{'fraction_non_alphanumeric': 0.04475457170356112, 'fraction_numerical': 0.032723772858517804, 'mean_word_length': 4.634146341463414, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Pelvic Injury Risk Curves for the Military Populations From Lateral Impact.

INTRODUCTION
Current methods for transporting military troops include nonstandard seating orientations, which may result in novel injuries because of different types/directions of loading impact. The objective of this study is to develop pelvic injury risk curves (IRCs) under lateral impacts from human cadaver tests using survival analysis for application to military populations.


METHODS
Published data from lateral impacts applied to whole-body cadaver specimens were analyzed. Forces were treated as response variables. Demographics and body mass index (BMI) were covariates. Injury risk curves were developed for forces without covariates, for males, females, 83 kg body mass, and 25 kg/m2 BMI. Mean and ± 95% confidence interval IRCs, normalized confidence interval sizes at discrete risk levels, and quality indices were obtained for each metric-covariate combination curve.


RESULTS
Mean age, stature, total body mass, and BMI were 70.1 ± 8.6 years, 1.67 ± 0.1 m, 67.0 ± 14.4 kg, and 23.9 ± 3.97 kg/m2, respectively. For a total body mass of 83 kg, peak forces at 10%, 25%, and 50% probability levels were 5.7 kN, 7.4 kN, and 9.6 kN, respectively. For males, peak forces at the 10%, 25%, and 50% probability levels were 4.8 kN, 6.4 kN, and 8.4 kN, respectively. For females, peak forces at the 10%, 25%, and 50% probability levels were 3.0 kN, 4.0 kN, and 5.2 kN, respectively. Other data and risk curves are given.


CONCLUSIONS
The IRCs developed in this study can be used as injury criteria for the crashworthiness of future generation military vehicles. The introduction of BMI, sex, and total body mass as covariates quantified their contributions. These IRCs can be used with finite element models to assess and predict injury in impact environments to advance Soldier safety. Manikins specific to relevant military anthropometry may be designed and/or evaluated with the present IRCs to assess and mitigate musculoskeletal injuries associated with this posture and impact direction.