Skip to main content
SpringerLink
Log in

Predictive value of postwashed total progressively motile sperm count using CASA estimates in 6871 non-donor intrauterine insemination cycles

  • Assisted Reproduction Technologies
  • Published:
Journal of Assisted Reproduction and Genetics Aims and scope Submit manuscript

Abstract

Purpose

To determine whether postwashed total progressively motile sperm count (TPMSC) obtained by CASA estimates could predict positive pregnancy test result in non-donor IUI cycles.

Methods

Six thousand eight hundred and seventy one (6,871) IUI cycles with non-donor semen were retrospectively analyzed. Patient, cycle characteristics and prewashed and postwashed semen parameters were included in analysis. The main outcome measure was the positive pregnancy test result.

Results

The pregnancy rate per cycle (PR/cycle) when postwashed TPMSC is between 0–0.5 million, 0.51–1 million, 1.01–5 million, 5.01–10 million and greater than 10 million were 8.1 % (42/520), 14.4 % (41/285), 16.1 % (237/1,469), 18.4 % (193/1,046) and 18.8 % (668/3,551) respectively. The predicted odd of positive pregnancy result is statistically significantly higher when TPMSC is >0.51 million compared to the TPMSC of <0.51 million (OR = 1.68, 95 % CI: 1.04–2.71). The predicted odd of positive pregnancy result is greatest when TPMSC is at least 5 million (OR = 2, 95 % CI: 1.38 to 2.9).

Conclusion

TPMSC is an independent predictor of pregnancy test result and TPMSC of half million or greater is adequate to achieve statistically similar pregnancy test results after non-donor IUI cycles.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

References

  1. Zhao Y et al. Impact of semen characteristics on the success of intrauterine insemination. J Assist Reprod Genet. 2004;21(5):143–8.

    Article  PubMed Central  PubMed  Google Scholar 

  2. Le Lannou D. Intrauterine insemination, indications, and results. Contracept Fertil Sex. 1994;22(6):361–9.

    PubMed  Google Scholar 

  3. Duran HE et al. Intrauterine insemination: a systematic review on determinants of success. Hum Reprod Update. 2002;8(4):373–84.

    Article  CAS  PubMed  Google Scholar 

  4. Branigan EF, Estes MA, Muller CH. Advanced semen analysis: a simple screening test to predict intrauterine insemination success. Fertil Steril. 1999;71(3):547–51.

    Article  CAS  PubMed  Google Scholar 

  5. Akanji Tijani H, Bhattacharya S. The role of intrauterine insemination in male infertility. Hum Fertil Camb. 2010;13(4):226–32.

    Article  PubMed  Google Scholar 

  6. Van Voorhis BJ et al. Effect of the total motile sperm count on the efficacy and cost-effectiveness of intrauterine insemination and in vitro fertilization. Fertil Steril. 2001;75(4):661–8.

    Article  PubMed  Google Scholar 

  7. Strandell A et al. Fallopian tube sperm perfusion: the impact of sperm count and morphology on pregnancy rates. Acta Obstet Gynecol Scand. 2003;82(11):1023–9.

    Article  PubMed  Google Scholar 

  8. Hughes EG. The effectiveness of ovulation induction and intrauterine insemination in the treatment of persistent infertility: a meta-analysis. Hum Reprod. 1997;12(9):1865–72.

    Article  CAS  PubMed  Google Scholar 

  9. Freour T et al. Computer-assisted sperm analysis (CASA) parameters and their evolution during preparation as predictors of pregnancy in intrauterine insemination with frozen-thawed donor semen cycles. Eur J Obstet Gynecol Reprod Biol. 2010;149(2):186–9.

    Article  PubMed  Google Scholar 

  10. Jorgensen N et al. Semen analysis performed by different laboratory teams: an intervariation study. Int J Androl. 1997;20(4):201–8.

    Article  CAS  PubMed  Google Scholar 

  11. Brazil C et al. Standardized methods for semen evaluation in a multicenter research study. J Androl. 2004;25(4):635–44.

    PubMed  Google Scholar 

  12. van Weert JM et al. Performance of the postwash total motile sperm count as a predictor of pregnancy at the time of intrauterine insemination: a meta-analysis. Fertil Steril. 2004;82(3):612–20.

    Article  PubMed  Google Scholar 

  13. Miller DC et al. Processed total motile sperm count correlates with pregnancy outcome after intrauterine insemination. Urology. 2002;60(3):497–501.

    Article  PubMed  Google Scholar 

  14. Horvath PM et al. The relationship of sperm parameters to cycle fecundity in superovulated women undergoing intrauterine insemination. Fertil Steril. 1989;52(2):288–94.

    CAS  PubMed  Google Scholar 

  15. Wainer R et al. Prognostic sperm factors in intra-uterine insemination with partner’s sperm. Contracept Fertil Sex. 1996;24(12):897–903.

    CAS  PubMed  Google Scholar 

  16. Berg U, Brucker C, Berg FD. Effect of motile sperm count after swim-up on outcome of intrauterine insemination. Fertil Steril. 1997;67(4):747–50.

    Article  CAS  PubMed  Google Scholar 

  17. Dodson WC et al. A randomized comparison of the methods of sperm preparation for intrauterine insemination. Fertil Steril. 1998;70(3):574–5.

    Article  CAS  PubMed  Google Scholar 

  18. Khalil MR et al. Homologous intrauterine insemination. an evaluation of prognostic factors based on a review of 2473 cycles. Acta Obstet Gynecol Scand. 2001;80(1):74–81.

    Article  CAS  PubMed  Google Scholar 

  19. Dodson WC, Haney AF. Controlled ovarian hyperstimulation and intrauterine insemination for treatment of infertility. Fertil Steril. 1991;55(3):457–67.

    CAS  PubMed  Google Scholar 

  20. Nulsen JC et al. A randomized and longitudinal study of human menopausal gonadotropin with intrauterine insemination in the treatment of infertility. Obstet Gynecol. 1993;82(5):780–6.

    CAS  PubMed  Google Scholar 

  21. Brasch JG et al. The relationship between total motile sperm count and the success of intrauterine insemination. Fertil Steril. 1994;62(1):150–4.

    CAS  PubMed  Google Scholar 

  22. Campana A et al. Intrauterine insemination: evaluation of the results according to the woman’s age, sperm quality, total sperm count per insemination and life table analysis. Hum Reprod. 1996;11(4):732–6.

    Article  CAS  PubMed  Google Scholar 

  23. Huang HY et al. The impact of the total motile sperm count on the success of intrauterine insemination with husband’s spermatozoa. J Assist Reprod Genet. 1996;13(1):56–63.

    Article  CAS  PubMed  Google Scholar 

  24. Kleppe, M., M.H. van Hooff, and J.P. Rhemrev, Effect of total motile sperm count in intra-uterine insemination on ongoing pregnancy rate. Andrologia, 2014

  25. Dinelli L et al. Prognosis factors of pregnancy after intrauterine insemination with the husband’s sperm: conclusions of an analysis of 2,019 cycles. Fertil Steril. 2014;101(4):994–1000.

    Article  PubMed  Google Scholar 

  26. Bollendorf A, Check JH, Lurie D. Evaluation of the effect of the absence of sperm with rapid and linear progressive motility on subsequent pregnancy rates following intrauterine insemination or in vitro fertilization. J Androl. 1996;17(5):550–7.

    CAS  PubMed  Google Scholar 

  27. Ok EK et al. The effect of post-wash total progressive motile sperm count and semen volume on pregnancy outcomes in intrauterine insemination cycles: a retrospective study. J Turk Ger Gynecol Assoc. 2013;14(3):142–5.

    Article  PubMed Central  PubMed  Google Scholar 

  28. Rhemrev JP et al. The postwash total progressively motile sperm cell count is a reliable predictor of total fertilization failure during in vitro fertilization treatment. Fertil Steril. 2001;76(5):884–91.

    Article  CAS  PubMed  Google Scholar 

  29. Nikbakht R, Saharkhiz N. The influence of sperm morphology, total motile sperm count of semen and the number of motile sperm inseminated in sperm samples on the success of intrauterine insemination. Int J Fertil Steril. 2011;5(3):168–73.

    PubMed Central  PubMed  Google Scholar 

  30. Wainer R et al. Influence of the number of motile spermatozoa inseminated and of their morphology on the success of intrauterine insemination. Hum Reprod. 2004;19(9):2060–5.

    Article  PubMed  Google Scholar 

  31. Sun Y et al. Does sperm morphology affect the outcome of intrauterine insemination in patients with normal sperm concentration and motility? Andrologia. 2012;44(5):299–304.

    Article  CAS  PubMed  Google Scholar 

  32. Nicopoullos JD et al. A decade of sperm washing: clinical correlates of successful insemination outcome. Hum Reprod. 2010;25(8):1869–76.

    Article  PubMed  Google Scholar 

  33. Farhi J, Orvieto R. Cumulative clinical pregnancy rates after COH and IUI in subfertile couples. Gynecol Endocrinol. 2010;26(7):500–4.

    Article  CAS  PubMed  Google Scholar 

  34. Streda R et al. Ovulation induction increases pregnancy rate during intrauterine insemination compared with natural cycles. Ceska Gynekol. 2007;72(6):397–402.

    CAS  PubMed  Google Scholar 

  35. Berker B et al. Recombinant FSH versus clomiphene citrate for ovarian stimulation in couples with unexplained infertility and male subfertility undergoing intrauterine insemination: a randomized trial. Arch Gynecol Obstet. 2011;284(6):1561–6.

    Article  CAS  PubMed  Google Scholar 

  36. Costello MF. Systematic review of the treatment of ovulatory infertility with clomiphene citrate and intrauterine insemination. Aust N Z J Obstet Gynaecol. 2004;44(2):93–102.

    Article  PubMed  Google Scholar 

  37. Badawy A, Elnashar A, Eltotongy M. Effect of sperm morphology and number on success of intrauterine insemination. Fertil Steril. 2009;91(3):777–81.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Division of Reproductive Endocrinology and Infertility, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA

    Orkun Tan, Thoa Ha, Bruce R. Carr & Kevin J. Doody

  2. ReproMed Fertility Center, 3800 San Jacinto, Dallas, TX, 75240, USA

    Orkun Tan

  3. Department of Clinical Sciences, Division of Biostatistics, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA

    Paul Nakonezny

  4. Center for Assisted Reproduction, 1701 Park Place Av, Bedford, TX, 76022, USA

    Kathleen M. Doody & Kevin J. Doody

Authors
  1. Orkun Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Thoa Ha
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Bruce R. Carr
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Paul Nakonezny
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Kathleen M. Doody
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Kevin J. Doody
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Orkun Tan.

Additional information

Capsule Postwashed total progressively motile sperm count is a predictor of pregnancy test result in nondonor IUI cycles.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tan, O., Ha, T., Carr, B.R. et al. Predictive value of postwashed total progressively motile sperm count using CASA estimates in 6871 non-donor intrauterine insemination cycles. J Assist Reprod Genet 31, 1147–1153 (2014). https://doi.org/10.1007/s10815-014-0306-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10815-014-0306-0

Keywords

Search

Navigation