The abbreviated injury scale as a predictor of outcome of severe head injury

Walder, A. D.; Yeoman, P; Turnbull, AE

doi:10.1007/bf01700170

Cited by 60 publications

(25 citation statements)

References 12 publications

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“…However, the AIS was less predictive with a score of 5 (positive predictive value 71%, specificity 75%, sensitivity 67%). [17] 2.6 Glasgow Coma Scale Developed to quantify the level of consciousness, the Glasgow Coma Scale has become a medical classic. [18] In the past 30 years since its development, many coma scales have been recommended as alternatives to the GCS, but none have achieved success.…”

Section: Tbi Severitymentioning

confidence: 99%

Classification of traumatic brain injury severity using retrospective data

Rogers

Trickey²

2017

JNEP

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Objective: Accurate classification of traumatic brain injury (TBI) severity is essential to brain injury research. TBI heterogeneity complicates classification of the injury; is a significant barrier in the design of therapeutic interventions; and results in retrospective data which is difficult to translate. The objective of this study is to describe the differences in two current tools used in the classification of TBI severity, the Glasgow Coma Scale (GCS) and the head Abbreviated Injury Score (AIS), using retrospective data to compare their performance. Methods: Using correlational and descriptive statistics, this study examined two TBI severity classification methods across a large sample of TBI patients (N = 56,131), who were treated at level I and level II trauma centers in the United States and were included in the 2010 National Sample Program (NSP) of the National Trauma Data Bank (NTDB R ). Results: The study population was 67% male, 67% non-Hispanic white, treated most often in trauma centers in the South (38%), with blunt trauma (93%) and from non-motor vehicle collisions (MVC's) (56%). Observation of the AIS classification system demonstrated that it tends to over-score TBI severity compared to the GCS classification. The methods (GCS & AIS) had a weak, inverse relationship with a correlation coefficient (Pearson's r) of -0.3980, which was significant at p < .001. Conclusions: The current study addressed the difficulties associated with categorizing TBI severity when analyzing retrospective data. Although AIS is commonly used to classify severity in retrospective data when GCS is unavailable, the relationship between the two scales is relatively unknown. Results show that AIS and GCS are more closely related for severely brain injured patients but in cases of mild and moderate injury, AIS is less predictive of GCS. Since they are often used in conjunction in identifying brain injured severity in retrospective data, researchers cannot be certain that the tools are similarly classifying mild, moderate, and severe injuries. This study reinforces the need for additional TBI severity classification methods, such as neuroimaging techniques and biomarkers.

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Section: Tbi Severitymentioning

confidence: 99%

Classification of traumatic brain injury severity using retrospective data

Rogers

Trickey²

2017

JNEP

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“…Comatose (GCS score ^ 8) patients, unable to open their eyes or to follow specific commands, are regarded as having severe TBI [25] . The AIS head is another commonly used instrument for the categorization of injury severity based on anatomical features using a 6-grade scale system [30] . AIS head scores 6 2 are considered moderate while scores 6 3 are severe to life-threatening.…”

Section: Assessment Of Relevant Tbimentioning

confidence: 99%

Incidence and Outcome of Traumatic Brain Injury in an Urban Area in Western Europe over 10 Years

et al. 2007

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Introduction: Valid epidemiological data on incidence and outcome of traumatic brain injury (TBI) show great variability. A study on incidence, severity and outcome of TBI was conducted in an urban area of one million inhabitants. Materials and Methods: 130,000 prehospital emergencies were screened for TBI. Inclusion criteria: Glasgow Coma Scale (GCS) score ≤8 and/or Abbreviated Injury Scale for head injuries (AIS_head) score ≧2 with confirmed TBI via appropriate diagnostics. Results: Annual incidence was 7.3/100,000. Overall mortality rate was 45.8%: 182 (28%) were prehospital deaths, 116 (17.8%) patients died in hospital. Two hundred and fourteen of 352 (60.8%) surviving patients were sufficiently rehabilitated at discharge [Glasgow Outcome Scale (GOS) score = 1], but 138 patients (39.2%) survived with persisting deficits. GOS was associated with initial GCS and AIS_head. Conclusion: The incidence of TBI was lower compared to the literature. The overall mortality was high, especially prehospital and early in-hospital mortality rates.

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“…Unfortunately, pupil reactivity and initial hypotension were not readily available in our database. Neither were brain CT results, but we believe that these should correlate closely with maximum AIS [9]. Ottochian et al [5] have retrospectively developed and prospectively validated a predictive model of survival in isolated head injuries based on parameters such as age, mechanism of injury, GCS and head AIS.…”

Section: Discussionmentioning

confidence: 99%

Towards Development of a Survival Prediction Tool for Pediatric Head Injury

2012

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Background: The ability to provide an accurate prognosis for children with traumatic brain injury (TBI) would be useful for the children’s families and the caregivers. In this study we examined whether an appropriate mathematical model can predict survival in this patient population. Methods: Data from the Children’s Hospital of Eastern Ontario (CHEO) TBI registry was analyzed. First, a series of univariate logistic regressions was performed to ascertain the significance of individual predictors, such as age, maximum Glasgow Coma Scale (GCS) score, maximum head injury Abbreviated Injury Scores (AIS) and the Injury Severity Score (ISS). Second, a multinomial logistic regression was fitted using only individually significant predictors and inmodel predictor significance, and interactions were tested. Only two significant predictors were kept in the final model. This final model was subsequently used to predict survival for each individual patient using the n-1 training set (i.e. Lachenbruch’s leave-one-out method). The receiver operating characteristics (ROC) method was used to ascertain specificity-sensitivity trade-offs at different probability cut-offs in order to predict survival. Results: Only the maximum GCS and head injury AIS remained significant, both individually and in the polynomial logistic regression. Empiric ROC curve analyses from leave-one-out survival predictions showed statistical significance (area under the curve = 0.87, Z = 6.8, p < 0.001). Only 12% of cases were misclassified using the ‘best’ cut-off. Conclusion: An outcome predictive model for pediatric TBI can be devised using an appropriate mathematical model. It may help to estimate expected outcomes in pediatric TBI more objectively.

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The abbreviated injury scale as a predictor of outcome of severe head injury

Abstract: The AIS, based on initial CT scan, provides useful prognostic information in patients with severe head injury.

Cited by 60 publications

References 12 publications

Classification of traumatic brain injury severity using retrospective data

Classification of traumatic brain injury severity using retrospective data

Incidence and Outcome of Traumatic Brain Injury in an Urban Area in Western Europe over 10 Years

Towards Development of a Survival Prediction Tool for Pediatric Head Injury

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