Initiation of Enteral Feeding After Necrotizing Enterocolitis
Bibliographic record
Abstract
Introduction Management of necrotizing enterocolitis (NEC) consists of cessation of enteral feeding, intravenous antibiotic administration, and supportive treatment. There is no evidence-based recommendation regarding when to restart feeding after a NEC episode. We performed a systematic review and meta-analysis to examine the effect of timing of enteral feeding reinitiation on NEC recurrence. Methods MEDLINE, Embase, Google scholar, and Cochrane databases were searched. Human studies evaluating enteral feeding timing with a primary outcome of NEC recurrence were included. A total of 2,257 titles or abstracts were screened, and 47 full-text articles were analyzed. A systematic review and meta-analysis comparing NEC recurrence and other associated outcomes between early (<5 days after NEC diagnosis) and delayed (>5 days) initiation of enteral feeding after NEC were performed according to the PRISMA statement. The meta-analysis data were analyzed using RevMan 5.3 to estimate odds ratios (ORs) with 95% confidence intervals (CIs). Results Two retrospective observational studies met the inclusion criteria, comprising 56 cases in which enteral feeding was started early and 35 cases of delayed enteral feeding initiation. There were no randomized controlled trials (RCTs). The recurrence rates of NEC were unchanged between early (5.4%) and delayed (8.6%) enteral feeding groups (pooled OR = 0.61; 95% CI: 0.12–3.16; p = 0.56; I 2 = 0%). Catheter-related sepsis (pooled OR = 0.20; 95% CI: 0.01–3.29; p = 0.26; I 2 = 67%) and post-NEC stricture (pooled OR = 0.28; 95% CI: 0.07–1.18; p = 0.08; I 2 = 23%) rates were not different between early and delayed enteral feeding groups. Conclusion Initiating early enteral feeding, within 5 days of NEC diagnosis, is not associated with adverse outcomes, including NEC recurrence. In addition, catheter-related sepsis and post-NEC stricture rates were unchanged between early and delayed enteral feeding groups after NEC. However, the quality of the evidence from the review of literature is suboptimal. A further RCT is needed to confirm these results.
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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.010 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".