Background: The purpose of this study was to assess the risk of motor-vehicle pregnant driver crashes in Pennsylvania using vital statistics linked to police and ambulance reports. This was supplemented with a review ...Background: The purpose of this study was to assess the risk of motor-vehicle pregnant driver crashes in Pennsylvania using vital statistics linked to police and ambulance reports. This was supplemented with a review of national age and sex specific crash and fertility data to put this risk into perspective and rank the likelihood for pregnancy-related crashes in other states. Methods: Motor vehicle police crash reports from the Pennsylvania Department of Transportation were probabilistically linked to four years of birth and fetal death data and five years of infant death records and ambulance reports. State specific motor-vehicle traffic injury rates (fatal and non-fatal) were compared to birth rates, by age, for women ages 15 - 34. Results: 5929 (1.1%) of the women with a birth or fetal death linked to a police reported motor vehicle driver crash during pregnancy. One-third (32.5%) of these crashes resulted in minor maternal injuries and 7.5% resulted in moderate to fatal maternal injuries. Crashes were evenly distributed across gestational ages. Young drivers (20 - 24) were at highest risk. Police reported non-belt use was 10%. Conclusions: This study quantifies the risk of motor vehicle crashes during pregnancy in Pennsylvania and offers a perspective on potential variations in other states. Pregnancy related crashes occur at a higher rate than infant related crashes with a concomitant threat to the fetus and new-born not usually tracked within current crash data systems.展开更多
BACKGROUND:The main objective was to identify common geographical buildup within the100-meter buffer of severely injured based on injury severity score(ISS) among the motor vehicle crash(MVC) victims in Malaysia.METHO...BACKGROUND:The main objective was to identify common geographical buildup within the100-meter buffer of severely injured based on injury severity score(ISS) among the motor vehicle crash(MVC) victims in Malaysia.METHODS:This was a prospective cohort study from July 2011 until June 2013 and involved all MVC patients attending emergency departments(ED) of two tertiary centers in a district in Malaysia.A set of digital maps was obtained from the Town Planning Unit of the district Municipal Office(local district map).Vector spaces were spanned over these maps using GIS software(ARCGIS 10.1licensed to the study center),and data from the identified severe injured cases based on ISS of 16 or more were added.Buffer analysis was performed and included all events occurring within a 100-meter perimeter around a reference point.RESULTS:A total of 439 cases were recruited over the ten-month data collection period.Fifty two(11%) of the cases were categorized as severe cased based on ISS scoring of 16 and more.Further buffer analysis looking at the buildup areas within the vicinity of the severely injured locations showed that most of the severe injuries occurred at locations on municipal roads(15,29%),straight roads(16,30%) and within villages buildup(suburban) areas(18,35%).CONCLUSION:This study has successfully achieved its objective in identifying common geographical factors and buildup areas within the vicinity of severely injured road traffic cases.展开更多
Accurate on-board occupant injury risk prediction of motor vehicle crashes(MVCs)can decrease fatality rates by providing critical information timely and improving injury severity triage rates.The present implemented p...Accurate on-board occupant injury risk prediction of motor vehicle crashes(MVCs)can decrease fatality rates by providing critical information timely and improving injury severity triage rates.The present implemented prediction algorithms in vehicle safety systems are probabilistic and rely on multi-variate logistic regression of real-world vehicle collision databases.As a result,they do not utilize important vehicle and occupant features and tend to overgeneralize the solution space.This study presents a framework to address these problems with deterministic and computationally efficient lumped parameter model simulations driven by a database of vehicle crash tests.A 648-case mixed database was generated with finite element and multi-body models and validated under the principal directions of impact with experimental results for a single vehicle body type.Using the finite element database,we developed lumped parameter models for four principal modes of impact(i.e.,frontal,rear,near side and far side)with parameters identified via genetic algorithm optimization.To obtain confidence bounds for the injury risk prediction,the parameter uncertainty and model adequacy were evaluated with arbitrary and bootstrapped polynomial chaos expansion.The developed algorithm was able to achieve over triage rates of 17.1%±8.5%,whilst keeping the under triage rates below 8%on a finite element-multi body model database of a single vehicle body type.This study demonstrated the feasibility and importance of using low-complexity deterministic models with uncertainty quantification in enhanced occupant injury risk prediction.Further research is required to evaluate the effectiveness of this framework under a wide range of vehicle types.With the flexibility of parameter adjustment and high computational efficiency,the present framework is generic in nature so as to maximize future applicability in improved on-board triage decision making in active safety systems.展开更多
Background: Blunt traumatic cervical spine fractures (TCSF) are serious injuries which may be associated with considerable mortality and morbidity. We describe the epidemiology of blunt traumatic cervical spine fractu...Background: Blunt traumatic cervical spine fractures (TCSF) are serious injuries which may be associated with considerable mortality and morbidity. We describe the epidemiology of blunt traumatic cervical spine fracture in Iran over a definable time period. Methods: In a cross-sectional study, the data including the distribution of TCSF, demographics, mechanisms, abbreviated injury scale (AIS), spinal cord associated injuries and final outcome of patients, was extracted from the Iranian national trauma registry database in target hospitals in eight major cities of Iran from 1999 to 2004. The Chi square test was used to compare mortality and one-way ANOVA was used to compare ISS amongst the categories of TCSF. Results: TCSF was identified in 120 cases, of these 70.8% were male. Their mean age was 36.6 ± 17.2 years. The overall incidence of TCSF among all trauma patients was 0.7% (95%CI: 0.61% - 0.88%). The TCSF incidence among all spine fractured patients was 19.38% (95%CI: 16.34% - 22.72%). The most common mechanism of TCSF was a motor vehicle collision (66.7%). The overall percentage of in-hospital death for TCSF was 12.6%. There were no statistically significant difference in death and injury severity scores (ISS) among TCSF categories (p > 0.05). Spinal cord and root injuries occurred in 34.9% and 2.4% of TCSF, respectively. Conclusions: Preventive strategies need to be developed in order to reduce the number and severity of TCSF in the general Iranian population.展开更多
文摘Background: The purpose of this study was to assess the risk of motor-vehicle pregnant driver crashes in Pennsylvania using vital statistics linked to police and ambulance reports. This was supplemented with a review of national age and sex specific crash and fertility data to put this risk into perspective and rank the likelihood for pregnancy-related crashes in other states. Methods: Motor vehicle police crash reports from the Pennsylvania Department of Transportation were probabilistically linked to four years of birth and fetal death data and five years of infant death records and ambulance reports. State specific motor-vehicle traffic injury rates (fatal and non-fatal) were compared to birth rates, by age, for women ages 15 - 34. Results: 5929 (1.1%) of the women with a birth or fetal death linked to a police reported motor vehicle driver crash during pregnancy. One-third (32.5%) of these crashes resulted in minor maternal injuries and 7.5% resulted in moderate to fatal maternal injuries. Crashes were evenly distributed across gestational ages. Young drivers (20 - 24) were at highest risk. Police reported non-belt use was 10%. Conclusions: This study quantifies the risk of motor vehicle crashes during pregnancy in Pennsylvania and offers a perspective on potential variations in other states. Pregnancy related crashes occur at a higher rate than infant related crashes with a concomitant threat to the fetus and new-born not usually tracked within current crash data systems.
文摘BACKGROUND:The main objective was to identify common geographical buildup within the100-meter buffer of severely injured based on injury severity score(ISS) among the motor vehicle crash(MVC) victims in Malaysia.METHODS:This was a prospective cohort study from July 2011 until June 2013 and involved all MVC patients attending emergency departments(ED) of two tertiary centers in a district in Malaysia.A set of digital maps was obtained from the Town Planning Unit of the district Municipal Office(local district map).Vector spaces were spanned over these maps using GIS software(ARCGIS 10.1licensed to the study center),and data from the identified severe injured cases based on ISS of 16 or more were added.Buffer analysis was performed and included all events occurring within a 100-meter perimeter around a reference point.RESULTS:A total of 439 cases were recruited over the ten-month data collection period.Fifty two(11%) of the cases were categorized as severe cased based on ISS scoring of 16 and more.Further buffer analysis looking at the buildup areas within the vicinity of the severely injured locations showed that most of the severe injuries occurred at locations on municipal roads(15,29%),straight roads(16,30%) and within villages buildup(suburban) areas(18,35%).CONCLUSION:This study has successfully achieved its objective in identifying common geographical factors and buildup areas within the vicinity of severely injured road traffic cases.
基金the National Natural Science Foundation of China(Grant Nos.51705276 and 51675295)Tsinghua University Initiative Scientific Research Program(Grant No.2019Z08QCX13)the National Key R&D Program of China(Grant Nos.2017YFE0118400 and2018YFE0192900)。
文摘Accurate on-board occupant injury risk prediction of motor vehicle crashes(MVCs)can decrease fatality rates by providing critical information timely and improving injury severity triage rates.The present implemented prediction algorithms in vehicle safety systems are probabilistic and rely on multi-variate logistic regression of real-world vehicle collision databases.As a result,they do not utilize important vehicle and occupant features and tend to overgeneralize the solution space.This study presents a framework to address these problems with deterministic and computationally efficient lumped parameter model simulations driven by a database of vehicle crash tests.A 648-case mixed database was generated with finite element and multi-body models and validated under the principal directions of impact with experimental results for a single vehicle body type.Using the finite element database,we developed lumped parameter models for four principal modes of impact(i.e.,frontal,rear,near side and far side)with parameters identified via genetic algorithm optimization.To obtain confidence bounds for the injury risk prediction,the parameter uncertainty and model adequacy were evaluated with arbitrary and bootstrapped polynomial chaos expansion.The developed algorithm was able to achieve over triage rates of 17.1%±8.5%,whilst keeping the under triage rates below 8%on a finite element-multi body model database of a single vehicle body type.This study demonstrated the feasibility and importance of using low-complexity deterministic models with uncertainty quantification in enhanced occupant injury risk prediction.Further research is required to evaluate the effectiveness of this framework under a wide range of vehicle types.With the flexibility of parameter adjustment and high computational efficiency,the present framework is generic in nature so as to maximize future applicability in improved on-board triage decision making in active safety systems.
文摘Background: Blunt traumatic cervical spine fractures (TCSF) are serious injuries which may be associated with considerable mortality and morbidity. We describe the epidemiology of blunt traumatic cervical spine fracture in Iran over a definable time period. Methods: In a cross-sectional study, the data including the distribution of TCSF, demographics, mechanisms, abbreviated injury scale (AIS), spinal cord associated injuries and final outcome of patients, was extracted from the Iranian national trauma registry database in target hospitals in eight major cities of Iran from 1999 to 2004. The Chi square test was used to compare mortality and one-way ANOVA was used to compare ISS amongst the categories of TCSF. Results: TCSF was identified in 120 cases, of these 70.8% were male. Their mean age was 36.6 ± 17.2 years. The overall incidence of TCSF among all trauma patients was 0.7% (95%CI: 0.61% - 0.88%). The TCSF incidence among all spine fractured patients was 19.38% (95%CI: 16.34% - 22.72%). The most common mechanism of TCSF was a motor vehicle collision (66.7%). The overall percentage of in-hospital death for TCSF was 12.6%. There were no statistically significant difference in death and injury severity scores (ISS) among TCSF categories (p > 0.05). Spinal cord and root injuries occurred in 34.9% and 2.4% of TCSF, respectively. Conclusions: Preventive strategies need to be developed in order to reduce the number and severity of TCSF in the general Iranian population.
