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Predictors of Mechanical Ventilation in Guillain-Barré Syndrome with Axonal Subtypes
Anaclara Michel-Chávez1, Erwin Chiquete1, Alfonso Gulías-Herrero2
1Department of Neurology and Psychiatry, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
Background:
The early clinical predictors of respiratory failure in Latin Americans with Guillain-Barré syndrome (GBS) have scarcely been studied. This is of particular importance since Latin America has a high frequency of axonal GBS variants that may imply a worse prognosis.
Methods:
We studied 86 Mexican patients with GBS admitted to the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, a referral center of Mexico City, to describe predictors of invasive mechanical ventilation (IMV).
Results:
The median age was 40 years (interquartile range: 26-53.5), with 60.5% men (male-to-female ratio: 1.53). Most patients (65%) had an infectious antecedent (40.6% gastrointestinal). At admission, 38% of patients had a Medical Research Council (MRC) sum score <30. Axonal subtypes predominated (60.5%), with acute motor axonal neuropathy being the most prevalent (34.9%), followed by acute inflammatory demyelinating polyneuropathy (32.6%), acute motor sensory axonal neuropathy (AMSAN) (25.6%), and Fisher syndrome (7%). Notably, 15.1% had onset in upper limbs, 75.6% dysautonomia, and 73.3% pain. In all, 86% received either IVIg (9.3%) or plasma exchange (74.4%). IMV was required in 39.5% patients (72.7% in AMSAN). A multivariate model without including published prognostic scores yielded the time since onset to admission <15 days, axonal variants, MRC sum score <30, and bulbar weakness as independent predictors of IMV. The model including grading scales yielded lower limbs onset, Erasmus GBS respiratory insufficiency score (EGRIS) >4, and dysautonomia as predictors.
Conclusion:
These results suggest that EGRIS is a good prognosticator of IMV in GBS patients with a predominance of axonal electrophysiological subtypes, but other early clinical data should also be considered.
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