Evidence map›Paper›PMID 42021854›Full record

ArticleInfection and drug resistance2026

Epidemiology of Urinary Pathogens and Antibiotic Resistance Trends: A Retrospective Analysis Stratified by Age and Sex from a Large Tertiary Hospital in Saudi Arabia.

Alyaa M Ajabnoor, Abrar K Thabit, Ohood S Alharbi, Karem Ibrahem, Turki Asiri, Abdulrahman M Al-Ghamdi, Rakan F Felemban

Abstract read
In one paragraph

Article in Infection and drug resistance, 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

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

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

7 authors.

Alyaa M AjabnoorDepartment of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID 0000-0001-5154-6183
Abrar K ThabitDepartment of Pharmacy Practice, Faculty of Pharmacy, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID 0000-0002-0369-9094
Ohood S AlharbiDepartment of Microbiology and Parasitology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.ORCID 0000-0002-8720-5054
Karem IbrahemDepartment of Clinical Microbiology and Immunology, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID 0009-0005-9473-3591
Turki AsiriDepartment of Microbiology and Parasitology, Faculty of Medicine, King Abdulaziz University, Rabigh, Saudi Arabia.
Abdulrahman M Al-GhamdiDepartment of Microbiology and Parasitology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Rakan F FelembanDepartment of Laboratory and Blood Bank, Alnoor Specialist Hospital, Makkah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Urinary tract infections (UTIs) are among the most prevalent bacterial infections worldwide, with notable variations in antimicrobial resistance (AMR) patterns influenced by age and sex. Local surveillance of resistance trends is essential for optimizing empirical treatment. Methods: This retrospective study analyzed urine culture data collected over a span of 7-year (2017-2023) from a tertiary hospital in Saudi Arabia. The distribution of Pathogens and patterns of AMR were examined based on sex, age group, and year. Logistic regression was used to assess predictors of resistance. Results: The analysis included 3,201 urinary isolates from patients with culture-confirmed UTIs. Conclusion: This study demonstrates significant variability in UTI pathogens and their resistance patterns based on sex and age. The findings support the need for targeted empirical treatment protocols and underscore the importance of ongoing monitoring of AMR.

Indexed as

antibioticsE. coliK. pneumoniaeresistanceurine

Identifiers

PMID42021854
PMCPMC13096822

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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.