ArticlePsychoradiology2025
Systematic review and meta-analysis of brain neuroimaging abnormalities in COVID-19 patients and survivors.
Article in Psychoradiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
Who cites it
2 citing papers in PubMed.
- Neuropsychiatric Involvement in Hospitalized COVID-19 Is Embedded in Multi-Organ Disease: A Retrospective Five-Axis Record-Derived Phenotype Atlas with Renal-Urinary Prognostic Dominance.Pathogens (Basel, Switzerland) · 2026Article
- Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome.Brain, behavior, & immunity - health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
25 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Accumulating evidence indicates that COVID-19 may cause neurological complications detectable on brain imaging. Yet, the overall prevalence, modality-specific characteristics, and clinical implications of these neuroimaging abnormalities have not been systematically summarized through comprehensive quantitative synthesis. Methods: We searched the PubMed, Web of Science, Scopus, Embase, Cochrane Library, and China National Knowledge Infrastructure (CNKI) databases, and Wanfang for original articles published up to August 5, 2025. The pooled proportions of brain-imaging findings on computed tomography (CT), magnetic resonance imaging (MRI), and electroencephalography (EEG), including hemorrhage, microbleeds, ischemia, stroke, encephalitis, background activity abnormality, periodic or rhythmic activity, and epileptiform discharge, were estimated using a random-effects model. This study was conducted according to PRISMA guidelines. Results: Eighty-three eligible studies that included 9466 COVID-19 patients were included in the meta-analysis. Pooled results from 27 studies, including 3081 patients, showed that more than two-fifths (42.60%) of patients who underwent CT/MRI had objective brain abnormalities. The most frequently reported abnormalities on CT/MRI were changes in white matter and non-specific stroke. Twenty-five EEG studies, including 1273 patients, reported epileptiform discharges in one-fifth (20.54%) of cases. The systematic review of long-term brain imaging manifestations in COVID-19 survivors also found common changes in brain microstructure and function. Conclusion: While these findings offer insights into the potential pathological mechanisms of neuroimaging abnormalities in COVID-19 patients, the high heterogeneity and variability across studies highlight the need for cautious interpretation. It will be necessary to conduct large-scale longitudinal studies with extended follow-up periods in order to validate these neuroimaging findings and clarify the long-term neuropsychiatric consequences of COVID-19.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.