Evidence map›Paper›PMID 42238213›Full record

ArticleSaudi medical journal2026

Prevalence and Antimicrobial Susceptibility Patterns of Nosocomial Bacteria across Different Units at King Faisal Complex Hospital, Taif, Kingdom of Saudi Arabia.

Nahed Hawsawi, Renad N Al-Jaiud, Layal L Khyyat, Kholoud Alsulimany, Manhal Shabat

Abstract read
In one paragraph

Article in Saudi medical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Nahed HawsawiDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif, Kingdom of Saudi Arabia.
Renad N Al-JaiudDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif, Kingdom of Saudi Arabia.
Layal L KhyyatDepartment of Clinical Laboratory Sciences, College of Applied Medical Sciences, Taif University, Taif, Kingdom of Saudi Arabia.
Kholoud AlsulimanyDepartment of Microbiology, King Faisal Medical Complex, Taif, Kingdom of Saudi Arabia.
Manhal ShabatDepartment of Microbiology, King Faisal Medical Complex, Taif, Kingdom of Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: Nosocomial infections significantly impact patient morbidity, mortality, and healthcare costs. To determine the prevalence, bacteriological profiles, antimicrobial susceptibility patterns, and resistance distribution of pathogens causing nosocomial infections at King Faisal Medical Complex, Taif, Kingdom of Saudi Arabia. Methods: This cross-sectional study was conducted between September 2023 and March 2024 at different hospital units following ethical approval. Samples (n = 667) were collected from patients (both genders; all ages) exhibiting infection symptoms ≥48 h post-admission and pre-antibiotic administration. Bacterial identification involved culture, Gram staining, and biochemical tests. Antimicrobial susceptibility was tested using the Phoenix100 system. Results: Of 667 patients, 55% were men/boys, and 45% were aged 14-59 years. The highest infection rate was noted in the intensive care unit (26%), followed by the male surgical (19%) and medical wards (14%). The female surgical ward (10%) had the lowest infection rate. The most common sample sources were urine (28%), blood (17%), wound and sputum (16%), and swabs (15%). Gram-negative bacteria (mainly Conclusion: Our results highlight the prevalence of nosocomial infections in different hospital units, with

Indexed as

Anti-Bacterial AgentsCross InfectionAdolescentAdultAgedCross-Sectional StudiesFemaleHumansMaleMicrobial Sensitivity TestsMiddle AgedPrevalenceSaudi ArabiaYoung AdultAnti-Bacterial AgentsAntimicrobial resistanceHospital-acquired infectionsIntensive care unitMultidrug resistanceNosocomial infectionsSurgical site infections

Identifiers

PMID42238213
PMCPMC13217625

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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.