Correlation between biometeorological forecast and the incidence of obstetric admissions in perinatal center during five years: A retrospective study of one center

Pub Date : 2023-05-05 DOI:10.18054/pb.v124i3-4.23435
Analena Robić, D. Habek, M. Prka, Egon Kruezi, D. Plačko-Vršnak, L. Srnec
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Abstract

Background and purpose: The aim of this study was to correlate obstetric admissions at a tertiary perinatal center with biometeorological forecast and weather conditions. Materials and methods: This retrospective study was conducted at the Department of Gynaecology and Obstetrics Clinical Hospital “Sveti Duh” over five years, from January 1, 2014 to December 31, 2018. The hospital’s emergency data was used for record of obstetric admissions on each day. The selected days were sorted in 4 groups based on biometeorological forecast. Results: In the observed period, there were a total of 18,072 obstetric admissions. There were 216 days with fifteen or more admissions. The results showed no significant difference between obstetric admission based on the biometeorological forecast one day before or three days before. Most hospitalization were on days with a favorable biometeorological forecast in the observed period, 68 days with more than fifteen admissions per day. The day before, the biometeorological forecast was mostly favorable or relatively favorable. Conclusion: Our retrospective single-center study did not show a significant difference between obstetric hospital admissions depending on biometeorological conditions, but the higher number of admissions during days with a favorable forecast is definitely the basis for future studies with larger dataset.
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五年间生物气象预报与围产期中心产科住院发生率的相关性:一项对某中心的回顾性研究
背景和目的:本研究的目的是将三级围产中心的产科入院与生物气象预报和天气条件联系起来。材料与方法:本回顾性研究于2014年1月1日至2018年12月31日在Sveti Duh妇产科临床医院进行,为期5年。医院的急诊数据被用于记录每天的产科入院情况。根据生物气象预报将选取的日数分为4组。结果:在观察期内,共有18072名产科住院患者。有216天有15人或更多的人入院。结果显示,根据生物气象预报1天前和3天前的产科入院无显著差异。大部分住院病例发生在观测期内生物气象预报良好的天数,68天,每天住院人数超过15人。前一天的生物气象预报基本有利或相对有利。结论:我们的回顾性单中心研究并未显示产科住院人数因生物气象条件而有显著差异,但在预报良好的天数内住院人数的增加无疑是未来更大数据集研究的基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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