Statistical Problems in the Diagnosis of Shaken Baby Syndrome/Abusive Head Trauma: Limitations to Algorithms and the Need for Reliable Data

The medical and legal controversy surrounding the diagnosis of Shaken Baby Syndrome/Abusive Head Trauma (SBS/AHT) raises critical questions about its scientific foundation and reliability. This article argues that SBS/AHT can only be understood by studying the statistical challenges with the data. Current health records are insufficient because there is a lack of ground truth, reliance on circular reasoning, contextual bias, heterogeneity across institutions, and integration of legal decisions into medical assessments. There exists no comprehensive source of legal data. Thus, current data is insufficient to reliably distinguish SBS/AHT from other medical conditions or accidental injuries. A privately-collected medico-legal dataset that has the relevant contextual information, but is limited by being a convenience sample, is used to show how a data analysis might be performed with higher-quality data. There is a need for systematic data collection of the additional contextual information used by physicians and pathologists to make determinations of abuse. Furthermore, because of the legal nature of the diagnosis, i.e., its accuracy, repeatability, and reproducibility, must be tested. Better data and evaluating the scientific validity of SBS/AHT are essential to protect vulnerable children while ensuring fairness and accuracy in legal proceedings involving allegations of abuse.