State of cognitive functions in elderly and senile patients with arterial hypertension, depending on the presence of concomitant chronic kidney disease stage G3a and G3b
Bibliographic record
Abstract
Background: the frequent combination (comorbidity) of arterial hypertension (AH) and chronic kidney disease (CKD), each of which is a risk factor for the development of cognitive impairment (CI) and dementia, determines the need to diagnose cognitive deficits in these multimorbid patients. Aims: to assess the impact of concomitant CKD and its stages on cognitive functions (CF) of elderly and senile patients with arterial hypertension. Materials and methods: 330 patients aged 60 years and older with essential АH were included in the study and were divided into 2 groups depending on the presence of CKD: group 1 - without concomitant CKD (n=110, mean age 76 [69.8; 82.3] years, 50 (45.5%) women), group 2 - patients with CKD stages G3a and G3b (n=220, mean age 81 [73; 85] years, 118 (53.6%) women). All the patients underwent the assessment of CF using the Montreal Cognitive Assessment (MoCA), Mini-Mental Status Examination (MMSЕ), Alzheimer's Disease Assessment Scale - Cognitive Subscale (ADAS-cog), Trial Making Test (TMT), Digit Symbol Substitution Test (DSST), Verbal Association Test (literal (letter) and categorical (animal) associations), Boston Naming Test (BNT), Word-Color Interference Test (Stroop color-word conflict test). Results: compared to patients without CKD, patients with CKD stage G3a and G3b had statistically significantly lower average final scores on the MoCA test (23 [21; 25] versus 24 [22; 26] points, respectively, p=0.005) and on the MMSE (27 [25; 29] versus 28 [25.8; 29] points, respectively, p=0.002), among them, patients who scored the lowest number of points on the MoCA test (10-17 points) (p=0.032) and the MMSE (20-24 points) (р<0.001). Patients with concomitant CKD stage G3a and G3b scored a statistically significantly higher number of points when testing according to ADAS-cog (14 [11;18] versus 11 [9; 15] points in the group without CKD, p<0.001), named fewer literal associations (11 [10]; 13] words versus 12 [11; 13], respectively, p<0.001), and had fewer correctly filled cells when performing the DSST test (20 [17; 23] versus 21.5 [19; 25], respectively, p<0.001). Patients with CKD G3b compared with patients with CKD G3a and without CKD had worse results when tested using the MoCА test, MMSE, and ADAS-cog. Conclusion: the results obtained indicate an unfavorable effect of concomitant CKD stage G3a and G3b on the CF of elderly and senile patients with arterial hypertension and a worsening of CF as the severity of CKD increases.
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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 | 0.000 |
| 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".