title: [An epidemiological study on the factors influencing length of hospitalization for inpatients of burns].
abstract: OBJECTIVE
  To provide evidence for intervention on secondary prevention of burns through studying the factors influencing the length of hospitalization on inpatients of burns.
  
  
  METHODS
  Seven hundred and ninety burnt patients with cluster sampling, combined analyzing with Cox regression and factor analysis.
  
  
  RESULTS
  The influential factors on the length of hospitalization in inpatients with burns included a) how did the patients come to the hospital (X3), b) total body surface area involved (X4), c) depth of burns (X5), and d) the time before hospitalization after burnt (X6). The Cox proportional hazard model used was h(t)/h0(t) = e(-0.193 3F1 -0.617 6F2 -0.118 0F3), and the conversion model between factors Fi and original variates were F1 = -0.132X3 - 0.009X4 + 0.655X5 + 0.583X6, F2 = 0.019X3 + 0.875X4 + 0.257X5 - 0.294X6, F3 = 1.010X3 + 0.025X4 - 0.176X5 + 0.030X6. Data showed that the burnt patients had longer hospitalization time when the burns were deep, larger body surface area involved, and with longer delay before getting to the hospitals, where as the patients got cured faster when taken to the hospital by ambulances.
  
  
  CONCLUSIONS
  One of the major prognostic factors of burns was to treat the patients in time. Secondary prevention of burns must be reinforced.
authors.affiliation: Department of Preventive Medicine, Medical College of Jinan University, Guangzhou 510632, China.
authors.forename: C
authors.initials: C
authors.lastname: Wu
authors.forename: S
authors.initials: S
authors.lastname: Wang
authors.forename: G
authors.initials: G
authors.lastname: Liu
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002056:Burns / Q000191:economics / Q000453:epidemiology* / Q000517:prevention & control; D002648:Child; D002675:Child, Preschool; D005260:Female; D006801:Humans; D007223:Infant; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D012044:Regression Analysis