Patient selection: 312 consecutive burn patients. The youngest age is not given but may be about 9 years of age (based on age range for survivors).
Data required:
(1) percent total BSA with partial or full thickness (second and third degree) burns, from 0 to 100
(2) percent BSA with partial thickness (second degree) burns, from 0 to 100
(3) percent BSA with full thickness (third degree) burns, from 0 to 100
(4) age in years
(5) body weight in kilograms
(6) age in years
(7) gender (male = 1, female = 2)
4 equations were derived based on what data was available.
(1) all data known
(2) weight unknown
(3) degree of burn unknown (but total area involved known)
(4) weight and degree of burn unknown
Y1 =
= 89.8882 – (0.0102 * ((percent total burn)^2) – (0.0116 * ((percent total burn) * (age in years)) – (0.0068 * ((age in years)^2)) + (0.6547 * (percent partial thickness burns)) + (0.2487 * (weight in kilograms))
Y2 =
= 90.4389 – (0.0156 * ((age in years)^2) – (0.0096 * ((percent total burn) ^2)) – (0.8596 * (age in years)) - (0.0132* (percent total burn) * (age in years)) + (0.7123 * (percent partial burns))
Y3 =
= 96.0987 – (0.0089 * ((percent total burn)^2) – (0.0092* ((age in years)^2)) – (0.0083 * (age in years) * (percent total burn)) + (0.2942 * (weight in kilograms))
Y4 =
= 111.28 – (0.0161 * ((age in years)^2) – (0.0085 * ((percent total burn) ^2) + (0.7168 * (age in years)) - (0.0084 * (percent total burns) * (age in years)) - (8.1455 * (points for gender))
probability of survival =
= 1 / (1 + EXP((-1) * Y))
Limitations:
• The values for Y's showed a wide variation, with a spectrum of survival probabilities given. I would probably favor Y1.
• Survival in patients with burns has improved since this paper was written. However, the prediction may still apply to regions where modern technologies are not available.
• The functions do not include inhalation injury.
• This approach may model the patients in the study well but may not be transportable to other sites.
