Prevalence and Associated Factors of Mild Cognitive Impairment in Young and Middle-aged Hospitalized Patients with Hypertension
Bibliographic record
Abstract
Background Mild cognitive impairment (MCI) is highly prevalent in hypertensive patients, but the current studies on MCI in hypertension mostly focus on the elderly group, while scarcely involve young and middle-aged patients. Objective To investigate the prevalence and associated factors of MCI in young and middle-aged hospitalized patients with hypertension. Methods A convenience sample of 213 young and middle-aged hypertensive inpatients were recruited from a tertiary grade A hospital in Harbin from May to December 2021. The General Demographic Questionnaire, Montreal Cognitive Assessment (MoCA) , and the Type-D Scale-14 (DS14) were used for understanding patients' demographics, cognitive impairment status, and D-type personality prevalence, respectively. Multiple Logistic regression was used to analyze associated factors of MCI. Results The prevalence of MCI was 37.56% (80/213) . Multiple Logistic regression analysis showed that age〔OR=1.073, 95%CI (1.033, 1.115) 〕, education level〔junior college education level: OR=0.278, 95%CI (0.084, 0.920) , smoking history〔OR=2.494, 95%CI (1.146, 5.426) 〕, stage of hypertension〔stage 2: OR=3.442, 95%CI (1.252, 9.468) ; stage 3: OR=3.934, 95%CI (1.518, 10.193) 〕, D-type personality〔OR=2.160, 95%CI (1.015, 4.598) , TG〔OR=1.596, 95%CI (1.125, 2.265) 〕, and HDL-C〔OR=0.185, 95%CI (0.049, 0.707) 〕were influential factors of MCI in hypertension (P<0.05) . Conclusion Young and middle-aged hospitalized patients with hypertension had a high prevalence of MCI. Older age, lower level of education, D-type personality, higher level of TG and lower level of HDL-C were related to increased risk of MCI in hypertension. In view of this, medical workers should screen MCI in these patients to identify those at high risk of MCI as early as possible, and deliver interventions to them timely.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".