Evidence map›Paper›PMID 40269119›Full record

ArticleScientific reports2025

Time to death and its predictors among neonates admitted to the neonatal intensive care unit at Boru Meda General Hospital, Northeast Ethiopia.

Adane Baylie Awoke, Feleke Tilahun, Seid Hassen, Fentaw Bialfew, Assressie Molla, Abdulkerim Mengistu Yimam

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Adane Baylie AwokeBoru Meda General Hospital, P.O. Box 70, Dessie, Ethiopia. adanebaylie6@gmail.com.
Feleke TilahunBoru Meda General Hospital, P.O. Box 70, Dessie, Ethiopia.
Seid HassenBoru Meda General Hospital, P.O. Box 70, Dessie, Ethiopia.
Fentaw BialfewBoru Meda General Hospital, P.O. Box 70, Dessie, Ethiopia.
Assressie MollaDepartment of Epidemiology and Biostatistics, School of Public Health, College of Medicine and Health Science, Wollo University, Wollo, Ethiopia.
Abdulkerim Mengistu YimamAmhara Regional Health Bureau, Bahir Dar, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite all efforts made, neonatal mortality remains a serious public health concern in Ethiopia, particularly in the Amhara region. Identifying the hazard time to death and its predictors plays a crucial role in reducing neonatal mortality. Therefore, this study aimed to determine time to death and its predictors among neonates admitted in the neonatal intensive care unit at Boru Meda General Hospital, northeast Ethiopia, in 2023. This institution -based retrospective cohort study was conducted among 323 neonates in the neonatal intensive care unit at Boru Meda General Hospital from November 20, 2021, to January 30, 2023. The extracted data entered in to epi- info version 7.3, exported to, and analyzed using STATA version 14. Kaplan-Meier failure function and failure probability table computed. A Cox proportional hazard model fitted to identify predictors of time to neonatal death. The hazard ratio with a 95% confidence interval reported, and statistical significance declared at a p-value of ≤ 0.05. The Proportionality assumption tested using a global test based on Schoenfeld residual analysis. Among 323 neonates studied at Boru Meda General Hospital, 28 (8.7%) died. And the overall incidence of neonatal mortality was 12.6 (95% CI: 8.7, 18.2) per 1000 neonate-days with a median time to death of 6 days and a high proportion of premature neonatal deaths of 10 (14.5%), which makes the incidence rate of premature neonatal mortality 17.2 (95% CI: 9.2, 31.9) per 1000 neonate - days. In this study, almost (85.7%) of neonatal deaths occurred within one week of their lives. Hypothermia at admission (AHR: 2.89, CI: 1.12-7.3), respiratory distress (AHR: 2.8, CI: 1.04-7.4), and congenital anomalies (AHR: 5.9, CI: 1.2-28.7) were independent predictors of neonatal mortality. In our study, we found a high rate of early neonatal mortality. Level of body temperature at admissions, respiratory distress, and congenital anomalies were independent predictors of the time to death of neonates. Therefore, an intervention that focuses on the identified predictors had a significant impact to reduce neonatal mortality.

Indexed as

Infant MortalityIntensive Care Units, NeonatalEthiopiaFemaleHospitals, GeneralHumansInfantInfant, NewbornMaleProportional Hazards ModelsRetrospective StudiesRisk FactorsMorbidityMortalityNeonatal intensive care unitNeonatePredictorsTime to death

Identifiers

PMID40269119
PMCPMC12019600

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LicenceCC BY-NC-ND
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