Evidence map›Paper›PMID 34605190›Full record

SynthesisCNS neuroscience & therapeutics2021

Correlation between the clinical disability and T1 hypointense lesions' volume in cerebral magnetic resonance imaging of multiple sclerosis patients: A systematic review and meta-analysis.

Amir Valizadeh, Mana Moassefi, Elham Barati, Mohammad Ali Sahraian, Faezeh Aghajani, Mohammad-Reza Fattahi

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in CNS neuroscience & therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 5 pooled it
–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

17 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  4. Role of lipoic acid in multiple sclerosis.CNS neuroscience & therapeutics · 2022
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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

6 authors.

Amir ValizadehTehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0001-5983-8527
Mana MoassefiTehran University of Medical Sciences, Tehran, Iran.ORCID 0000-0002-0111-7791
Elham BaratiTehran University of Medical Sciences, Tehran, Iran.
Mohammad Ali SahraianTehran University of Medical Sciences, Tehran, Iran.
Faezeh AghajaniTehran University of Medical Sciences, Tehran, Iran.
Mohammad-Reza FattahiTehran University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo evaluate the correlation between T1 hypointense lesions' mean volume on cerebral MRI with disability level of patients with multiple sclerosis.

methodsWe included studies testing the desired outcome in adult patients diagnosed with RRMS or SPMS. In Feb 2021, we searched PubMed, Embase, CENTRAL, and Web of Science to find relevant studies. All included studies were assessed for the risk of bias using a tailored version of the Quality in Prognosis Studies (QUIPS) tool. Extracted correlation coefficients were converted to the Fisher's z scale, and a meta-analysis using a random-effects model was performed on the results.

resultsWe included 27 studies (1919 participants). Meta-analysis revealed a correlation coefficient of 0.32 (95% CI 0.26-0.37) between T1 hypointense lesions' mean volume and EDSS score. DISCUSSION: The correlation between T1 hypointense lesions' mean volume and EDSS was interpreted as low to slightly moderate. The certainty of the evidence was judged to be high.

Indexed as

Disability EvaluationMagnetic Resonance ImagingAnimalsBrainDemyelinating DiseasesDisease ProgressionHumansMultiple Sclerosisdemyelinationmagnetic resonance imagingmultiple sclerosisneurologyneurosciences

Identifiers

PMID34605190
PMCPMC8504532

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Registered trials

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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.