Toward a machine learning model for a primary diagnosis of Guillain-Barré syndrome subtypes

Abstract

Guillain-Barré Syndrome (GBS) is a neurological disorder affecting people of any age and sex, mainly damaging the peripheral nervous system. GBS is divided into several subtypes, in which only four are the most common, demanding different treatments. Identifying the subtype is an expensive and time-consuming task. Early GBS detection is crucial to save the patient’s life and not aggravate the disease. This work aims to provide a primary screening tool for GBS subtypes fast and efficiently without complementary invasive methods, based only on clinical variables prospected in consultation, taken from clinical history, and based on risk factors. We conducted experiments with four classifiers with different approaches, five different filters for feature selection, six wrappers, and One versus All (OvA) classification. For the experiments, we used a data set that includes 129 records of Mexican patients and 26 clinical representative variables. Random Forest filter obtained the best results in each classifier for the diagnosis of the four subtypes, in the same way, this filter with the SVM classifier achieved the best result (0.6840). OvA with SVM classifier reached a balanced accuracy of 0.8884 for the Miller-Fisher (MF) subtype.

Anti-sulfatide antibody-related Guillain–Barré syndrome presenting with overlapping syndromes or severe pyramidal tract damage: a case report and literature review

“…Nevertheless, patient 1 initially experienced diplopia and limb numbness, followed by bilateral facial paralysis and manifestations of encephalopathy (mental disorder, ataxia, and pyramidal tract damage), and finally had obvious residual neurological sequelae. This patient simultaneously presented with the characteristic clinical features of both MSF ( 18 , 19 ) and BBE ( 20 ), which has rarely been reported in patients with anti-sulfatide antibody-related GBS. MFS is considered the most common variant of GBS and is characterized by the medical triad of ophthalmoplegia, ataxia, and areflexia ( 18 , 19 ).…”

“…This patient simultaneously presented with the characteristic clinical features of both MSF ( 18 , 19 ) and BBE ( 20 ), which has rarely been reported in patients with anti-sulfatide antibody-related GBS. MFS is considered the most common variant of GBS and is characterized by the medical triad of ophthalmoplegia, ataxia, and areflexia ( 18 , 19 ). BBE is characterized by the medical triad of ophthalmoplegia, ataxia, and encephalopathy ( 20 ).…”

Celastrol attenuates Guillain-Barré syndrome by inhibiting TLR4/NF-κB/STAT3 pathway-mediated Th1/Th17 cell differentiation

“…In the present study, the clinical symptoms of GBS in EAN rats were observably improved by celastrol. GBS primarily damages the peripheral nervous system (Alarcón-Narváez et al 2021). This study showed that celastrol mitigated the pathological damage of GBS in EAN rats.…”

Diagnosis and treatment of Guillain-Barre using the prolog expert system

“…Alarcón-Narváez et al [15], developed a primary screening tool for the identification of GBS subtypes from clinical variables collected in consultation, without resorting to additional invasive methods. Through experiments involving four classifiers, five filters for feature selection, and six wrappers, along with the oneversus-all (OvA) classification technique, a dataset consisting of 129 patient records from Mexico and 26 key clinical variables was evaluated.…”