Predict probability of being unable to walk independently during follow up in patients with Guillain-Barré syndrome. Score taken at hospital admission.
The mEGOS is a clinical prediction model that can be applied early in the course of disease to predict the probability of being unable to walk independently during the first six months of follow up, in individual patients with Guillain-Barré syndrome.
The score is developed and validated using prospectively collected data from a Dutch GBS cohort, and recently showed good performance in a GBS cohort from Japan.
Age at onset of neurological symptoms, preceding diarrhoea and severity of muscle weakness (at hospital admission, and at day 7 of admission) defined by the MRC sum score were independently associated with the ability to walk independently during the first six months of follow up. Two logistic regression models were generated based on these risk factors:
Walgaard C, Lingsma HF, Ruts L, van Doorn PA, Steyerberg EW, Jacobs BC.
Yamagishi Y, Suzuki H, et al.
Age at the development of first symptoms.
The mEGOS is a clinical prediction model that can be applied early in the course of disease to predict the probability of being unable to walk independently during the first six months of follow up, in individual patients with Guillain-Barré syndrome.
The score is developed and validated using prospectively collected data from a Dutch GBS cohort, and recently showed good performance in a GBS cohort from Japan.
Age at onset of neurological symptoms, preceding diarrhoea and severity of muscle weakness (at hospital admission, and at day 7 of admission) defined by the MRC sum score were independently associated with the ability to walk independently during the first six months of follow up. Two logistic regression models were generated based on these risk factors:
Walgaard C, Lingsma HF, Ruts L, van Doorn PA, Steyerberg EW, Jacobs BC.
Yamagishi Y, Suzuki H, et al.
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