Geometrical changes of the left ventricle and cognitive impairment in hypertensive patients
Bibliographic record
Abstract
Abstract Funding Acknowledgements Type of funding sources: None. Introduction From the view of the heart-brain axis, several biomarkers have been suggested for the assessment, eventually for the prevention of cognitive impairment. Remodeling of the left ventricular (LV) structure could be such a marker. Purpose: This study aimed to investigate the relationship between cognitive functions and left ventricular geometrical structure. Methods: We enrolled 512 consecutive hypertensive patients (mean age 68 ±9.5 years, females: 51%, males 49%), the mean blood pressure was 135/81 mmHg (±19/11 mmHg). Cognitive abilities were measured with two questionnaires the Mini Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), considering cognitive impairment under 24 and 26 points respectively. Measures of the left ventricular structure were performed with transthoracic echocardiography using left ventricular mass indexed to body surface area (LVMI) and relative wall thickness (RWT). Cut off value for LV geometrical changes were: LVMI 115 g/m2 in males and 95 g/m2 in females and RWT 0.42 mm. IBM SPSS v20. was used for statistical analyses. Results: Normal geometry of LV was present in 7.4% and remodeling of LV in the studied group was: concentric remodeling in 16.8%, concentric hypertrophy in 61.9% and eccentric hypertrophy in 13.9%. Lower MoCA scores were observed in LV hypertrophy (22.6 vs. 23.4, p = 0.08). Patients with LV concentric hypertrophy had significantly lower cognitive scores compared to eccentric hypertrophy (mean MoCA 22.4 vs. 23.8 p = 0.02; mean MMSE 26.1 vs. 27.0 p = 0.02). Increased RWT alone were associated with poorer cognition (mean MoCA 22.58 vs. 23.89 p = 0.009; mean MMSE 26.17 vs. 26.99 p = 0.02). Higher LVMI negatively correlated with MoCA scores (p = 0.018, r=-0.105), but not with MMSE scores (p = 0.216, r=-0.006). Conclusions: Left ventricular hypertrophy and even changes in relative wall thickness may cause cognitive impairment. Preventing LV geometrical changes may prevent the deterioration of cognitive abilities.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".