Risk factors for development of diabetes mellitus (Type 3c) after partial pancreatectomy: A systematic review
Bibliographic record
Abstract
OBJECTIVES: Type 3c diabetes mellitus (T3cDM) occurring post pancreatectomy can be challenging to treat due to the frequent combination of decreased circulating levels of insulin and glucagon and concurrent exocrine insufficiency. Relatively, little is known regarding the risk factors for development of T3cDM post pancreatectomy. Our aim was to review the literature and assess what is known of the risk factors for the development of new-onset DM following partial pancreatic resection and where possible determines the incidence, time of onset and the management approach to hyperglycaemia in this context. DESIGN: Medline and Embase databases were reviewed using specific keyword criteria. Original manuscripts published in 1990 or later included. Articles with study population <20, lacking information on new-onset DM, follow-up duration or specifically targeting rare procedures/pathology were excluded. The Newcastle Ottawa Quality Assessment form was applied. Results reported according to PRISMA guidelines. Pooled effect size calculated using random effects model. PATIENTS: Thirty six articles were identified that described a total of 5636 patients undergoing pancreaticoduodenectomy, 3922 patients having distal pancreatectomy and 315 with central pancreatectomy. RESULTS: The incidence of new-onset DM was significantly different between different types of resection from 9% to 24% after pancreaticoduodenectomy (pooled estimate 16%; 95% CI: 14%-17%), 3%-40% after distal pancreatectomy (pooled estimate 21%; 95% CI: 16%-25%) and 0%-14% after central pancreatectomy (pooled estimate 6%; 95% CI: 3%-9%). Surgical site, higher preoperative HbA1c, fasting plasma glucose and lower remnant pancreatic volume had strongest associations with new-onset DM. CONCLUSIONS: This systematic review supports that risk of development of T3cDM is associated with type of pancreatic resection, lower remnant pancreatic volume and higher preoperative HbA1c.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".