Prevalence and Associated Factors of Diabetic ketoacidosis among Patients Living with Type 1 Diabetes in Makkah Al-Mukarramah City
Bibliographic record
Abstract
Objective: To assess magnitude of diabetic ketoacidosis (DKA) among type-1 diabetics and to identify associated risk factors. Methods: A cross-sectional study was conducted among 236 type-1 diabetics in Makkah Al-Mukarramah City, Saudi Arabia. Results: Among participants, 59.3% were males, 44.1% were diabetic for more than 5 years, while 70.8% reported past history of DKA. The main causes of DKA were gfirst presentation of the diseaseh (40.9%), and gdiscontinued treatmenth (37%). The HbA1c among 53.6% was above 9%. Almost all cases who experienced DKA were hospitalised (98.8%). Out of them, 9 (5.4%) suffered complications. Female patients were more likely to suffer from episodes of DKA than males (76% and 68.3%, respectively). Most patients whose parentsf highest education was primary level had DKA more frequently than those whose parentsf had postgraduate education. Patients with unemployed fathers had significantly higher frequency of DKA (p=0.004). Ketoacidosis was significantly more frequent among patients with parentsf consanguinity (p<0.001). Patients who had their current HbA1c level exceeding 9% had positive history of DKA compared to those with HbA1c level .7% (87.9% and 28.6%, respectively, p<0.001). Conclusion: Most type-1 diabetics experience DKA, mainly with their first presentation of disease or due to discontinuation of treatment. DKA tends to occur more frequently among female patients, those with less educated parents or when their parents are relatives. Key words: Type 1 diabetes, diabetic ketoacidosis, magnitude, risk factors.
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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 | 0.000 | 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".