在用药量不断增加的情况下加快不良妊娠结局研究:通过平行回顾性队列分析确定信号的优先次序。

IF 7 1区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Yeon Mi Hwang, Samantha N Piekos, Alison G Paquette, Qi Wei, Nathan D Price, Leroy Hood, Jennifer J Hadlock
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引用次数: 0

摘要

背景:孕妇在临床试验中的比例明显偏低,尽管安全性数据有限,但她们中的大多数人都在孕期服用药物。本研究的目的是描述孕期用药的特点,并在患者记录中大规模应用倾向得分匹配法,以加速并优先发现与早产和其他不良妊娠结局风险相关的药物效应信号:这是一项回顾性研究,研究对象是普罗维登斯圣约瑟夫医疗中心在 2013/01/01 至 2022/12/31 期间连续注册的活产妇女(n = 365,075 人)。我们关注的暴露是孕期开具的所有门诊药物。我们的分析仅限于符合最小样本量(n = 600)的药物。我们关注的主要结果是早产。次要结果是胎龄小和出生体重低。在对人口统计学、妊娠特征和合并症进行调整后,我们采用倾向得分匹配法来评估这些不良妊娠结局与药物暴露相关的风险:结果:总的药物处方率从 58.5% 增加到 75.3%(P 结论:大多数孕妇在怀孕期间都会服用药物:大多数孕妇在怀孕期间都会被处方药物。这凸显了利用现有真实世界数据来提高我们对孕期用药安全性的认识的必要性。通过倾向得分匹配,我们将与早产风险有显著统计学关联的药物从 1329 种减少到 58 种。这种以数据为导向的方法表明,妊娠药理学中的多个可检验假设可以按规模进行优先排序,并为应用于其他妊娠结局奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Accelerating adverse pregnancy outcomes research amidst rising medication use: parallel retrospective cohort analyses for signal prioritization.

Background: Pregnant women are significantly underrepresented in clinical trials, yet most of them take medication during pregnancy despite the limited safety data. The objective of this study was to characterize medication use during pregnancy and apply propensity score matching method at scale on patient records to accelerate and prioritize the drug effect signal detection associated with the risk of preterm birth and other adverse pregnancy outcomes.

Methods: This was a retrospective study on continuously enrolled women who delivered live births between 2013/01/01 and 2022/12/31 (n = 365,075) at Providence St. Joseph Health. Our exposures of interest were all outpatient medications prescribed during pregnancy. We limited our analyses to medication that met the minimal sample size (n = 600). The primary outcome of interest was preterm birth. Secondary outcomes of interest were small for gestational age and low birth weight. We used propensity score matching at scale to evaluate the risk of these adverse pregnancy outcomes associated with drug exposure after adjusting for demographics, pregnancy characteristics, and comorbidities.

Results: The total medication prescription rate increased from 58.5 to 75.3% (P < 0.0001) from 2013 to 2022. The prevalence rate of preterm birth was 7.7%. One hundred seventy-five out of 1329 prenatally prescribed outpatient medications met the minimum sample size. We identified 58 medications statistically significantly associated with the risk of preterm birth (P ≤ 0.1; decreased: 12, increased: 46).

Conclusions: Most pregnant women are prescribed medication during pregnancy. This highlights the need to utilize existing real-world data to enhance our knowledge of the safety of medications in pregnancy. We narrowed down from 1329 to 58 medications that showed statistically significant association with the risk of preterm birth even after addressing numerous covariates through propensity score matching. This data-driven approach demonstrated that multiple testable hypotheses in pregnancy pharmacology can be prioritized at scale and lays the foundation for application in other pregnancy outcomes.

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来源期刊
BMC Medicine
BMC Medicine 医学-医学:内科
CiteScore
13.10
自引率
1.10%
发文量
435
审稿时长
4-8 weeks
期刊介绍: BMC Medicine is an open access, transparent peer-reviewed general medical journal. It is the flagship journal of the BMC series and publishes outstanding and influential research in various areas including clinical practice, translational medicine, medical and health advances, public health, global health, policy, and general topics of interest to the biomedical and sociomedical professional communities. In addition to research articles, the journal also publishes stimulating debates, reviews, unique forum articles, and concise tutorials. All articles published in BMC Medicine are included in various databases such as Biological Abstracts, BIOSIS, CAS, Citebase, Current contents, DOAJ, Embase, MEDLINE, PubMed, Science Citation Index Expanded, OAIster, SCImago, Scopus, SOCOLAR, and Zetoc.
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