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Acute Medicine & Surgery
Article . 2014 . Peer-reviewed
License: Wiley Online Library User Agreement
Data sources: Crossref
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Model for predicting the injury severity score

Authors: Shuichi, Hagiwara; Kiyohiro, Oshima; Masato, Murata; Minoru, Kaneko; Makoto, Aoki; Masahiko, Kanbe; Takuro, Nakamura; +2 Authors

Model for predicting the injury severity score

Abstract

AimTo determine the formula that predicts the injury severity score from parameters that are obtained in the emergency department at arrival.MethodsWe reviewed the medical records of trauma patients who were transferred to the emergency department of Gunma University Hospital between January 2010 and December 2010. The injury severity score, age, mean blood pressure, heart rate, Glasgow coma scale, hemoglobin, hematocrit, red blood cell count, platelet count, fibrinogen, international normalized ratio of prothrombin time, activated partial thromboplastin time, and fibrin degradation products, were examined in those patients on arrival. To determine the formula that predicts the injury severity score, multiple linear regression analysis was carried out. The injury severity score was set as the dependent variable, and the other parameters were set as candidate objective variables. IBM spss Statistics 20 was used for the statistical analysis. Statistical significance was set at P < 0.05. To select objective variables, the stepwise method was used.ResultsA total of 122 patients were included in this study. The formula for predicting the injury severity score (ISS) was as follows: ISS = 13.252–0.078(mean blood pressure) + 0.12(fibrin degradation products). The P‐value of this formula from analysis of variance was <0.001, and the multiple correlation coefficient (R) was 0.739 (R2 = 0.546). The multiple correlation coefficient adjusted for the degrees of freedom was 0.538. The Durbin–Watson ratio was 2.200.ConclusionsA formula for predicting the injury severity score in trauma patients was developed with ordinary parameters such as fibrin degradation products and mean blood pressure. This formula is useful because we can predict the injury severity score easily in the emergency department.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
7
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