Weekes Anthony J, Pikus Angela M, Hambright Parker L, Goonan Kelly L, O'Connell Nathaniel
Atrium Health's Carolinas Medical Center, Department of Emergency Medicine, Charlotte, North Carolina.
Wake Forest School of Medicine, Department of Biostatistics and Data Science, Winston-Salem, North Carolina.
West J Emerg Med. 2025 Mar;26(2):219-232. doi: 10.5811/westjem.20763.
Most pulmonary embolism response teams (PERT) use a radiologist-determined right ventricle to left ventricle ratio (RV:LV) cut-off of 1.0 to risk-stratify pulmonary embolism (PE) patients. Continuous measurements from computed tomography pulmonary angiograms (CTPAs) may improve risk stratification. We assessed associations of CTPA cardiac measurements with acute clinical deterioration and use of advanced PE interventions.
This was a retrospective study of a PE registry used by eight affiliated emergency departments. We used an artificial intelligence (AI) algorithm to measure RV:LV on anonymized CTPAs from registry patients for whom the PERT was activated (2018-2023) by institutional guidelines. Primary outcome was in-hospital PE-related clinical deterioration defined as cardiac arrest, vasoactive medication use for hypotension, or rescue respiratory interventions. Secondary outcome was advanced intervention use. We used bivariable and multivariable analyses. For the latter, we used least absolute shrinkage and selection operator (LASSO) and random forest (RF) to determine associations of all candidate variables with the primary outcome (clinical deterioration), and the Youden index to determine RV:LV optimal cut-offs for primary outcome.
Artificial intelligence analyzed 1,467 CTPAs, with 88% agreement on RV:LV categorization with radiologist reports (kappa 0.36, 95% confidence interval [CI] 0.28-0.43). Of 1,639 patients, 190 (11.6%) had PE-related clinical deterioration, and 314 (19.2%) had advanced interventions. Mean RV:LV were 1.50 (0.39) vs 1.30 (0.32) for those with and without clinical deterioration and 1.62 (0.33) vs 1.35 (0.32) for those with and without advanced intervention use. The RV:LV cut-off of 1.0 by AI and radiologists had 0.02 and 0.53 -values for clinical deterioration, respectively. With adjusted LASSO, top clinical deterioration predictors were cardiac arrest at presentation, lowest systolic blood pressure, and intensive care unit admission. The RV:LV measurement was a top 10 predictor of clinical deterioration by RF. Optimal cut-off for RV:LV was 1.54 with odds ratio of 2.50 (1.85, 3.45) and area under the curve 0.6 (0.66, 0.70).
Artifical intelligence-derived RV:LV measurements ≥1.5 on initial CTPA had strong associations with in-hospital clinical deterioration and advanced interventions in a large PERT database. This study points to the potential of capitalizing on immediately available CTPA RV:LV measurements for gauging PE severity and risk stratification.
大多数肺栓塞反应团队（PERT）使用放射科医生确定的右心室与左心室比值（RV:LV）截断值1.0对肺栓塞（PE）患者进行风险分层。计算机断层扫描肺动脉造影（CTPA）的连续测量可能会改善风险分层。我们评估了CTPA心脏测量值与急性临床恶化及高级PE干预措施使用之间的关联。
这是一项对八个附属急诊科使用的PE登记处进行的回顾性研究。我们使用人工智能（AI）算法，对登记处患者（2018 - 2023年）符合机构指南激活PERT条件的匿名CTPA上的RV:LV进行测量。主要结局是住院期间与PE相关的临床恶化，定义为心脏骤停、使用血管活性药物治疗低血压或进行挽救性呼吸干预。次要结局是高级干预措施的使用。我们采用了双变量和多变量分析。对于多变量分析，我们使用最小绝对收缩和选择算子（LASSO）和随机森林（RF）来确定所有候选变量与主要结局（临床恶化）之间的关联，并使用尤登指数来确定主要结局的RV:LV最佳截断值。
人工智能分析了1467例CTPA，与放射科医生报告的RV:LV分类一致性为88%（kappa值0.36，95%置信区间[CI] 0.28 - 0.43）。在1639例患者中，190例（11.6%）出现与PE相关的临床恶化，314例（19.2%）接受了高级干预。临床恶化组和未恶化组的平均RV:LV分别为1.50（0.39）和1.30（0.32），接受高级干预组和未接受干预组分别为1.62（0.33）和1.35（0.32）。AI和放射科医生确定的RV:LV截断值1.0对于临床恶化的预测值分别为0.02和0.53。经调整的LASSO分析显示，临床恶化的主要预测因素为就诊时心脏骤停、最低收缩压和入住重症监护病房。RV:LV测量值是RF预测临床恶化的前10个因素之一。RV:LV的最佳截断值为1.54，优势比为2.50（1.85，3.45），曲线下面积为0.6（0.66，0.70）。
在一个大型PERT数据库中，初始CTPA上人工智能得出的RV:LV测量值≥1.5与住院期间临床恶化和高级干预措施有很强的关联。本研究指出了利用CTPA上即时可得的RV:LV测量值来评估PE严重程度和进行风险分层的潜力。
