Blackburn Jessica, Chapur Valeria F, Stephens Julie A, Zhao Jing, Shepler Anne, Pierson Christopher R, Otero José Javier
Division of Neuropathology, Department of Pathology, The Ohio State University College of Medicine, Columbus, OH, United States.
Division of Anatomy, Department of Biomedical Education & Anatomy, The Ohio State University College of Medicine, Columbus, OH, United States.
Front Neurol. 2020 Dec 17;11:594550. doi: 10.3389/fneur.2020.594550. eCollection 2020.
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. 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. 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. 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.
婴儿猝死综合征(SIDS)是美国婴儿死亡的主要原因之一。SIDS在多大程度上表现为潜在的神经病理学机制极具争议。SIDS与产前和产后护理不佳的指标相关,这通常源于特定种族和族裔群体所特有的医疗保健可及性和质量的缺乏,因此可以在健康差距的背景下看待。然而,一些证据表明,至少一部分SIDS病例可能是由神经病理学机制导致的。为了解释这些问题,有人提出了三重风险假说,据此假设在关键发育时期面临外部风险的婴儿存在潜在的生物学异常时SIDS就会发生。因此,每个SIDS死亡者都被认为有导致其死亡的这些风险因素的独特组合。本文回顾了SIDS的神经病理学文献,并使用机器学习工具根据流行病学数据识别SIDS死亡者的不同亚型。我们分析了1990年至2017年(不包括1992 - 1994年)的美国时期链接出生/婴儿死亡档案。使用t - SNE(一种无监督机器学习降维算法),我们识别出了SIDS死亡者的聚类。在识别出这些群体之后,我们确定了州一级以及三个国家的SIDS发生率变化。通过t - SNE和基于距离的统计分析,我们识别出了三组SIDS死亡者,每组都有独特的死亡高峰年龄。在美国,SIDS在地理上存在异质性。在此之后,我们发现低出生体重和正常出生体重的SIDS发生率并未受到临床指南实施的同等影响。我们表明,在文化异质性程度不同的国家中,低出生体重与正常出生体重的死亡者之间SIDS发生率的降低情况也有所不同。基于我们用t - SNE和基于距离的统计测量方法识别出的三个独特的SIDS群体,存在不同的流行病学和外部风险因素。临床指南对这些群体的影响并不相同,尽管低出生体重婴儿的SIDS发生率较高,但正常出生体重婴儿占SIDS病例的比例更大。