Prevalence of Chronic Complication among Type 2 Diabetics Attending Primary Health Care Centers of Al Ahsa District of Saudi Arabia: A Cross Sectional Survey
Bibliographic record
Abstract
BACKGROUND: The morbidity and mortality related to diabetes is a great global concern. The knowledge of chronic complications of diabetes and associated co morbidity factors is very important for formulating the necessary policies and action plan. AIMS: To determine the prevalence of chronic complications and comorbidity among the type 2 diabetics attending the primary health care centers of Al Ahsa district of Saudi Arabia. MATERIAL & METHODS: This cross sectional retrospective survey was carried out on 506 type 2 diabetic patients attending the different primary health care centers of ministry of health, Al Ahsa. Data regarding the co morbidity factors and chronic complications were recorded from the health records of the selected diabetic patients. Data analysis was done by SPSS version 16. A p < 0.05 was considered significant for all statistical calculations. RESULTS: Overall 72.72% (95% CI 69.78-74.45) of the study subjects were suffering from one or more complications of diabetic mellitus. Among them 33.39% (165) were suffering from single, 25.29% (128) with two and 15% (75) from more than two complications. The overall prevalence of complication among the female subjects was significantly higher than the male (78.16%, 95% CI 76.76-84.40 Vs 65.76%, 95% CI 61.63-69.89, p=.038). The chronic complication was higher among the urban population than the rural population (77.3% 95% CI 72.88-80.26 Vs 69.78% 95% CI 66.1%-76.92%, p=.035). CONCLUSION: The result showed a high percentage of chronic complications among the diabetic patients of this region. The high percentage of obesity, hypertension and dyslipidaemia among them are important co morbidity factors which if not controlled can cause further increase in the number of chronic complications.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".