Brunner Michael P, Yu Changhong, Hussein Ayman A, Tarakji Khaldoun G, Wazni Oussama M, Kattan Michael W, Wilkoff Bruce L
Departments of Cardiac Pacing and Electrophysiology.
Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, Ohio.
Heart Rhythm. 2015 Dec;12(12):2381-6. doi: 10.1016/j.hrthm.2015.07.024. Epub 2015 Jul 17.
For each clinical circumstance, the benefits of transvenous lead extraction (TLE) need to be weighed against the risks. Clinical decision-making tools for predicting mortality after TLE are lacking.
To create a preoperative risk score for prediction of 30-day all-cause mortality after TLE of pacemaker and defibrillator leads.
Consecutive patients undergoing TLE at the Cleveland Clinic between August 1996 and August 2011 were included in the analysis. A risk nomogram for predicting 30-day all-cause mortality was developed using baseline clinical variables and multivariable logistic regression modeling. Discrimination and calibration were assessed by using bootstrapping for internal validation. Continuous data are presented as median (25th, 75th percentile); categorical data are presented as number (percentage).
A total of 5521 (4137 [74.9%] pacemaker and 1384 [25.1%] defibrillator) leads were extracted during 2999 TLE procedures (patient age 67.2 [55.2, 76.2] years, 30.2% female). Lead implant duration was 4.7 (2.4, 8.3) years and 2.0 (1.0, 2.0) leads were extracted per procedure. Sixty-seven patients (2.2%) had died by 30 days after TLE. Variables with the highest predictive value for 30-day all-cause mortality included age, body mass index, hemoglobin, end-stage renal disease, left ventricular ejection fraction, New York Heart Association functional class, extraction for infection, number of prior lead extractions performed by the operator, and extraction of a dual-coil defibrillator lead. These variables were used to create a nomogram with a bootstrap-corrected concordance index value of 0.867.
Thirty-day all-cause mortality after TLE can be assessed with good discriminative power using readily available clinical information.
对于每种临床情况，经静脉导线拔除术（TLE）的获益都需要与风险相权衡。目前缺乏预测TLE术后死亡率的临床决策工具。
创建一个术前风险评分系统，用于预测起搏器和除颤器导线TLE术后30天全因死亡率。
纳入1996年8月至2011年8月在克利夫兰诊所接受TLE的连续患者进行分析。使用基线临床变量和多变量逻辑回归模型开发预测30天全因死亡率的风险列线图。通过自举法进行内部验证来评估辨别力和校准度。连续数据以中位数（第25、75百分位数）表示；分类数据以数量（百分比）表示。
在2999例TLE手术中，共拔除了5521根导线（4137根[74.9%]起搏器导线和1384根[25.1%]除颤器导线）（患者年龄67.2[55.2,76.2]岁，女性占30.2%）。导线植入时间为4.7（2.4,8.3）年，每次手术拔除2.0（1.0,2.0）根导线。67例患者（2.2%）在TLE术后30天内死亡。对30天全因死亡率预测价值最高的变量包括年龄、体重指数、血红蛋白、终末期肾病、左心室射血分数、纽约心脏协会心功能分级、因感染进行的拔除、术者既往进行导线拔除的次数以及双线圈除颤器导线的拔除。这些变量被用于创建一个列线图，其自举校正一致性指数值为0.867。
使用容易获得的临床信息，可以很好地辨别TLE术后30天全因死亡率。
