Patients and methods: Seizures were reported prospectively up to day 90. Cox regression analyses were used to determine the predictors of seizures within 90 days and early seizures (≤7 days). We explored the effect of early seizures on day 90 outcomes.

MATERIALS AND METHODS: We conducted a cross-sectional study of men aged above 40 years with no history of prostate cancer, prostate surgery, or 5α-reductase inhibitor treatment. Serum prostate-specific antigen (PSA) and total PV were measured in each subject. Potential sociodemographic and clinical variables including age, weight, comorbidities, and International Prostate Symptom Score (IPSS) were collected. Of 1034 subjects, 837 were used in building the PV calculator using regression analysis. The remaining 1/5 (n = 197) was used for model validation.

METHODS: The derivation cohort included 90 Malaysian GBS patients with two sets of NCS performed early (1-20days) and late (3-8 weeks). Potential predictors of AIDP were considered in univariate and multivariate logistic regression models to develop a predictive model. The model was externally validated in 102 Japanese GBS patients.

RESULTS: Median motor conduction velocity (MCV), ulnar distal motor latency (DML) and abnormal ulnar/normal sural pattern were independently associated with AIDP at both timepoints (median MCV: p = 0.038, p = 0.014; ulnar DML: p = 0.002, p = 0.003; sural sparing: p = 0.033, p = 0.009). There was good discrimination of AIDP (area under the curve (AUC) 0.86-0.89) and this was valid in the validation cohort (AUC 0.74-0.94). Scores ranged from 0 to 6, and corresponded to AIDP probabilities of 15-98% at early NCS and 6-100% at late NCS.

CONCLUSION: The probabilities of AIDP could be reliably predicted based on median MCV, ulnar DML and ulnar/sural sparing pattern that were determined at early and late stages of GBS.