ArticleCritical care explorations2021
Using Classification Tree Analysis to Predict the Type of Infection in Preterm Neonates: Proof of Concept Study.
Article in Critical care explorations, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- Future perspectives of heart rate and oxygenation monitoring in the neonatal intensive care unit - a narrative review.Journal of clinical monitoring and computing · 2025Review
- Biomarker Potential of Interleukin-6 in Differentiating Necrotizing Enterocolitis from Late-Onset Sepsis in Neonates Born Preterm.Journal of pediatrics. Clinical practice · 2025Article
- Diagnosis of Neonatal Sepsis: The Role of Inflammatory Markers.Frontiers in pediatrics · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLate-onset neonatal sepsis is a major complication in preterm neonates. Early identification of the type of infection could help to improve therapy and outcome depending on the suspected microorganism by tailoring antibiotic treatment to the individual patient based on the predicted organism. Results of blood cultures may take up to 2 days or may remain negative in case of clinical sepsis. Chemical biomarkers may show different patterns in response to different type of microorganisms.
objectiveThe aim of this study was to develop, as a proof of concept, a simple classification tree algorithm using readily available information from biomarkers to show that biomarkers can potentially be used in discriminating in the type of infection in preterm neonates suspected of late-onset neonatal sepsis. DERIVATION COHORT: A total of 509 suspected late-onset neonatal sepsis episodes in neonates born before less than 32 weeks of gestation were analyzed. To examine model performance, 70% of the original dataset was randomly selected as a derivation cohort ( VALIDATION COHORT: The remaining 30% of the original dataset was used as a validation cohort ( PREDICTION MODEL: A classification tree prediction algorithm was applied to predict type of infection (defined as no/Gram-positive/Gram-negative sepsis).
resultsSuspected late-onset neonatal sepsis episodes were classified as no sepsis (80.8% [
conclusionWe have developed and internally validated a simple, clinically relevant model to discriminate patients with different types of infection at moment of onset. Further research is needed to prospectively validate this in a larger population and assess whether adaptive antibiotic regimens are feasible.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.