Categorization of burn severity.
- Author:
Xiao-dong YANG
1
;
Guo-an LIN
;
Guang-he ZHAO
;
Wen-jun LI
;
Qiu-yun JIAO
;
Shi-an YUAN
Author Information
- Publication Type:Journal Article
- MeSH: Adolescent; Adult; Burns; classification; Child; Child, Preschool; Humans; Injury Severity Score; Logistic Models; Middle Aged; Young Adult
- From: Chinese Journal of Burns 2007;23(5):362-364
- CountryChina
- Language:Chinese
-
Abstract:
OBJECTIVETo seek a new method for the categorization of burn severity.
METHODSBurn patients hospitalized in our center from December of 1958 to December of 2004 were enrolled in the study, and they were divided into different age groups according to same mortality, then the patients in each group were subdivided into 4 groups according to the burn severity: i.e., mild burns, moderate burns, severe burns, serious severe burns. The total burn area, the number of cases, the mortality, and the area of DI degree burns were statistically analyzed in each subgroup, and the scope in total burn area and area of III degree burns were taken as standards to define the degree of burns. The logistic regression equation was established with probability of death as the variable, and age, total burn area, burn area of different degrees as concomitant variables to form a logistic regression formula. It was used to predict the probability of death of patients hospitalized in 2005, 50 as to check whether the corresponding indices of these patients were consistant with above standard of categorization into degrees, and to judge hum severity of the patients who had concomitant inhalation injury, severe associated injury, or those with serious disease before burns.
RESULTSThe patients were divided into three groups: less than 2 years of age (including 2 years of age), 2 to 55 years of age(including 55 years of age), and older than 55 years of age groups. The classification standard of burn area was shown in table 2 of the article. The probability of death and corresponding indices predicted hy the logistic regression equation were highly coincident with our standard. Patients with moderate inhalation injury could be regarded as patients with severe or most severe burns, while severity of those with mild inhalation injury could be determined by burn area alone.
CONCLUSIONThe logistic regression equation is a good method to predict the severity of burn patients, with reasonable age specificity grouping, and accurate and practical scoring of division for corresponding burn severity.