PROFILE OF DIABETIC NEPHROPATHY PATIENTS AT WALED GENERAL HOSPITAL, CIREBON DISTRICT, INDONESIA: HIGH PREVALENCE IN PRODUCTIVE AGE GROUP, FEMALE AND HOUSEWIVES
Bibliographic record
Abstract
Objective: Diabetes Mellitus (DM) is a metabolic disease characterized by hyperglycemia due to insufficiency of insulin function. One of the complications caused by DM is Diabetic Nephropathy. This study aims to determine the profile of diabetic nephropathy patients at Waled General Hospital, Cirebon Regency, Indonesia. Methods: A descriptive observational study was conducted at Waled General Hospital, Cirebon Regency, Indonesia. All patients diagnosed with diabetic nephropathy at Internal Medicine Polyclinic from January 2018 to December 2021 were recruited. The inclusion criteria were adult diabetic nephropathy patients (aged >17 years). Results: There were 58 patients recruited into the sample, consisting of 37.9% male and 62.1% female. The majority of the sample were aged 55-64 years (44.8%) and housewives (60.3%). We also found that 87.9% of sample were productive age group (<65 years). A total of 79.4% sample had hypertension stage 1 and 2. Based on body mass index (BMI), it was found that 15.5% of the sample were overweight and 10.3% were obese. More than half (51.7%) had Random Blood Glucose (RBG) 200-300 mg/dL and about 32.8% had RBG >300 mg/dL. Conclusion: It can be concluded that diabetic nephropathy is mostly suffered productive age group <65 years, female, housewives, uncontrolled hypertension, lipid and blood glucose. Efforts to prevent DM and diabetic nephropathy need to be carried out in productive age groups, female and housewives by avoiding sedentary lifestyle, maintaining ideal body weight, preventing hypertension, dyslipidemia and optimal blood gulcose control.
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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 | 0.000 |
| 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".