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Optimizing IVF lab workflows through data-driven insights: associations between lab management, procedural timings, and workload with blastulation rates

工作量 工作流程 囊胚 计算机科学 生物 操作系统 数据库 生物化学 基因 原肠化 胚胎干细胞
作者
Federica Innocenti,Greta Chiara Cermisoni,Marilena Taggi,Valentina Casciani,Daria Soscia,Lisa Dovere,Marta Stoppa,L Albricci,Alberto Vaiarelli,Giovanni Coticchio,Roberta Maggiulli,Laura Rienzi,Danilo Cimadomo
出处
期刊:Human Reproduction [Oxford University Press]
卷期号:40 (11): 2101-2114 被引量:2
标识
DOI:10.1093/humrep/deaf164
摘要

STUDY QUESTION: Do IVF laboratory workflows influence the mean blastulation rate per cohort of inseminated metaphase II oocytes (m-BR)? SUMMARY ANSWER: Neither the total number of procedures nor the workload per operator affected m-BR; instead, each additional hour in the interval from ovulation trigger to oocyte denudation (range 36-44 h) was associated with a measurable decline, especially beyond the 40-h threshold. WHAT IS KNOWN ALREADY: Control of laboratory conditions and standardized protocols are essential for optimizing m-BR in IVF. While advancements in technology and culture systems have improved ART outcomes, the effect of laboratory managerial decisions and procedural timing on embryological outcomes remains unclear. Previous studies have suggested that factors, such as prolonged oocyte handling, suboptimal culture conditions, and organizational inefficiencies, may affect in vitro embryo development, but available data are still limited. STUDY DESIGN, SIZE, DURATION: This retrospective study analyzed 7986 ICSI cycles performed between 2015 and 2022 at a private IVF center. Data were automatically registered and then retrospectively extracted from an Electronic Witnessing System to evaluate workload distribution and procedural timings. The study aimed to assess whether variations in laboratory managerial decisions influence the m-BR. PARTICIPANTS/MATERIALS, SETTING, METHODS: The study included all patients undergoing ICSI with fresh own oocytes. Metrics under investigation included the number of daily procedures overall and per operator and procedural timings, such as the interval between ovulation trigger and oocyte denudation. Results were adjusted for confounders, including maternal age, male factor infertility, and culture conditions. Multivariate linear regression and generalized estimating equations were used to assess associations with m-BR, accounting for repeated measures in couples undergoing multiple retrievals. MAIN RESULTS AND THE ROLE OF CHANCE: The overall m-BR was 35.7 ± 28.1% with 79% of the cycles resulting in at least one blastocyst obtained. No significant association was found between daily workload and m-BR, indicating that the number of daily procedures did not impact laboratory performance. After adjusting for confounders (maternal age, sperm factor, incubation conditions, and culture medium type), only the timing between ovulation trigger and oocyte denudation emerged as critical. A consistent and significant decline in m-BR was observed with each additional hour of delay between 36- and 44-h post-trigger (unstandardized coefficient B: -1.6%, 95% CI: -2.1 to -1.1%). The time between oocyte retrieval and denudation (range: 2-6 h) showed a significant association with a lower chance to obtain at least one blastocyst in each ICSI cycle (adjusted OR: 0.91, 95% CI: 0.86-0.96, P < 0.001). LIMITATIONS, REASONS FOR CAUTION: This was a retrospective single-center study. While the findings are robust and relevant for high-volume IVF laboratories, they may not be directly generalizable to smaller clinics with different workflows or lower caseloads. Additionally, only ICSI cycles were included; further studies are needed to confirm the findings for conventional IVF in different settings and patient populations. WIDER IMPLICATIONS OF THE FINDINGS: These findings suggest that even large workloads can be managed without compromising IVF performance, provided that lab schedules and personnel are carefully coordinated to meet ideal timing requirements. In the future, artificial intelligence models may support these lab management activities by predicting workloads and helping maintain timely schedules. STUDY FUNDING/COMPETING INTEREST(S): No funding. The authors declare no conflict of interest related with the content of this study. TRIAL REGISTRATION NUMBER: N/A.
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