Enteral and parenteral nutrition in cancer patients: a systematic review and meta-analysis.
Bibliographic record
Abstract
BACKGROUND: In cancer patients, weight loss is an ominous sign suggesting disease progression and shortened survival time. As a result, providing nutrition support for cancer patients has been proposed as a logical approach for improving clinical outcomes. Nutrition support can be given to patients through enteral nutrition (EN) or parenteral nutrition (PN). The purpose of the review was to compare the outcomes of PN and EN in cancer patients. METHODS: A literature search was conducted in Ovid MEDLINE and OLDMEDLINE, Embase Classic and Embase, and Cochrane Central Register of Controlled Trials. Studies were included if over half of the patient population had cancer and reported on any of the following endpoints: the percentage of patients that experienced no infection, nutrition support complications, major complications or mortality. Risk ratios (RR) and 95% confidence intervals (CIs) using Review Manager Version 5.3 were calculated. Primary endpoints were stratified according to type of EN for subgroup analysis, grouping studies into either tube feeding (TF) or standard care (SC). Additionally, another subgroup analysis was conducted comparing studies with protein-energy malnutrition (PEM) patients and studies without PEM patients. RESULTS: The literature search yielded 674 articles of which 36 were included for the meta-analysis. There were no difference in the endpoints between the two study interventions except that PN resulted in more infection when compared with EN (RR =1.09, 95% CI: 1.01-1.18; P=0.03). CONCLUSIONS: Other than increased incidence of infection, PN has not resulted in prolonging the survival, increasing nutrition support complications, or major complications when compared with EN in cancer patients.
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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 | 0.009 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.032 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".