RESUMO
BACKGROUND: ChatGPT is an open-source natural language processing software that replies to users' queries. We conducted a cross-sectional study to assess people living with Multiple Sclerosis' (PwMS) preferences, satisfaction, and empathy toward two alternate responses to four frequently-asked questions, one authored by a group of neurologists, the other by ChatGPT. METHODS: An online form was sent through digital communication platforms. PwMS were blind to the author of each response and were asked to express their preference for each alternate response to the four questions. The overall satisfaction was assessed using a Likert scale (1-5); the Consultation and Relational Empathy scale was employed to assess perceived empathy. RESULTS: We included 1133 PwMS (age, 45.26 ± 11.50 years; females, 68.49%). ChatGPT's responses showed significantly higher empathy scores (Coeff = 1.38; 95% CI = 0.65, 2.11; p > z < 0.01), when compared with neurologists' responses. No association was found between ChatGPT' responses and mean satisfaction (Coeff = 0.03; 95% CI = - 0.01, 0.07; p = 0.157). College graduate, when compared with high school education responder, had significantly lower likelihood to prefer ChatGPT response (IRR = 0.87; 95% CI = 0.79, 0.95; p < 0.01). CONCLUSIONS: ChatGPT-authored responses provided higher empathy than neurologists. Although AI holds potential, physicians should prepare to interact with increasingly digitized patients and guide them on responsible AI use. Future development should consider tailoring AIs' responses to individual characteristics. Within the progressive digitalization of the population, ChatGPT could emerge as a helpful support in healthcare management rather than an alternative.
RESUMO
BACKGROUND: Cerebrospinal fluid (CSF) kappa free light chains (KFLC) are gaining increasing interest as markers of intrathecal immunoglobulin synthesis. The main aim of this study was to assess the diagnostic accuracy (AUC) of the kappa index (CSF/serum KFLC divided by the CSF/serum albumin ratio) compared to CSF oligoclonal IgG bands (OCB) in predicting Multiple Sclerosis (MS) or a central nervous system infectious/inflammatory disorder (CNSID). METHODS: We enrolled patients who underwent a diagnostic spinal tap throughout two years. KFLC levels were determined using a Freelite assay (Binding Site) and the turbidimetric Optilite analyzer. RESULTS: Of 540 included patients, 223 had a CNSID, and 84 had MS. The kappa index was more sensitive (0.89 versus 0.85) and less specific (0.84 versus 0.89), with the same AUC (0.87) as OCB for MS diagnosis (optimal cut-off: 6.2). Adding patients with a single CSF IgG band to the OCB-positive group slightly increased the AUC (0.88). Likewise, the kappa index (cut-off: 3.9) was more sensitive (0.67 versus 0.50) and less specific (0.81 versus 0.97), with the same AUC (0.74) as OCB, for a CNSID diagnosis. CONCLUSION: The kappa index and CSF OCB have comparable diagnostic accuracies for a MS or CNSID diagnosis and supply the clinician with useful, complementary information.