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Investigations on the Cellular and Morphologic Characteristics of Cranial Vault Fracture: Research and Development of a Time Since Fracture Protocol and Database, Arizona and Michigan, 2017-2020 (ICPSR 38054)

Released/updated on: 2023-05-30

Geographic coverage: United States, Arizona, Michigan

Time period: 2017-01-01--2020-01-01

The primary objective of this study was to determine the histological features associated with fracture repair in the human cranial vault, and to derive the trajectory of these features over the course of healing. Variations in the fracture repair process due to decedent age and type of injury were explored. The impacts of laboratory techniques, including decalcification and histological staining, upon the quality of fracture histology slides were also assessed. Calvarial fracture samples were collected from medical examiner cases and body donations from January 1, 2017 to November 31, 2020 for use in the analyses and for the creation of the Repository of Antemortem Injury Response (REPAIR), a deidentified online database of known-age cranial fractures and defects.

Curated

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Tool Mark Analysis of Cut Costal Cartilage, 2009-2010 [United States] (ICPSR 28741)

Released/updated on: 2014-09-16

Geographic coverage: United States

Time period: 2009-01-01--2010-01-01

The study was designed to establish the potential error rate associated with the generally accepted method of tool mark analysis of cut marks in costal cartilage. Three knives with different blade types were used to make experimental cut marks in costal cartilage of pigs. Each cut surface was cast, and each cast was examined by three analysts working independently. Presence of striations, regularity of striations, and presence of a primary and secondary striation pattern were recorded for each cast. The distance between each striation was measured. The Cut Mark Measurement Data (Dataset 1) are comprised of the observations and measurements of three analysts on 180 distinct specimen identifiers. The repeated measurements were aggregated by taking the Mean Interstriation Distance (MID) and the medians of the numeric variables for each combination of the categorical variables, resulting in the Aggregated Cut Mark Measurement Data (Dataset 2).