Reducing multiples: a mathematical formula that accurately predicts rates of singletons, twins, and higher-order multiples in women undergoing in vitro fertilization. Academic Article uri icon

Overview

abstract

  • OBJECTIVE: To develop a mathematical formula that accurately predicts the probability of a singleton, twin, and higher-order multiple pregnancy according to implantation rate and number of embryos transferred. DESIGN: A total of 12,003 IVF cycles from a single center resulting in ET were analyzed. Using mathematical modeling we developed a formula, the Combined Formula, and tested for the ability of this formula to accurately predict outcomes. SETTING: Academic hospital. PATIENT(S): Patients undergoing IVF. INTERVENTION(S): None. MAIN OUTCOME MEASURE(S): Goodness of fit of data from our center and previously published data to the Combined Formula and three previous mathematical models. RESULT(S): The Combined Formula predicted the probability of singleton, twin, and higher-order pregnancies more accurately than three previous formulas (1.4% vs. 2.88%, 4.02%, and 5%, respectively) and accurately predicted outcomes from five previously published studies from other centers. An online applet is provided (https://secure.ivf.org/ivf-calculator.html). CONCLUSION(S): The probability of pregnancy with singletons, twins, and higher-order multiples according to number of embryos transferred is predictable and not random and can be accurately modeled using the Combined Formula. The embryo itself is the major predictor of pregnancy outcomes, but there is an influence from "barriers," such as the endometrium and collaboration between embryos (embryo-embryo interaction). This model can be used to guide the decision regarding number of embryos to transfer after IVF.

publication date

  • September 15, 2012

Research

keywords

  • Algorithms
  • Embryo Transfer
  • Fertilization in Vitro
  • Models, Statistical
  • Pregnancy Outcome
  • Pregnancy Tests
  • Pregnancy, Multiple

Identity

Scopus Document Identifier

  • 84870308180

Digital Object Identifier (DOI)

  • 10.1016/j.fertnstert.2012.08.014

PubMed ID

  • 22985944

Additional Document Info

volume

  • 98

issue

  • 6