Evidence map›Paper›PMID 42226867›Full record

ArticleCureus2026

Utility of the Medical Knowledge AI Copilot, OpenEvidence: A Patient With 100 Cerebral Microhemorrhages.

Amber N Navarra, Salman Ikramuddin, Steven M Greenberg, P Murali Doraiswamy

Abstract read
In one paragraph

Article in Cureus, 2026. 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

4 authors.

Amber N NavarraPsychiatry, Duke University School of Medicine, Durham, USA.
Salman IkramuddinNeurology, Duke University School of Medicine, Durham, USA.
Steven M GreenbergNeurology, Harvard Medical School, Boston, USA.
P Murali DoraiswamyPsychiatry, Duke University School of Medicine, Durham, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebral amyloid angiopathy (CAA) is a highly prevalent condition that often poses diagnostic and therapeutic challenges, especially in people with comorbid mild cognitive impairment (MCI). OpenEvidence (OE; Miami, Florida, US), a leading free medical knowledge copilot, reports it has supported over 100 million Artificial Intelligence (AI)-powered clinical consultations from U.S. doctors and other frontline clinicians. The objective of this study is to use a single case with two common comorbid neurological conditions to retrospectively appraise the ability of OE to serve as a clinically relevant knowledge aid. We input the de-identified summary of a case of probable CAA and MCI in OE. Overall, the AI recommendations very closely matched the diagnosis and care that was actually provided. We identified some areas (e.g., prognostication, geriatric risk-benefit trade-offs, diagnostic terminology) where it could be improved to match the logic and knowledge of a subspecialist. OE used as a knowledge copilot can help inform point-of-care physician decisions by giving them more information than they may have otherwise considered.

Indexed as

alzheimer’s dementiaartificial intelligence in medicinecerebral amyloid angiopathy (caa)large language models (llm)mild cognitive impairment (mci)openevidence

Identifiers

PMID42226867
PMCPMC13222736

What Socratic holds

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LicenceCC BY
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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.