Harnessing Generative Artificial Intelligence in Pediatric Anesthesia: Enhancing Learning, Patient Care, and Family Communication.

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.

1. Mechanism-aware benchmarking of large language models as learning aids in pediatric difficult airway training: true hallucinations vs. false contraindications.BMC medical education · 2026
   Article
2. Pediatric Preanesthesia Assessment Electronic Triage Tool: Implementation, Quality Improvement, and Retrospective Observational Evaluation of a Patient-Administered Questionnaire.Paediatric anaesthesia · 2026
   Observational
3. Evaluation of Five Large Language Models for Parental Education in Pediatric Anesthesia: Reliability and Readability Study.JMIR medical informatics · 2026
   Article

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

Authors and funding

4 authors.

Funding

Abstract

PubMed holds no abstract for this paper.