Risk factors affecting injury severity determined by the MAIS score

Ferreira, Sara; Amorim, Marco; Couto, António

doi:10.1080/15389588.2016.1246724

Cited by 28 publications

(17 citation statements)

References 25 publications

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“…Injury was then dichotomized as either injured or not injured. Any MAIS score greater than 0 was defined as injured, and any score equal to 0 was defined as uninjured (Ferreira et al, 2017 ) .…”

Section: Methodsmentioning

confidence: 99%

“…Multivariable backward stepwise logistic regression analyses were performed to evaluate the adjusted association between seating position (front seat vs. rear seat) and the outcome in the 2012–2014 NYS CODES linked data. The outcome variable, medically-diagnosed injury for child occupants aged 0–12 years involved in a MV crash was dichotomized using the MAIS calculated from ICD-9-CM diagnosis codes (Ferreira et al, 2017 ) . MAIS ranged from 0 (uninjured) to 6 (maximum, untreatable) injury.…”

Section: Methodsmentioning

confidence: 99%

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Using Crash Outcome Data Evaluation System (CODES) to examine injury in front vs. rear-seated infants and children involved in a motor vehicle crash in New York State

et al. 2021

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Background In New York State (NYS), motor vehicle (MV) injury to child passengers is a leading cause of hospitalization and emergency department (ED) visits in children aged 0–12 years. NYS laws require appropriate child restraints for ages 0–7 years and safety belts for ages 8 and up while traveling in a private passenger vehicle, but do not specify a seating position. Methods Factors associated with injury in front-seated (n = 11,212) compared to rear-seated (n = 93,092) passengers aged 0–12 years were examined by age groups 0–3, 4–7 and 8–12 years using the 2012–2014 NYS Crash Outcome Data Evaluation System (CODES). CODES consists of Department of Motor Vehicle (DMV) crash reports linked to ED visits and hospitalizations. The front seat was row 1 and the rear rows 2–3. Vehicle towed from scene and air bag deployed were proxies for crash severity. Injury was dichotomized based on Maximum Abbreviated Injury Severity (MAIS) scores greater than zero. Multivariable logistic regression (odds ratios (OR) with 95% CI) was used to examine factors predictive of injury for the total population and for each age group. Results Front-seated children had more frequent injury than those rear-seated (8.46% vs. 4.92%, p < 0.0001). Children in child restraints experienced fewer medically-treated injuries compared to seat belted or unrestrained children (3.80, 6.50 and 13.62%, p < 0.0001 respectively). A higher proportion of children traveling with an unrestrained vs. restrained driver experienced injury (14.50% vs 5.26%, p < 0.0001). After controlling for crash severity, multivariable adjusted predictors of injury for children aged 0–12 years included riding in the front seat (1.20, 1.10–1.31), being unrestrained vs. child restraint (2.13, 1.73–2.62), being restrained in a seat belt vs. child restraint (1.20, 1.11–1.31), and traveling in a car vs. other vehicle type (1.21, 1.14–1.28). Similarly, protective factors included traveling with a restrained driver (0.61, 0.50–0.75), a driver aged < 25 years (0.91, 0.82–0.99), being an occupant of a later vehicle model year 2005–2008 (0.68, 0.53–0.89) or 2009–2015 (0.55, 0.42–0.71) compared to older model years (1970–1993). Conclusions Compared to front-seated children, rear-seated children and children in age-appropriate restraints had lower adjusted odds of medically-treated injury.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Using Crash Outcome Data Evaluation System (CODES) to examine injury in front vs. rear-seated infants and children involved in a motor vehicle crash in New York State

et al. 2021

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“…At present, there are mainly five kinds of classification methods of traffic crash severity widely used in some developed countries. Advancement of Automotive Medicine and is universally accepted as the foundation of injury severity scaling systems [22]. The AIS level is determined for nine different body regions, which includes minor (1), moderate (2), serious (3), severe (4), critical (5), and unsurvivable (6).…”

Section: Some Developed Countriesmentioning

confidence: 99%

An Assessment Method of Urban Traffic Crash Severity Considering Traveling Delay and Non-Essential Fuel Consumption of Third Parties

Cao

2020

Sustainability

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Urban traffic crashes may lead to only a few casualties, but may generate severe negative impacts on the surrounding traffic, such as evidently increasing traveling delay and non-essential fuel consumption of third parties (i.e., vehicles not involved in the crash). Such detrimental consequences of urban traffic crashes are usually ignored by the traditional crash severity evaluation approaches. Therefore, this study attempts to classify urban traffic crash severity by considering the traveling delay and non-essential fuel consumption of third parties in addition to casualties and property damages. Based on the losses of traveling delay and non-essential fuel consumption of third parties, the losses of crash casualties, and property damages, a comprehensive index of urban traffic crash severity was developed. Moreover, the thresholds of the proposed comprehensive index for urban crash severity classification were determined based on the crash data from 2013 to 2014 collected from Harbin, China. The developed comprehensive index was applied to a case study, which also compared the crash severity classification outcomes from the developed method and the current approach. The results indicate that the developed method of urban traffic crash severity classification is more reasonable than the existing approach. Such superiority of the proposed urban crash severity classification method is due to considering the traveling delay and non-essential fuel consumption of third parties caused by a crash.

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“…The under‐reporting of road collisions is a well‐known issue, one that exists (to varying degrees) across the majority of, if not all nations (e.g., Abegaz et al, 2014; Bhatti & Salmi, 2012; Chokotho et al, 2013; Janstrup et al, 2016; Periyasamy et al, 2013; Puvanachandra et al, 2012; Watson et al, 2015; Yannis et al, 2014). Furthermore, there is a widely recognized issue with the differences in data collected by emergency departments, ambulance crews, and police, both in terms of the numbers of casualties recorded (e.g., Abay, 2015; Bhatti et al, 2011; Dandona et al, 2008; Ward et al, 2002), and the classification of injury severity (e.g., Couto et al, 2016; Ferreira et al, 2017, 2015; Schmitt et al, 2015; Van Belleghem et al, 2016). Nevertheless, such databases are unlikely to undergo significant changes in the near future.…”

Section: Introductionmentioning

confidence: 99%

Intuition, the Accimap, and the question “why?” Identifying and classifying higher‐order factors contributing to road traffic collisions

McIlroy

Plant

Stanton

2021

Hum Ftrs & Erg Mfg Svc

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Although the physical and environmental factors contributing to road traffic collisions are often the most straightforward to identify, they may not necessarily be the most useful in terms of guiding road safety intervention design. From a sociotechnical systems perspective, it is the higher system factors that, if addressed, would provide the widest‐reaching benefits to system outcomes. That said, the identification of these higher‐order factors often requires a level of intuition or imagination; they are not always objectively obvious given the facts of a particular case. Here, we argue for the use of the Accimap approach to accident (or collision) analysis, supplemented with a modified version of the five whys causal analysis technique, for the support and structuring of this intuiting process. We use an analysis of a fatal motorcycle collision to illustrate how coroners in the United Kingdom could be supported in their task of identifying and summarizing factors in accordance with the levels of the Accimap, and according to a categorization scheme indicating how abstract those factors are (i.e., immediate, proximal, or distal). Our analysis identified 21 immediate, 12 proximal, and 33 distal factors contributing to the collision. It is these distal factors that are most likely to lead to longer‐term road safety improvements.

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Risk factors affecting injury severity determined by the MAIS score

Cited by 28 publications

References 25 publications

Using Crash Outcome Data Evaluation System (CODES) to examine injury in front vs. rear-seated infants and children involved in a motor vehicle crash in New York State

Using Crash Outcome Data Evaluation System (CODES) to examine injury in front vs. rear-seated infants and children involved in a motor vehicle crash in New York State

An Assessment Method of Urban Traffic Crash Severity Considering Traveling Delay and Non-Essential Fuel Consumption of Third Parties

Intuition, the Accimap, and the question “why?” Identifying and classifying higher‐order factors contributing to road traffic collisions

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