MATHEMATICAL MODEL OF FORECASTING FOR OUTCOMES IN VICTIMS OF METHANE-COAL MIXTURE EXPLOSION
Abstract
BACKGROUND. The severity of the victims’ state in the early period after the combined trauma (with the prevalence of a thermal injury) is associated with the development of numerous changes in all organs and systems which make proper diagnosis of complications and estimation of lethal outcome probability extremely difficult to be performed.
MATERIAL AND METHODS. The article presents a mathematical model for predicting lethal outcomes in victims of methanecoal mixture explosion, based on case histories of 220 miners who were treated at the Donetsk Burn Center in 1994–2012.
RESULTS. It was revealed that the probability of lethal outcomes in victims of methane-coal mixture explosion was statistically significantly affected with the area of deep burns (p<0.001), and the severe traumatic brain injury (p<0.001). In the probability of lethal outcomes, tactics of surgical treatment for burn wounds in the early hours after the injury was statistically significant (p=0.003). It involves the primary debridement of burn wounds in the period of burn shock with the simultaneous closure of affected surfaces with temporary biological covering.
CONCLUSION. These neural network models are easy to practice and may be created for the most common pathologic conditions frequently encountered in clinical practice.
About the Authors
E. Y. FistalUkraine
V. G. Guryanov
Ukraine
V. V. Soloshenko
Ukraine
References
1. Kim V.L., Khakimov M.Sh. Quantitative clinical system assess the severity of the patients (review). Vestnik vracha obshchey praktiki. 2005;1;65–
2. (In Russian).
3. Matveenko A.V., Chmyrev I.V., Petrachkov S.A. Practical application of coordinate grids of probability of the lethal outcome in treatment of the burnt. Skoraya meditsinskaya pomoshch’. 2013;14(1):34–43. (In Russian).
4. Jaimes F., Farbiarz J., Alvarez D., Martinez C. Comparison between logistic regression and neural networks to predict death in patients with suspected sepsis in the emergency room. Crit Care. 2005;9(2):150–156.
5. Swanson J.W., Otto A.M., Gibran N.S., et al. Trajectories to death in patients with burn injury. J Trauma Acute Care Surg. 2013;74(1):282–288.
6. Fistal’ E.Ya., Soloshenko V.V., Fistal’ N.N. Comprehensive treatment and rehabilitation of miners, victims of explosions of methane-coal mixtures. Energiya innovatsiy. 2008;5:50–54. (In Russian).
7. Mironov P.I., Stepanova P.I., Smol’nikov V.V. Estimation of severity and outcomes of severe burn injury on the hospital early stage. Skoraya meditsinskaya pomoshch’. 2010;4:59–61. (In Russian).
8. Lyakh Yu.E., Gur’yanov V.G., Khomenko V.N., Panchenko O.A. Fundamentals of computer biostatistics: analysis of information in biology, medicine and pharmacy statistical package Medstat. Donetsk: Papakitsa E.K. Publ., 2006. 214 p. (In Russian).
9. Petri A., Sebin K. Transparent statistics in medicine. Moscow: GEOTARMED Publ., 2003. 144 p. (In Russian).
Review
For citations:
Fistal E.Y., Guryanov V.G., Soloshenko V.V. MATHEMATICAL MODEL OF FORECASTING FOR OUTCOMES IN VICTIMS OF METHANE-COAL MIXTURE EXPLOSION. Russian Sklifosovsky Journal "Emergency Medical Care". 2016;(3):43-47. (In Russ.)