Comparative Analysis of the Effectiveness of Riskometer Scales in Predicting the Risk of in-Hospital Mortality in Patients With ST-Segment Elevation Myocardial Infarction After Percutaneous Coronary Intervention.

IF 0.5 4区 医学 Q4 CARDIAC & CARDIOVASCULAR SYSTEMS Kardiologiya Pub Date : 2024-08-31 DOI:10.18087/cardio.2024.8.n2602
B I Geltser, K I Shahgeldyan, I G Domzhalov, N S Kuksin, V N Kotelnikov, E A Kokarev
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Abstract

Aim: Comparative evaluation of the effectiveness of riskometer scales in predicting in-hospital death (IHD) in patients with ST-segment elevation myocardial infarction (STEMI) after percutaneous coronary intervention (PCI) and the development of new models based on machine learning methods.

Material and methods: A single-center cohort retrospective study was conducted using data from 4,675 electronic medical records of patients with STEMI (3,202 men and 1,473 women) with a median age of 63 years who underwent emergency PCI. Two groups of patients were isolated: group 1 included 318 (6.8%) patients who died in hospital; group 2 consisted of 4,359 (93.2%) patients with a favorable outcome. The GRACE, CADILLAC, TIMI-STe, PAMI, and RECORD scales were used to assess the risk of IHD. Prognostic models of IHD predicted by the sums of these scale scores were developed using single- and multivariate logistic regression, stochastic gradient boosting, and artificial neural networks (ANN). Risk of adverse events was stratified based on the ANN model data by calculating the median values of predicted probabilities of IHD in the compared groups.

Results: Comparative analysis of the prognostic value of individual scales for the STEMI patients showed differences in the quality of the risk stratification for IHD after PCI. The GRACE scale had the highest prognostic accuracy, while the PAMI scale had the lowest accuracy. The CADILLAC and TIMI-STe scales had acceptable and comparable prognostic abilities, while the RECORD scale showed a significant proportion of false-positive results. The integrative ANN model, the predictors of which were the scores of 5 scales, was superior in the prediction accuracy to the algorithms of single- and multivariate logistic regression and stochastic gradient boosting. Based on the ANN model data, the probability of IHD was stratified into low (<0.3%), medium (0.3-9%), high (9-17%), and very high (>17%) risk groups.

Conclusion: The GRACE, CADILLAC and TIMI-STe scales have advantages in the stratification accuracy of IHD risk in patients with STEMI after PCI compared to the PAMI and RECORD scales. The integrated ANN model that combines the prognostic resource of the five analyzed scales, had better quality criteria, and the stratification algorithm based on the data of this model was characterized by accurate identification of STEMI patients with high and very high risk of IHD after PCI.

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经皮冠状动脉介入术后 ST 段抬高型心肌梗死患者院内死亡风险的风险量表预测效果对比分析。
目的:比较评估风险量表在预测经皮冠状动脉介入治疗(PCI)后ST段抬高型心肌梗死(STEMI)患者院内死亡(IHD)方面的有效性,并开发基于机器学习方法的新模型:我们利用 4,675 份 STEMI 患者(3,202 名男性和 1,473 名女性)的电子病历数据开展了一项单中心队列回顾性研究,这些患者接受了急诊 PCI,中位年龄为 63 岁。其中分为两组:第一组包括 318 名(6.8%)在医院死亡的患者;第二组包括 4359 名(93.2%)预后良好的患者。GRACE、CADILLAC、TIMI-STe、PAMI和RECORD量表用于评估IHD风险。利用单变量和多变量逻辑回归、随机梯度提升和人工神经网络(ANN)建立了由这些量表得分之和预测的 IHD 预后模型。根据人工神经网络模型数据,通过计算比较组的 IHD 预测概率中值,对不良事件风险进行分层:对 STEMI 患者各量表预后价值的比较分析表明,PCI 后 IHD 风险分层的质量存在差异。GRACE量表的预后准确性最高,而PAMI量表的准确性最低。CADILLAC量表和TIMI-STe量表的预后能力可以接受且不相上下,而RECORD量表则显示出相当比例的假阳性结果。综合 ANN 模型的预测因子是 5 个量表的评分,其预测准确性优于单变量和多变量逻辑回归算法以及随机梯度提升算法。根据 ANN 模型的数据,IHD 的概率被分为低(0.3%)、中(0.3%-9%)、高(9%-17%)和极高(17%)风险组:结论:GRACE、CADILLAC 和 TIMI-STe 量表与 PAMI 和 RECORD 量表相比,在对 PCI 后 STEMI 患者进行 IHD 风险分层的准确性方面具有优势。综合了五个分析量表的预后资源的集成 ANN 模型具有更好的质量标准,基于该模型数据的分层算法的特点是能准确识别 STEMI 患者在 PCI 术后发生 IHD 的高风险和极高风险。
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来源期刊
Kardiologiya
Kardiologiya 医学-心血管系统
CiteScore
1.70
自引率
20.00%
发文量
94
审稿时长
3-8 weeks
期刊介绍: “Kardiologiya” (Cardiology) is a monthly scientific, peer-reviewed journal committed to both basic cardiovascular medicine and practical aspects of cardiology. As the leader in its field, “Kardiologiya” provides original coverage of recent progress in cardiovascular medicine. We publish state-of-the-art articles integrating clinical and research activities in the fields of basic cardiovascular science and clinical cardiology, with a focus on emerging issues in cardiovascular disease. Our target audience spans a diversity of health care professionals and medical researchers working in cardiovascular medicine and related fields. The principal language of the Journal is Russian, an additional language – English (title, authors’ information, abstract, keywords). “Kardiologiya” is a peer-reviewed scientific journal. All articles are reviewed by scientists, who gained high international prestige in cardiovascular science and clinical cardiology. The Journal is currently cited and indexed in major Abstracting & Indexing databases: Web of Science, Medline and Scopus. The Journal''s primary objectives Contribute to raising the professional level of medical researchers, physicians and academic teachers. Present the results of current research and clinical observations, explore the effectiveness of drug and non-drug treatments of heart disease, inform about new diagnostic techniques; discuss current trends and new advancements in clinical cardiology, contribute to continuing medical education, inform readers about results of Russian and international scientific forums; Further improve the general quality of reviewing and editing of manuscripts submitted for publication; Provide the widest possible dissemination of the published articles, among the global scientific community; Extend distribution and indexing of scientific publications in major Abstracting & Indexing databases.
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