Diet and Exercise Interventions in Patients With Pancreatic Cancer
Bibliographic record
Abstract
ABSTRACT: Diet and exercise interventions may help reverse malnutrition and muscle wasting common in pancreatic cancer. We performed a scoping review to identify the knowledge gaps surrounding diet and exercise interventions. We searched PubMed, Scopus, Cumulative Index to Nursing and Allied Health Literature, Embase, ProQuest Theses and Dissertations, and Google Scholar using the umbrella terms of "pancreatic cancer," "diet/nutrition," and "exercise." Included were articles reporting on ambulatory adults with diagnosed pancreatic cancer. Excluded were studies examining prevention and/or risk, animal, or cell lines. Of the 15,708 articles identified, only 62 met the final inclusion criteria. Almost half of the articles were randomized controlled studies (n = 27). Most studies were from the United States (n = 20). The majority examined dietary interventions (n = 41), with 20 assessing the use of omega-3 fatty acids. Exercise interventions were reported in 13 studies, with 8 examining a diet and exercise intervention. Most studies were small and varied greatly in terms of study design, intervention, and outcomes. We identified 7 research gaps that should be addressed in future studies. This scoping review highlights the limited research examining the effect of diet and exercise interventions in ambulatory patients with pancreatic cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".