Guillain-Barre Syndrome

For GBD 2017, we modelled non-fatal disease burden using DisMod-MR 2.1, a meta-analysis tool that uses a compartmental model structure with a series of differential equations that synthesise sparse and heterogeneous epidemiological data for non-fatal disease and injury outcomes. Estimation occurred at the five levels of the GBD location hierarchy—global, super-regional, regional, national, and subnational—with results of each higher level providing guidance for the analysis at the lower geographical level. Important modelling strategy changes from GBD 2016 to GBD 2017 for specific causes, as well as further details on these causes and their respective models, can be found in the supplementary methods (appendix 1 section 4).
Custom models were created if DisMod-MR 2.1 did not capture the complexity of the disease or if incidence and prevalence needed to be calculated from other data, or both. Further details of these custom models can be found in the cause-specific methods sections of the supplementary methods (appendix 1 section 4).
Prevalence was estimated for nine impairments, defined as sequelae of multiple causes for which better data were available to estimate the overall occurrence than for each underlying cause: anaemia, intellectual disability, epilepsy, hearing loss, vision loss, heart failure, infertility, pelvic inflammatory disease, and Guillain-Barré syndrome. Different methodological approaches were used for each impairment estimation process; these details are described in the supplementary methods (appendix 1 section 4).

The SwiSCI community survey included Swiss residents with a traumatic or non-traumatic SCI aged over 16 years. Exclusion criteria were congenital conditions leading to SCI, new SCI in the context of palliative care, neurodegenerative disorders, and Guillain-Barré syndrome. Given the lack of a central registry covering all persons with SCI in Switzerland, the SwiSCI population was recruited through the national association for persons with SCI (Swiss Paraplegic Association), three specialized SCI-rehabilitation centers, and a SCI-specific home care institution [33 (link)]. Of 3144 eligible persons, 1549 completed the first two questionnaires relevant for this study (cumulative response rate 49.3%). We found minimal response bias in relation to key characteristics such as gender, age and lesion severity, indicating that the SwiSCI sample good representation of the sampling frame [34 (link)]. The sample of the present study was restricted to 1198 persons in employable age. The lower age limit of 16 years was defined by the inclusion criteria of the study and the fact that many adolescents start an apprenticeship at the age of 16, which is to be considered as first paid employment. The upper age limit was defined by the legal age of employment in Switzerland (< 65 for men, < 64 for women). We only included men and women in employable age for whom information on mental health and QoL was available (n = 1157). Further details on recruitment outcomes, participation rates, and non-response bias in the SwiSCI community survey 2012 can be found elsewhere [34 (link), 35 (link)].

Participants were recruited from the movement disorder clinic of the Samsung Medical Center. The Institutional Review Board of Samsung Medical Center approved this study, and all subjects provided written informed consent. Patients were enrolled if they were diagnosed with PD based on the United Kingdom Brain Bank Criteria for PD^{38 (link)}. Patients with any of the following conditions were excluded: any neurologic disorder other than PD, systemic vasculitis, cardiovascular disease, musculoskeletal disease, end-stage renal disease, peripheral nervous system autonomic failure (diabetic neuropathy, Guillain-Barre syndrome, amyloid neuropathy, surgical sympathectomy, and pheochromocytoma, etc.), ocular pathology that could affect OCTA measurements (glaucoma, a refractive error >+6.0 diopters of spherical equivalent or <−6.0 diopters of spherical equivalent, astigmatism ≥ 3.0 diopters, epiretinal membrane, age-related macular degeneration, diabetic retinopathy, hypertensive retinopathy, retinal artery/vein occlusion, or optic neuropathy) or previous retinal surgery. Exact age- and sex-matched controls were recruited. The healthy controls were required to have normal visual acuity, normal intraocular pressure ≤21 mm Hg, and normal optic discs. The same exclusion criteria were applied to healthy controls and PD patients. Demographic and clinical data, including age, sex, and comorbid vascular risk factors (hypertension, diabetes mellitus, dyslipidemia), were collected for all enrolled participants. The UPDRS III^{39 (link)}, H&Y scale^{40 (link)}, LEDD^{41 (link)}, and MoCA^{42 (link)} were investigated in all enrolled PD patients.

The outcome of interest in this study was newly diagnosed autoimmune diseases after the index dates. In Taiwan, people with several autoimmune diseases can apply for catastrophic illness certification to receive a copayment exemption from the NHI program, and all the applications are reviewed by rheumatologists. These autoimmune diseases, including SLE, systemic sclerosis, Sjögren’s syndrome, inflammatory myopathy, rheumatoid arthritis, Behcet’s syndrome, systemic vasculitis, type I diabetes mellitus, multiple sclerosis, myasthenia gravis, inflammatory bowel diseases, autoimmune hemolytic anemia, and pemphigus, were identified from the Registry for Catastrophic Illness, and thus the diagnoses should be valid. For autoimmune diseases that did not fulfill the requirements to be considered catastrophic illnesses in Taiwan, including ankylosing spondylitis, post-infectious arthritis, uveitis, psoriasis, autoimmune thyroid disease, primary adrenocortical insufficiency, Guillain–Barré syndrome, autoimmune encephalomyelitis, and celiac disease, one hospital admission or at least three outpatient visits with relevant ICD-9-CM or ICD-10-CM codes were regarded as the confirmed diagnosis (S1 Table). The follow-up of study participants started on the index dates and continued until the confirmation of study outcomes, death, or August 31, 2018, whichever occurred first.

A retrospective design was used to study patients with confirmed acute GBS who were admitted to the Department of Neurology at the Beijing Tongren Hospital of Capital Medical University from 2007 to 2021. (1) Inclusion criteria: (i) met the diagnostic criteria of the 2019 Chinese Guillain-Barré Syndrome Diagnosis and Treatment Guidelines developed by the Chinese Medical Association [3 ]; (ii) first-onset admission. (2) Exclusion criteria: (i) patients with combined definite intracranial lesions; (ii) patients with chronic inflammatory demyelinating polyradiculoneuropathy (CIDP); (iii) patients who could not be excluded from peripheral neuropathy caused by other etiologies; (iv) patients with incomplete case data.
Measured characteristics included gender, age at onset, antecedent infection (whether diarrhea, upper respiratory tract infection, pulmonary infection, or other unexplained infection occurred within 4 weeks prior to onset), cranial nerve involvement (presence of ophthalmoplegia, facial palsy, dysarthria, dysphagia, weak neck, and shoulder rotation), presence of pulmonary infection (symptoms such as cough, sputum, and fever during the course of the disease, and confirmation with high-resolution computed tomography (HRCT) of the lungs). Mechanical ventilatory support, hyponatremia, hypoalbuminemia, impaired fasting glucose and the peripheral blood neutrophil-to-lymphocyte ratio (NLR) were analyzed as alternative influencing factors. Peripheral blood was collected from all patients within 24 h of admission. Plasma sodium < 135 mmol/L was considered as combined hyponatremia. Fasting plasma glucose (FPG) > 6.1 mmol/L was considered impaired fasting glucose. Plasma albumin < 35 g/L was defined as hypoalbuminemia. An elevated NLR was defined as an NLR value > 2.135.
The GBS disability score developed by Hughes (Hughes functional grading scale, HFGS) [4 (link)] et al. was used for assessment on the day of discharge: 0 represented a completely normal state; 1 represented mild signs or symptoms and ability to run; 2 represented the ability to walk ≥ 10 m alone but the inability to run; 3 represented the ability to walk 10 m in open space with assistance; 4 represented a bedridden or wheelchair bound state; 5 represented a requirement of assisted ventilatory support; and 6 referred to death. Those with GBS disability scores > 3 at discharge were considered to have a poor early prognosis and those with GBS scores ≤ 3 had better early prognoses.
SPSS 23.0 and MedCalc statistical software were used for the analysis. The χ2 test or Fisher's exact test was used to compare groups of count data. (1) Univariate analysis was used to derive risk factors for poorer early prognosis (HFGS score > 3) in patients with GBS. (2) Statistically significant (P < 0.05) influencing factors obtained from this analysis were then included in a multivariate logistic regression analysis, and regression coefficients were calculated. (3) The integer value closest to the regression coefficient was used as the influencing factor score value in order to establish an early prognostic scoring system. (4) The predictive value of the scoring system was evaluated by plotting the receiver operating curve (ROC) curve: the area under the ROC curve (AUC) was calculated, the appropriate cut-off value was selected, and the sensitivity, specificity, positive predictive value, and negative predictive value were calculated.