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Predictive value of sperm morphology and movement characteristics in the outcome of in vitro fertilization of human oocytes.

作者信息

Chan S Y, Wang C, Chan S T, Ho P C, So W W, Chan Y F, Ma H K

机构信息

Department of Obstetrics and Gynaecology, University of Hong Kong, Queen Mary Hospital.

出版信息

J In Vitro Fert Embryo Transf. 1989 Jun;6(3):142-8. doi: 10.1007/BF01130778.

Abstract

One hundred fourteen semen samples from Chinese males were analyzed for routine semen parameters including the semen volume, sperm count, percentage motility, and percentage normal morphology. Of these 114 samples, 54 also had movement characteristics of seminal and swim-up sperm evaluated by the computer image analyzer system (Cellsoft; Cryo Resources Co., New York). All semen samples were subjected to the swim-up procedure to harvest the motile sperm before inseminations of human oocytes. Fertilization was considered to have occurred when at least one oocyte was observed with two or more pronuclei. Semen samples were classified as infertile (0% fertilization rate; N = 32) or fertile (greater than 0% fertilization rate; N = 82) before statistical analyses. There was a significant difference (P less than 0.005) in percentage normal morphology of seminal sperm between the fertile (mean +/- SE; 67.3 +/- 1.2%) and the infertile (59.3 +/- 2.2%) samples. The percentage normal morphology of seminal sperm correlated (r = 0.3049; P less than 0.002) with the fertilization rate and this parameter was selected by the multivariate stepwise discriminant analysis as the discriminator capable of predicting the fertilization rate with 57.9% accuracy. Statistical analyses of samples where sperm movement was also evaluated demonstrated that there was significant differences (P less than 0.01) between the fertile (N = 38) and the infertile (N = 16) samples in percentage normal morphology of seminal sperm (67.8 +/- 1.8% vs 56.2 +/- 2.6%) and curvilinear velocity of swim-up sperm (89.2 +/- 3.5 vs 68.2 +/- 7.2 microns/sec).(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

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