New-Onset Diabetes Mellitus After Distal Pancreatectomy: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background and Objective: Endocrine insufficiency must be considered following distal pancreatectomy (DP), because diabetes mellitus can impose a long-term burden on patients. This systematic review and meta-analysis aimed to identify the incidence and severity of new-onset diabetes mellitus (NODM) after DP for benign and malignant tumors, and other indications. Methods: Articles reporting NODM after DP from PubMed, Embase, Cochrane Library, and Google Scholar were analyzed. The quality of the studies was assessed using the Newcastle–Ottawa Scale or MOGA scale. Inverse variance analysis calculated the overall NODM incidence, and 95% confidence intervals (CIs) and P values were determined. Subgroup analyses considered pre-existing pancreatic diseases. Results: The quantitative analysis involved 18 articles that described 2356 patients with pancreatic neoplasms or inflammatory lesions. The overall incidence of NODM after DP was 29% (95% CI 25–33). The NODM rates were 23% (95% CI 17–30) and 38% (95% CI 30–45) for patients with pancreatic neoplasms and chronic pancreatitis, respectively. Pre-existing chronic pancreatitis and being male were risks associated with NODM. Conclusion: NODM is fairly common after DP. Surgeons and patients should be aware of postoperative treatment-dependent endocrine dysfunction. Larger cohort studies are required to clarify the risk factors for NODM after DP.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.025 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".