Omega-3 Long-Chain Polyunsaturated Fatty Acids for Extremely Preterm Infants: A Systematic Review
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Omega-3 long chain polyunsaturated fatty acid (LCPUFA) exposure can be associated with reduced neonatal morbidities. We systematically review the evidence for the benefits of omega-3 LCPUFAs for reducing neonatal morbidities in extremely preterm infants. METHODS: Data sources were PubMed, Embase, Center for Reviews and Dissemination, and the Cochrane Register of Controlled Trials. Original studies were selected that included infants born at <29 weeks' gestation, those published until May 2013, and those that evaluated the relationship between omega-3 LCPUFA supplementation and major adverse neonatal outcomes. Data were extracted on study design and outcome. Effect estimates were pooled. RESULTS: Of the 1876 studies identified, 18 randomized controlled trials (RCTs) and 6 observational studies met the defined criteria. No RCT specifically targeted a population of extremely preterm infants. Based on RCTs, omega-3 LCPUFA was not associated with a decreased risk of bronchopulmonary dysplasia in infants overall (pooled risk ratio [RR] 0.97, 95% confidence interval [CI] 0.82-1.13], 12 studies, n = 2809 infants); however, when considering RCTs that include only infants born at ≤32 weeks' gestation, a trend toward a reduction in the risk of bronchopulmonary dysplasia (pooled RR 0.88, 95% CI 0.74-1.05, 7 studies, n = 1156 infants) and a reduction in the risk of necrotizing enterocolitis (pooled RR 0.50, 95% CI 0.23-1.10, 5 studies, n = 900 infants) was observed with LCPUFA. CONCLUSIONS: Large-scale interventional studies are required to determine the clinical benefits of omega-3 LCPUFA, specifically in extremely preterm infants, during the neonatal period.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".