Quality of additional embryos transferred on pregnancy outcomes in IVF: predictions using a mathematical approach.

This study assessed the influence of adding embryos with different embryo quality on pregnancy rate and multiple pregnancy rate (MPR). The study included 1891 IVF transfers performed at two centres with different embryo transfer policies. Pregnancy rate and MPR were analysed following three models and then including embryo quality. A predictive mathematical model and two scatter plots were constructed. The model based on embryo independence was incompatible with the observed data, while both the ground and collaborative models provided excellent fits. The collaborative model, however, predicted multiple pregnancies, especially triplets, more accurately. Transfer of additional embryos, irrespective of embryo quality, always increased pregnancy rate and MPR. When implantation rate was low, there was a marked increase in pregnancy rate but only a relatively small increase in MPR. In contrast, with higher implantation rates, the increase in pregnancy rate was mainly due to the increase in MPR, with the same singleton pregnancy rate. Transfer of additional embryos, irrespective of embryo quality, follows a collaborative pattern and always results in an increase in pregnancy rate and MPR. The scatter plots accurately predicted the influence of the different combinations of number and embryo quality on pregnancy rate and MPR.

Decline in human fertility rates with male age: a consequence of a decrease in male fecundity with aging?

BACKGROUND: The objective of this study is to investigate the influence of male age on human fertility, defined as the birth rate for a given population. METHODS: Data from the Spanish National Statistics Institute (INE) for the year 2004 from a total of 454,753 newborn infants and sorted by male and female age groups were evaluated. In order to correct the influence of female age-related fertility, a different analysis was performed considering only women under 30 years of age. RESULTS: From a demographic point of view, male fertility started to decline at 35-39 years of age. This decline is constant and follows an exponential pattern (slope -0.11 to -0.12). The trend persisted when the data were adjusted for every 1,000 men in the age group, as well as when only women under the age of 30 were considered. Male fertility showed a 21-23% annual decrease starting at the age of 39. CONCLUSION: An exponential decrease in human fertility which is independent of the woman's age was observed with male aging. This decay is probably due to a downfall in male fecundity, closely related to a decline in sperm quality. However, social or behavioral causes for this trend cannot be excluded.

The implantation of every embryo facilitates the chances of the remaining embryos to implant in an IVF programme: a mathematical model to predict pregnancy and multiple pregnancy rates.

BACKGROUND: We aimed to assess the validity of a theoretical mathematical model to predict the pregnancy rate and the multiple pregnancy rate in IVF/oocyte donation programmes on the basis of the implantation rate and the number of transferred embryos. METHODS: A total of 1835 embryo transfers corresponding to three different programmes in two centres with different implantation rates were analysed. Pregnancy and multiple pregnancy rates observed in the aforementioned programmes were compared with those obtained following different mathematical models. Four models were tested: binomial model, ground model, maternal variability model and collaborative model. The goodness of fit was performed by means of the maximum likelihood fit method. RESULTS: The binomial model could not predict the pregnancy rate, and especially the multiple pregnancy rate. The multiple pregnancy rate predicted following the binomial model was much lower than observed, up to 40-fold reduced. Ground model and maternal variability model adjusted to the data with more precision, but were still not accurate. Finally, the collaborative model reproduced with very great accuracy both pregnancy rate and the multiple pregnancy rate. A collaborative parameter of 22% was found, implying that the implantation probability of each embryo is increased by 22% for every embryo previously implanted. CONCLUSIONS: Embryonic implantation does not follow a binomial law, showing that the implantation is not independent from the number of embryos implanted. The best fit to the data is obtained following a collaborative model by which the implantation of one embryo is facilitated by the implantation of other embryo(s). The mathematical formula of the collaborative model predicts very accurately the pregnancy rate and the multiple pregnancy rate in IVF/oocyte donation programmes, based on the implantation rate of this specific programme and the number of embryos transferred up to five embryos. We recommend using the aforementioned formula to quantify the pregnancy rate and the risk of multiple pregnancy in the counselling of the infertile couple at embryo transfer. Such a formula is freely available at www.ifca.unican.es/matorras/mathpreg/.

Relevamiento de recursos de salud en la Ciudad de Buenos Aires. Una mirada desde la protección de derechos de la infancia / Assessment of the health resources of the City of Buenos Aires from the point of view of the protection of children's rigths

Esta investigación se inscribe en un convenio entre el Consejo de Derechos de Niños, Niñas y Adolescentes (G.C.B.A.) y la IIº Cátedra de Salud Pública/Salud Mental. Facultad de Psicología-UBA. Como objetivo general, se propuso realizar un relevamiento de recursos de salud, que sirva como insumo para las instituciones involucradas, destinado a afianzar la atención integral de la salud en la infancia, y contribuir al acceso gratuito, universal e igualitario. Se trata de un estudio exploratorio-descriptivo desarrollado en la Ciudad de Buenos Aires. Se trabajó en dos zonas geográficas seleccionadas: Palermo y Boca/Barracas. Como unidades de análisis se seleccionaron instituciones en base a tres criterios: 1-Pertenecer al Sector Público Estatal o la Sociedad Civil, 2-Desarrollar prácticas relacionadas a salud, 3-Implementar acciones en el campo de la infancia. Se presentan los resultados obtenidos del procesamiento de datos cuanti-cualitativos, recolectados durante tres cuatrimestres en base al cuestionario diseñado.