Presence of cerebral microbleeds is associated with cognitive decline in acromegaly
Bibliographic record
Abstract
Background Cognitive decline in acromegaly has gained increasing attention. Cerebral microbleeds (CMBs) as radiographic markers for microvascular injury have been linked to various types of cognitive decline. However, the association between CMB formation and acromegaly has not yet been quantified. This study is designed to investigate the prevalence and the radiographic patterns of CMBs and the association between cognitive function and acromegaly-related CMBs in growth hormone (GH)-secreting pituitary adenoma, which is characterized by acromegaly. Methods In a cohort of 55 patients with GH-secreting pituitary adenoma (acromegaly) and 70 healthy control (HC) patients, we determined the presence of CMBs using a 3.0-T MRI scanner. The numbers, locations, and grades of CMBs were determined via susceptibility-weighted imaging (SWI) and the Microbleed Anatomical Rating Scale. Obstructive sleep apnea (OSA) was assessed using the criteria of the American Academy of Sleep Medicine (AASM) Scoring Manual Version 2.2. The Montreal Cognitive Assessment (MoCA) was used to assess cognitive performance within 3 days of admission. The association between CMBs and cognitive function as well as clinical characteristics was explored. Results The incidence of CMBs was 29.1%, whereas that of OSA was 65.5% in acromegaly. There was a statistically significant difference in the prevalence of CMBs between subjects with and without acromegaly (29.1% and 5.3%, respectively) (p < 0.01). The age of acromegaly patients with CMBs was much younger compared with HCs with CMBs. Compared with HCs, a significant cognitive decline and the occurrence of OSA were demonstrated in patients with acromegaly (p < 0.01). Binary logistic regression analysis adjusted for age, education, and body mass index (BMI) revealed that CMB was an independent risk factor for cognitive impairment in patients with acromegaly (OR = 3.19, 95% CI 1.51–6.76, p = 0.002). Furthermore, in the logistic regression models adjusted for age, BMI, diabetes, and hypertension, OSA was independently associated with the occurrence of CMBs in patients with acromegaly (OR = 13.34, 95% CI 3.09–57.51, p = 0.001). Conclusions A significant increase of CMBs was demonstrated in patients with acromegaly, which may be a result of OSA in acromegaly. The present study indicated that increasing CMBs are responsible for cognitive decline in patients with acromegaly.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".