Evidence mapPaperPMID 40455288Full record

ReviewNeurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology2025

Recent advances in diagnostic technologies for postoperative central nervous system infections: a review.

Junan Hu, Wei Yu, Jiating Cui, Lun Zhang, Wangfang Yu

Abstract readReview
In one paragraph

Review in Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
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.

Junan Hu *Department of Neurosurgery, Beilun District People's Hospital, Ningbo, 315800, Zhejiang, China.
Wei Yu *Department of Neurosurgery, Beilun District People's Hospital, Ningbo, 315800, Zhejiang, China.
Jiating Cui *Department of Neurosurgery, Beilun District People's Hospital, Ningbo, 315800, Zhejiang, China.
Lun ZhangDepartment of Radiology, Beilun District People's Hospital, Ningbo, 315800, Zhejiang, China. blrmyyfskzl@163.com.ORCID http://orcid.org/0009-0009-7611-2934
Wangfang YuDepartment of Neurosurgery, Beilun District People's Hospital, Ningbo, 315800, Zhejiang, China. yuwangfangblrmyy@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Postoperative central nervous system infections (PCNSIs), including meningitis, cerebral abscesses, and implant-associated infections, represent critical complications following neurosurgical procedures. These infections pose significant risks to patient outcomes due to delayed diagnosis, escalating antimicrobial resistance, and limited therapeutic efficacy. Conventional diagnostic approaches, such as cerebrospinal fluid (CSF) analysis, microbial cultures, and neuroimaging, exhibit notable limitations in sensitivity, specificity, and rapidity. This review highlights transformative technologies reshaping PCNSI diagnostics, including molecular assays (e.g., quantitative PCR, digital droplet PCR), metagenomic next-generation sequencing (mNGS), CRISPR-based pathogen detection platforms, metabolomics, and advanced molecular imaging modalities. Furthermore, we address translational challenges in clinical adoption, including cost barriers, standardization gaps, and the need for interdisciplinary collaboration. Emerging artificial intelligence (AI)-driven strategies are proposed to optimize pathogen identification, predict antimicrobial resistance profiles, and tailor personalized therapeutic regimens.

Indexed as

Central Nervous System InfectionsNeurosurgical ProceduresPostoperative ComplicationsHumansAntimicrobial resistanceArtificial intelligenceCRISPR-Cas systemsmNGSMolecular diagnosticsPCNSIs

Identifiers

PMID40455288
PMCPMC12394297

What Socratic holds

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LicenceCC BY
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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.