Evidence map›Paper›PMID 31378866›Full record

ReviewSeminars in neurology2019

Diagnostic Testing in Central Nervous System Infection.

Sanjat Kanjilal, Tracey A Cho, Anne Piantadosi

Abstract readReview
In one paragraph

Review in Seminars in neurology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Recent advances in diagnostic technologies for postoperative central nervous system infections: a review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025
    Review
  6. Review
  7. Article
  8. Review
  9. Article
  10. Article
  11. Observational
  12. Article
  13. Article
  14. Value of lipocalin 2 as a potential biomarker for bacterial meningitis.Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases · 2020
    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

3 authors.

Sanjat KanjilalDivision of Infectious Diseases, Department of Pathology, Brigham and Women's Hospital, Boston, Massachusetts.
Tracey A ChoDepartment of Neurology, University of Iowa Hospitals and Clinics, Iowa City, Iowa.
Anne PiantadosiDivision of Infectious Diseases, Massachusetts General Hospital, Boston, Massachusetts.ORCID 0000-0002-5942-1534

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Patients with central nervous system (CNS) infection experience very high levels of morbidity and mortality, in part because of the many challenges inherent to the diagnosis of CNS infection and identification of a causative pathogen. The clinical presentation of CNS infection is nonspecific, so clinicians must often order and interpret many diagnostic tests in parallel. This can be a daunting task given the large number of potential pathogens and the availability of different testing modalities. Here, we review traditional diagnostic techniques including Gram stain and culture, serology, and polymerase chain reaction (PCR). We highlight which of these are recommended for the pathogens most commonly tested among U.S. patients with suspected CNS infection. Finally, we describe the newer broad-range diagnostic approaches, multiplex PCR and metagenomic sequencing, which are increasingly used in clinical practice.

Indexed as

MetagenomeCentral Nervous System InfectionsDiagnostic Tests, RoutineGentian VioletHumansPhenazinesPolymerase Chain ReactionGentian VioletGram's stainPhenazines

Identifiers

PMID31378866
PMCPMC7117082

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.