Background: Multimodal analgesia in rib fractures (RFs) is designed to maximize pain control while minimizing narcotics. Prior research with intravenous lidocaine (IVL) efficacy produced conflicting results. We hypothesized IVL infusion reduces opioid utilization and pain scores. Methods: A retrospective review of RF patients at an ACS-verified Level I trauma center from April 2018 to 2/2020 was conducted. Patients (pts) stratified as receiving IVL vs no IVL. Initial lidocaine dose: 1 mg/kg/hr with a maximum of 3 mg/kg/hr. Duration of infusion: 48 h. Pain quantified by the Stanford Pain Score system (PS). Bivariate and multivariate analyses of variables were performed on SPSS, version 21 (IBM Corp). Results: 414 pts met inclusion criteria: 254 males and 160 females. The average age for the non-IVL = 67.4 ± 15.2 years vs IVL = 58.3 ± 17.1 years (P <.001). There were no statistically significant differences between groups for ISS, PS for initial 48 h, and ICU length of stay (LOS). There was a difference in morphine equivalents per hour: non-IVL = 1.25 vs IVL = 1.72 (P =.004) and LOS non-IVL = 10.2+/−7.6 vs IVL = 7.82+/−4.94. By analyzing IVL pts in a crossover comparison before and after IVL, there was reduction in opiates: 3.01 vs 1.72 (P <.001) and PS: 7.0 vs 4.9 (P <.001). Stanford Pain Score system reduction in the IVL = 48.3 ± 23.9%, but less effective in narcotic dependency (27 ± 22.9%, P =.035); IVL pts had hospital cost reduction: $82,927 vs $118,202 (P <.01). Discussion: In a crossover analysis, IVL is effective for reduction of PS and opiate use and reduces hospital LOS and costs. Patient age may confound interpretation of results. Our data support IVL use in multimodal pain regimens. Future prospective study is warranted.

The introduction of airbags has not significantly reduced serious thoracic injury for belted occupants in frontal crashes. This thesis has investigated the effectiveness of airbags and the characteristics of residual thoracic organ injury incurred by belted occupants in vehicles equipped with airbags. This study was based on the injury outcome of over 28,000 belted front seat occupants involved in frontal collisions. Data for this analysis was extracted from National Automotive Sampling System / Crashworthiness Data System (NASS/CDS) case years 1993-2007. The use of odds ratios for comparing the effect of airbags on the occurrence of injury has shown that airbags do not significantly increase protection against head and chest injuries. Overall, the lower extremity and the upper extremity were shown to be adversely affected by airbags. The face was the only body region that was shown to benefit from the combination of seat belts and airbags as compared to seat belts alone. An investigation into the characteristics and distributions associated with thoracic organ injuries showed the heart and great vessels are the only thoracic organs that showed a significant reduction in the rate of injury with the inclusion of airbags. In vehicles with airbags, the thoracic organs are injured more frequently than the ribs. When occupants sustain thoracic organ injury, the delta-V of the crash for vehicles with and without airbags is not significantly different. The odds of serious injury to the lungs and spleen are higher for occupants in vehicles with airbags as compared to those in vehicles without airbags. Rib fracture was found to be a poor predictor of moderate to fatal thoracic organ injury. Only 31-61% of thoracic organ injuries occur with an associated rib fracture. / Master of Science

No description available.

Introduction. Road traffic injuries are the eighth leading cause of death globally and the leading cause of death among young people aged 15-29. Of individuals killed or injured in road traffic injuries, a large group comprises occupants sustaining a thorax injury in frontal crashes. The elderly are particularly at risk, as they are more fragile. The evaluation of the frontal crash performance of new vehicles is normally based on barrier crash tests. Such tests are only representative of a small portion of real-life crashes, but it is not feasible to test vehicles in all real-life conditions. However, the rapid development of computers opens up possibilities for simulating whole populations of real-life crashes using so-called stochastic simulations. This opportunity leads to the aim of this thesis, which is to develop and validate a simplified, parameterized, stochastic vehicle simulation model for the evaluation of passive restraint systems in real-life frontal crashes with regard to rib fracture injuries. Methods. The work was divided into five phases. In phase one, the geometry and properties of a finite element (FE) generic vehicle buck model were developed based on data from 14 vehicles. In the second phase, a human FE model was validated for oblique frontal crashes. This human FE model was then used to represent the vehicle occupant. In the third phase, vehicle buck boundary conditions were derived based on real-life crash data from the National Automotive Sampling System (NASS) and crash test data from the Insurance Institute for Highway Safety. In phase four, a validation reference was developed by creating risk curves for rib fracture in NASS real-life crashes. Next, these risk curves were compared to the risk of rib fractures computed using the generic vehicle buck model. In the final phase, injury mechanisms in nearside oblique frontal crashes were evaluated. Results. In addition to an averaged geometry, parametric distributions for 27 vehicle and boundary condition parameters were developed as guiding properties for the stochastic model. Particular aspects of the boundary conditions such as pulse shape, pulse angle and pulse severity were analyzed in detail. The human FE model validation showed that the kinematics and rib fracture pattern in frontal oblique crashes were acceptable for this study. The validation of the complete FE generic vehicle buck model showed that the model overestimates the risk of rib fractures. However, if the reported under-prediction of rib fractures (50-70%) in the NASS data is accounted for using statistical simulations, the generic vehicle buck model accurately predicts injury risk for senior (70-year-old) occupants. The chest injury mechanisms in nearside oblique frontal crashes were found to be a combination of (I) belt and airbag loading and (II) the chest impacting the side structure. The debut of the second mechanism was found for pulse angles of about 30 degrees. Conclusion. A parameterized FE generic passenger vehicle buck model has been created and validated on a population of real life crashes in terms of rib fracture risk. With the current validation status, this model provides the possibility of developing and evaluating new passive safety systems for fragile senior occupants. Further, an injury mechanism responsible for the increased number of outboard rib fractures seen in small overlap and near-side oblique frontal impacts has been proposed and analyzed. / Vinnova Project: Real Life Safety Innovations

Finite element human body models have in recent years become widely used in the area of vehicle safety evaluations. They make it possible to predict injury risk in specific areas, down to the organ level in the human body. An existing human body model, SAFER HBM includes a rib cage representing an average male. However, humans have a large variability in rib geometry and material properties leading to uncertainties in non-linear phenomena such as rib fracture risk. Hence, it cannot be known if predictions based on an average male representation are applicable to other similar individuals. In simulation studies with the SAFER HBM, rib cortical bone thickness, rib cross-sectional width, and rib cortical bone material properties have been identified as the most influential for the magnitude of rib strains and thus, they have a large influence on the strain-based rib fracture risk. This means that the predicted injury outcome is sensitive to the particular rib properties of an individual, and in a real-world scenario, a distribution of injury outcomes is expected across a population. Knowledge of the injury risk distribution can aid vehicle designers in developing safer vehicles. This distribution can be found through repeated human body model simulations with various rib properties, but due to the lengthy simulation times, this is not feasible. This thesis aims to predict human body model rib strain histories, given variations in the three biomechanical parameters, rib cortical bone thickness, rib cross-section width and rib cortical bone material with the help of graph neural networks (GNNs) for both single and mixed impact scenarios. Several variations of GNNs were used and implemented with help of PyTorch and PyTorch Geometric. An extensive hyperparameter study was performed on a small part of one human body model rib, to find the optimal combinations of hyperparameters and GNNs. The data used in training and evaluation of the networks was generated in LS-DYNA with SAFER HBM v10 and post-processed in Meta post processor. To be able to generate many training examples, the HBM was subjected to a simplified impact scenario consisting of a pendulum impact to the chest. As final verification, the trained GNNs were applied to predict rib strains in a vehicle impact scenario. Evaluation of the GNNs' prediction accuracy on the whole rib cage for all impact scenarios was made by studying the root mean square error along with differences in predicted and actual peak strain, rib fracture risk, time the peak strain occurs and the euclidean distance between the locations within the rib of real and predicted peak strains. The results showed that it is possible to accurately predict strain histories. Further, a multilayer perceptron (MLP) model consistently achieved the lowest errors in all measurements for mixed impacts. However, the trained model produced slightly unexpected errors for test data extracted from vehicle simulations compared to simplified simulations. This is an indication that retraining the model on data from vehicle simulations may be necessary. In conclusion, this thesis has shown the possibility to predict strain histories from a SAFER HBM rib cage extracted from simplified simulations and simulations including the full vehicle model, the SAFER HBM and all safety systems, to investigate the effects of human variability in the rib cage.