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<p><i>Objective</i>.&#xa0;This study assessed associations between season, temperature, direct normal irradiance (DNI), and clinical pregnancy outcomes in first fresh in vitro fertilization (IVF) cycle.&#xa0;<i>Methods</i>.&#xa0;We conducted a retrospective cohort study (June 2021-October 2023) of 1179 patients undergoing fresh IVF cycles. Inclusion criteria required age ≤ 45 years, first-time fresh embryo transfer cycles (long/antagonist protocol), excluding preimplantation genetic testing, frozen cycles, or incomplete data. Temperature and DNI were recorded from gonadotropin (Gn) initiation to oocyte retrieval. Binary logistic regression assessed seasonal impacts on clinical pregnancy, while restricted cubic splines (RCS) independently modeled temperature/DNI effects.&#xa0;<i>Results</i>.&#xa0;Compared to winter, clinical pregnancy likelihood was 1.74-fold higher in spring (95% CI:1.11–2.71, <i>P</i> = 0.015) and 1.53-fold in summer (95% CI:1.02–2.30, <i>P</i> = 0.042). Stratified analysis revealed a 2.02-fold increased likelihood in summer cycles using the long protocol (95% CI:1.07–3.82, <i>P</i> = 0.031), whereas no seasonal variation was observed in antagonist protocol. RCS regression analysis indicated a nonlinear relationship between temperature and clinical pregnancy outcomes, which was confirmed in the long protocol group. No significant correlations were observed with DNI or in patients treated with the antagonist protocol.&#xa0;<i>Conclusions</i>.&#xa0;Season and ambient temperature significantly impact IVF clinical pregnancy, especially in the long protocol, with the highest increase in pregnancy rates observed in summer, as well as within the 26.13℃ to 29.68℃ temperature range. No significant effects were observed with DNI or the antagonist protocol. These findings suggest that summer treatment may optimize IVF outcomes, but future studies should prioritize multi-center prospective designs with continuous temperature monitoring to define precise optimal ranges.</p>

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The impact of season, temperature, and direct normal irradiance on IVF pregnancy outcomes: a retrospective cohort study

  • 期刊论文

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  • 发表日期：

    2025年6月18日

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  • Chao Wang,
  • Jiehua Chen,
  • Zhong Lin,
  • Li Shi,
  • Qiuyan Ruan,
  • Jiamin Long,
  • Yanping Lao,
  • Xiangli Niu

摘要

Objective. This study assessed associations between season, temperature, direct normal irradiance (DNI), and clinical pregnancy outcomes in first fresh in vitro fertilization (IVF) cycle. Methods. We conducted a retrospective cohort study (June 2021-October 2023) of 1179 patients undergoing fresh IVF cycles. Inclusion criteria required age ≤ 45 years, first-time fresh embryo transfer cycles (long/antagonist protocol), excluding preimplantation genetic testing, frozen cycles, or incomplete data. Temperature and DNI were recorded from gonadotropin (Gn) initiation to oocyte retrieval. Binary logistic regression assessed seasonal impacts on clinical pregnancy, while restricted cubic splines (RCS) independently modeled temperature/DNI effects. Results. Compared to winter, clinical pregnancy likelihood was 1.74-fold higher in spring (95% CI:1.11–2.71, P = 0.015) and 1.53-fold in summer (95% CI:1.02–2.30, P = 0.042). Stratified analysis revealed a 2.02-fold increased likelihood in summer cycles using the long protocol (95% CI:1.07–3.82, P = 0.031), whereas no seasonal variation was observed in antagonist protocol. RCS regression analysis indicated a nonlinear relationship between temperature and clinical pregnancy outcomes, which was confirmed in the long protocol group. No significant correlations were observed with DNI or in patients treated with the antagonist protocol. Conclusions. Season and ambient temperature significantly impact IVF clinical pregnancy, especially in the long protocol, with the highest increase in pregnancy rates observed in summer, as well as within the 26.13℃ to 29.68℃ temperature range. No significant effects were observed with DNI or the antagonist protocol. These findings suggest that summer treatment may optimize IVF outcomes, but future studies should prioritize multi-center prospective designs with continuous temperature monitoring to define precise optimal ranges.