Evidence map›Paper›PMID 42787013›Full record

ArticleFrontiers in medicine2026

Screening for inflammation and treatment with colchicine in adults with known cardiovascular disease: an analysis of 13.5 million patients.

Arch G Mainous, Lu Yin, Frank A Orlando

Abstract read
In one paragraph

Article in Frontiers in medicine, 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
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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

3 authors.

Arch G MainousDepartment of Community Health and Family Medicine, University of Florida, Gainesville, FL, United States.
Lu YinDepartment of Community Health and Family Medicine, University of Florida, Gainesville, FL, United States.
Frank A OrlandoDepartment of Community Health and Family Medicine, University of Florida, Gainesville, FL, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Identifying and treating inflammation is a recommended atherosclerotic cardiovascular disease (ASCVD) prevention strategy. The practice of screening for and treating inflammation is unknown. This study examined screening for inflammation and treatment with colchicine among patients with established ASCVD. Methods: Using the Epic COSMOS electronic health record (EHR) database, we compared adults with known ASCVD between two time frames: (1) 2023 (colchicine FDA approved for ASCVD prevention) until April 2026 and (2) September 2025 [American College of Cardiology (ACC) scientific statement released] until April 2026. We examined screening for inflammation and treatment of inflammation. Chi-square tests compared differences before and after the ACC scientific statement on inflammation. Results: The study contained 13.5 million adults aged 18 years or older diagnosed within the EHR with ASCVD. Only 1.2% of the patients with ASCVD were on colchicine. The proportion of patients with known ASCVD who were screened to assess inflammation was also very low (3.1%). Among patients who had hs-CRP measurements, 65.3% had elevated levels. Additionally, even in light of documented inflammation, the proportion of patients with elevated documented inflammation are on colchicine was low but did increase after the ACC scientific statement from 2.1% to 2.9%. Conclusion: The evidence on inflammation and its role in ASCVD is substantial. Screening for inflammation and treatment of the inflammation pathway in patients with ASCVD is very low and not consistent with evidence-based practice.

Indexed as

clinical guidelineclinical guideline adherencecolchicineinflammationscreening

Identifiers

PMID42787013
PMCPMC13600809

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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.