Inherited Metabolic Disorders
Conditions
Brief summary
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_TESTArtificial 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., those covering only 29 analytes), this system is trained and validated on over 300,000 real-world Chinese newborn samples, making it the first AI diagnostic tool tailored to China's current expanded newborn screening program.
Sponsors
The Children's Hospital of Zhejiang University School of Medicine
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SCREENING
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
2 Days to 28 Days
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Sensitivity of the AI interpretation system for detecting inherited metabolic disorders | Within 12 months after newborn screening |
| Specificity of the AI interpretation system for detecting inherited metabolic disorders | Within 12 months after newborn screening |
Countries
China
Contacts
CONTACTHu, PhD
Outcome results
None listed