Evidence map›Paper›PMID 40140116›Full record

ReviewAntonie van Leeuwenhoek2025

Leveraging innovative diagnostics as a tool to contain superbugs.

Ngozi J Anyaegbunam, Kenneth Emenike Okpe, Aisha Bisola Bello, Theophilus Izuchukwu Ajanaobionye, Chukwuma Christian Mgboji, Aanuoluwapo Olonade, Zikora Kizito Glory Anyaegbunam, Ifeanyi Elibe Mba

Abstract readReview
PubMed Publisher
In one paragraph

Review in Antonie van Leeuwenhoek, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

8 authors.

Ngozi J AnyaegbunamMeasurement and Evaluation Unit, Science Education Department, University of Nigeria Nsukka, Nsukka, Nigeria.
Kenneth Emenike OkpeDepartment of Science Education, University of Nigeria Nsukka, Nsukka, Nigeria.
Aisha Bisola BelloDepartment of Biological Sciences, Federal Polytechnic Bida Niger State, Bida, Nigeria.
Theophilus Izuchukwu AjanaobionyeDepartment of Microbiology, Faculty of Biological Sciences, University of Nigeria Nsukk, Nsukka, 410001, Nigeria.
Chukwuma Christian MgbojiDepartment of Computer and Robotics Education, University of Nigeria Nsukka, Nsukka, Nigeria.
Aanuoluwapo OlonadeDepartment of Biochemistry, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria.
Zikora Kizito Glory AnyaegbunamDepartment of Microbiology, Faculty of Biological Sciences, University of Nigeria Nsukk, Nsukka, 410001, Nigeria.
Ifeanyi Elibe MbaDepartment of Microbiology, Faculty of Biological Sciences, University of Nigeria Nsukk, Nsukka, 410001, Nigeria. mbaifeanyie@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The evolutionary adaptation of pathogens to biological materials has led to an upsurge in drug-resistant superbugs that significantly threaten public health. Treating most infections is an uphill task, especially those associated with multi-drug-resistant pathogens, biofilm formation, persister cells, and pathogens that have acquired robust colonization and immune evasion mechanisms. Innovative diagnostic solutions are crucial for identifying and understanding these pathogens, initiating efficient treatment regimens, and curtailing their spread. While next-generation sequencing has proven invaluable in diagnosis over the years, the most glaring drawbacks must be addressed quickly. Many promising pathogen-associated and host biomarkers hold promise, but their sensitivity and specificity remain questionable. The integration of CRISPR-Cas9 enrichment with nanopore sequencing shows promise in rapid bacterial diagnosis from blood samples. Moreover, machine learning and artificial intelligence are proving indispensable in diagnosing pathogens. However, despite renewed efforts from all quarters to improve diagnosis, accelerated bacterial diagnosis, especially in Africa, remains a mystery to this day. In this review, we discuss current and emerging diagnostic approaches, pinpointing the limitations and challenges associated with each technique and their potential to help address drug-resistant bacterial threats. We further critically delve into the need for accelerated diagnosis in low- and middle-income countries, which harbor more infectious disease threats. Overall, this review provides an up-to-date overview of the diagnostic approaches needed for a prompt response to imminent or possible bacterial infectious disease outbreaks.

Indexed as

BacteriaBacterial InfectionsCRISPR-Cas SystemsDrug Resistance, Multiple, BacterialHigh-Throughput Nucleotide SequencingHumansAntimicrobial resistanceBacteriaCRISPR-Cas systemDiagnosisLMICSequencing

Identifiers

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.