Diabetes Melitus Tipe 2 dan Hipertensi sebagai Faktor Risiko PJK pada Lansia
Bibliographic record
Abstract
The elderly are still a significant concern today, because of the many types of diseases that this group suffers from, including coronary heart disease. This disease often coincides in the elderly due to changes in the characteristics of the elderly blood vessels coupled with uncontrolled diet and physical activity, therefore it is important to conduct research related to the relationship between type 2 diabetes mellitus and hypertension in the elderly as a risk of heart disease so that education can be carried out to prevent an increase in the incidence of coronary heart disease. The purpose of this study was to analyze the risk factors for type 2 diabetes mellitus and the incidence of hypertension as a risk factor for coronary heart disease (CHD) using a Framingham risk score for the elderly at the nursing home at Lhokseumawe City in 2022. The research design used was a cross-sectional study in which exposure and impact are measured at the same time. The sample is all the elderly in the nursing home in Lhokseumawe City. The results showed a significant relationship between diabetes mellitus and hypertension on the risk of coronary heart disease. In conclusion, diabetes mellitus and hypertension are risk factors for coronary heart disease.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".