A LOGISTIC-REGRESSION MODEL INCLUDING DNA STATUS AND MORPHOLOGY OF SPERMATOZOA FOR PREDICTION OF FERTILIZATION IN-VITRO

To determine predictive values of routine semen analysis, sperm morpho logy evaluation using strict criteria and DNA status for in-vitro fert ilization (IVF), 66 consecutive couples undergoing IVF in a university hospital IVF programme were prospectively investigated. Semen samples from 66 men were evaluated by routine semen analysis, morphology eval uation using strict criteria and acridine orange staining for determin ation of DNA status. A new technique is described for acridine orange scoring which consisted of evaluation of two smears per case, with and without heat treatment. Resistance to heat-provoked denaturation was determined by the difference between two evaluations. A logistic regre ssion model was built and receiver operating characteristic curves wer e constructed to determine the threshold values and to compare diagnos tic properties. Morphology evaluation using strict criteria and concen tration of progressively motile spermatozoa were found to be the princ ipal parameters determining the sperm fertilizing capacity in vitro. T he logistic regression model composed of morphology evaluation using s trict criteria and acridine orange score had a powerful diagnostic cap ability for prediction of fertilization in vitro.