Evidence map›Paper›PMID 33437263›Full record

ArticlePakistan journal of medical sciences

Diagnostic accuracy of magnetic resonance imaging in detection of intra-axial gliomas.

Sohbia Munir, Sohail Ahmed Khan, Hina Hanif, Maria Khan

Abstract read
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Article in Pakistan journal of medical sciences. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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  11. Bridging Neuroimaging and Neuropathology: A Comprehensive Workflow for Targeted Sampling of White Matter Lesions.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    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

4 authors.

Sohbia MunirSohbia Munir, Resident, Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan.
Sohail Ahmed KhanSohail Ahmed Khan, Assistant Professor, Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan.
Hina HanifHina Hanif, Resident, Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan.
Maria KhanMaria Khan, Resident, Dow Institute of Radiology, Dow University of Health Sciences, Karachi, Pakistan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo evaluate the diagnostic accuracy of magnetic resonance imaging (MRI) in detection of intra-axial gliomas in suspected cases keeping histopathology as gold standard.

methodsThis cross-sectional study was conducted at Dow Institute of Radiology, DUHS from October 2017 - April 2018. Patients of either gender aged 30-70 years presenting with headache were included. Patients already diagnosed and referred for follow up were excluded. MRI was performed on 1.5T scanner by a trained MRI technician. T1, T2, FLAIR, diffusion weighted and T1 post contrast images were acquired and reviewed by two radiologists having more than five years post fellowship experience. Sensitivity, specificity, PPV, NPV and diagnostic accuracy of MRI for intraaxial gliomas was calculated taking histopathology findings as gold standard.

resultsMean age of the patient`s was 51.71 ±10.85 years. Positive intraaxial gliomas on MRI were observed in 123 (79.90%) patients while on histopathology, positive intraaxial gliomas were observed in 131 (85.10%) patients. Diagnostic accuracy of MRI in detection of intra-axial gliomas taking histopathology findings as gold standard showed sensitivity, specificity, positive predicted value (PPV), negative predicted value (NPV) and overall diagnostic accuracy as 89.31%, 73.91%, 95.12%, 54.84% and 87.01%.

conclusionsMRI has high sensitivity, moderate specificity and high diagnostic accuracy in detection of intraaxial gliomas.

Indexed as

Diagnostic accuracyGliomaMagnetic resonance imagingSensitivitySpecificity

Identifiers

PMID33437263
PMCPMC7794124

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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.