AI Article Synopsis

  • The study aimed to assess how seasonal changes (winter vs. summer) impact oocyte (egg) quality in women struggling with infertility during in vitro fertilization.
  • Researchers analyzed 155 IVF cycles, noting significant differences in oocyte quality during summer (71 cycles) compared to winter (84 cycles), using specific quality assessment categories.
  • The results indicated that summer oocytes generally had better quality, while winter oocytes exhibited more abnormalities and lower quality, highlighting the need for further research on potential influencing factors like diet and exercise.

Article Abstract

Objective: The aim of this study was to determine the effects of seasons (winter vs. summer) on oocyte quality in infertile women undergoing ovulation induction for in vitro fertilization.

Methods: This retrospective cross-sectional study assessed 155 cycles of in vitro fertilization-induced ovulation in women, with 71 and 84 cycles occurring in the summer and winter, respectively. Oocytes were evaluated for quality, with 788 and 713 assessed during summer and winter, and classified according to Nikiforov's categories: (a) category I, good quality; (b) category 2, medium quality; and (c) category 3, low quality.

Results: Thickened zona pellucida (p<0.001), increased perivitelline space (p<0.001), oocyte shape abnormalities (p=0.01), and the presence of refractile bodies (p<0.0001) were more frequent in the summer cycles, whereas cytoplasmic granularity (p<0.001) was more frequent in the winter cycles. In winter, we observed a higher frequency of category 3 (p<0.001) and category 2 (p<0.001) oocytes and a lower frequency of category 1 (p<0.001) oocytes.

Conclusion: Oocyte dysmorphisms were found in 70-80% of cases and were more common in winter. The main features include a thickened zona pellucida, enlarged perivitelline space, irregular shape, and cytoplasmic granularity. This implies better-quality oocytes in the summer than in the winter. However, retrospective studies have limitations due to data collection biases and potential confounding variables such as diet and exercise. Future research is needed to confirm these findings and explore the underlying mechanisms.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11415068PMC
http://dx.doi.org/10.1590/1806-9282.20240408DOI Listing

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