Evidence map›Paper›PMID 42257074›Full record

ArticlePakistan journal of medical sciences2026

Whole-Genome Sequencing for Antimicrobial Resistance Detection: A Simulation-Based Evaluation of WHO-Recommended Workflow in Pakistan.

Hayam A Alrasheed, Asif Jan, Abdur Rahim, Bushra Waheed, Rani Akbar

Abstract read
In one paragraph

Article in Pakistan journal of medical sciences, 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

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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

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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.

Hayam A AlrasheedHayam A. Alrasheed Department of Pharmacy Practice, College of Pharmacy, Princess Nourah bint Abdulrahman University, Saudi Arabia.
Asif JanAsif Jan Saidu Group of Teaching Hospital Saidu Sharif Swat, KP, Pakistan. Department of Pharmacy, University of Peshawar, Peshawar, KP, Pakistan. District Headquarter Hospital Charsadda, Charsadda, KP, Pakistan.
Abdur RahimAbdur Rahim Department of Pharmacy, Cecos University of IT & Emerging Sciences, Peshawar, KP, Pakistan.
Bushra WaheedBushra Waheed Department of Pharmacy, University of Swabi, Swabi, KP, Pakistan.
Rani AkbarRani Akbar Department of Pharmacy, Abdul Wali Khan University, Mardan, KP, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To evaluate the performance and feasibility of whole-genome sequencing works for detecting antimicrobial resistance and to determine whether it is practical to use in Pakistan, using a simulation-based model following World Health Organization's antimicrobial resistance genome sequencing guidelines. Methodology: A simulation-based evaluation was conducted at the Centre of Genomics, Rehman Medical Institute (January to December 2025) to investigate the effectiveness of whole-genome sequencing (WGS) in detecting antimicrobial resistance (AMR) patterns in Pakistan. A simulation model was developed according to the guidelines described in World Health Organization (WHO) report for detection of Antimicrobial Resistance using Whole Genome Sequencing (WGS). Simulation inputs included common AMR genes circulating in Pakistan (mecA, blaCTX-M, blaNDM-1, blaOXA-48, aac(6')-Ib), pathogenic species profiles, and metadata recommendations. Evidence from WHO-recommended WGS workflows was used for AMR detection and validation. The study was carried out over a period of 12 months. Results: Simulated WGS workflows showed high predicted accuracy for AMR gene detection (94-100%), virulence factor identification (≥90%), plasmid and mobile genetic element (MGE) resolution, and outbreak-level genomic typing. WGS reduced theoretical AMR detection time from 48-72 hours (phenotypic methods) to <12 hours post-culture. WHO-recommended quality metrics including ≥30× coverage, Q30 base accuracy, appropriate metadata capture, and standardized laboratory workflows were achievable within Pakistan health care system, though limited by workforce training, bioinformatics infrastructure. Conclusion: WGS is a feasible and highly accurate method for detecting antimicrobial resistance (AMR) in Pakistan. Using WGS according to the World Health Organization (WHO) recommended standards can greatly improve Pakistan's national AMR surveillance system.

Indexed as

AMR genesAntimicrobial resistanceGenomic surveillancePakistanWHOWhole-genome sequencing

Identifiers

PMID42257074
PMCPMC13238182

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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.