Jiayi Ye

Objectives: Hyperuricaemia has been linked to cognitive decline, yet cerebral structural and haemodynamic changes in this population remain poorly defined. We evaluated transcranial colour-coded duplex (TCCD) sonography as a non-invasive screening tool for early mild cognitive impairment (MCI) in elderly hyperuricaemic men. Methods: In this cross-sectional study, 195 men aged ≥ 60 years with hyperuricaemia were stratified by the Montreal Cognitive Assessment (MoCA) into HUA + MCI (MoCA < 26, n = 46) and HUA (MoCA ≥ 26, n = 149) groups. TCCD measured third-ventricle width (TVW) and peak systolic/end-diastolic velocities to calculate resistive (RI) and pulsatility (PI) indices in the middle (MCA) and posterior (PCA) cerebral arteries. Serum uric acid was recorded. Kernel density plots and receiver operating characteristic (ROC) curves assessed diagnostic performance. Results: The HUA + MCI group exhibited higher serum uric acid (508.5 ± 36.3 vs. 492.9 ± 44.0 µmol/L; p = 0.031), greater TVW (0.55 ± 0.11 vs. 0.51 ± 0.08 cm; p = 0.037), and elevated left PCA RI (0.69 ± 0.07 vs. 0.64 ± 0.06) and PI (1.05 ± 0.17 vs. 0.95 ± 0.12; both p < 0.001). ROC analysis identified left PCA PI as the most specific marker (AUC = 0.701; specificity 90.6%; sensitivity 45.7%). Kernel density plots confirmed distinct distributions of key parameters. Conclusions: TCCD-detected ventricular enlargement and raised PCA pulsatility accurately distinguish MCI among hyperuricaemic men. As a non-invasive, accessible technique with high specificity, TCCD may complement MRI and cognitive testing in early screening of at-risk populations.

Background: This study evaluates the performance of GPT-4o in detecting errors in ACR TIRADS ultrasound reports and its potential to reduce report generation time. Methods: A retrospective analysis of 200 thyroid ultrasound reports from the Second Affiliated Hospital of Fujian Medical University was conducted, with reports categorized as correct or containing up to three errors. GPT-4o's performance was compared with ultrasound physicians of varying experience levels in error detection and processing time. Results: GPT-4o detected 90.0% (180/200) of errors, slightly less than the best-performing senior ultrasound physician's 93.0% (186/200) with no significant difference ( p =  0.281). GPT-4o's error detection rate was comparable to that of ultrasound physicians overall ( p =  0.098 to 0.866). It outperformed Resident 2 in diagnostic errors (87% vs. 69%). Reader agreement was low (Cohen's kappa = 0 to 0.31). GPT-4o reviewed reports significantly faster than all ultrasound physicians (0.79 vs. 1.8 to 3.1 h, p  < 0.001), making it a reliable and efficient tool for error detection in medical imaging. Conclusions: GPT-4o is comparable to experienced ultrasound physicians in error detection and significantly improves report processing efficiency, offering a valuable tool for enhancing diagnostic accuracy and aiding junior residents.