Time to Death and Its Predictors among Neonates Hospitalized with Sepsis in Eastern Ethiopia

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
Usmael Jibro, Assefa Desalew, Galana Mamo Ayana, Abera Kenay Tura
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The Kaplan-Meier curves and log-rank tests were used to describe survival experience among different categories. The proportional hazard assumption and goodness of fit for the Cox regression model were checked. The Cox regression model was used to identify the significant predictors. Hazard ratios (HRs) with 95% confidence intervals (CI) were calculated. Finally, statistical significance was set at a <svg height=\"10.2124pt\" style=\"vertical-align:-3.42943pt\" version=\"1.1\" viewbox=\"-0.0498162 -6.78297 7.83752 10.2124\" width=\"7.83752pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\"><g transform=\"matrix(.013,0,0,-0.013,0,0)\"></path></g></svg> value &lt; 0.05 in the Cox regression analysis. <i>Results</i>. Of the 415 neonates with neonatal sepsis, 71 (17.1%) (95% CI: 13.60-21.08) died at discharge, with a median time to death of 14 days. The overall incidence rate of mortality was 36.5 per 1000 neonate days. 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引用次数: 0

Abstract

Background. Although neonatal sepsis is a major public health problem contributing to 30-50% of neonatal deaths in low- and middle-income countries, data on predictors of time to death are limited in Eastern Ethiopia. This study is aimed at determining predictors of time to death among neonates with sepsis admitted in public hospitals in Eastern Ethiopia. Methods. An institutional-based retrospective cohort study was conducted among 415 neonates admitted to referral hospitals in Eastern Ethiopia with sepsis from January 1, 2021, to December 31, 2021. Data were collected from medical records by using structured checklist and entered using EpiData 3.1 and analyzed using Stata 17. The Kaplan-Meier curves and log-rank tests were used to describe survival experience among different categories. The proportional hazard assumption and goodness of fit for the Cox regression model were checked. The Cox regression model was used to identify the significant predictors. Hazard ratios (HRs) with 95% confidence intervals (CI) were calculated. Finally, statistical significance was set at a value < 0.05 in the Cox regression analysis. Results. Of the 415 neonates with neonatal sepsis, 71 (17.1%) (95% CI: 13.60-21.08) died at discharge, with a median time to death of 14 days. The overall incidence rate of mortality was 36.5 per 1000 neonate days. Low birthweight (; 95% CI: 1.15-5.44), maternal years (; 95% CI: 1.11, 9.04), low fifth-minute Apgar score (AHR: 2.32; 95% CI: 1.30-4.14), and late initiation of breastfeeding (; 95% CI: 1.40-16.65) were independent predictors of mortality among neonates with sepsis. Conclusions. Almost one in five neonates with sepsis died at discharge. Low birthweight, maternal years, low fifth-minute Apgar score, and late initiation of breastfeeding were predictors of mortality.
埃塞俄比亚东部因败血症住院的新生儿死亡时间及其预测因素
背景。虽然新生儿败血症是一个主要的公共卫生问题,在低收入和中等收入国家造成 30-50% 的新生儿死亡,但在埃塞俄比亚东部,有关死亡时间预测因素的数据却很有限。本研究旨在确定埃塞俄比亚东部公立医院收治的败血症新生儿死亡时间的预测因素。研究方法在 2021 年 1 月 1 日至 2021 年 12 月 31 日期间,对埃塞俄比亚东部转诊医院收治的 415 名患有败血症的新生儿进行了一项基于机构的回顾性队列研究。研究人员使用结构化核对表从病历中收集数据,并使用 EpiData 3.1 进行输入,然后使用 Stata 17 进行分析。采用卡普兰-梅耶曲线和对数秩检验来描述不同类别患者的生存情况。检查了比例危险假设和 Cox 回归模型的拟合度。Cox 回归模型用于确定重要的预测因素。计算出危险比(HRs)和 95% 置信区间(CI)。最后,Cox 回归分析的统计显著性设定为 <0.05。结果在415名患有新生儿败血症的新生儿中,有71人(17.1%)(95% CI:13.60-21.08)在出院时死亡,中位死亡时间为14天。总死亡率为每 1000 个新生儿日 36.5 例。低出生体重(95% CI:1.15-5.44)、孕产妇年龄(95% CI:1.11, 9.04)、低第五分钟阿普加评分(AHR:2.32;95% CI:1.30-4.14)和晚开始母乳喂养(95% CI:1.40-16.65)是预测败血症新生儿死亡率的独立因素。结论几乎五分之一的败血症新生儿在出院时死亡。低出生体重、孕产妇年龄、低第五分钟阿普加评分和较晚开始母乳喂养是预测死亡率的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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