摘要
一位新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-人工智能的新研究是一篇报道的主题。根据来自德国Bad Oeynhausen的新闻，NewsRx记者报道，研究表明：“三维分析得出的基线右心室(RV)功能已被证明在接受经导管三尖瓣修复术(TTVR)的患者中具有预测作用。这些繁琐分析的复杂性使得基于稳定成像方法选择患者具有挑战性。”我们的新闻记者从Ruhr-Universitat Bo Chum的研究中获得了一句话，人工智能(AI)驱动的计算机断层扫描(CT)RV分割可以作为评估PRI或TVR患者的快速和预测工具。患有严重三尖瓣返流的患者接受全L周期心脏CT检查。AI驱动的分析与常规CT分析进行比较。结果指标与TVR后因耳衰竭或死亡而不再住院的生存率相关。100例患者（平均年龄77±8岁，女性63%）的CT分析显示，与常规的核心实验室评估的CT分析相比，腔定量具有极好的相关性（R 0.963-0.966；p<0.001）。在1年（平均随访229±134天）时，主要终点在RV射血分数降低(EF)<50%（36.6%vs 13.7%；HR 2.864，CI 1.21 2-6.763）功能障碍RVs定义为舒张末期RV容积>210ml和RV EF<50%的患者比功能障碍RVs患者预后更差(43.7%vs 12.2%;HR 3.753,CI 1.621-8.693;P=0.002),衍生RVEF和功能障碍RV是TTVR后死亡和住院的预测因素。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News-New research on Artificial Intelligenc e is the subject of a report. According to news originating from Bad Oeynhausen, Germany, by NewsRx correspondents, research stated, "Baseline right ventricular (RV) function derived from 3-dimensional analyses has been demonstrated to be p redictive in patients undergoing transcatheter tricuspid valve repair (TTVR). Th e complex nature of these cumbersome analyses makes patient selection based on e stablished imaging methods challenging." Our news journalists obtained a quote from the research from Ruhr-Universitat Bo chum, "Artificial intelligence (AI)-driven computed tomography (CT) segmentation of the RV might serve as a fast and predictive tool for evaluating patients pri or to TTVR. Patients suffering from severe tricuspid regurgitation underwent ful l cycle cardiac CT. AI-driven analyses were compared to conventional CT analyses . Outcome measures were correlated with survival free of rehospitalization for h eart-failure or death after TTVR as the primary endpoint. Automated AI-based ima ge CT-analysis from 100 patients (mean age 77 ± 8 years, 63% femal e) showed excellent correlation for chamber quantification compared to conventio nal, core-lab evaluated CT analysis (R 0.963-0.966; p<0.00 1). At 1 year (mean follow-up 229 ± 134 days) the primary endpoint occurred sign ificantly more frequently in patients with reduced RV ejection fraction (EF) <50 % (36.6% vs. 13.7%; HR 2.864, CI 1.21 2-6.763; p = 0.016). Furthermore, patients with dysfunctional RVs defined as end -diastolic RV volume > 210 ml and RV EF <50% demonstrated worse outcome than patients with functional RVs ( 43.7% vs. 12.2%; HR 3.753, CI 1.621-8.693; p = 0.002) . Derived RVEF and dysfunctional RV were predictors for death and hospitalizatio n after TTVR."
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