A prospective study on the predictive value of normal sperm morphology as evaluated by computer (IVOS)

Kruger T.F. ; Lacquet F.A. ; Sarmiento C.A.S. ; Menkveld R. ; Ozgur K. ; Lombard C.J. ; Franken D.R. (1996)


Objective: To evaluate the IVOS (Hamilton Thorne Research Version 2.1 Dimension Program, Beverly, MA) system's ability to predict fertilization in vitro in a prospective study. Design: A prospective clinical study. Setting: Hospital-based academic ART program. Patients: Eighty patients from the IVF- GIFT program were evaluated. The same semen sample was analyzed on a day-to- day basis by both laboratory (manual method) and the computerized system for percentage normal morphology, concentration/mL, motility, and forward progression. Only patients with two or more metaphase II (MII) oocytes available were allowed into the study and excluded where the male partner had antisperm antibodies or qualified for intracytoplasmic sperm injection (<500,000 motile spermatozoa obtained after glass wool separation). Statistical Analysis: Logistic regression analysis was used to study predictors of fertilization in vitro. Results: Three hundred thirty-eight oocytes were obtained from 80 patients of which 239 fertilized. The logistic regression analysis of the manual method (percentage normal morphology) and IVOS indicated that both were predictors of fertilization. Sperm morphology as evaluated by IVOS in patients with <10 x 106 motile spermatozoa/mL retrieved after swim-up was a significant predictor of fertilization as was the number of oocytes obtained. Thus, the more oocytes obtained in the lower morphological groups, the better the chance of fertilization. The fertilization rate in the morphology group 0% to 4% normal forms was 45.6% (37/81) and in the group >14% normal forms was 85.2% (69/81). Conclusions: It was shown that in patients where ≤10 x 106 motile spermatozoa were obtained, the role of morphology (evaluated by IVOS) as well as the number of oocytes were important predictors of fertilization. The computer can assist to identify these patient with a poor prognosis for fertilization.

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