Safety and impact of peripheral parenteral nutrition on nutrient delivery in patients with nutrition risk: A prospective observational study
Bibliographic record
Abstract
BACKGROUND: Malnutrition is common in hospitalized patients and strategies to improve energy and protein intake have a positive impact on outcome. Despite early evidence suggesting the usefulness of peripheral parenteral nutrition (PPN), its adoption has been hampered by concerns regarding safety and efficacy. This study addresses this issue. METHODS: This prospective observational study was performed in medical and surgical inpatients in who were screened for nutrition risk and assessed using Subjective Global Assessment (SGA). Data captured included nutrition status, energy and protein requirements, intravenous access, indications for PPN, use of supplemental micronutrients, and disposition of patients on PPN. RESULTS: Ninety-eight patients were recruited from two centers over 8 months. The average age was 61.5 years, the mean Charlson Comorbidity Index was 4.21 (±3.09), 52% were male, and 48% were admitted to medicine, whereas 52% were admitted to surgery. Thirty-three percent of patients were SGA C, 44% were SGA B, and 19% were SGA A. Twenty-seven percent of patients had cancer. The average length of hospital stay was 22 days. The main indications for PPN were gastrointestinal tract dysfunction (72%) and postsurgical status (16%). PPN provided an average of 1296 kcal (±191) and 46 g of protein (±7). Intravenous access complications in patients receiving PPN did not occur in excess of expected. Almost 40% of patients required transition to central PN. CONCLUSIONS: PPN is a safe, effective way to deliver supplemental protein, energy, and micronutrients to malnourished patients and supports transition to other modes of nutrition care.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".