Evidence map›Paper›PMID 38855713›Full record

ArticleNeurology. Clinical practice2024

Predictive Value of Clinical, CSF and Vessel Wall MRI Variables in Diagnosing Primary Angiitis of the CNS.

G Abbas Kharal, Sidonie E Ibrikji, Youssef M Farag, Aaron Shoskes, Matthew P Kiczek, Richa Sheth, Muhammad S Hussain

Abstract read
In one paragraph

Article in Neurology. Clinical practice, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Clinical implications of vessel wall imaging-State-of-the-art review.Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
    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

7 authors.

G Abbas KharalCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0000-0001-6074-1028
Sidonie E IbrikjiCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0000-0003-3830-474X
Youssef M FaragCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0000-0003-1692-1851
Aaron ShoskesCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0000-0003-1526-5258
Matthew P KiczekCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0000-0003-1729-5389
Richa ShethCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0009-0003-1960-7128
Muhammad S HussainCerebrovascular Center (GAK, SEI, MSH), Neurological Institute, Cleveland Clinic, OH; Department of Epidemiology (YMF), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Neurology (AS), University of Utah, Salt Lake City; Section of Neuroradiology (MPK), Imaging Institute, Cleveland Clinic, OH; and Northeast Ohio Medical School (RS), Rootstown.ORCID https://orcid.org/0000-0002-8506-7743

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objectives: Without brain biopsy, there are limited diagnostic predictors to differentiate primary angiitis of the CNS (PACNS) from intracranial atherosclerotic disease (ICAD). We examined the utility of clinical, CSF, and quantitative vessel wall magnetic resonance imaging (VWMRI) variables in predicting PACNS from ICAD. Methods: In this cross-sectional design, observational study, we reviewed electronic medical records to identify patients (18 years and older) who presented to our medical center between January 2015 and December 2021 for ischemic stroke due to intracranial vasculopathy. Patients with biopsy-proven PACNS, probable PACNS, or ICAD were included. Patients with secondary CNS vasculitis or no VWMRI data were excluded. On VWMRI, for each patient, a total of 20 vessel wall segments were analyzed for percent concentricity, percent irregularity, and concentricity to eccentricity (C/E) ratios. We also collected several clinical and CSF variables. Using logistic regression models, we assessed the diagnostic value of VWMRI, CSF, and clinical variables in predicting PACNS in patients with biopsy-proven disease. We then performed a sensitivity analysis to assess predictors of biopsy-proven and probable PACNS. Results: Thirty-two patients with ICAD (54.2%) and 27 patients with PACNS (45.8%) were included. Of the patients with PACNS, 21 (77.8%) were not biopsied and considered probable PACNS. Twenty-four patients with ICAD (75%) and 6 biopsy-proven patients with PACNS (22.2%) showed large vessel involvement and were included in the primary analysis. Encephalopathy (odds ratio [OR], 7.60; 95% CI 1.07-54.09) and seizure (OR 23.00; 95% CI 1.77-298.45) were significantly associated with PACNS. All patients were included in the sensitivity analysis, in which headache significantly predicted PACNS (OR 7.60; 95% CI 1.07-54.09). In the primary analysis, for every 1 white blood cell/µL increase in CSF, there was a 47% higher odds of PACNS (OR 1.47; 95% CI 1.04-2.07). On VWMRI, a C/E ratio >1 (OR 115.00; 95% CI 6.11-2165.95), percent concentricity ≥50% (OR 55.00; 95% CI 4.13-732.71), and percent irregularity <50% (OR 55.00; 95% CI 4.13-732.71) indicated significantly higher odds of PACNS compared with ICAD. Discussion: Our results suggest that quantitative VWMRI metrics, CSF pleocytosis, and clinical features of encephalopathy, seizure, and headache significantly predict a diagnosis of probable PACNS when compared with ICAD.

Identifiers

PMID38855713
PMCPMC11160479

What Socratic 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 Socratic graph.