Suppr超能文献

利用电子病历估算 COVID-19 大流行期间妊娠和出生率的变化。

Use of Electronic Medical Records to Estimate Changes in Pregnancy and Birth Rates During the COVID-19 Pandemic.

机构信息

Department of Obstetrics and Gynecology, University of Michigan, Ann Arbor.

Department of Internal Medicine, University of Michigan, Ann Arbor.

出版信息

JAMA Netw Open. 2021 Jun 1;4(6):e2111621. doi: 10.1001/jamanetworkopen.2021.11621.

Abstract

IMPORTANCE

The influence of the COVID-19 pandemic on fertility rates has been suggested in the lay press and anticipated based on documented decreases in fertility and pregnancy rates during previous major societal and economic shifts. Anticipatory planning for birth rates is important for health care systems and government agencies to accurately estimate size of economy and model working and/or aging populations.

OBJECTIVE

To use projection modeling based on electronic health care records in a large US university medical center to estimate changes in pregnancy and birth rates prior to and after the COVID-19 pandemic societal lockdowns.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study included all pregnancy episodes within a single US academic health care system retrospectively from 2017 and modeled prospectively to 2021. Data were analyzed September 2021.

EXPOSURES

Pre- and post-COVID-19 pandemic societal shutdown measures.

MAIN OUTCOMES AND MEASURES

The primary outcome was number of new pregnancy episodes initiated within the health care system and use of those episodes to project birth volumes. Interrupted time series analysis was used to assess the degree to which COVID-19 societal changes may have factored into pregnancy episode volume. Potential reasons for the changes in volumes were compared with historical pregnancy volumes, including delays in starting prenatal care, interruptions in reproductive endocrinology and infertility services, and preterm birth rates.

RESULTS

This cohort study documented a steadily increasing number of pregnancy episodes over the study period, from 4100 pregnancies in 2017 to 4620 in 2020 (28 284 total pregnancies; median maternal [interquartile range] age, 30 [27-34] years; 18 728 [66.2%] White women, 3794 [13.4%] Black women; 2177 [7.7%] Asian women). A 14% reduction in pregnancy episode initiation was observed after the societal shutdown of the COVID-19 pandemic (risk ratio, 0.86; 95% CI, 0.79-0.92; P < .001). This decrease appeared to be due to a decrease in conceptions that followed the March 15 mandated COVID-19 pandemic societal shutdown. Prospective modeling of pregnancies currently suggests that a birth volume surge can be anticipated in summer 2021.

CONCLUSIONS AND RELEVANCE

This cohort study using electronic medical record surveillance found an initial decline in births associated with the COVID-19 pandemic societal changes and an anticipated increase in birth volume. Future studies can further explore how pregnancy episode volume changes can be monitored and birth rates projected in real-time during major societal events.

摘要

重要性

在大众媒体和基于先前生育和怀孕率下降的记录的基础上,都提出了 COVID-19 大流行对生育率的影响。出生率的预期规划对于医疗保健系统和政府机构来说非常重要,因为这可以准确地估计经济规模并模拟工作和/或老龄化人口。

目的

使用大型美国大学医疗中心的电子医疗记录进行预测建模,以估算 COVID-19 大流行社会封锁前后的怀孕和出生率变化。

设计、地点和参与者: 本队列研究回顾性地纳入了一个单一的美国学术医疗系统中的所有妊娠事件,从 2017 年开始进行前瞻性建模,至 2021 年。数据分析于 2021 年 9 月进行。

暴露

COVID-19 大流行前和大流行后社会关闭措施。

主要结果和测量

主要结果是医疗系统内新妊娠事件的数量以及使用这些事件预测分娩量。中断时间序列分析用于评估 COVID-19 社会变化对妊娠事件数量的影响程度。与历史妊娠量相比,比较了导致这些变化的潜在原因,包括产前护理开始时间延迟、生殖内分泌和不孕服务中断以及早产率。

结果

本队列研究记录了研究期间妊娠事件数量的稳步增加,从 2017 年的 4100 例妊娠增加到 2020 年的 4620 例(总妊娠 28428 例;产妇中位数[四分位数范围]年龄,30 [27-34] 岁;18728 例[66.2%]为白人女性,3794 例[13.4%]为黑人女性;2177 例[7.7%]为亚裔女性)。COVID-19 大流行后,妊娠事件的启动减少了 14%(风险比,0.86;95%CI,0.79-0.92;P < .001)。这似乎是由于 3 月 15 日强制 COVID-19 大流行社会关闭后受孕减少所致。对目前妊娠的前瞻性建模表明,预计 2021 年夏季将迎来生育高峰期。

结论和相关性

本队列研究使用电子病历监测发现,与 COVID-19 大流行社会变化相关的生育初降,以及预期的生育量增加。未来的研究可以进一步探讨如何在重大社会事件期间实时监测妊娠事件数量的变化并预测出生率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c20f/8176329/e5939bc33691/jamanetwopen-e2111621-g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验