Predictive value of classical and automated sperm analysis for in-vitro fertilization
Patricia Barlow, Annick Delvigne, Jean Van Dromme, Jeanine Van Hoeck, Kathleen Vandenbosch, Fernand O. G. Leroy
Abstract
Patricia Barlow, Annick Delvigne, Jean Van Dromme, Jeanine Van Hoeck, Kathleen Vandenbosch, Fernand O. G. Leroy
Abstract
The fertilization rates observed in 122 attempts at in-vitro fertilization were examined in relation to sperm characteristics assessed by visual and automated screening. Using linear regression analysis, a significant correlation was found between the fertilization rate and (i) evaluations in fresh semen sperm concentration, percentages of sperm motility, vitality and normal morphology and velocity, (ii) measurements in swim-up preparations of percentages of sperm motility, vitality and morphology, velocity and amplitude of lateral head displacement. No significant correlation was found between the fertilization rate and any of the parameters studied in 24-h-old swim-up suspensions. Analysis by multiple variable stepwise linear regression showed an optimal correlation (R6 = 0.62) between the observed fertilization rate and theoretical calculation obtained from the following predictive function: fertilization rate = -0.3 + (0.008 x swim-up motility) + (0.004 x normal sperm morphology in fresh semen). Introduction of kinematic characteristics studied by automated screening improved the multiple correlation between the calculated and observed fertilization rate in cases of normal or mildly defective semen. Because of the limited availability of motile spermatozoa, automated analysis could not supersede classical sperm analysis in cases of more severe sperm defects.
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The fertilization rates observed in 122 attempts at in-vitro fertilization were examined in relation to sperm characteristics assessed by visual and automated screening. Using linear regression analysis, a significant correlation was found between the fertilization rate and (i) evaluations in fresh semen sperm concentration, percentages of sperm motility, vitality and normal morphology and velocity, (ii) measurements in swim-up preparations of percentages of sperm motility, vitality and morphology, velocity and amplitude of lateral head displacement. No significant correlation was found between the fertilization rate and any of the parameters studied in 24-h-old swim-up suspensions. Analysis by multiple variable stepwise linear regression showed an optimal correlation (R6 = 0.62) between the observed fertilization rate and theoretical calculation obtained from the following predictive function: fertilization rate = -0.3 + (0.008 x swim-up motility) + (0.004 x normal sperm morphology in fresh semen). Introduction of kinematic characteristics studied by automated screening improved the multiple correlation between the calculated and observed fertilization rate in cases of normal or mildly defective semen. Because of the limited availability of motile spermatozoa, automated analysis could not supersede classical sperm analysis in cases of more severe sperm defects.
Key concepts: Human fertilization, Sperm, Semen, Sperm motility, Biology, Andrology, In vitro fertilisation, Semen analysis