Prediction of respiratory insufficiency in Guillain-Barré syndrome

Objective Respiratory insufficiency is a frequent and serious complication of the Guillain‐Barré syndrome (GBS). We aimed to develop a simple but accurate model to predict the chance of respiratory insufficiency in the acute stage of the disease based on clinical characteristics available at hospita...

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Vydáno v:Annals of neurology Ročník 67; číslo 6; s. 781 - 787
Hlavní autoři: Walgaard, Christa, Lingsma, Hester F., Ruts, Liselotte, Drenthen, Judith, van Koningsveld, Rinske, Garssen, Marcel J. P., van Doorn, Pieter A., Steyerberg, Ewout W., Jacobs, Bart C.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.06.2010
Wiley-Liss
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ISSN:0364-5134, 1531-8249, 1531-8249
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Shrnutí:Objective Respiratory insufficiency is a frequent and serious complication of the Guillain‐Barré syndrome (GBS). We aimed to develop a simple but accurate model to predict the chance of respiratory insufficiency in the acute stage of the disease based on clinical characteristics available at hospital admission. Methods Mechanical ventilation (MV) in the first week of admission was used as an indicator of acute stage respiratory insufficiency. Prospectively collected data from a derivation cohort of 397 GBS patients were used to identify predictors of MV. A multivariate logistic regression model was validated in a separate cohort of 191 GBS patients. Model performance criteria comprised discrimination (area under receiver operating curve [AUC]) and calibration (graphically). A scoring system for clinical practice was constructed from the regression coefficients of the model in the combined cohorts. Results In the derivation cohort, 22% needed MV in the first week of admission. Days between onset of weakness and admission, Medical Research Council sum score, and presence of facial and/or bulbar weakness were the main predictors of MV. The prognostic model had a good discriminative ability (AUC, 0.84). In the validation cohort, 14% needed MV in the first week of admission, and both calibration and discriminative ability of the model were good (AUC, 0.82). The scoring system ranged from 0 to 7, with corresponding chances of respiratory insufficiency from 1 to 91%. Interpretation This model accurately predicts development of respiratory insufficiency within 1 week in patients with GBS, using clinical characteristics available at admission. After further validation, the model may assist in clinical decision making, for example, on patient transfer to an intensive care unit. ANN NEUROL 2010;67:781–787
Bibliografie:Clinical Fellowship grant from the Netherlands organization for health research and development - No. ZonMW 907-00-111
ArticleID:ANA21976
Dutch Prinses Beatrix Fonds - No. PBF WAR07-28
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istex:CB16C97022CEEB479BF60CE5BD2CCF9C7EB526C0
ObjectType-Article-1
SourceType-Scholarly Journals-1
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content type line 23
ISSN:0364-5134
1531-8249
1531-8249
DOI:10.1002/ana.21976