Evidence map›Paper›PMID 30602964›Full record

ArticleAfrican health sciences2018

Neonatal mortality at the neonatal unit: the situation at a teaching hospital in Ghana.

Benjamin Atta Owusu, Apiradee Lim, Nifatamah Makaje, Priscilla Wobil, Areeyuth SameAe

Abstract read
In one paragraph

Article in African health sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Benjamin Atta OwusuDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, Thailand.
Apiradee LimDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, Thailand.
Nifatamah MakajeDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, Thailand.
Priscilla WobilChild Health Directorate, Komfo Anokye Teaching Hospital, Kumasi, Ghana.
Areeyuth SameAeDepartment of Mathematics and Computer Science, Faculty of Science and Technology, Prince of Songkla University, Pattani, Thailand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe first 28 days of life- the neonatal period is the most vulnerable time for a child's survival. Globally, neonatal mortality has seen a downward trend in recent years. The main objective of this study was to determine the percentage of neonatal mortality and to provide information on factors associated with neonatal mortality at the neonatal unit of a tertiary health facility or teaching hospital.

methodsData of neonates admitted to the neonatal in-patient unit of the Komfo Anokye Teaching Hospital (KATH) in Ghana from January 2013 to May 2014 were analyzed. Logistic regression model was performed to assess the association between neonatal mortality and predictors.

resultsA total of 5,195 neonatal admissions were recorded. The overall percentage of neonatal mortality was 20.2%. Infants with very low birth weight, having 5-minute Apgar score lower than 4, newborns with pre-term delivery, being referred from other health facilities, and being diagnosed with respiratory distress and birth asphyxia had a higher percentage of neonatal mortality.

conclusionThe mortality at the neonatal in-patient unit at the Komfo Anokye Teaching Hospital in Ghana is very high. There is the need for continuous attention and interventions to help reduce the risk of mortality among neonates admitted to the facility.

Indexed as

Intensive Care Units, NeonatalApgar ScoreFemaleGhanaHospitals, TeachingHumansInfantInfant MortalityInfant, NewbornInpatientsMaleRetrospective StudiesKumasiLogistic regressionneonatal mortality

Identifiers

PMID30602964
PMCPMC6306982

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.