ArticleAmerican heart journal2022
Rationale and design of a pragmatic trial aimed at improving treatment of hyperlipidemia in outpatients with very high risk atherosclerotic cardiovascular disease: A pragmatic trial of messaging to providers about treatment of hyperlipidemia (PROMPT-LIPID).
Article in American heart journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04394715 (Pragmatic Trial of Messaging to Providers About Treatment of Hyperlipidemia), which is not on this map. Cited by 5 papers.
What it found
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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.
Pragmatic Trial of Messaging to Providers About Treatment of Hyperlipidemia (PROMPT-LIPID)
Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- Artificial Intelligence in Cardiovascular Disease Prevention: Is it Ready for Prime Time?Current atherosclerosis reports · 2024Review
- LOGAN-CV: A Prospective Study of a Multifaceted Intervention Targeting United States Clinicians to Improve Guideline-Based Management of Lipid-Lowering Therapy.Advances in therapy · 2024Article
- Article
- Evolving Management of Low-Density Lipoprotein Cholesterol: A Personalized Approach to Preventing Atherosclerotic Cardiovascular Disease Across the Risk Continuum.Journal of the American Heart Association · 2023Review
- Natural language processing to identify reasons for sex disparity in statin prescriptions.American journal of preventive cardiology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundDespite guideline recommendations to optimize low-density lipoprotein cholesterol (LDL-C) reduction with intensification of lipid-lowering therapy (LLT) in patients with atherosclerotic cardiovascular disease (ASCVD), few of these patients achieve LDL-C < 70 mg/dL in practice. PURPOSE: We developed a real-time, targeted electronic health record (EHR) alert with embedded ordering capability to promote intensification of evidence based LLT in outpatients with very high risk ASCVD.
methodsWe designed a pragmatic, multicenter, single-blind, cluster randomized trial to test the effectiveness of an EHR-based LLT intensification alert. The study will enroll about 100 providers who will be randomized to either receive the alert or undergo usual care for outpatients with high risk ASCVD with LDL-C > 70 mg/dL. Total enrollment will include 2,500 patients. The primary outcome will be the proportion of patients with LLT intensification at 90 days. Secondary outcomes include achieved LDL-C at 6 months and the proportion of patients with LDL-C < 70 mg/dL or < 55 mg/dL at 6 months.
resultsEnrollment of 1,250 patients (50% of goal) was reached within 47 days (50% women, mean age 72, median LDL-C 91). At baseline, 71%, 9%, and 3% were on statins, ezetimibe, or proprotein convertase subtilisin/kexin type 9 inhibitors, respectively.
conclusionsPRagmatic Trial of Messaging to Providers about Treatment of HyperLIPIDemia has rapidly reached 50% enrollment of patients with very high risk ASCVD, demonstrating low baseline LLT utilization. This pragmatic, EHR-based trial will determine the effectiveness of a real-time, targeted EHR alert with embedded ordering capability to promote LLT intensification. Findings from this low-cost, widely scalable intervention to improve LDL-C may have important public health implications.
trial registrationclinicaltrials.gov NCT04394715.
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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 Socratic graph.