{"doi":"10.1016/j.jacadv.2024.100868","title":"Cardiometabolic Disease Staging and Major Adverse Cardiovascular Event Prediction in 2 Prospective Cohorts","abstract":"BACKGROUND: Cardiometabolic risk prediction models that incorporate metabolic syndrome traits to predict cardiovascular outcomes may help identify high-risk populations early in the progression of cardiometabolic disease. OBJECTIVES: The purpose of this study was to examine whether a modified cardiometabolic disease staging (CMDS) system, a validated diabetes prediction model, predicts major adverse cardiovascular events (MACE). METHODS: We developed a predictive model using data accessible in clinical practice [fasting glucose, blood pressure, body mass index, cholesterol, triglycerides, smoking status, diabetes status, hypertension medication use] from the REGARDS (REasons for Geographic And Racial Differences in Stroke) study to predict MACE [cardiovascular death, nonfatal myocardial infarction, and/or nonfatal stroke]. Predictive performance was assessed using receiver operating characteristic curves, mean squared errors, misclassification, and area under the curve (AUC) statistics. RESULTS: Among 20,234 REGARDS participants with no history of stroke or myocardial infarction (mean age 64 ± 9.3 years, 58% female, 41% non-Hispanic Black, and 18% diabetes), 2,695 developed incident MACE (13.3%) during a median 10-year follow-up. The CMDS development model in REGARDS for MACE had an AUC of 0.721. Our CMDS model performed similarly to both the ACC/AHA 10-year risk estimate (AUC 0.721 vs 0.716) and the Framingham risk score (AUC 0.673). CONCLUSIONS: The CMDS predicted the onset of MACE with good predictive ability and performed similarly or better than 2 commonly known cardiovascular disease prediction risk tools. These data underscore the importance of insulin resistance as a cardiovascular disease risk factor and that CMDS can be used to identify individuals at high risk for progression to cardiovascular disease.","journal":"JACC Advances","year":2024,"id":430115,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":20,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9616,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":737503,"name":"Li Zhang","orcid":"0000-0003-4132-9382","position":1,"is_corresponding":false},{"id":454551,"name":"Tapan Mehta","orcid":"0000-0002-2016-2344","position":2,"is_corresponding":false},{"id":461254,"name":"Lua Wilkinson","orcid":"0000-0001-6665-9463","position":3,"is_corresponding":false},{"id":57638,"name":"April P. Carson","orcid":"0000-0002-7970-6756","position":4,"is_corresponding":false},{"id":342610,"name":"Emily B. Levitan","orcid":"0000-0002-5429-3852","position":5,"is_corresponding":false},{"id":313577,"name":"Andrea Cherrington","orcid":"0000-0002-8321-3567","position":6,"is_corresponding":false},{"id":455514,"name":"Nengjun Yi","orcid":"0000-0001-5857-5868","position":7,"is_corresponding":false},{"id":269614,"name":"W. Timothy Garvey","orcid":null,"position":8,"is_corresponding":false},{"id":255610,"name":"Carrie R. Howell","orcid":"0000-0002-6554-6237","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T01:59:16.092672Z","pmid":"38765187","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}