What question did this study set out to answer?

To validate an AI-enabled ECG model for predicting biological sex in pediatric patients.

February 28, 2026Open Access

Multicenter validation of AI-enabled ECG for pediatric biological sex prediction

Q: What is the clinical evidence from this study?

Study design: Observational. Population: Pediatric patients aged 0-18 years undergoing electrocardiogram (ECG) testing with known biological sex (n=67578). Intervention: AI-enabled electrocardiogram (AI-ECG) biological sex prediction model vs. None (model performance evaluated against actual biological sex). Primary outcome: Accuracy of AI-enabled ECG model in predicting biological sex across pubertal stages measured by AUROC (AUROC 0.80 overall).

Key Result

AI-enabled ECG predicted pediatric biological sex with an overall AUROC of 0.80, improving from 0.64 pre-puberty to 0.94 post-puberty at Texas Children’s Hospital.

Key Points

To validate an AI-enabled ECG model for predicting biological sex in pediatric patients.
Multicenter validation across Mayo Clinic, Texas Children’s Hospital, and Boston Children’s Hospital.
External validation of a previously published ECG model with a focus on puberty-linked changes.
Assessment of AUROC (Area Under the Receiver Operating Characteristic) curves during different developmental stages.
Pre-puberty AUROC of 0.64, peri-puberty AUROC of 0.84, and post-puberty AUROC of 0.94 were observed.
The phenomenon of AUROC gradients linked to puberty was replicated at multiple sites.
Saliency mapping showed distinct electrophysiologic patterns tied to biological sex.

Study Design

Type

Observational (n=67,578)

Multicenter

Yes

Structured PICO

Does an AI-enabled ECG model accurately predict biological sex across different stages of pediatric development?

Population

Pediatric patients ≤18 years old across multiple institutions. Texas Children's Hospital (TCH) cohort: n=67,578, 52.7% male, median age 9.0 years. Boston Children's Hospital (BCH) training cohort: n=151,215, 49% male, median age 11.6 years. BCH test cohort: n=50,405, 49% male, median age 12.0 years.

Intervention

AI-enabled 12-lead ECG model (one-dimensional convolutional neural network) for biological sex prediction

Outcome

Prediction of biological sex measured by Area Under the Receiver Operating Characteristic curve (AUROC) across pubertal strata (pre-puberty, peri-puberty, post-puberty)surrogate

AI-enabled ECG prediction of biological sex in pediatric patients is highly dependent on pubertal status, suggesting the model captures a hormone-linked electrophysiologic profile that emerges during puberty.

Main Result

Effect estimate: AUROC 0.80 overall

Limitations

Absence of clinical pubertal staging or hormone assays to corroborate pubertal status
Reliance on binary biological sex labels from electronic health records
Incomplete race and ethnicity data across cohorts
Variability in ECG recording sample rates between institutions
No assessment of impact of ECG recording duration on model performance

Abstract

Biological sex is closely linked to patterns embedded within the electrocardiogram (ECG) with essential health and disease implications. We report multicenter verification of an AI-enabled ECG model to predict biological sex across pediatric development. A previously published Mayo Clinic model confirmed puberty-linked AUROC gradient during external validation at Texas Children’s Hospital (pre-puberty AUROC 0.64, peri-puberty AUROC 0.84, post-puberty AUROC 0.94). This phenomenon was replicated at Boston Children’s Hospital. Saliency mapping revealed established sex-related electrophysiologic patterns.

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Cite This Study

O’Sullivan et al. (Thu,) conducted a observational in Pediatric patients aged 0-18 years undergoing electrocardiogram (ECG) testing with known biological sex (n=67,578). AI-enabled electrocardiogram (AI-ECG) biological sex prediction model vs. None (model performance evaluated against actual biological sex) was evaluated on Accuracy of AI-enabled ECG model in predicting biological sex across pubertal stages measured by AUROC (AUROC 0.80 overall). AI-enabled ECG predicted pediatric biological sex with an overall AUROC of 0.80, improving from 0.64 pre-puberty to 0.94 post-puberty at Texas Children’s Hospital.

synapsesocial.com/papers/69a286b80a974eb0d3c01d9a https://doi.org/https://doi.org/10.1038/s41746-026-02416-9

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