Abstract P171: Smaller Body Mass Index is Associated With Mild Cognitive Impairment in Elderly Hypertensive Patients
Bibliographic record
Abstract
Backgrounds: In elderly hypertensive patients, it might be important to pay attention to cognitive function when achieving aggressive blood pressure goal; therefore we evaluated factors associated with cognitive impairment in elderly hypertensive patients. Methods: We performed Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) in 209 elderly hypertensive patients who were evaluated frailty (Aged > 65 years, Male 38.3 %). Dementia was diagnosed as MMSE scores < 23 and/or anti-dementia drug use; mild cognitive impairment (MCI), MoCA<24 points and MMSE > 24 points. Results: Mean age was 78.6±6.2 years. There were 84.2 % of patients who were taking antihypertensive drug. Clinic blood pressure was 133.2±17.6 / 74.3±11.9 mmHg and body mass index (BMI) was 23.7±7.6 kg/m 2 . MMSE score was 27.0±3.8 and MoCA was 21.1±4.9 points. There were 53.0 % of patients with MCI; 12.9 % with dementia. Patients with MCI and dementia had lower BMI than those without (MCI group, BMI=23.2±3.5 kg/m 2 ; dementia group, 23.4±2.7 kg/m 2 ; no MCI or dementia group, 24.8±3.9 kg/m 2 ; P=0.012). The risk of MCI increased by 13.2 % per smaller BMI of 1 kg/m 2 (P=0.006); that of dementia increased by 18.6 % per smaller BMI of 1 kg/m 2 (P=0.055) after adjustment for age, gender, antihypertensive drugs use, diabetes, dyslipidemia, smoking habit, alcohol drinking, history of stroke, and systolic and diastolic blood pressure. Patients with the lowest quartile of BMI (< 21.34 kg/m2) had 3.82 (95%CI 1.42-10.27) times greater risk of MCI and had 7.59 (95%CI 1.22-47.27) times greater risk of dementia than those with highest quartile of BMI (> 25.69 kg/m2). Conclusion: In elderly hypertensive outpatients who were suspected of frailty, smaller BMI was associated with presence of MCI and dementia, suggested that we needed to decide optimal blood pressure level carefully in lean hypertensive patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".