Glycemic Control X Invisible Risk Factors Among Diabetic Patients In Eastern Province
Bibliographic record
Abstract
PURPOSE: The present study tried to compare the glycemic profile of diabetic patients who live in the main two cities of in the Eastern province of (Khobar and Dammam) KSA and to find out the possible links with the environmental factors and socioeconomic status of patients. METHODS: This was a retrospective cohort study carried out in King Fahd Teaching Hospital, involving a chart review of diabetic patients during the period 1 January 2018 and 31 December 2018. All of the patients in this study were required to be living in the main studied cities of the eastern province, Saudi Arabia (Dammam and Khobar). The electronic medical records of all participants included: medication, admission, diagnosis, investigations, nursing and surgical. The invisible data (environmental and socioeconomic factors) were collected from the Urban Observatory Eastern Region. RESULTS: Evolution of the medical records in this study revealed that the level of fasting blood glucose and HbA1c was significantly higher among the resident of the Al-Khobar city. The dramatic changes in socioeconomic behaviours in the KSA along with the lack of public Education about diabetes mellitus and the imbalance between food intake and energy expenditure has brought as a real health risk for Diabetes mellitus in the Al-Khobar city, KSA. By linking the findings, the environment in Dammam tends to be healthier for its residents compared to Khobar in regard to open spaces, and pollution indicators. Moreover, The results showed that, residents of the Al-Khobar city have a higher income. CONCLUSION: The present findings suggest that there are many unseen risk factors may influence the progress and aggravation of diabetes mellitus. Very restrict strategies that create opportunities for diabetic patients to promote their health education are highly needed to control or reduce the expected diabetic complications.
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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) | 0.002 | 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".