Paracetamol for the treatment of patent ductus arteriosus in preterm neonates: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: We performed a systematic review and meta-analysis of all the available evidence to assess the efficacy and safety of paracetamol for the treatment of patent ductus arteriosus (PDA) in neonates, and to explore the effects of clinical variables on the risk of closure. DATA SOURCE: MEDLINE, Scopus and ISI Web of Knowledge databases, using the following medical subject headings and terms: paracetamol, acetaminophen and patent ductus arteriosus. Electronic and manual screening of conference abstracts from international meetings of relevant organisations. Manual search of the reference lists of all eligible articles. STUDY SELECTION: Studies comparing paracetamol versus ibuprofen, indomethacin, placebo or no intervention for the treatment of PDA. DATA EXTRACTION: Data regarding efficacy and safety were collected and analysed. RESULTS: Sixteen studies were included: 2 randomised controlled trials (RCTs) and 14 uncontrolled studies. Quality of selected studies is poor. A meta-analysis of RCTs does not demonstrate any difference in the risk of ductal closure (Mantel-Haenszel model, RR 1.07, 95% CI 0.87 to 1.33 and RR 1.03, 95% CI 0.92 to 1.16, after 3 and 6 days of treatment, respectively). Proportion meta-analysis of uncontrolled studies demonstrates a pooled ductal closure rate of 49% (95% CI 29% to 69%) and 76% (95% CI 61% to 88%) after 3 and 6 days of treatment with paracetamol, respectively. Safety profiles of paracetamol and ibuprofen are similar. CONCLUSIONS: Efficacy and safety of paracetamol appear to be comparable with those of ibuprofen. These results should be interpreted with caution, taking into account the non-optimal quality of the studies analysed and the limited number of neonates treated with paracetamol so far.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.037 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".