Verstraelen Tom E, van Barreveld Marit, van Dessel Pascal H F M, Boersma Lucas V A, Delnoy Peter-Paul P H M, Tuinenburg Anton E, Theuns Dominic A M J, van der Voort Pepijn H, Kimman Gerardus P, Buskens Erik, Hulleman Michiel, Allaart Cornelis P, Strikwerda Sipke, Scholten Marcoen F, Meine Mathias, Abels René, Maass Alexander H, Firouzi Mehran, Widdershoven Jos W M G, Elders Jan, van Gent Marco W F, Khan Muchtiar, Vernooy Kevin, Grauss Robert W, Tukkie Raymond, van Erven Lieselot, Spierenburg Han A M, Brouwer Marc A, Bartels Gerard L, Bijsterveld Nick R, Borger van der Burg Alida E, Vet Mattheus W, Derksen Richard, Knops Reinoud E, Bracke Frank A L E, Harden Markus, Sticherling Christian, Willems Rik, Friede Tim, Zabel Markus, Dijkgraaf Marcel G W, Zwinderman Aeilko H, Wilde Arthur A M
Department of Cardiology, Amsterdam UMC, Location AMC, University of Amsterdam, Heart Center, Amsterdam, the Netherlands.
Department of Clinical Epidemiology, Biostatistics and Bio-informatics, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, the Netherlands.
Europace. 2021 Jun 7;23(6):887-897. doi: 10.1093/europace/euab012.
This study was performed to develop and externally validate prediction models for appropriate implantable cardioverter-defibrillator (ICD) shock and mortality to identify subgroups with insufficient benefit from ICD implantation.
We recruited patients scheduled for primary prevention ICD implantation and reduced left ventricular function. Bootstrapping-based Cox proportional hazards and Fine and Gray competing risk models with likely candidate predictors were developed for all-cause mortality and appropriate ICD shock, respectively. Between 2014 and 2018, we included 1441 consecutive patients in the development and 1450 patients in the validation cohort. During a median follow-up of 2.4 (IQR 2.1-2.8) years, 109 (7.6%) patients received appropriate ICD shock and 193 (13.4%) died in the development cohort. During a median follow-up of 2.7 (IQR 2.0-3.4) years, 105 (7.2%) received appropriate ICD shock and 223 (15.4%) died in the validation cohort. Selected predictors of appropriate ICD shock were gender, NSVT, ACE/ARB use, atrial fibrillation history, Aldosterone-antagonist use, Digoxin use, eGFR, (N)OAC use, and peripheral vascular disease. Selected predictors of all-cause mortality were age, diuretic use, sodium, NT-pro-BNP, and ACE/ARB use. C-statistic was 0.61 and 0.60 at respectively internal and external validation for appropriate ICD shock and 0.74 at both internal and external validation for mortality.
Although this cohort study was specifically designed to develop prediction models, risk stratification still remains challenging and no large group with insufficient benefit of ICD implantation was found. However, the prediction models have some clinical utility as we present several scenarios where ICD implantation might be postponed.
本研究旨在开发并外部验证用于预测合适的植入式心律转复除颤器（ICD）电击治疗及死亡率的模型，以识别从ICD植入中获益不足的亚组。
我们招募了计划接受一级预防ICD植入且左心室功能降低的患者。分别针对全因死亡率和合适的ICD电击治疗，开发了基于自抽样法的Cox比例风险模型以及带有可能候选预测因素的Fine和Gray竞争风险模型。在2014年至2018年期间，我们在开发队列中纳入了1441例连续患者，在验证队列中纳入了1450例患者。在中位随访2.4（四分位间距2.1 - 2.8）年期间，开发队列中有109例（7.6%）患者接受了合适的ICD电击治疗，193例（13.4%）患者死亡。在中位随访2.7（四分位间距2.0 - 3.4）年期间，验证队列中有105例（7.2%）患者接受了合适的ICD电击治疗，223例（15.4%）患者死亡。合适的ICD电击治疗的选定预测因素为性别、非持续性室性心动过速（NSVT）、使用血管紧张素转换酶抑制剂/血管紧张素Ⅱ受体拮抗剂（ACE/ARB）、房颤病史、使用醛固酮拮抗剂、使用地高辛、估算肾小球滤过率（eGFR）、使用（新型）口服抗凝药（(N)OAC）以及外周血管疾病。全因死亡率的选定预测因素为年龄、使用利尿剂、血钠、N末端脑钠肽前体（NT-pro-BNP）以及使用ACE/ARB。对于合适的ICD电击治疗，内部验证和外部验证时的C统计量分别为0.61和0.60；对于死亡率，内部验证和外部验证时的C统计量均为0.74。
尽管本队列研究专门设计用于开发预测模型，但风险分层仍然具有挑战性，且未发现从ICD植入中获益不足的大组人群。然而，由于我们展示了几种可能推迟ICD植入的情况，所以这些预测模型具有一定的临床实用性。
