PDF(Pubmed)
Abstract：
UNASSIGNED: Neonatal deaths are still a major leading cause of social and economic crises. Identifying neonatal near-miss events and identifying their predictors is crucial to developing comprehensive and pertinent strategies to alleviate neonatal morbidity and death. However, neither neonatal near-miss events nor their predictors were analyzed in the study area. Therefore, this study is aimed at assessing the predictors of neonatal near-misses among neonates born at Worabe Comprehensive Specialized Hospital, Southern Ethiopia, in 2021.
UNASSIGNED: A hospital-based unmatched case-control study was conducted from 10 November 2021 to 30 November 2021. A pre-tested, structured, and standard abstraction checklist was used to collect the data. After checking the data for completeness and consistency, it was coded and entered into Epi-Data 3.1 and then exported to Stata version 14 for analysis. All independent variables with a p-value ≤0.25 in bivariable binary logistic regression were entered into a multivariable analysis to control the confounding. Variables with p-values <0.05 were considered statistically significant.
UNASSIGNED: In this study, 134 neonatal near-miss cases and 268 controls were involved. The identified predictors of neonatal near-misses were rural residence [adjusted odds ratio (AOR): 2.01; 95% confidence interval (CI): 1.31-5.84], no antenatal care (ANC) follow-up visits (AOR: 2.98; 95% CI: 1.77-5.56), antepartum hemorrhage (AOR: 2.12; 95% CI: 1.18-4.07), premature rupture of the membrane (AOR: 2.55; 95% CI: 1.54-5.67), and non-vertex fetal presentation (AOR: 3.05; 95% CI: 1.93-5.42).
UNASSIGNED: The current study identified rural residents, no ANC visits, antepartum hemorrhage, premature rupture of membrane, and non-vertex fetal presentation as being significantly associated with neonatal near-miss cases. As a result, local health planners and healthcare practitioners must collaborate in enhancing maternal healthcare services, focusing specifically on the early identification of issues and appropriate treatment.
UNASSIGNED: A hospital-based unmatched case-control study was conducted from 10 November 2021 to 30 November 2021. A pre-tested, structured, and standard abstraction checklist was used to collect the data. After checking the data for completeness and consistency, it was coded and entered into Epi-Data 3.1 and then exported to Stata version 14 for analysis. All independent variables with a p-value ≤0.25 in bivariable binary logistic regression were entered into a multivariable analysis to control the confounding. Variables with p-values <0.05 were considered statistically significant.
UNASSIGNED: In this study, 134 neonatal near-miss cases and 268 controls were involved. The identified predictors of neonatal near-misses were rural residence [adjusted odds ratio (AOR): 2.01; 95% confidence interval (CI): 1.31-5.84], no antenatal care (ANC) follow-up visits (AOR: 2.98; 95% CI: 1.77-5.56), antepartum hemorrhage (AOR: 2.12; 95% CI: 1.18-4.07), premature rupture of the membrane (AOR: 2.55; 95% CI: 1.54-5.67), and non-vertex fetal presentation (AOR: 3.05; 95% CI: 1.93-5.42).
UNASSIGNED: The current study identified rural residents, no ANC visits, antepartum hemorrhage, premature rupture of membrane, and non-vertex fetal presentation as being significantly associated with neonatal near-miss cases. As a result, local health planners and healthcare practitioners must collaborate in enhancing maternal healthcare services, focusing specifically on the early identification of issues and appropriate treatment.
摘要：
新生儿死亡仍然是社会和经济危机的主要主要原因。识别新生儿未遂事件并确定其预测因素对于制定全面和相关的策略以减轻新生儿发病率和死亡至关重要。然而,在研究区域中,未对新生儿未遂事件及其预测因素进行分析.因此,这项研究旨在评估在Worabe综合专科医院出生的新生儿中新生儿未遂的预测因素，埃塞俄比亚南部,2021年。
■一项基于医院的无匹配病例对照研究于2021年11月10日至2021年11月30日进行。一个预先测试，结构化，和标准的抽象清单被用来收集数据。在检查数据的完整性和一致性之后，它被编码并输入到Epi-Data3.1中，然后导出到Stata版本14进行分析。将双变量二元逻辑回归中p值≤0.25的所有自变量输入多变量分析以控制混杂。P值<0.05的变量被认为是统计学上显著的。
■在这项研究中，134例新生儿未遂病例和268例对照。确定的新生儿险些的预测因素是农村居住地[调整后的优势比（AOR）：2.01；95％置信区间（CI）：1.31-5.84]，没有产前护理（ANC）随访（AOR：2.98；95％CI：1.77-5.56），产前出血（AOR：2.12;95％CI：1.18-4.07），胎膜早破(AOR:2.55;95%CI:1.54-5.67),和非顶点胎儿表现(AOR:3.05;95%CI:1.93-5.42)。
■当前的研究确定了农村居民，没有ANC访问,产前出血,胎膜早破,非顶点胎儿表现与新生儿近漏诊病例显著相关。因此,当地卫生规划师和保健从业人员必须合作加强孕产妇保健服务，特别关注问题的早期识别和适当的治疗。
■一项基于医院的无匹配病例对照研究于2021年11月10日至2021年11月30日进行。一个预先测试，结构化，和标准的抽象清单被用来收集数据。在检查数据的完整性和一致性之后，它被编码并输入到Epi-Data3.1中，然后导出到Stata版本14进行分析。将双变量二元逻辑回归中p值≤0.25的所有自变量输入多变量分析以控制混杂。P值<0.05的变量被认为是统计学上显著的。
■在这项研究中，134例新生儿未遂病例和268例对照。确定的新生儿险些的预测因素是农村居住地[调整后的优势比（AOR）：2.01；95％置信区间（CI）：1.31-5.84]，没有产前护理（ANC）随访（AOR：2.98；95％CI：1.77-5.56），产前出血（AOR：2.12;95％CI：1.18-4.07），胎膜早破(AOR:2.55;95%CI:1.54-5.67),和非顶点胎儿表现(AOR:3.05;95%CI:1.93-5.42)。
■当前的研究确定了农村居民，没有ANC访问,产前出血,胎膜早破,非顶点胎儿表现与新生儿近漏诊病例显著相关。因此,当地卫生规划师和保健从业人员必须合作加强孕产妇保健服务，特别关注问题的早期识别和适当的治疗。
