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Fertil Steril. 2014 Jun;101(6):1649-55.e1-2. doi: 10.1016/j.fertnstert.2014.02.028. Epub 2014 Mar 29.

Patient-specific predictions of outcome after gonadotropin ovulation induction/intrauterine insemination.

Author information

  • 1Vincent Department of Obstetrics and Gynecology, Massachusetts General Hospital Fertility Center, Harvard Medical School, Boston, Massachusetts. Electronic address: rhgoldman@partners.org.
  • 2Reproductive Endocrinology and Infertility Division, Massachusetts General Hospital Fertility Center, Harvard Medical School, Boston, Massachusetts.
  • 3Vincent Department of Obstetrics and Gynecology, Massachusetts General Hospital Fertility Center, Harvard Medical School, Boston, Massachusetts; Reproductive Endocrinology and Infertility Division, Massachusetts General Hospital Fertility Center, Harvard Medical School, Boston, Massachusetts.

Abstract

OBJECTIVE:

To use patient-specific and cycle-specific characteristics to predict clinical pregnancy, multiple pregnancy, and spontaneous abortion rates after gonadotropin ovulation induction (OI)/IUI.

DESIGN:

Retrospective chart review.

SETTING:

Academic fertility center.

PATIENT(S):

A total of 1,438 women who underwent 3,375 gonadotropin OI/IUI cycles.

INTERVENTION(S):

Individual and cycle-specific characteristics were evaluated to determine predictors of the rates of clinical pregnancy, multiple pregnancy, and spontaneous abortion. Logistic regression using individual parameters was used to create predictive models.

MAIN OUTCOME MEASURE(S):

Clinical pregnancy (CPR), multiple pregnancy (MPR), and spontaneous abortion rates (SABR).

RESULT(S):

Multiple predictors were identified for CPR, MPR, and SABR. The presence of at least two follicles ≥ 13 mm at ovulation trigger significantly increased CPR (odds ratio [OR], 95% confidence interval [CI] = 1.45, 1.18-1.78) and MPR (OR, 95% CI = 5.17, 2.16-12.41). An E2 level >400 pg/mL significantly increased MPR (OR, 95% CI = 9.54, 2.31-39.42). Logistic regression models were developed for individualized predictions of outcome.

CONCLUSION(S):

Regression analysis reveals the patient and cycle-specific characteristics that are significant predictors of CPR, MPR, and SABR after OI/IUI. Logistic models using significant or nearly significant predictors for CPR, MPR, and SABR offer improved predictive power relative to simpler models, and allow for the development of a risk calculator for personalized patient counseling.

Copyright © 2014 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

KEYWORDS:

Ovulation induction; clinical pregnancy rate; intrauterine insemination; multiple pregnancy; predictive models

[PubMed - indexed for MEDLINE]
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