B I Geltser, I G Domzhalov, K I Shakhgeldyan, N S Kuksin, E A Kokarev, R L Pak, V N Kotelnikov
{"title":"ST段抬高型心肌梗死患者住院死亡率的预测:风险测量技术的发展及其有效性评估(综述)","authors":"B I Geltser, I G Domzhalov, K I Shakhgeldyan, N S Kuksin, E A Kokarev, R L Pak, V N Kotelnikov","doi":"10.17691/stm2024.16.4.07","DOIUrl":null,"url":null,"abstract":"<p><p>Risk stratification of hospital mortality in patients with ST segment elevation myocardial infarction on the electrocardiogram is an important part of the specialized medical care provision. The systematic review presents scientific literature data characterizing the predictive value of both classical prognostic scales (GRACE, CADDILLAC, TIMI risk score for STEMI, RECORD, etc.) and new risk measurement tools developed on the basis of modern machine learning techniques. Most studies on this issue are often focused on the search for new predictors of adverse events, which allow to detail the relations between indicators of the clinical and functional status of patients and the end point of the study. Here, an important task is to develop hospital mortality prognostic algorithms characterized by explainable artificial intelligence and trusted by doctors.</p>","PeriodicalId":520289,"journal":{"name":"Sovremennye tekhnologii v meditsine","volume":"16 4","pages":"61-72"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773138/pdf/","citationCount":"0","resultStr":"{\"title\":\"Prediction of Hospital Mortality in Patients with ST Segment Elevation Myocardial Infarction: Evolution of Risk Measurement Techniques and Assessment of Their Effectiveness (Review).\",\"authors\":\"B I Geltser, I G Domzhalov, K I Shakhgeldyan, N S Kuksin, E A Kokarev, R L Pak, V N Kotelnikov\",\"doi\":\"10.17691/stm2024.16.4.07\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Risk stratification of hospital mortality in patients with ST segment elevation myocardial infarction on the electrocardiogram is an important part of the specialized medical care provision. The systematic review presents scientific literature data characterizing the predictive value of both classical prognostic scales (GRACE, CADDILLAC, TIMI risk score for STEMI, RECORD, etc.) and new risk measurement tools developed on the basis of modern machine learning techniques. Most studies on this issue are often focused on the search for new predictors of adverse events, which allow to detail the relations between indicators of the clinical and functional status of patients and the end point of the study. Here, an important task is to develop hospital mortality prognostic algorithms characterized by explainable artificial intelligence and trusted by doctors.</p>\",\"PeriodicalId\":520289,\"journal\":{\"name\":\"Sovremennye tekhnologii v meditsine\",\"volume\":\"16 4\",\"pages\":\"61-72\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11773138/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sovremennye tekhnologii v meditsine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.17691/stm2024.16.4.07\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/8/30 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sovremennye tekhnologii v meditsine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.17691/stm2024.16.4.07","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/8/30 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
Prediction of Hospital Mortality in Patients with ST Segment Elevation Myocardial Infarction: Evolution of Risk Measurement Techniques and Assessment of Their Effectiveness (Review).
Risk stratification of hospital mortality in patients with ST segment elevation myocardial infarction on the electrocardiogram is an important part of the specialized medical care provision. The systematic review presents scientific literature data characterizing the predictive value of both classical prognostic scales (GRACE, CADDILLAC, TIMI risk score for STEMI, RECORD, etc.) and new risk measurement tools developed on the basis of modern machine learning techniques. Most studies on this issue are often focused on the search for new predictors of adverse events, which allow to detail the relations between indicators of the clinical and functional status of patients and the end point of the study. Here, an important task is to develop hospital mortality prognostic algorithms characterized by explainable artificial intelligence and trusted by doctors.