.
  • Frens MA; Department of Biostatistics, Erasmus University Medical Center, Rotterdam, the Netherlands.
  • Meskers C; Department of Rehabilitation Medicine, Amsterdam University Medical Centre, VU University Medical Center, Amsterdam Neurosciences and Amsterdam Movement Sciences, Amsterdam, the Netherlands.
  • Kwakkel G; Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, IL.
Ann Neurol ; 87(3): 383-393, 2020 03.
Article em En | MEDLINE | ID: mdl-31925838
OBJECTIVE: Spontaneous recovery is an important determinant of upper extremity recovery after stroke and has been described by the 70% proportional recovery rule for the Fugl-Meyer motor upper extremity (FM-UE) scale. However, this rule is criticized for overestimating the predictability of FM-UE recovery. Our objectives were to develop a longitudinal mixture model of FM-UE recovery, identify FM-UE recovery subgroups, and internally validate the model predictions. METHODS: We developed an exponential recovery function with the following parameters: subgroup assignment probability, proportional recovery coefficient r k , time constant in weeks τ k , and distribution of the initial FM-UE scores. We fitted the model to FM-UE measurements of 412 first-ever ischemic stroke patients and cross-validated endpoint predictions and FM-UE recovery cluster assignment. RESULTS: The model distinguished 5 subgroups with different recovery parameters ( r1 = 0.09, τ1 = 5.3, r2 = 0.46, τ2 = 10.1, r3 = 0.86, τ3 = 9.8, r4 = 0.89, τ4 = 2.7, r5 = 0.93, τ5 = 1.2). Endpoint FM-UE was predicted with a median absolute error of 4.8 (interquartile range [IQR] = 1.3-12.8) at 1 week poststroke and 4.2 (IQR = 1.3-9.8) at 2 weeks. Overall accuracy of assignment to the poor (subgroup 1), moderate (subgroups 2 and 3), and good (subgroups 4 and 5) FM-UE recovery clusters was 0.79 (95% equal-tailed interval [ETI] = 0.78-0.80) at 1 week poststroke and 0.81 (95% ETI = 0.80-0.82) at 2 weeks. INTERPRETATION: FM-UE recovery reflects different subgroups, each with its own recovery profile. Cross-validation indicates that FM-UE endpoints and FM-UE recovery clusters can be well predicted. Results will contribute to the understanding of upper limb recovery patterns in the first 6 months after stroke. ANN NEUROL 2020;87:383-393 Ann Neurol 2020;87:383-393.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Valor Preditivo dos Testes / Recuperação de Função Fisiológica / Transtornos Motores / Modelos Neurológicos Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Valor Preditivo dos Testes / Recuperação de Função Fisiológica / Transtornos Motores / Modelos Neurológicos Idioma: En Ano de publicação: 2020 Tipo de documento: Article