Evaluation of a Machine Learning-guided Strategy for Elevated Lipoprotein(a) Screening in Health Systems

Background While universal screening for Lp(a) is increasingly recommended, fewer than 0.5% of the patients undergo Lp(a) testing. Here, we assessed the feasibility of deploying Algorithmic Risk Inspection for Screening Elevated Lp(a) (ARISE), a validated machine learning tool, to health system EHRs to increase the yield of Lp(a) testing. Methods We randomly sampled 100,000 patients from the Yale-New Haven Health System (YNHHS) to evaluate the feasibility of ARISE deployment. We also evaluated Lp(a) tested populations in the YNHHS (N=7,981) and the Vanderbilt University Medical Center (VUMC) (N=10,635) to assess the association of ARISE score with elevated Lp(a). To compare the representativeness of the Lp(a) tested population, we included 456,815 participants from the UK Biobank and 23,280 from three US-based cohorts of ARIC, CARDIA, and MESA. Results Among 100,000 randomly selected YNHHS patients, 413 (0.4%) had undergone Lp(a) measurement. ARISE score could be computed for 31,586 patients based on existing data, identifying 2,376 (7.5%) patients with a high probability of elevated Lp(a). A positive ARISE score was associated with significantly higher odds of elevated Lp(a) in the YNHHS (OR 1.87, 95% CI, 1.65-2.12) and the VUMC (OR 1.41, 95% CI, 1.24-1.60). The Lp(a) tested population significantly differed from other study cohorts in terms of ARISE features. Conclusions We demonstrate the feasibility of deployment of ARISE in US health systems to define the risk of elevated Lp(a), enabling a high-yield testing strategy. We also confirm the very low adoption of Lp(a) testing, which is also being restricted to a highly selected population. ### Competing Interest Statement Dr. Khera is an Associate Editor at JAMA and receives research grant support, through Yale, from Bristol Myers Squibb, Novo Nordisk, and BridgeBio. He is a coinventor of U.S. Pending Patent Applications 63/619,241, 63/606,203, 63/177,117, 63/346,610, 63/428,569, and 63/484,426, unrelated to the current work. He receives support from the Blavatnik Foundation through the Blavatnik Fund for Innovation at Yale. Dr. Khera is a cofounder of Ensight-AI, and Dr. Khera and Dr. Oikonomou are co-founders of Evidence2Health, both representing precision health platforms to improve evidence-based cardiovascular care. Dr. Oikonomou is a co-inventor of the U.S. Patent Applications 63/508,315 and 63/177,117, and has served as a consultant to Caristo Diagnostics Ltd (Oxford, U.K.), unrelated to the current work. The remaining authors have no disclosures to report. ### Funding Statement The study was supported by the National Heart, Lung, and Blood Institute of the National Institutes of Health (under award K23HL153775 to Dr. Khera and 1F32HL170592-01 to Dr. Oikonomou) and the Doris Duke Charitable Foundation (under award, 2022060 to Dr. Khera). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Yale Institutional Review Board approved the study protocol and waived the need for informed consent as the study involves analyzing pre-existing data. Patients who opted out of research studies at the Yale-New Haven Health System (YNHHS) were not included in the study. The use of Vanderbilt University Medical Center (VUMC) data was classified as non-human subject research by the VUMC Institutional Review Board as the study involves analyzing de-identified records. This research has been conducted using the UK Biobank (UKB) Resource under Application Number #71033. The participants of Atherosclerosis Risk in Communities (ARIC), Coronary Artery Risk Development in Young Adults (CARDIA), and Multi-Ethnic Study of Atherosclerosis (MESA) provided informed consent for participation, and their de-identified data were analyzed in this study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The analyzed de-identified data are available for the UK Biobank cohort from the UK Biobank's Access Management System and for ARIC, CARDIA, and MESA cohorts from the NHLBI's Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). The analyzed data from Yale-New Haven Health System and Vanderbilt University Medical Center cannot be made publicly available. * ARIC : Atherosclerosis Risk in Communities ARISE : Algorithmic Risk Inspection for Screening Elevated Lp(a) ASCVD : atherosclerotic cardiovascular disease CARDIA : Coronary Artery Risk Development in Young Adults EHR : electronic health records HDL-C : high-density lipoprotein cholesterol LDL-C : low-density lipoprotein cholesterol Lp(a) : Lipoprotein(a) MESA : Multi-Ethnic Study of Atherosclerosis UKB : UK Biobank UMAP : uniform manifold approximation and projection VUMC : Vanderbilt University Medical Center YNHHS : Yale-New Haven Health System