{"title":"用冠状动脉风险评分预测女性主要不良冠状动脉事件","authors":"Guillermo Romero-Farina, Santiago Aguadé-Bruix, Ignacio Ferreira-González","doi":"10.1148/ryct.230381","DOIUrl":null,"url":null,"abstract":"<p><p>Purpose To establish a COronary Risk Score in WOmen (CORSWO) to predict major adverse coronary events (MACE). Materials and Methods This retrospective analysis included 2226 female individuals (mean age, 66.7 years ± 11.6 [SD]) from a cohort of 25 943 consecutive patients referred for clinical gated SPECT myocardial perfusion imaging (gSPECT MPI). During the follow-up (mean, 4 years ± 2.7) after gSPECT MPI, occurrence of MACE (unstable angina requiring hospitalization, nonfatal myocardial infarction, coronary revascularization, cardiac death) was assessed. The patients were divided into training (<i>n</i> = 1460) and validation (<i>n</i> = 766) groups. To obtain the predictor model, multiple Cox regression analyses were performed. Results In the training group, 148 female individuals had MACE (2.6% per year). The best model (area under the receiver operating characteristic curve [AUC]: 0.80 [95% CI: 0.74, 0.83]; Brier score: 0.08) to predict MACE in female individuals included the following variables: age older than 69 years (hazard ratio [HR]: 1.58, <i>P</i> = .01), diabetes mellitus (HR: 1.47, <i>P</i> = .03), pharmacologic test (HR: 1.63, <i>P</i> = .01), ST-segment depression (≥1 mm) (HR: 2.02, <i>P</i> < .001), myocardial ischemia greater than 5% (HR: 2.21, <i>P</i> < .001), perfusion defect at rest greater than 9% (HR: 1.96, <i>P</i> = .009), perfusion defect at stress greater than 6% (HR: 1.63, <i>P</i> = .03), and end-systolic volume index greater than 15 mL (HR: 2.04, <i>P</i> < .001). During validation, the model achieved moderate performance (AUC: 0.78 [95% CI: 0.70, 0.83]). CORSWO obtained from these variables allowed for stratification of female individuals into four risk levels: low (score: 0-3, HR: 1), moderate (score: 4-6, HR: 1.58), high (score: 7-11, HR: 4.13), and very high (score: >11, HR: 13.87). The high and very high risk levels (HR: 5.29) predicted MACE in female individuals, with excellent performance (AUC: 0.78 [95% CI: 0.72, 0.80]). Conclusion With clinical, stress test, and gSPECT MPI variables, CORSWO effectively stratified female individuals according to coronary risk and was able to detect those with high and very high risk. <b>Keywords:</b> SPECT, Cardiac, Coronary Arteries, Women, Risk Stratification, Cardiac Event, CORSWO, MACE, Gated SPECT <i>Supplemental material is available for this article.</i> ©RSNA, 2024.</p>","PeriodicalId":21168,"journal":{"name":"Radiology. Cardiothoracic imaging","volume":"6 6","pages":"e230381"},"PeriodicalIF":3.8000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Prediction of Major Adverse Coronary Events Using the Coronary Risk Score in Women.\",\"authors\":\"Guillermo Romero-Farina, Santiago Aguadé-Bruix, Ignacio Ferreira-González\",\"doi\":\"10.1148/ryct.230381\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Purpose To establish a COronary Risk Score in WOmen (CORSWO) to predict major adverse coronary events (MACE). Materials and Methods This retrospective analysis included 2226 female individuals (mean age, 66.7 years ± 11.6 [SD]) from a cohort of 25 943 consecutive patients referred for clinical gated SPECT myocardial perfusion imaging (gSPECT MPI). During the follow-up (mean, 4 years ± 2.7) after gSPECT MPI, occurrence of MACE (unstable angina requiring hospitalization, nonfatal myocardial infarction, coronary revascularization, cardiac death) was assessed. The patients were divided into training (<i>n</i> = 1460) and validation (<i>n</i> = 766) groups. To obtain the predictor model, multiple Cox regression analyses were performed. Results In the training group, 148 female individuals had MACE (2.6% per year). The best model (area under the receiver operating characteristic curve [AUC]: 0.80 [95% CI: 0.74, 0.83]; Brier score: 0.08) to predict MACE in female individuals included the following variables: age older than 69 years (hazard ratio [HR]: 1.58, <i>P</i> = .01), diabetes mellitus (HR: 1.47, <i>P</i> = .03), pharmacologic test (HR: 1.63, <i>P</i> = .01), ST-segment depression (≥1 mm) (HR: 2.02, <i>P</i> < .001), myocardial ischemia greater than 5% (HR: 2.21, <i>P</i> < .001), perfusion defect at rest greater than 9% (HR: 1.96, <i>P</i> = .009), perfusion defect at stress greater than 6% (HR: 1.63, <i>P</i> = .03), and end-systolic volume index greater than 15 mL (HR: 2.04, <i>P</i> < .001). During validation, the model achieved moderate performance (AUC: 0.78 [95% CI: 0.70, 0.83]). CORSWO obtained from these variables allowed for stratification of female individuals into four risk levels: low (score: 0-3, HR: 1), moderate (score: 4-6, HR: 1.58), high (score: 7-11, HR: 4.13), and very high (score: >11, HR: 13.87). The high and very high risk levels (HR: 5.29) predicted MACE in female individuals, with excellent performance (AUC: 0.78 [95% CI: 0.72, 0.80]). Conclusion With clinical, stress test, and gSPECT MPI variables, CORSWO effectively stratified female individuals according to coronary risk and was able to detect those with high and very high risk. <b>Keywords:</b> SPECT, Cardiac, Coronary Arteries, Women, Risk Stratification, Cardiac Event, CORSWO, MACE, Gated SPECT <i>Supplemental material is available for this article.</i> ©RSNA, 2024.</p>\",\"PeriodicalId\":21168,\"journal\":{\"name\":\"Radiology. Cardiothoracic imaging\",\"volume\":\"6 6\",\"pages\":\"e230381\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Radiology. Cardiothoracic imaging\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1148/ryct.230381\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Radiology. Cardiothoracic imaging","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1148/ryct.230381","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
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