Vascular markers of cognitive dysfunction in patients with uncontrolled arterial hypertension
Bibliographic record
Abstract
The presence of arterial hypertension (AH) leads to the development of cognitive dysfunction, in the genesis of which a significant role is assigned to vascular factors. Aim. To study the state of cognitive function and associated vascular factors in patients with uncontrolled AH. Materials and methods. The research involved 88 patients with uncontrolled AH (UAH) — group 1 (median age 60, men — 39%) and 46 patients with controlled AH (CAH) — group 2 (median age 59, men — 41%). Cognitive function was assessed using the Montreal Cognitive Assessment (MoCA). There were studied vascular factors: thickness of the intima-media complex (IMC), pulse wave velocity (PWV), microcirculation flow index (MFI) and asymmetric dimethylarginine (ADMA) concentrations. For the statistical analysis the following criteria were used: Student t-test, Mann—Whitney test. Multifactorial linear regression analysis was performed in groups. Results. In Group 1, there was a lower cognitive function index by MoCA — 24 [22; 26] points against 26 [25; 27] points in Group 2 (p = 0.002). IMC thickness was higher in Group 1 than in Group 2 (1.1 [0.90; 1.20] mm vs 1.0 [0.80; 1.10] mm, p = 0.042), concentration of ADMA was higher in Group 1 (0.73 ± 0.21 µmol/l vs 0.65 ± 0.1 µmol/l, p = 0.02), MFI was higher in Group 2 (30.6 [27.1; 34.4] perf. units vs. 22.8 [18.6; 26.1] perf. units, р < 0.001). No differences between the groups were found in PWV. In regression analysis, the following factors had a statistically significant effect on MoCA scores: in Group 1 — age, IMC thickness, ADMA and MFI; in Group 2 — age and glomerular filtrate rate. Conclusion. Patients with uncontrolled AH have more pronounced cognitive dysfunction than those with controlled AH, which is associated with increased IMC thickness, impaired microcirculation and increased ADMA concentration.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".