{"doi":"10.1016/j.jacadv.2024.101462","title":"Cardiovascular Risk Prediction Scores in Type 1 Diabetes","abstract":"Background: The extent of the performance and utility of scores for the risk of cardiovascular disease (CVD) in persons with type 1 diabetes (T1DM) largely remains unclear. Objective: The purpose of this study was to synthesize data on the performance of CVD risk scores in people living with T1DM. Methods: This study is a systematic review and meta-analysis. PubMed and EMBASE were searched through December 31, 2023. The included studies: 1) were retrospective, prospective, or cross-sectional in design; 2) included persons with T1DM; 3) assessed CVD outcomes; and 4) had data on at least on CVD risk score. Measures of calibration and discrimination qualitatively summarized. Measures of discrimination were combined using random-effects models stratified by type of risk model. Results: In a meta-analysis of observational studies of CVD risk scores in T1DM individuals, including 11 studies and 73,664 participants (mean age of 34 years, mainly White individuals and male [55%]), we evaluated 12 CVD risk prediction models (7 T1DM-specific, 1 type 2 diabetes-specific, and 4 general population models). Most risk scores had a moderate to excellent discrimination (C-statistic: 0.73-0.85) and predicted CVD risk well when compared to actual clinical events. CVD risk scores specifically developed in T1DM individuals exhibited a higher discriminative performance-pooled C-statistic of 0.81 vs 0.75 for risk scores developed in the general population or those with type 2 diabetes and also showed a better calibration. Conclusions: Among individuals with T1DM, CVD risk models had a moderate to excellent discrimination, with a better discrimination and accuracy for T1DM-specific scores.","journal":"JACC Advances","year":2024,"id":441633,"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":9,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.6928,"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":1254691,"name":"Ahmed Shahab","orcid":"0000-0001-5997-1977","position":1,"is_corresponding":false},{"id":1254692,"name":"Fayez H. Fayad","orcid":"0000-0003-4074-0321","position":2,"is_corresponding":false},{"id":1061166,"name":"Mohammed Haji","orcid":null,"position":3,"is_corresponding":false},{"id":755104,"name":"Matthew F. Yuyun","orcid":"0000-0002-2390-3320","position":4,"is_corresponding":false},{"id":266924,"name":"Jacob Joseph","orcid":"0000-0002-7279-4896","position":5,"is_corresponding":false},{"id":440205,"name":"Wen‐Chih Wu","orcid":"0000-0002-2834-2024","position":6,"is_corresponding":false},{"id":233056,"name":"Amanda Adler","orcid":"0000-0002-2797-3385","position":7,"is_corresponding":false},{"id":309261,"name":"Trevor J. Orchard","orcid":"0000-0001-9552-3215","position":8,"is_corresponding":false},{"id":377294,"name":"Justin B. Echouffo‐Tcheugui","orcid":"0000-0002-8460-1617","position":9,"is_corresponding":false},{"id":233768,"name":"Sebhat Erqou","orcid":"0000-0001-6763-3804","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T02:01:11.152920Z","pmid":"39801813","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":[]}