ABSTRACT
BACKGROUND: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) syndrome is a newly discovered autoinflammatory condition characterised by somatic mutation of the UBA1 gene. The syndrome leads to multi-system inflammation affecting predominantly the skin, lungs and bone marrow. METHODS: We undertook a systematic review of the multisystem features and genotypes observed in VEXAS syndrome. Articles discussing VEXAS syndrome were included. Medline, Embase and Cochrane databases were searched. Information was extracted on: demographics, type and prevalence of clinical manifestations, genetic mutations and treatment. Meta-analysis using a random effects model was used to determine pooled estimates of serum markers. RESULTS: From 303 articles, 90 were included, comprising 394 patients with VEXAS. 99.2% were male, with a mean age of 67.1 years (SD 8.5) at disease onset. The most frequent diagnoses made prior to VEXAS were: relapsing polychondritis (n = 59); Sweet's syndrome (n = 24); polyarteritis nodosa (n = 11); and myelodysplastic syndrome (n = 10). Fever was reported in 270 cases (68.5%) and weight loss in 79 (20.1%). Most patients had haematological (n = 342; 86.8%), dermatological (n = 321; 81.5%), pulmonary (n = 297; 75.4%%) and musculoskeletal (n = 172; 43.7%) involvement, although other organ manifestations of varying prevalence were also recorded. The most commonly reported mutations were "c.122T > C pMET41Thr" (n = 124), "c.121A > G pMET41Val" (n = 62) and "c.121A > C pMet41Leu" (n = 52). Most patients received glucocorticoids (n = 240; 60.9%) followed by methotrexate (n = 82; 20.8%) and IL-6 inhibitors (n = 61, 15.4%). One patient underwent splenectomy; 24 received bone marrow transplants. CONCLUSION: VEXAS syndrome is a rare disorder affecting predominantly middle-aged men. This is the first systematic review to capture clinical manifestations, genetics and treatment of reported cases. Further studies are needed to optimise treatment and subsequently reduce morbidity and mortality.
Subject(s)
Ubiquitin-Activating Enzymes , Humans , Male , Ubiquitin-Activating Enzymes/genetics , Female , Mutation , Syndrome , Aged , Middle Aged , Myelodysplastic Syndromes/genetics , Myelodysplastic Syndromes/therapy , Sweet Syndrome/genetics , Sweet Syndrome/drug therapy , Sweet Syndrome/epidemiology , Polyarteritis Nodosa/genetics , Polyarteritis Nodosa/drug therapy , Polyarteritis Nodosa/therapy , Hereditary Autoinflammatory Diseases/genetics , Hereditary Autoinflammatory Diseases/drug therapy , Hereditary Autoinflammatory Diseases/therapy , Hereditary Autoinflammatory Diseases/diagnosisABSTRACT
OBJECTIVES: As a large language model (LLM) trained on a large data set, ChatGPT can perform a wide array of tasks without additional training. We evaluated the performance of ChatGPT on postgraduate UK medical examinations through a systematic literature review of ChatGPT's performance in UK postgraduate medical assessments and its performance on Member of Royal College of Physicians (MRCP) Part 1 examination. METHODS: Medline, Embase and Cochrane databases were searched. Articles discussing the performance of ChatGPT in UK postgraduate medical examinations were included in the systematic review. Information was extracted on exam performance including percentage scores and pass/fail rates. MRCP UK Part 1 sample paper questions were inserted into ChatGPT-3.5 and -4 four times each and the scores marked against the correct answers provided. RESULTS: 12 studies were ultimately included in the systematic literature review. ChatGPT-3.5 scored 66.4% and ChatGPT-4 scored 84.8% on MRCP Part 1 sample paper, which is 4.4% and 22.8% above the historical pass mark respectively. Both ChatGPT-3.5 and -4 performance was significantly above the historical pass mark for MRCP Part 1, indicating they would likely pass this examination. ChatGPT-3.5 failed eight out of nine postgraduate exams it performed with an average percentage of 5.0% below the pass mark. ChatGPT-4 passed nine out of eleven postgraduate exams it performed with an average percentage of 13.56% above the pass mark. ChatGPT-4 performance was significantly better than ChatGPT-3.5 in all examinations that both models were tested on. CONCLUSION: ChatGPT-4 performed at above passing level for the majority of UK postgraduate medical examinations it was tested on. ChatGPT is prone to hallucinations, fabrications and reduced explanation accuracy which could limit its potential as a learning tool. The potential for these errors is an inherent part of LLMs and may always be a limitation for medical applications of ChatGPT.