Evidence map›Paper›PMID 40963751›Full record

ArticlemedRxiv : the preprint server for health sciences2025

Incidentally discovered Covert Cerebrovascular Disease by CT versus MRI: Agreement and Prognostic Value for Stroke and Dementia in a Large Real-World Cohort.

David M Kent, Eric J Puttock, Lester Y Leung, Navdeep Sangha, Neel Madan, Eric E Smith, Mai N Nguyen-Huynh, Wansu Chen

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

David M KentPredictive Analytics and Comparative Effectiveness Center, Tufts Medical Center, Boston, Massachusetts, USA.
Eric J PuttockDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.
Lester Y LeungDepartment of Neurology, Tufts Medical Center, Boston, Massachusetts, USA.
Navdeep SanghaDepartment of Neurology, Kaiser Permanente Southern California, Pasadena, California, USA.
Neel MadanDepartment of Radiology, Tufts Medical Center, Boston, Massachusetts, USA.
Eric E SmithDepartment of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Alberta, Canada.
Mai N Nguyen-HuynhDepartment of Neurology, Kaiser Permanente Northern California, Oakland, California, USA.
Wansu ChenDepartment of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, California, USA.

Funding

Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): A Platform for Pragmatic Evidence Generation for Stroke and Dementia PreventionRF1NS102233 · NINDS · TUFTS MEDICAL CENTER · PI KENT, DAVID M · 2023 to 2025
$3.1M
Covert Cerebrovascular Disease Detected by Artificial Intelligence (C2D2AI): Pragmatic Neuroimaging Biomarkers for Future Stroke and Dementia RiskR01NS134859 · NINDS · TUFTS MEDICAL CENTER · PI DAVID M KENT · 2024 to 2026
$2.3M
NINDS NIH HHS R01 NS134859NINDS NIH HHS RF1 NS102233
6 · The paper itself

Abstract

Background: Covert cerebrovascular disease (CCD), comprising covert brain infarction (CBI) and white matter disease (WMD), is common in older adults and linked to increased risk of stroke and dementia. While most CCD research relies on MRI, CT remains the predominant imaging modality in clinical care. The influence of imaging modality on detection and prognosis of incidentally discovered CCD remains unclear. Methods: We identified 18,626 patients aged ≥50 years from Kaiser Permanente Southern California who underwent both CT and MRI brain scans within 30 days between 2009-2022. Patients with known prior stroke or dementia were excluded. Natural language processing algorithms were applied to radiology reports to identify CBI and WMD status and WMD severity (none, mild, moderate, severe). We assessed prevalence, cross-modality agreement (Cohen's kappa), and reclassification patterns. Prognostic associations with incident stroke or dementia were estimated using Cox Proportional Hazards regression adjusted for vascular and cognitive risk factors. Findings: CBI prevalence was similar for CT (6.3%) and MRI (6.1%), but agreement was modest (κ=0.27). WMD was reported far more often on MRI (60.5%) than CT (24.4%). Among 15,551 patients with classifiable severity on both modalities, 47.9% (n=7,441) had discordant grades, with 92.3% upgraded on MRI. The incidence rates of stroke or dementia per 1,000 person-years were 12.7 (95% CI 11.5 - 14.0) for patients without WMD on either modality (36.3% of the cohort), 22.6 (21.0 - 24.2) for WMD detected on MRI only (39.2% of the cohort), and 52.2 (48.69 to 55.95) for WMD detected on both CT and MRI (21.2% of the cohort). In adjusted Cox models, WMD detected on MRI only was associated with a 23% higher hazard of stroke or dementia (HR=1.23, 95% CI 1.07-1.41) compared with no WMD on either modality, while WMD detected on both CT and MRI was associated with an 82% higher hazard (1.82, 1.58-2.11). Interpretation: MRI detects substantially more WMD than CT; however, WMD visible on CT has stronger prognostic significance, despite CT's low sensitivity. These findings emphasize modality-based diagnostic and prognostic differences and support the need for modality-specific approaches when translating CCD research into clinical risk assessment and patient counselling.

Identifiers

PMID40963751
PMCPMC12440058

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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.