ABSTRACT
OBJECTIVE: To establish a discriminant model and to provide a relatively accurate scientific basis for the early diagnosis of tuberculosis (TB) and detection of the close contacts. METHODS: Through logistic regression analysis, key factors were selected according to Bayes theory and key factors of TB incidence of the close contacts were screened as well as a discriminant model was established. RESULTS: The non-TB incidence discriminant function of the close contacts was described as: Y1= -39.831 (constant) + 1.927 X1 (sputum-frequency) + 3.528 X2 (education) + 0.309 X3 (contact time) + 5.893 X4 (evade) +2.140 X5 (ventilation) + 8.706 X6 (cough) + 30.970 X7 (fever). The discriminant function of non-TB incidence of the close contacts was as: Y2 =-57.875 (constant) + 2.343 X1 (sputum-frequency) + 3.965 X2 (education) + 0.361 X3 (contact time) + 6.296 X4 (evade) + 1.348 X5 (ventilation) + 12.984 X6 (cough) + 36.555 X7 (fever). CONCLUSION: The discriminant model night be used to contribute to the early diagnosis, early intervention and timely treatment on those close contacts of tuberculosis cases.
