ArticleThe Pan African medical journal2019
Prescribing patterns of antimicrobials in the Internal Medicine Department of Ibrahim Malik Teaching Hospital in Khartoum, 2016.
Article in The Pan African medical journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed, 9 citations in OpenAlex.
- Bacteriological profile and antibiotic susceptibility of diabetic Foot infections at Ribat University hospital; a retrospective study from Sudan.Journal of diabetes and metabolic disorders · 2020Article
- Assessment of drug utilization pattern of antimicrobial agents in hospitalized patients with Infectious Diseases: A cross-sectional study in the United Arab Emirates.Journal of advanced pharmaceutical technology & researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAntimicrobials are among the most commonly prescribed therapeutic agents in hospitals. Irrational use of antimicrobials results in the development of antimicrobial resistance which could lead to life-threatening illnesses. Therefore, the assessment of antimicrobial prescribing and use is of utmost importance. This study aimed to examine the prescribing patterns of antimicrobials in the Internal Medicine Department of Ibrahim Malik Teaching Hospital in Khartoum, Sudan.
methodsA descriptive, cross-sectional study was conducted using World Health Organization (WHO) indicators for antimicrobial use in hospitals. Systematic random sampling was used to select 245 medical records from the 2613 medical records of patients admitted to the internal medicine department in 2016. Data were collected using a data collection form and a structured interview with the chief pharmacist in the hospital.
resultsOf the 245 medical records examined, 201 (82%) patients were prescribed one or more antimicrobial drug. The average number of antimicrobials per patient was (2.1±1.1). The average duration of antimicrobial treatment was (4.9±3.8) days. The generic name was used in (35.6%) of antimicrobials, while (95.5%) of all antimicrobials were prescribed from the national essential medicines list. Overall, there were 421 courses of antimicrobials prescribed. The most frequently prescribed antimicrobials were ceftriaxone (131 courses) and metronidazole (89 courses). Among the documented infectious diseases, the most frequently encountered was pneumonia, followed by malaria. There was no drug and therapeutic committee, hospital formulary or essential medicines list, and standard treatment guidelines for infectious diseases in the hospital.
conclusionThe results of the study revealed a high percentage of antimicrobial use in the Internal Medicine Department. Multifaceted interventions are urgently needed to promote rational prescribing of antimicrobials.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.