Evidence map›Paper›PMID 32614832›Full record

ArticlePloS one2020

Antibiotic consumption study in two hospitals in Asmara from 2014 to 2018 using WHO's defined daily dose (DDD) methodology.

Nebyu Daniel Amaha, Dawit G Weldemariam, Yohana H Berhe

Abstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

15 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  14. Inpatient antibacterial use trends and patterns, China, 2013-2021.Bulletin of the World Health Organization · 2023
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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

3 authors.

Nebyu Daniel AmahaDepartment of Nutrition and Dietetics, College of Health Sciences, Mekelle University, Mekelle, Ethiopia.ORCID 0000-0001-5900-5939
Dawit G WeldemariamDepartment of Pharmacy, Hazhaz Hospital, Asmara, Eritrea.ORCID 0000-0001-7179-4993
Yohana H BerhePharmacy, Addis Ababa, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study compares the antibiotic consumption rates over a period of five years in two hospitals in Eritrea, Orotta National Referral and Teaching Hospital (ONRTH) and Hazhaz Zonal Referral Hospital (HZRH). Antibiotic consumption is an important parameter in the study of antibiotic use. However, no published data on consumption rates exist for these two hospitals, thus the aim of the study is to measure and compare a five year antibiotic consumption trends of the two hospitals' medical wards using Defined Daily Dose per 100 bed-days (DDD/100-BD). Antibiotics dispensed from January 2014 to December 2018 were considered. Non-parametric Pearson's correlation coefficient was used for comparison of consumption, while non-parametric Friedman's test measured annual rates. The total antibiotic consumption in the HZRH was almost double that of ONRTH. The analysis showed that antibiotic consumption in ONRTH was significantly decreased from 2014 to 2018 while there was no significant difference in consumption in HZRH. Benzyl penicillin was the most consumed antibiotic in HZRH and ONRTH throughout the study period at 87.8DDD/100-BD and 35.4 DDD/100-BD respectively. Ceftriaxone and ciprofloxacin were among the most commonly consumed antibiotics in both hospitals. Establishment of Antibiotic stewardship program would benefit both hospitals greatly, and further studies need to be done to establish the national antibiotic consumption baseline.

Indexed as

Practice Guidelines as TopicWorld Health OrganizationAntimicrobial StewardshipEritreaHospitalsHumans

Identifiers

PMID32614832
PMCPMC7332034

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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.