| Summary: | Abstract Background It remains an urgent need for early recognition of disease severity, treatment option and outcome of Guillain-Barré syndrome (GBS). The chief complaint may be quickly obtained in clinic and is one of the candidates for early predictors. However, studies on the chief complaint are still lacking in GBS. The aim of the study is to describe the components of chief complaints of GBS patients, and to explore association between chief complaints and disease severity/treatment option/outcome of GBS, so as to aid the early prediction of the disease course and to assist the clinicians to prescribe an optimal early treatment. Methods A total of 523 GBS patients admitted to the First Hospital of Jilin University from 2003 to 2013 were enrolled for retrospective analysis. The data of chief complaints, clinical manifestations, and treatment options, etc. were collected. The clinical severity was evaluated by the Medical Research Council sum score and the Hughes Functional Grading Scale. The prognosis at 6 month after discharge was described by modified Erasmus GBS outcome score. The clinic GBS severity evaluation scale (CGSES), a newly established model in our study, was used to explore the role of chief complaints to predict intravenous immunoglobulin (IVIg). Results The major components of the chief complaints of GBS patients were weakness, numbness, pain, cranial nerve involvement, dyspnea, ataxia and autonomic dysfunction. Chief complaint of weakness was a predictor of severe disease course and poor short-term outcome, while chief complaint of numbness and cranial nerve involvement were promising predictors. Cranial nerve involvement was the predictor of ventilator dependence. The percentages of 366 GBS patients, who need IVIg treatment at nadir with CGSES ranging from 1 to 4, were 50.00, 67.34, 80.61, and 90.67%, respectively. Conclusions Chief complaints are clinic predictors of disease severity, ventilator dependence and short-term outcome. IVIg treatment during hospitalisation could be predicted in clinic using CGSES score.
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