# From touch to triage: translating the NAME model into clinical practice for enhanced neonatal assessment

**Authors:** Francesco Cerritelli, Caterina Accardi, Alessia Alati, Adele Alberti, Marco Chiera, Matteo Galli, Chiara Leva, Erica Lombardi, Micol Pivotto, Sonia Travaglini, Sonia Zanini, Jordan Keys, Kimberly Wolf, Andrea Manzotti

PMC · DOI: 10.3389/fped.2026.1734450 · Frontiers in Pediatrics · 2026-03-04

## TL;DR

This paper explores how to integrate the NAME model into neonatal care to improve early detection and outcomes for newborns in NICUs.

## Contribution

The paper proposes a clinically implementable framework for integrating the NAME model into NICU workflows.

## Key findings

- NAME scores correlate significantly with gestational age, birth weight, and complexity indices (p < 0.001).
- Inter-rater reliability is moderate-to-good, with high content validity (CVI ≥ 0.9) across NICU disciplines.
- A structured roadmap for NAME integration includes training guidelines and score interpretation algorithms.

## Abstract

The Neonatal Assessment Manual scorE (NAME) model has emerged as a novel, structured, touch-based approach to evaluating neonates’ general conditions, with growing evidence supporting its validity and reliability in NICU settings. However, there is a critical need to integrate this method into clinical workflows and explore its translational potential in improving neonatal care. This paper aims to consolidate the body of evidence surrounding the NAME model and propose a clinically implementable strategy to enhance neonatal assessment, early detection of complications, and overall health outcomes in NICU settings.

We critically appraised key NAME studies encompassing theoretical rationale, construct and content validity, inter-rater reliability, and clinical correlations in NICU populations. Drawing from these findings, we developed a stepwise clinical framework for NAME integration, aligning it with existing neonatal care protocols.

Evidence demonstrates that NAME scores correlate significantly with infants’ gestational age, birth weight, and complexity indices (p < 0.001), providing a rapid and non-invasive method to stratify newborns’ health conditions. Inter-rater reliability is moderate-to-good, particularly for “Marginal” classifications, and professionals across NICU disciplines found the method to have high content validity (CVI ≥ 0.9). A structured roadmap for clinical integration is proposed, including operator training guidelines, NAME score interpretation algorithms, and embedding NAME within multidisciplinary rounds.

The NAME model, grounded in physiological and clinical evidence, represents a promising paradigm shift in neonatal assessment. Its systematic adoption may facilitate early risk detection, personalized care planning, and improved outcomes in NICU populations. Future implementation studies are needed to validate its operational impact across diverse care settings and age groups.

## Full text

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## Figures

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## References

38 references — full list in the complete paper: https://tomesphere.com/paper/PMC12996127/full.md

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Source: https://tomesphere.com/paper/PMC12996127