Department of Anesthesia, Critical Care and Emergency Medicine, College of Medicine and Health Sciences, University of Rwanda, Kigali, Rwanda.
University of Virginia, Charlottesville, USA.
BMC Pregnancy Childbirth. 2020 Sep 29;20(1):568. doi: 10.1186/s12884-020-03187-1.
Despite reaching Millennium Development Goal (MDG) 3, the maternal mortality rate (MMR) is still high in Rwanda. Most deaths occur after transfer of patients with obstetric complications from district hospitals (DHs) to referral hospitals; timely detection and management may improve these outcomes. The RI and MEOWS tool has been designed to predict morbidity and decrease delay of transfer. Our study aimed: 1) to determine if the use of the RI and MEOWS tool is feasible in DHs in Rwanda and 2) to determine the role of the RI and MEOWS tool in predicting morbidity.
A cross-sectional study enrolled parturient admitted to 4 district hospitals during the study period from April to July 2019. Data was collected on completeness rate (feasibility) to RI and MEOWS tool, and prediction of morbidity (hemorrhage, infection, and pre-eclampsia).
Among 478 RI and MEOWS forms used, 75.9% forms were fully completed suggesting adequate feasibility. In addition, the RI and MEOWS tool showed to predict morbidity with a sensitivity of 28.9%, a specificity of 93.5%, a PPV of 36.1%, a NPV of 91.1%, an accuracy of 86.2%, and a relative risk of 4.1 (95% Confidential Interval (CI), 2.4-7.1). When asked about challenges faced during use of the RI and MEOWS tool, most of the respondents reported that the tool was long, the staff to patient ratio was low, the English language was a barrier, and the printed forms were sometimes unavailable.
The RI and MEOWS tool is a feasible in the DHs of Rwanda. In addition, having moderate or high scores on the RI and MEOWS tool predict morbidity. After consideration of local context, this tool can be considered for scale up to other DHs in Rwanda or other low resources settings.
This is not a clinical trial rather a quality improvement project. It will be registered retrospectively.
尽管已经实现了千年发展目标 3，但卢旺达的孕产妇死亡率仍然很高。大多数死亡发生在将患有产科并发症的患者从地区医院（DH）转移到转诊医院后；及时发现和处理可能会改善这些结果。RI 和 MEOWS 工具旨在预测发病率并减少转移延误。我们的研究旨在：1）确定在卢旺达的 DH 使用 RI 和 MEOWS 工具是否可行，2）确定 RI 和 MEOWS 工具在预测发病率方面的作用。
一项横断面研究在 2019 年 4 月至 7 月期间纳入了 4 家地区医院收治的产妇。收集 RI 和 MEOWS 工具的完整性（可行性）以及发病率（出血、感染和子痫前期）预测的数据。
在使用的 478 份 RI 和 MEOWS 表格中，75.9%的表格完整填写，表明可行性良好。此外，RI 和 MEOWS 工具显示可以预测发病率，其敏感性为 28.9%，特异性为 93.5%，阳性预测值为 36.1%，阴性预测值为 91.1%，准确性为 86.2%，相对风险为 4.1（95%置信区间（CI），2.4-7.1）。当被问及在使用 RI 和 MEOWS 工具时面临的挑战时，大多数受访者表示该工具很长，医护人员与患者的比例低，英语是一个障碍，并且有时无法提供印刷表格。
RI 和 MEOWS 工具在卢旺达的 DH 中是可行的。此外，RI 和 MEOWS 工具的中等或高分预测发病率。在考虑到当地情况后，该工具可考虑在卢旺达或其他资源匮乏的地区的其他 DH 中推广使用。
这不是临床试验，而是一项质量改进项目。它将被追溯性注册。
