Pentraxin-3 and neonatal sepsis: a systematic review and meta-analysis
Bibliographic record
Abstract
The potential bond between pentraxin-3 levels and neonatal sepsis has been the center of research in many primary studies. The aim of the current meta-analysis is to examine whether there are differences among pentraxin-3 levels in septic and in healthy neonates. Our search strategy included the systematic search of the following databases: MEDLINE, Clinicaltrials.gov, Cochrane Central Register of Controlled Trials (CENTRAL), Google Scholar, using a structured algorithm. Statistical analysis of the overall outcome was done using Revman 5.4 software while leave-one-out and meta-regression analysis were done using the R software. Quality assessment of the included studies was done using the Newcastle-Ottawa scale. Pentraxin-3 levels were found to be higher in newborns affected by sepsis than in healthy neonates with an MD = 7.66 [95% CI 0.89, 14.42 (p = .03, I2 = 99%)]. Subgroup analysis, based on the country of origin of the included study, led to I2 = 0 with an MD = 1.25 with 95% CI [0.82, 1.69], p < 10−5. Publication bias was assessed using the trim and fill method together with visual inspection of the funnel plots, showcasing no missing studies. The results of our study show that pentraxin-3 is elevated in neonates with sepsis making it a potential biomarker that needs to be assessed for its diagnostic accuracy in future cohort studies.
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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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.041 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".