AB047. 8. Prevalence of diabetes mellitus in patients with chronic pancreatitis: a systematic review
Bibliographic record
Abstract
Background: Diabetes mellitus is one of the most common chronic illness and the economic burden of it on Irish health care system is significant. The CODEIRE study showed that 207,490 (6.5%) had it in 2013 and will increase to 233,000 by 2020. Pancreatogenic diabetes [AKA type 3c diabetes (T3cDM)] is frequently misclassified as type 1 or 2. The failure to correctly diagnose T3cDM and to recognise its distinctive complications leads to failure to implement an appropriate medical therapy. However, there is no systematic analysis of the prevalence or occurrence of diabetes in patients with chronic pancreatitis. The aim of the study is to conduct a systematic review of the prevalence of diabetes in patient with chronic pancreatitis and if data is amenable, a metanalysis will be conducted. Methods: According to the Joanna Briggs Institute Reviewers’ Manual 2014, CoCoPop mnemonic was used for inclusion criteria. Two reviewers independently evaluate the studies for quality using Newcastle-Ottawa Scale. Results: Based on the study, a prevalence of 5–10% of the population was observed. Similarly, an analysis of the factors associated with the increase occurrence of diabetes in chronic pancreatitis including age, gender, duration of follow-up, geographical location, surgery and smoking. Conclusions: According to our systematic review, the prevalence of T3cDM is higher than the calculated occurrence as most of them are underdiagnosed, undertreated and under-appreciated. Better understanding of T3DM would help in better evaluation and treatment of the disease
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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 | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".