ArticleEndocrine2026
Sex differences in cardiovascular risk factors and cardiovascular disease in patients with hyperprolactinemia: a multicenter cross-sectional study.
Article in Endocrine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Importance of clinical profiling to determine excess mortality in prolactinomas: insights from a large, registry-based cohort.Pituitary · 2026Article
- Cardiometabolic effects of sequential prolactin states in dopamine agonist-treated prolactinoma patients: a retrospective longitudinal study.Pituitary · 2026Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionHyperprolactinemia is classically linked to reproductive dysfunction, but emerging evidence suggests an association with metabolic and cardiovascular (CV) risk. This study evaluated sex differences in CV risk factors (CVRFs) and cardiovascular disease (CVD) in patients with hyperprolactinemia.
methodsA multicenter, retrospective cross-sectional study was conducted in 449 adult patients (199 men, 250 women) with confirmed hyperprolactinemia from 19 tertiary referral centers in Spain. Clinical, biochemical, and hormonal data were collected and analyzed. The prevalence of CVRFs and CVD was compared between sexes. Associations between serum prolactin levels and CVRFs/CVD were assessed using nonparametric tests, correlation analyses, and multivariable logistic regression.
resultsMen had significantly higher serum prolactin levels than women (median 796 [IQR 250–1499] vs. 114 [74.5–224] ng/mL; p < 0.001) and a greater crude prevalence of all major CVRFs (p < 0.001 for all). After adjustment for age, male sex remained independently associated with smoking (OR 2.16; p = 0.007) and hyperlipidemia (OR 1.97; p = 0.031). Serum prolactin levels positively correlated with age, BMI, systolic blood pressure, glucose, total cholesterol, and triglycerides (all p < 0.001). In sex-stratified analyses, prolactin was associated with BMI and lipid profile in men, and with hypertension and hyperlipidemia in women. Prolactin levels were significantly elevated in patients with any form of CVD (p = 0.007), particularly arrhythmias (p = 0.013), while a trend was noted for ischemic heart disease (p = 0.050).
conclusionMen with hyperprolactinemia exhibit a more adverse cardiometabolic profile, characterized by higher serum prolactin levels and a greater burden of classical CVRFs and CVD. Prolactin concentrations are positively associated with multiple metabolic and CV parameters, with sex-specific patterns suggesting distinct mechanisms of susceptibility and regulation. These findings underscore the importance of incorporating sex and hormonal context into CV risk assessment in patients with hyperprolactinemia.
Indexed as
Identifiers
41629737What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.