Evidence mapPaperPMID 41586367Full record

ArticleFrontiers in microbiology2025

Burden and trends of antimicrobial non-susceptibility in skin and soft tissue infections: nine-year microbiological surveillance from a tertiary hospital in Riyadh, Saudi Arabia.

Yahya Shabi, Abdullah A Alshehri, Khalifa Binkhamis, Mohammed Alqahtani, Thamir Saad Alsaeed, Ali Abdullah Aljaberi, Saleh Abdullah Alkhamis, Mohammad K Alshomrani, Abdullah Z Almutairi, Abdulah J Alqahtani and 2 more

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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

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

12 authors.

Yahya ShabiDepartment of Microbiology and Clinical Parasitology, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Abdullah A AlshehriMicrobiology Laboratory, Prince Mohammed bin Abdulaziz Hospital, Riyadh, Saudi Arabia.
Khalifa BinkhamisDepartment of Pathology, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
Mohammed AlqahtaniMicrobiology Section, Pathology and Medical Laboratories, Department and Blood Banks, Security Forces Hospital, Riyadh, Saudi Arabia.
Thamir Saad AlsaeedDepartment of Biology and Immunology, College of Medicine, Qassim University, Qassim, Saudi Arabia.
Ali Abdullah AljaberiMicrobiology Laboratory, Prince Mohammed bin Abdulaziz Hospital, Riyadh, Saudi Arabia.
Saleh Abdullah AlkhamisMicrobiology Laboratory, Prince Mohammed bin Abdulaziz Hospital, Riyadh, Saudi Arabia.
Mohammad K AlshomraniMicrobiology Department, Riyadh Regional Laboratory, Riyadh, Saudi Arabia.
Abdullah Z AlmutairiMicrobiology Laboratory, King Fahad Hospital, Medina, Saudi Arabia.
Abdulah J AlqahtaniDepartment of Microbiology and Clinical Parasitology, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Ahmad Jebril M BosailyDepartment of Surgery, College of Medicine, King Khalid University, Abha, Saudi Arabia.
Fatimah AlshahraniDivision of Infectious Diseases, Department of Internal Medicine, King Saud University Medical City, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Skin and soft tissue infections (SSTIs) impose a substantial global and regional burden, and their management is increasingly complicated by antimicrobial non-susceptibility. In Saudi Arabia, data remain fragmented, with few studies providing species-level analyses stratified by specimen type and infection depth. Methods: We retrospectively analyzed 6,760 wound and tissue specimens (2016-2024) from a tertiary hospital in Riyadh, Saudi Arabia. Organisms were identified using standard microbiological methods and VITEK 2. Antimicrobial susceptibility testing was interpreted according to CLSI M100, defining non-susceptibility as resistant or intermediate categories. Binary logistic regression was used to assess temporal trends in antimicrobial non-susceptibility, with year of isolation entered as a continuous predictor. Results: Gram-negative organisms predominated (63.2%), followed by Gram-positives (35.6%) and yeast (1.2%). Conclusion: Gram-negative organisms predominated in SSTIs, showing rising non-susceptibility to amikacin and carbapenems. Separately, among Gram-positive pathogens,

Indexed as

antimicrobial resistancecarbapenem-resistant EnterobacteralesEscherichia colimethicillin-resistant Staphylococcus aureusmultidrug resistancenon-susceptibilityPseudomonas aeruginosaSaudi Arabia

Identifiers

PMID41586367
PMCPMC12827636

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.