Neurorehabilitation and neural repair · 2026
Individualized Prediction of Upper Limb Strength Recovery After Cervical Spinal Cord Injury: Development and Validation of Simple Prognostic Models.
СтатьяМногоцентровое исследованиеВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Furlan Leonardo, Russo Thiago Luiz
Аннотация
BACKGROUND: Early accurate prediction of upper limb strength recovery after cervical spinal cord injury (SCI) can optimize rehabilitation and research practices. However, no adequately validated, individualized prognostic model exists.
OBJECTIVE: To develop and validate individual prognostic models for predicting Upper Extremity Motor Score (UEMS) recovery after cervical SCI.
METHODS: We developed and internally validated prognostic models using data from 423 patients from the European Multicenter Study about Spinal Cord Injury (EMSCI) collaboration. Predictors included UEMS at week 1/week 4 and American Spinal Injury Association Impairment Scale (AIS) category. Ordinal regression models to predict UEMS at 4, 12, 24, and 48 weeks were developed and internally validated using bootstrap-based stability plots. External validation of the 12-week model was performed using a North American cohort of 365 patients. Performance metrics included overall fit and calibration.
RESULTS: Internal validation showed stable predictions, good and stable calibration curves, and low prediction errors for all models. At external validation, the model demonstrated good overall fit (R2 = .81, 95% confidence interval [CI] [0.77 to 0.85]; MAPE = 4.77, 95% CI [4.28 to 5.28]), and good calibration (intercept = 1.10, 95% CI [-0.08 to 2.41]; slope = 1.01, 95% CI [0.97 to 1.05]). The calibration curve indicated a minor underestimation of UEMS for lower predicted values.
CONCLUSIONS: Simple individualized prognostic models based solely on AIS category and early UEMS allow accurate predictions of upper limb strength recovery after cervical SCI. Our models contribute to expanding the existing literature on motor recovery patterns and prognosis/prediction after cervical SCI. If further validated, these models can inform early clinical decision-making, patient referral and counselling, and clinical trial eligibility.
OBJECTIVE: To develop and validate individual prognostic models for predicting Upper Extremity Motor Score (UEMS) recovery after cervical SCI.
METHODS: We developed and internally validated prognostic models using data from 423 patients from the European Multicenter Study about Spinal Cord Injury (EMSCI) collaboration. Predictors included UEMS at week 1/week 4 and American Spinal Injury Association Impairment Scale (AIS) category. Ordinal regression models to predict UEMS at 4, 12, 24, and 48 weeks were developed and internally validated using bootstrap-based stability plots. External validation of the 12-week model was performed using a North American cohort of 365 patients. Performance metrics included overall fit and calibration.
RESULTS: Internal validation showed stable predictions, good and stable calibration curves, and low prediction errors for all models. At external validation, the model demonstrated good overall fit (R2 = .81, 95% confidence interval [CI] [0.77 to 0.85]; MAPE = 4.77, 95% CI [4.28 to 5.28]), and good calibration (intercept = 1.10, 95% CI [-0.08 to 2.41]; slope = 1.01, 95% CI [0.97 to 1.05]). The calibration curve indicated a minor underestimation of UEMS for lower predicted values.
CONCLUSIONS: Simple individualized prognostic models based solely on AIS category and early UEMS allow accurate predictions of upper limb strength recovery after cervical SCI. Our models contribute to expanding the existing literature on motor recovery patterns and prognosis/prediction after cervical SCI. If further validated, these models can inform early clinical decision-making, patient referral and counselling, and clinical trial eligibility.