MORTALITY RATE OF PATIENTS WITH ARTERIAL HYPERTENSION AND MILD COGNITIVE IMPAIRMENT
Bibliographic record
Abstract
Objective: People with mild cognitive impairment (MCI) are with elevated risk of death. On the other hand, patients with cardiovascular risk factors are at a higher risk of death in comparison with the general population. Thus, the combination of mild cognitive impairment and hypertension/high cardio-vascular risk, may lead to even higher mortality rate than expected. However, this has not been proven. The question is important in the light of effective early screening and prophylaxis, because the real patients in our everyday practice are not with a single isolated disease or risk factor. Design and method: This is a retrospective analysis. We compared the general death rate of hypertensive high-cardio-vascular-risk patients with and without MCI. Two hundred-forty-nine patients underwent neuropsychological screening twice at least 6 months apart with MMSE and MoCA, Geriatric Depression scale and 4-point version of the scale for evaluating the performance in instrumental activities of daily living (4-IADL). The patients also had laboratory testing, ambulatory blood pressure monitoring, ECG echocardiography. Their death rate was examined 8 to 10 years afterwards. Results: The patients with arterial hypertension and clinically diagnosed mild cognitive impairment (MoCA and MMSE) had significantly higher general death rate compared to those without MCI. Logistic regression analysis showed that about 14.6% of the mortality rate in this high-risk group could be attributed to MCI. The home blood pressure values were not in the target range for 63.85% at the initial neuropsychological test and for 56.43% on the reevaluation 8–10 years ago, despite the multi-drug antihypertensive regimen. The yearly all-cause mortality rate for the recent years for Bulgaria was about 14.1–15.4/1000. The relative all-cause mortality rate of this studied population was about 25.7/1000 patient on yearly basis – 1.67 times higher. Conclusions: It is known that MCI is correlated with cardiovascular risk factors and mainly - arterial hypertension. We found that the combination of MCI and arterial hypertension may lead to high mortality rate. This has important clinical implications. We will study further this issue to define in detail the factors responsible for the higher death rate in this group.
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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 | 0.000 |
| 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 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".