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Copyright of Universidad Médica Pinareña is the property of Editorial Ciencias Medicas and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: maternal death is a problem of global importance, a very important public health problem that has generated a great socioeconomic impact in Ecuador. Objective: to describe maternal mortality in the province of Imbabura in the period 2017-2021. Methods: a study without intervention, observational and descriptive was carried out. The population was made up of the 42 pregnant women who died in the period 2017-2021 from the province of Imbabura in Ecuador. For data collection, we worked with the Maternal Death Epidemiological Gazettes for the years 2017 to 2021. The following variables were analyzed: number of maternal deaths by canton and causes of maternal mortality. To determine the causes of maternal mortality, the diagnoses defined by ICD 10 were taken into account: hypertensive disorders in pregnancy, bleeding during pregnancy or childbirth, pregnancy, childbirth and puerperium infection, abortion, complications during labor and delivery. childbirth, ectopic pregnancy, puerperal sepsis, obstetric embolism, deaths from unspecified causes, among others Results: during 2017 the highest number of maternal deaths occurred, it was 20. In the years 2018 and 2019 there were only 8 and 3 deaths, respectively. During 2020 the number increased up to 10 and in 2021 only one maternal death was reported. The main causes of maternal death were: other maternal diseases that complicate pregnancy, any obstetric cause, gestational hypertension and postpartum hemorrhage. Conclusions: adequate follow-up during pregnancy, childbirth and the puerperium is vital to reduce maternal deaths. [ABSTRACT FROM AUTHOR]

Copyright of Neutrosophic Computing & Machine Learning is the property of Multimedia Larga and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)