AI for Newborn Metabolic Screening
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Artificial intelligence-based interpretation system for newborn genetic metabolic disease screening.
- Who it may be relevant to
- Registry conditions: Inherited Metabolic Disorders. Basic parameters: 2 Days — 28 Days · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
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Official title
Development and Clinical Validation of an Artificial Intelligence-Based Interpretation System for Newborn Screening of Inherited Metabolic Disorders
Overview
The goal of this clinical trial is to evaluate whether an artificial intelligence (AI)-based interpretation system can accurately diagnose inherited metabolic disorders in newborns undergoing routine screening. The main questions it aims to answer are: What is the sensitivity and specificity of the AI system compared to standard manual interpretation? Does the AI system reduce variability in screening results? Researchers will compare the AI interpretation results with those from standard manual review by trained laboratory staff to assess diagnostic performance. Participants will: Have their routine newborn screening blood samples analyzed using both the AI system and standard manual interpretation Be followed according to national newborn screening guidelines if either method indicates a positive result
Interventions
- Diagnostic test Artificial intelligence-based interpretation system for newborn genetic metabolic disease screening
This intervention is a deep learning-based software algorithm designed specifically for the interpretation of tandem mass spectrometry (MS/MS) data from routine newborn screening in Chinese neonates. It integrates clinical covariates-including gestational age, birth weight, and blood collection time-to perform multiple-of-the-median (MOM) normalization and simultaneously evaluates 42 inherited metabolic disorders. Unlike existing AI tools developed for older-generation screening panels (e.g., th
Primary outcome measures
- Sensitivity of the AI interpretation system for detecting inherited metabolic disorders [Time frame: Within 12 months after newborn screening]
- Specificity of the AI interpretation system for detecting inherited metabolic disorders [Time frame: Within 12 months after newborn screening]
Eligibility criteria
Inclusion criteria
- Newborns who underwent routine newborn screening for inherited metabolic disorders at the Zhejiang Provincial Newborn Screening Center between May 2025 and December 2027
- Blood samples collected between 2 and 28 days of age
- Availability of complete newborn screening test data and essential clinical information
Exclusion criteria
- Missing, incomplete, or poor-quality screening data
- Duplicate samples from the same newborn
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- N/A
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Screening
Study locations
China · 1 center
- The Children's Hospital, Zhejiang University School of Medicine — Hangzhou
Identifiers
NCT: NCT07368504 · 2025-IRB-0550-P-01