Paper
Dose-Dependent Cardiac Complexity Changes in Children Following Prenatal Glucocorticoid Exposure: Complementary Evidence from Multiscale Entropy Analysis and ECG Foundation Models
Authors
Nicolas B. Garnier, Michelle Dreiling, Valeska Kozik, Matthias Schwab, Florian Rakers, Martin G Frasch
Abstract
\noindent\textbf{Background} Prenatal glucocorticoid exposure alters cardiac development, but whether persistent cardiac effects in childhood follow a dose-response relationship remains unknown. We recently showed that ECG foundation models detect robust cardiac differences between steroid-exposed and control children, while traditional heart rate variability metrics lose significance after covariate adjustment. Here, we investigate the dose-response dimension using complementary analytical approaches. \noindent\textbf{Methods} We studied 49 children (ages 8--15) whose mothers received betamethasone during pregnancy for multiple sclerosis: 12 low-dose ({$<$}5\,g cumulative), 13 high-dose ({$\geq$}5\,g), and 24 controls. Five-minute ECG recordings during the Trier Social Stress Test yielded 251 observations. We computed 12 multiscale complexity features and tested 11 ECG foundation model (FM) dimensions using linear mixed models, Kruskal--Wallis tests with Dunn's post-hoc comparisons, Spearman correlations, and Jonckheere--Terpstra trend tests. \noindent\textbf{Findings} The binary exposed-versus-controls comparison showed no significant complexity effects ($p>0.39$). However, dose-based analysis revealed that high-dose children exhibited significantly faster entropy rate ($h$) decay rates than low-dose children ($p=0.031$); neither sample entropy nor approximate entropy decay rates reached significance ($p=0.18$ and $p=0.12$, respectively). Effects localized to the mental arithmetic stress segment (Kruskal--Wallis $p=0.005$; Dunn's $p=0.004$). A cross-condition robustness analysis confirmed that $h$ decay rate is invariant to input signal choice and normalization ($r>0.98$), while sample and approximate entropy are not. In contrast, the 11 FM dimensions showed weak dose-response evidence: only 1 of 22 covariate-adjusted contrasts survived FDR correction, with paradoxically stronger low-dose effects. \noindent\textbf{Interpretation} The entropy rate decay rate -- uniquely robust across input conditions -- reveals a dose-dependent effect on cardiac autonomic dynamics under cognitive stress, while FM dimensions detect a dose-independent morphological ``exposure fingerprint.'' These exploratory findings suggest a two-component model of prenatal glucocorticoid cardiac programming -- ~morphological (dose-independent) and dynamical (dose-dependent)~ -- providing more complete characterization than either approach alone. Given the small sample size, these results should be considered hypothesis-generating and require replication in larger cohorts.
Metadata
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"raw_xml": "<entry>\n <id>http://arxiv.org/abs/2603.04074v1</id>\n <title>Dose-Dependent Cardiac Complexity Changes in Children Following Prenatal Glucocorticoid Exposure: Complementary Evidence from Multiscale Entropy Analysis and ECG Foundation Models</title>\n <updated>2026-03-04T13:48:07Z</updated>\n <link href='https://arxiv.org/abs/2603.04074v1' rel='alternate' type='text/html'/>\n <link href='https://arxiv.org/pdf/2603.04074v1' rel='related' title='pdf' type='application/pdf'/>\n <summary>\\noindent\\textbf{Background} Prenatal glucocorticoid exposure alters cardiac development, but whether persistent cardiac effects in childhood follow a dose-response relationship remains unknown. We recently showed that ECG foundation models detect robust cardiac differences between steroid-exposed and control children, while traditional heart rate variability metrics lose significance after covariate adjustment. Here, we investigate the dose-response dimension using complementary analytical approaches. \\noindent\\textbf{Methods} We studied 49 children (ages 8--15) whose mothers received betamethasone during pregnancy for multiple sclerosis: 12 low-dose ({$<$}5\\,g cumulative), 13 high-dose ({$\\geq$}5\\,g), and 24 controls. Five-minute ECG recordings during the Trier Social Stress Test yielded 251 observations. We computed 12 multiscale complexity features and tested 11 ECG foundation model (FM) dimensions using linear mixed models, Kruskal--Wallis tests with Dunn's post-hoc comparisons, Spearman correlations, and Jonckheere--Terpstra trend tests. \\noindent\\textbf{Findings} The binary exposed-versus-controls comparison showed no significant complexity effects ($p>0.39$). However, dose-based analysis revealed that high-dose children exhibited significantly faster entropy rate ($h$) decay rates than low-dose children ($p=0.031$); neither sample entropy nor approximate entropy decay rates reached significance ($p=0.18$ and $p=0.12$, respectively). Effects localized to the mental arithmetic stress segment (Kruskal--Wallis $p=0.005$; Dunn's $p=0.004$). A cross-condition robustness analysis confirmed that $h$ decay rate is invariant to input signal choice and normalization ($r>0.98$), while sample and approximate entropy are not. In contrast, the 11 FM dimensions showed weak dose-response evidence: only 1 of 22 covariate-adjusted contrasts survived FDR correction, with paradoxically stronger low-dose effects. \\noindent\\textbf{Interpretation} The entropy rate decay rate -- uniquely robust across input conditions -- reveals a dose-dependent effect on cardiac autonomic dynamics under cognitive stress, while FM dimensions detect a dose-independent morphological ``exposure fingerprint.'' These exploratory findings suggest a two-component model of prenatal glucocorticoid cardiac programming -- ~morphological (dose-independent) and dynamical (dose-dependent)~ -- providing more complete characterization than either approach alone. Given the small sample size, these results should be considered hypothesis-generating and require replication in larger cohorts.</summary>\n <category scheme='http://arxiv.org/schemas/atom' term='q-bio.QM'/>\n <published>2026-03-04T13:48:07Z</published>\n <arxiv:primary_category term='q-bio.QM'/>\n <author>\n <name>Nicolas B. Garnier</name>\n <arxiv:affiliation>Phys-ENS, INP-CNRS</arxiv:affiliation>\n </author>\n <author>\n <name>Michelle Dreiling</name>\n </author>\n <author>\n <name>Valeska Kozik</name>\n </author>\n <author>\n <name>Matthias Schwab</name>\n </author>\n <author>\n <name>Florian Rakers</name>\n </author>\n <author>\n <name>Martin G Frasch</name>\n </author>\n </entry>"
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