Paul Animesh Kumar, Kalmady Sunil Vasu, Greiner Russell, Kaul Padma
Department of Computing Science, University of Alberta, Edmonton, AB Canada.
Alberta Machine Intelligence Institute, Edmonton, AB Canada.
NPJ Womens Health. 2025;3(1):43. doi: 10.1038/s44294-025-00093-9. Epub 2025 Jul 25.
Pregnant women are often excluded from randomized clinical trials due to safety concerns, yet the increasing prevalence of pre-existing conditions and pregnancy complications necessitates medication use. Observational cohort data can provide valuable insights to support clinical decision-making. We developed a web-based tool that presents population-level data on medication use and preterm birth risk. By integrating real-world evidence, this tool helps clinicians assess medication-related outcomes and improve maternal and neonatal health.
由于安全问题，孕妇通常被排除在随机临床试验之外，但既往疾病和妊娠并发症的患病率不断上升，使得用药成为必要。观察性队列数据可为临床决策提供有价值的见解。我们开发了一种基于网络的工具，该工具展示了药物使用和早产风险的人群水平数据。通过整合真实世界证据，该工具可帮助临床医生评估与药物相关的结果，并改善孕产妇和新生儿健康。
