ArticleNature cardiovascular research2024
Development and multinational validation of an algorithmic strategy for high Lp(a) screening.
Article in Nature cardiovascular research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Artificial Intelligence-enhanced Electrocardiography for Heart Failure Screening and Risk Stratification.Current heart failure reports · 2026Review
- Artificial intelligence in cardiovascular pharmacotherapy: applications and perspectives.European heart journal · 2025Review
- Lipoprotein (a) in primary cardiovascular disease prevention is actionable today.American heart journal plus : cardiology research and practice · 2025Review
- Artificial Intelligence-Enabled Prediction of Heart Failure Risk From Single-Lead Electrocardiograms.JAMA cardiology · 2025Article
- Many Journeys Originating at the Same Source to Arrive at Solutions to the Common Problem of High Lipoprotein(a).Circulation. Genomic and precision medicine · 2025Article
- Harnessing Artificial Intelligence for Innovation in Interventional Cardiovascular Care.Journal of the Society for Cardiovascular Angiography & Interventions · 2025Review
- Evaluation of a Machine Learning-Guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems.Circulation. Genomic and precision medicine · 2025Article
- Artificial Intelligence Enabled Prediction of Heart Failure Risk from Single-lead Electrocardiograms.medRxiv : the preprint server for health sciences · 2024Article
- Lipoprotein(a) and the atherosclerotic burden - Should we wait for clinical trial evidence before taking action?Atherosclerosis plus · 2024Review
- Cardiovascular care with digital twin technology in the era of generative artificial intelligence.European heart journal · 2024Review
Corrections and comments
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Authors and funding
8 authors.
Funding
Abstract
Elevated lipoprotein (a) (Lp(a)) is associated with premature atherosclerotic cardiovascular disease. However, fewer than 0.5% of individuals undergo Lp(a) testing, limiting the evaluation and use of novel targeted therapeutics currently under development. Here we describe the development of a machine learning model for targeted screening for elevated Lp(a) (≥150 nmol l
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What Socratic 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 Socratic graph.