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Revisiting the Neuropathology of Sudden Infant Death Syndrome (SIDS)
Jessica Blackburn1,2, Valeria F Chapur3,4, Julie A Stephens5
1Division of Neuropathology, Department of Pathology, The Ohio State University College of Medicine, Columbus, OH, United States.
Insights
Sudden infant death syndrome (SIDS) may have distinct subtypes with unique risk factors. Machine learning identified three SIDS groups, revealing disparities in clinical guideline impact and birth weight outcomes.
Area of Science:
- Pediatrics
- Public Health
- Computational Biology
Background:
- Sudden infant death syndrome (SIDS) is a leading cause of infant mortality.
- The neuropathological basis of SIDS remains controversial, with potential links to prenatal/postnatal care and health disparities.
- The triple-risk hypothesis suggests SIDS occurs from a combination of biological abnormality, extrinsic risk, and critical developmental period.
Purpose of the Study:
- To review SIDS neuropathological literature.
- To utilize machine learning to identify distinct SIDS decedent subtypes based on epidemiological data.
- To analyze geographical and demographic variations in SIDS rates.
Main Methods:
- Analysis of US Period Linked Birth/Infant Mortality Files (1990-2017, excluding 1992-1994).
- Application of t-SNE (t-distributed Stochastic Neighbor Embedding) for unsupervised clustering of SIDS decedents.
- Examination of SIDS rate changes at state and international levels.
Main Results:
- Three distinct SIDS decedent groups were identified using t-SNE, each with a unique peak age of death.
- SIDS rates exhibit geographical heterogeneity within the US.
- Clinical guideline implementation has unequally affected SIDS rates for low and normal birth weight infants.
Conclusions:
- Identified SIDS groups possess different epidemiological and extrinsic risk factors.
- Clinical guidelines have not uniformly reduced SIDS across all identified groups.
- Normal birth weight infants represent a larger proportion of SIDS cases, despite higher SIDS rates in low birth weight infants.
Abstract:
Background: Sudden infant death syndrome (SIDS) is one of the leading causes of infant mortality in the United States (US). The extent to which SIDS manifests with an underlying neuropathological mechanism is highly controversial. SIDS correlates with markers of poor prenatal and postnatal care, generally rooted in the lack of access and quality of healthcare endemic to select racial and ethnic groups, and thus can be viewed in the context of health disparities. However, some evidence suggests that at least a subset of SIDS cases may result from a neuropathological mechanism. To explain these issues, a triple-risk hypothesis has been proposed, whereby an underlying biological abnormality in an infant facing an extrinsic risk during a critical developmental period SIDS is hypothesized to occur. Each SIDS decedent is thus thought to have a unique combination of these risk factors leading to their death. This article reviews the neuropathological literature of SIDS and uses machine learning tools to identify distinct subtypes of SIDS decedents based on epidemiological data. Methods: We analyzed US Period Linked Birth/Infant Mortality Files from 1990 to 2017 (excluding 1992-1994). Using t-SNE, an unsupervised machine learning dimensionality reduction algorithm, we identified clusters of SIDS decedents. Following identification of these groups, we identified changes in the rates of SIDS at the state level and across three countries. Results: Through t-SNE and distance based statistical analysis, we identified three groups of SIDS decedents, each with a unique peak age of death. Within the US, SIDS is geographically heterogeneous. Following this, we found low birth weight and normal birth weight SIDS rates have not been equally impacted by implementation of clinical guidelines. We show that across countries with different levels of cultural heterogeneity, reduction in SIDS rates has also been distinct between decedents with low vs. normal birth weight. Conclusions: Different epidemiological and extrinsic risk factors exist based on the three unique SIDS groups we identified with t-SNE and distance based statistical measurements. Clinical guidelines have not equally impacted the groups, and normal birth weight infants comprise more of the cases of SIDS even though low birth weight infants have a higher SIDS rate.
