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Record W4379526741 · doi:10.31850/makes.v6i1.1894

Diabetes Melitus Tipe 2 dan Hipertensi sebagai Faktor Risiko PJK pada Lansia

2023· article· en· W4379526741 on OpenAlexaff
Nora Maulina, Harvina Sawitri, Najwa Zakiyya, Siti Syifa

Bibliographic record

VenueJurnal Ilmiah Manusia Dan Kesehatan · 2023
Typearticle
Languageen
FieldMedicine
TopicPublic Health and Nutrition
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMedicineFramingham Risk ScoreDiabetes mellitusCoronary heart diseaseIncidence (geometry)Risk factorFramingham Heart StudyInternal medicineType 2 Diabetes MellitusDiseasePhysical therapyCardiologyEndocrinology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.148
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.028
GPT teacher head0.292
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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