To quantify sex- and age-related differences in hypercholesterolaemia diagnosis and associated comorbidities around the menopausal transition, using a population-based real-world dataset.

Retrospective, multicentre, non-interventional observational cohort study.

Region-wide public healthcare system data (primary and secondary care) from Andalusia (Spain), 2016–2022.

All adult patients meeting inclusion criteria with a recorded diagnosis of hypercholesterolaemia between 1 January 2016 and 31 December 2022 (n=557 034; 227 834 men and 329 200 women).

None.

Primary outcomes were age- and sex-stratified patterns of hypercholesterolaemia diagnosis and comorbidity burden before and after age 50 years (proxy for post-menopausal age). Secondary outcomes included comorbidity-specific comparisons between sexes across age strata and trajectory-based analyses (OR trajectories and incidence-ratio summaries).

Women were diagnosed later than men (mean age 59.1 vs 56.0 years; mean difference 3.1 years, 95% CI 3.03 to 3.17). Hypercholesterolaemia diagnoses in women rose sharply around ages 50–55 and remained higher than in men at older ages. Comorbidity patterns differed by sex across age strata: compared with men, women aged ≥50 years had higher frequencies of osteoporosis (42 255 vs 2623), anxiety disorder (94 916 vs 31 374) and hypertension (147 538 vs 91 532), with statistically significant differences for these comparisons (p

Menopause age is a pivotal period associated with a shift towards higher hypercholesterolaemia diagnosis rates and a greater burden of specific comorbidities in women. These findings support sex-specific prevention and management strategies, particularly targeting the menopausal transition and early post-menopause.

Liver tumours are a leading cause of global morbidity and mortality. Current diagnostic tools, including computed tomography (CT), magnetic resonance imaging (MRI) and intraoperative ultrasound (IOUS), have limitations in detecting liver neoplasms. Indocyanine green (ICG) has emerged as a promising tool for improving liver tumour detection. This study aims to assess the impact of preoperative ICG on intraoperative tumour detection in minimally invasive surgery and develop a machine-learning algorithm to enhance tumour detection using ICG fluorescence.

This prospective, multicentre, phase IV clinical trial adheres to Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines. Patients with liver tumours eligible for minimally invasive surgery and a preoperative imaging test will be included. ICG will be administered intravenously 24 hours before surgery. Intraoperative procedures will include IOUS, ICG mapping and photographic documentation. Patients will be followed for 90 days to assess tumour progression, morbidity and mortality. The photographic analysis will enable the development of an artificial intelligence algorithm using machine learning and neural networks to identify lesions based on ICG fluorescence. The estimated sample size is 173 patients and the trial is predicted to accrue in 3 years.

The trial will be conducted in accordance with the Declaration of Helsinki and the Spanish Agency of Medicines and Medical Devices (AEMPS) guidelines. Approved by the local institutional Ethics Committee and the AEMPS, the results will be shared with the scientific community through publications and conferences.

2023–5 08 316-27-00.

NCT06398028.

V.12, 18 March 2025