New Onset of Diabetes and Pancreatic Exocrine Insufficiency After Pancreaticoduodenectomy for Benign and Malignant Tumors
Bibliographic record
Abstract
OBJECTIVE: The aim of this study was to assess the frequency and severity of new onset of diabetes mellitus (NODM) and pancreatic exocrine insufficiency (PEI) after pancreaticoduodenectomy (PD) for benign and malignant tumors. SUMMARY BACKGROUND DATA: When PD is performed on patients for benign tumors, the question of long-term metabolic dysfunctions becomes of importance. METHODS: Medline/PubMed, Embase, and Cochrane Library were searched for articles reporting results of measuring endocrine and exocrine pancreatic functions after PD. The methodological quality of 19 studies was assessed by means of the Newcastle-Ottawa scale and Moga-Score. The mean weighted overall percentages of NODM and PEI after PD were calculated with a 95% confidence interval (CI). RESULTS: Of 1295 patients, data valid-for-efficacy-analysis are based on 845 patients measuring pancreatic endocrine and on 964 patients determining exocrine functions after PD. The cumulative incidence of NODM was 40 of 275 patients (14.5%; 95% CI: 10.3-18.7) in the benign tumor group, 25 of 161 (15.5%; 95% CI: 9.9-21.2) in the malignant tumor group, and 91 of 409 patients (22.2%; 95% CI: 18.2-26.3) in the benign and malignant tumor group. Comparing the frequency of NODM after PD revealed significant differences between the groups (benign vs benign and malignant P < 0.0121; malignant vs benign and malignant P < 0.0017). Exocrine pancreatic insufficiency was found in the benign tumor group in 76 of 301 patients (25.2%; 95% CI: 20.3-30.7) and in the malignant tumor group in 80 of 163 patients (49.1%, 95% CI: 41.4-56.8) (P < 0.0001). CONCLUSION: The results of a significant increase of NODM after PD for benign and malignant tumors and a significant decrease of exocrine functions contribute to a rational weighting of metabolic long-term risks following PD.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".