What is the association between common medications (indomethacin, ibuprofen and acetaminophen) and spontaneous intestinal perforations in premature infants? A systematic review protocol
Bibliographic record
Abstract
<ns3:p><ns3:bold>Background</ns3:bold><ns3:bold>:</ns3:bold> Spontaneous intestinal perforation (SIP) affects very low birth weight preterm neonates and accounts for 44% of gastrointestinal perforations. Commonly used medications such as indomethacin, ibuprofen and acetaminophen for PDA closure, increases the risk of intestinal perforation. Unfortunately, the majority of the data combine SIP with those affected by necrotizing enterocolitis (NEC) despite them being separate entities. This systematic review aims to explore the association between the use of common medications and SIP in the premature infant cohort independently from NEC.</ns3:p><ns3:p> <ns3:bold>Methods</ns3:bold><ns3:bold>:</ns3:bold><ns3:bold> </ns3:bold>Our study will focus on preterm infants with exposure to either indomethacin, ibuprofen or acetaminophen where SIP is a reported outcome. A health science librarian will search Medline and Medline in Process via OVID, Embase Classic + Embase via OVID, the LILACS database, the ScIELO database and the Cochrane Library including EBM Reviews - Cochrane Central Register of Controlled Trials. Search dates for each database will be from their respective dates of inception to March 2022. All articles will undergo screening by two independent reviewers, and if selected, data extraction with risk of bias assessment by two independent reviewers. A third reviewer will settle any disagreements that may occur. Incidence of SIP will be measured as a proportion. Individual proportions will be pooled using a random effects logistic regression model. The comparative incidence of SIP by treatment group will be measured using the odds ratio. Odds ratios will be pooled using the DerSimonian and Laird random effects model for meta-analysis.</ns3:p><ns3:p> <ns3:bold>PROSPERO Registration</ns3:bold><ns3:bold>:</ns3:bold><ns3:bold> </ns3:bold>CRD42017058603</ns3:p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".