Evidence map›Paper›PMID 39527601›Full record

ArticlePloS one2024

Bacterial profile and antimicrobial susceptibility patterns of isolates from inanimate objects used by healthcare professionals at Debre Markos Comprehensive Specialized Hospital, Northwest Ethiopia.

Senedu Kindie, Getachew Mengistu, Mulatu Kassahun, Abebaw Admasu, Tebelay Dilnessa

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Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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3citing 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

Who cites it

3 citing papers in PubMed.

  1. Search for Potentially VirulentInternational journal of molecular sciences · 2026
    Article
  2. Article
  3. EnteroaggregativeFrontiers in microbiology · 2025
    Article
4 · The record

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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.

Senedu KindieDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Debre Markos University, Debre Markos, Ethiopia.
Getachew MengistuDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Debre Markos University, Debre Markos, Ethiopia.ORCID 0000-0002-3556-3650
Mulatu KassahunStudents' Clinic Burie Campus, Debre Markos University, Burie, Ethiopia.ORCID 0009-0005-2973-8142
Abebaw AdmasuDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Debre Markos University, Debre Markos, Ethiopia.
Tebelay DilnessaDepartment of Medical Laboratory Sciences, College of Medicine and Health Sciences, Debre Markos University, Debre Markos, Ethiopia.ORCID 0000-0002-3713-6783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthcare-associated infections occur in patients under medical care, which is a major public health issue in hospitals worldwide. The prevalence is two to three folds higher in developing countries compared to developed countries. Inanimate objects used by healthcare professionals such as gowns, mobile phones, and stethoscopes are highly prone to bacterial contamination from the healthcare setting. In Ethiopia, there is a paucity of published data on the bacterial profile and susceptibility patterns of an isolates.

objectiveTo determine the bacterial profile and antimicrobial susceptibility patterns from inanimate objects used by healthcare professionals and associated factors at Debre Markos Comprehensive Specialized Hospital, Northwest Ethiopia.

methodsA cross-sectional study was conducted at Debre Markos Comprehensive Specialized Hospital from inanimate objects from April 10, 2023 to June 30, 2023 using simple random sampling technique with lottery method. Socio-demographic data was collected using a structured questionnaire. A swab sample from healthcare professionals' gowns, mobile phones, and stethoscopes were collected and inoculated onto blood agar, chocolate and MacConkey agar. Isolates were identified and characterized by colony morphology, Gram staining and biochemical tests. Antimicrobial susceptibility testing was performed in all isolates by the disk diffusion technique on Muller Hinton agar according to CLSI, 2022 guidelines. Data was entered into EPI-Data and analyzed using SPSS version 25. Logistic regression model was used. Variables with p-value ≤ 0.25 in bivariable logistic regression was fitted to multivariate logistic regression analysis. A p-value of ≤ 0.05 with 95%CI was considered statistically significant.

resultA total of 376 healthcare professionals' inanimate objects were included from 191 study participants. Overall, 60.1% (226/376) (95%CI: 55.1-65) inanimate objects were contaminated. The proportion of bacterial contamination was (65.1%; 82/126), (60.3%; 76/126) and (54.8%; 68/124) for mobile phones, gowns and stethoscopes, respectively. Staphylococcus aureus was the most frequent isolate accounting (22.1%; 83/376) followed by Staphylococcus epidermidis (17.0%; 64/376), Escherichia coli (8.8%; 33/376) and Pseudomonas aeruginosa (4.9%; 18/376). Working in gynecology/ obstetrics wards (AOR: 8.69; 95%CI: 1.09-69.41, P = 0.041), did not disinfect mobile phones (AOR: 2.69; 95%CI: 1.15-6.25; P = 0.021) and stethoscopes regularly (AOR: 3.06, 95%CI: 1.23-7.59; P = 0.016), carry mobile phones with patient care materials (AOR: 2.72; 95%CI: 1.18-6.29, P = 0.019) and not taken infection prevention training (AOR:3.91; 95%CI:1.71-8.93; P = 0.001) were significantly associated with bacterial contamination.Most Gram-negative bacteria were resistant to ampicillin, trimethoprim-sulfamethoxazole and amoxacilline-clavunic acid, while Gram-positive isolates showed high level of resistant to penicillin. On the other hand, meropenem, for Gram-negative and clindamycin for Gram-positive bacteria showed lower level of resistance. Multidrug resistance among Gram-positive and Gram-negative bacteria were (62.6%; 92/147) and (75.3%; 64/85), respectively with over all MDR (67.2%, 156/232).

conclusionInanimate objects commonly used by healthcare professionals are important sources of bacterial contamination. S. aureus, S. epidermidis and E. coli were the predominant isolates. Most Gram-negative bacteria were resistant to ampicillin while Gram-positive isolates showed high level of resistant to penicillin. All healthcare professionals should regularly disinfect their inanimate objects to prevent bacterial colonization and potential spread of infection.

Indexed as

BacteriaCell PhoneEquipment ContaminationMicrobial Sensitivity TestsStethoscopesSurgical AttireAnti-Bacterial AgentsCross InfectionCross-Sectional StudiesEthiopiaHospitals, SpecialHumansLogistic ModelsMedical Staff, HospitalSurveys and QuestionnairesAnti-Bacterial Agents

Identifiers

PMID39527601
PMCPMC11554123

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LicenceCC BY
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Registered trials

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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.