Relation Between Hypertension and Cognitive Impairment in Elderly at Posyandu Lansia Developed by Puskesmas Ngoresan, Surakarta
Bibliographic record
Abstract
Introduction: Hypertension is a condition of increasing blood pressure and it causes certain symptoms which will further damage the body. Elderly or a person older than 60 years old will be more susceptible to hypertension because there were many changes in body function and structure. Hypertension will lead to changes in vascular structures, disruption of cerebral autoregulation, white matter lesion, lacunar infarction, and eventually result in cognitive impairment. This study aim s to determine a relation of hypertension to cognitive impairment in elderly at Posyandu Lansia developed by Puskesmas Ngoresan , Surakarta and factors which affect cognitive impairment. Methods: This was an observational analytic research with a cross sectional study. This research was done in Posyandu Lansia and general clinic of Puskesmas Ngoresan , Surakarta. The subject of the research was the elderly with hypertension at Puskesmas Ngoresan , Surakarta, male, aged ≥ 60 years, and literate. The 60 sample s were taken using purposive sampling technique, which consist of 30 with hypertension and 30 without hypertension. Blood pressure was measured by using mercury sphygmomanometer. The assesment of cognitive function was done by using the Indonesian version of Montreal Cognitive Assessment (MoCA-Ina). The data were analyzed using chi square and multiple logistic regression . Result s : The result of analytic test between hypertension and cognitive impairment showed significant relation (OR = 7.59; CI 95% = 1.73 – 33.30; p = 0,007) . There was significant relation between smoking activity and cognitive impairment (OR = 0.07; CI 95% = 0.01 – 0.40; p = 0.003 ). L evel of education and hypertension duration showed no n significant relation to cognitive impairment with each value is p = 0.059; p = 0.697. Conclusion s : Hypertension is a factor that increases the risk of cognitive impairment and smoking is a factor that decreases the risk of cognitive impairment. Keywords : Cognitive Impairment, Hypertension
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.001 | 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".