Analysis of cognitive dysfunction and its risk factors in patients with hypertension
Bibliographic record
Abstract
ABSTRACT: To observe whether obstructive sleep apnea syndrome (OSAS) can aggravate the cognitive dysfunction of patients with hypertension (HTN), and to explore other risk factors.One hundred one hypertensive patients were selected for information collection. After the polysomnography test, they were divided into HTN-obstructive sleep apnea (OSA) and HTN groups. The Montreal cognitive assessment and the mini-mental state examination scales were used to appraise the patients' cognitive function. Logistic regressive analysis was used to determine the risk factors of cognitive dysfunction in patients with HTN.Compared with the HTN patients, HTN-OSA patients performed worse in mini-mental state examination (25.5 ± 2.9 vs 23.5 ± 3.2; P = .01) and Montreal cognitive assessment (28 ± 1.58 vs 21.2 ± 3.96; P = .003), and patients in the HTN-OSA group seemed more likely to suffer from dementia (31% vs 66%; P < .01). The apnea-hypopnea index (AHI) in the HTN group was lower than HTN-OSA group. Through multivariate logistic regression analysis, we can found that alcohol drinking, body mass index, long-term medication, diabetes, hypercholesterolemia, coronary heart disease, and OSAS were the independent risk factors of cognitive dysfunction in patients with HTN.OSAS can aggravate the cognitive dysfunction of hypertensive patients, besides, drinking, high-body mass index, long-term medication, diabetes, hypercholesterolemia, and coronary heart disease were also the risk factors of cognitive dysfunction in patients with hypertension. The cognitive dysfunction of patients with HTN can benefit from sleep apnea treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".