Decreased Cognitive Function in People with Type 2 Diabetes Mellitus
Bibliographic record
Abstract
ABSTRACTBackground: The number of cases and the prevalence of diabetes has continued to increase over the past few decades. DM itself is associated with an increased risk of cancer, kidney failure, stroke, and decreased cognitive function that leads to dementia. In 2016 Indonesia has an estimated 1.2 million people with dementia and is expected to grow to 4 million by 2050.Objective: The purpose of this study was to find out the risk factors for decreased cognitive function in people with type 2 diabetes mellitus.Method: This type of research is observational analytics with cross sectional design. The sample was 62 respondents with purposive sampling techniques. The instrument used in the study was a structured questionnaire. Measurement of cognitive function using MoCA-INA questionnaire. Data collection is done by interview method to respondents.Result: The results showed that there was a relationship between the age of the respondent (PR= 2.98; 95% CI= 0.97-9.17), and the respondent's blood sugar level (PR= 3.31; 95% CI= 1.12-9.74) to decreased cognitive function in people with type 2 diabetes mellitus.Conclusion: Age and blood sugar levels of respondents contributed to decreased cognitive function of people with type 2 diabetes mellitus.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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".