A formal statistical analysis confirms the superior predictive power of NISS over ISS. Virtually every measure examined was statistically significantly better for NISS than for ISS: misclassification rates, ROC curve areas, and Hosmer Lemeshow statistics (Table 1). Only the misclassification rate in the Portland data set is not statistically significantly improved under NISS.
Although the ISS has served as the standard summary measure of human trauma for more than two decades, its division of the human body into regions seems unnatural and now appears to be unnecessary. The use of only a single injury per body region in the calculation of the original ISS  was simply the result of the design of Baker's original study and has never been tested or validated. Although the ISS's ability to consider as many as three different injuries in its final outcome score represented a considerable advance over the earlier practice of summarizing a patient's injuries based on the single worst injury (maximum AIS), today's modern trauma data bases routinely record all of the injuries that a patient sustains. It seemed likely to us that a more modern summary measure of trauma that could take advantage of this richer description of patients' injuries would more accurately predict outcome than the original ISS.
Two problems follow from the dependence of the ISS on body regions. First, the ISS often leaves some injuries out of the scoring process altogether, such as when a patient sustains multiple injuries to a single body region, in which case only the single worst injury contributes to the ISS. A second, related problem is that the ISS often ignores some more severe injuries in one body region in favor of less severe injuries to some other body region or regions, such as when multiple body regions are injured. NISS, by contrast, simply considers the three most severe injuries that a patient has sustained and thus avoids both of these shortcomings of the traditional ISS.
An example may make the differences between ISS and NISS scoring more clear. Suppose a patient involved in a motor vehicle crash sustains a steering wheel compression injury to the abdomen. At laparotomy, a small bowel perforation (AIS score = 3) is first discovered. The ISS is now 9, as is the NISS. Next, a moderate liver laceration is discovered (AIS score = 3). The ISS remains 9, but the NISS increases to 18. Next, a moderate pancreatic laceration with duct involvement is encountered (AIS score = 3). The ISS still remains 9, whereas the NISS increases again to 27. A bladder perforation is next discovered (AIS score = 4). The ISS now increases to 16, whereas the NISS continues its climb to 34. Next, a bimalleolar fibular fracture (AIS score = 2) is discovered. The ISS increases to 20, but the NISS remains unchanged at 34. The NISS thus behaves in a way that is more consistent with a trauma surgeon's instincts than does the ISS: as injuries increase in number, death becomes more likely, even if these injuries are accumulating in a single body region. Furthermore, adding a trivial injury (fibular fracture) to a different body region should not significantly affect the likelihood of death.
The price for the traditional ISS ignoring injuries or substituting less severe injuries in calculating its final outcome measure is, not surprisingly, a loss of predictive power. Additionally, this loss of predictive power is accompanied by substantially increased scoring complexity; not only must every injury be assigned to a body region before scoring, but these six scoring regions do not correspond to the nine anatomic body regions of the AIS lexicon. This complexity increases the likelihood of scoring errors and hinders "on the fly" mental estimation of ISS.
The NISS prediction of mortality is based solely on the anatomic information specified by a patient's AIS injury descriptors. Its predictive accuracy can be increased by the addition of other types of information to the scoring process, such as patient reserve (usually specified by the surrogate of patient age) and physiologic derangement (usually specified as the Revised Trauma Score).  We have chosen to keep these three types of information separate, but they can be easily combined using a variety of statistical techniques, such as logistic regression or tree analysis, should a single predictor be called for. Other outcome prediction approaches (American College of Surgeons' Committee on Trauma (ASCOT))  combine anatomic and physiologic data at the outset, but we believe that this is an error. Not only is the contribution of injury per se disguised, but the calculation of ASCOT is itself so complicated that a computer is required. We believe that part of the value of an injury summary score is that it can be calculated by clinicians. The popularity of ISS has stemmed in some measure from its ease of computation, relying as it does on the information contained in the AIS severity descriptors rather than on complex computation. NISS inherits and extends this advantage, relying as it does on the AIS severities for each injury, but simplifies the actual calculation by eliminating the need to consider body region. This is a retrospective, nonconcurrent cohort study that compares NISS with ISS values calculated at the time of discharge. A concurrent cohort study would presumably yield identical results, but would be of interest to further verify our results.
Although the ISS has seen stalwart service as the de facto standard of trauma scoring, it was developed 20 years ago in an environment very different from the information-rich, computer-dominated world of today. NISS is better suited to take advantage of the richer, more complete injury descriptions now available in trauma systems. Because NISS is simpler to calculate and better predicts outcome, it should replace ISS.
NISS better predicts survival and is easier to calculate than ISS. This difference is highly statistically significant and practically important, because NISS better separates survivors from nonsurvivors. We recommend that NISS replace ISS as the standard summary measure of human trauma.
The authors thank the following reviewers who read the manuscript in draft form and improved it greatly with their comments and observations: Edward Bedrick, Guohua Li, Ellen MacKenzie, and Brian O'Neill.
Dr. Carl A. Soderstrom (Baltimore, Maryland): Dr. Reath, Dr. Poole, members, and guests. In the beginning was AIS, which begat maximum AIS, which begat ISS. And their creators found it was good, but not perfect. Then there was TS (Trauma Score), RTS (Revised Trauma Score), TRISS (Trauma and Injury Severity Score), PATI (Penetrating Abdominal Trauma Index), ASCOT, and very recently a hierarchical network model using ICD-9 (International Classification of Diseases, Ninth Revision) codes. Now we add NISS to the alphabet soup.
ISS is an old friend, a criterion standard that has been with us for more than 20 years. This methodology, which allowed us to begin to compare apples to apples, has three obvious inherent pitfalls. First, it was designed for blunt trauma. Despite attempts to improve the penetrating trauma scoring, many feel that it is still limited in this regard. Second, it does not take into account physiologic variables, hence TRISS. Third, as has been well articulated today, the ISS methodology takes into account only one injury per body region; hence, the patient's overall anatomic injury severity is often underestimated.
The authors present a simple yet elegant modification of the ISS to overcome the third pitfall. By taking into account the patient's three most severe injuries, they were able to better discriminate patients who will die from those who will survive. This is demonstrated by almost a doubling of median scores among survivors and nonsurvivors in each group and 12-point increases in ROC-generated cut points that predict survival. The ISS is designed to evaluate live-or-die outcome from blunt trauma patients.
The authors have a combined data base of 6,585 patients, including more than 1,200 patients who were 19% injured as a result of penetrating trauma. A much larger cohort, such as that of the Major Trauma Outcome Study, with almost 200,000 subjects, or even larger ones employed in other assessments, is needed to investigate the study question. Using two, T-W-O and T-O-O, small data bases, one with 3,000 blunt trauma victims and the other with fewer than 2,400, can make analysis dependent on individual cells with small numerators and denominators, resulting in obvious consequences.
Questions: Did you analyze your data bases only for blunt trauma? If so, what were the results? If not, why not? Do you have any plans to tap into larger data sets to verify these preliminary findings?
There were almost twice as many penetrating trauma victims in the Albuquerque group than in the Portland group. In the Albuquerque group, there was a significantly higher misclassification rate using the ISS compared with the NISS; however, there was no significant difference in ISS and NISS misclassification in the Portland group with its greater percentage of blunt trauma victims. Furthermore, the Hosmer Lemeshow statistics for each data set conflict with this misclassification trend and therefore are counterintuitive.
Questions: How do you explain these findings? Do they suggest that the new methodology is not much of an improvement over the older one? Abbreviated injury severity scoring and NISS calculation, which is needed for calculation of TRISS, generally required trauma center registrars.
Thus, if adopted, NISS would be limited to trauma center settings unless the MacKenzie ICD-9-to-AIS conversion is used, which is recommended only for very large sample sizes. Hence, studying all hospitalized trauma patients, the vast majority of whom are not treated in trauma centers, is not possible unless the MacKenzie conversion is used.
As noted, ISS and NISS do not take into account physiologic variables. Furthermore, it is by no means certain that a quadratic equation is the best way to take into account the effects of multiple injuries.
Questions: Considering these observations, why should we embrace the NISS? Shouldn't we focus our efforts elsewhere?
In any case, six days haven't passed, it is not time to rest. My apologies to King James. I congratulate the authors on a much-needed research effort, and I thank the Association for the privilege of the floor.
Dr. Turner Osler (closing): Thank you for your constructive suggestions and criticisms.
We too noticed that we had more penetrating trauma in Albuquerque and that the NISS seemed to offer greater improvement in lowering misclassification. And that is not surprising, because with penetrating trauma, injuries tend to be clustered. And the whole idea behind this is that you allow multiple injuries in a single body region to contribute to the final score.
So it is not surprising that it works better in the penetrating arena. NISS, however, also seems to work better in the blunt arena. We did separate out the blunt trauma, and the improvements are about half what they are for penetrating trauma, which seems, intuitively, just about right.
I agree that there is a problem in requiring AIS scoring for every trauma patient in the country because not every hospital has the zeal or the financial resources to hire a trauma nurse coordinator to look after a trauma registry. They are extremely expensive, which is why we also suggested, in our previous paper, the business of simply using the ICD-9 data from the hospital information system.
I do not think that there is ever going to be a best scoring system, or at least there will not be a final scoring system. But there is no question that the Injury Severity Score can easily be improved upon by simply calculating it based on the three worst injuries regardless of body region.
I think that as long as we persist in using the Injury Severity Score, we should move right along to the New Injury Severity Score and obtain those benefits right away. Thank you.
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