Division of Cardiovascular Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, University of Manchester, Manchester, UK; BHF Manchester Centre for Heart & Lung Magnetic Resonance Research, Manchester University NHS Foundation Trust, Manchester, UK.
Department of Medicine, University of Pittsburgh School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Clinical and Translational Science Institute, University of Pittsburgh, Pittsburgh, PA, USA; UPMC Cardiovascular Magnetic Resonance Center, Heart and Vascular Institute, Pittsburgh, PA, USA.
Lancet Digit Health. 2022 Jun;4(6):e445-e454. doi: 10.1016/S2589-7500(22)00045-0. Epub 2022 May 10.
Identifying people who are at risk of being admitted to hospital (hospitalised) for heart failure and death, and particularly those who have not previously been hospitalised for heart failure, is a priority. We aimed to develop and externally validate a prognostic model involving contemporary deep phenotyping that can be used to generate individual risk estimates of hospitalisation for heart failure or all-cause mortality in patients with, or at risk of, heart failure, but who have not previously been hospitalised for heart failure.
Between June 1, 2016, and May 31, 2018, 3019 consecutive adult patients (aged ≥16 years) undergoing cardiac magnetic resonance (CMR) at Manchester University National Health Service Foundation Trust, Manchester, UK, were prospectively recruited into a model development cohort. Candidate predictor variables were selected according to clinical practice and literature review. Cox proportional hazards modelling was used to develop a prognostic model. The final model was validated in an external cohort of 1242 consecutive adult patients undergoing CMR at the University of Pittsburgh Medical Center Cardiovascular Magnetic Resonance Center, Pittsburgh, PA, USA, between June 1, 2010, and March 25, 2016. Exclusion criteria for both cohorts included previous hospitalisation for heart failure. Our study outcome was a composite of first hospitalisation for heart failure or all-cause mortality after CMR. Model performance was evaluated in both cohorts by discrimination (Harrell's C-index) and calibration (assessed graphically).
Median follow-up durations were 1118 days (IQR 950-1324) for the development cohort and 2117 days (1685-2446) for the validation cohort. The composite outcome occurred in 225 (7·5%) of 3019 patients in the development cohort and in 219 (17·6%) of 1242 patients in the validation cohort. The final, externally validated, parsimonious, multivariable model comprised the predictors: age, diabetes, chronic obstructive pulmonary disease, N-terminal pro-B-type natriuretic peptide, and the CMR variables, global longitudinal strain, myocardial infarction, and myocardial extracellular volume. The median optimism-adjusted C-index for the externally validated model across 20 imputed model development datasets was 0·805 (95% CI 0·793-0·829) in the development cohort and 0·793 (0·766-0·820) in the external validation cohort. Model calibration was excellent across the full risk profile. A risk calculator that provides an estimated risk of hospitalisation for heart failure or all-cause mortality at 3 years after CMR for individual patients was generated.
We developed and externally validated a risk prediction model that provides accurate, individualised estimates of the risk of hospitalisation for heart failure and all-cause mortality in patients with, or at risk of, heart failure, before first hospitalisation. It could be used to direct intensified therapy and closer follow-up to those at increased risk.
The UK National Institute for Health Research, Guerbet Laboratories, and Roche Diagnostics International.
识别有住院（住院）心力衰竭和死亡风险的人，特别是那些以前没有因心力衰竭住院的人，是当务之急。我们旨在开发和外部验证一个涉及当代深度表型的预后模型，该模型可用于生成心力衰竭或全因死亡率的个体风险估计，适用于有或有心力衰竭风险但以前未因心力衰竭住院的患者。
2016 年 6 月 1 日至 2018 年 5 月 31 日，英国曼彻斯特大学国民保健署信托基金的 3019 名连续成年患者（年龄≥16 岁）前瞻性入组模型开发队列，进行心脏磁共振（CMR）检查。候选预测变量根据临床实践和文献综述进行选择。使用 Cox 比例风险模型建立预后模型。在匹兹堡大学医学中心心血管磁共振中心的 1242 名连续成年患者的外部队列中（2010 年 6 月 1 日至 2016 年 3 月 25 日）验证了最终模型。两个队列的排除标准均为以前因心力衰竭住院。我们的研究结果是 CMR 后首次因心力衰竭或全因死亡的复合结果。在两个队列中，通过区分度（Harrell 的 C 指数）和校准（图形评估）来评估模型性能。
开发队列的中位随访时间为 1118 天（IQR 950-1324），验证队列为 2117 天（1685-2446）。在开发队列的 3019 名患者中，有 225 名（7.5%）发生了复合结局，在验证队列的 1242 名患者中，有 219 名（17.6%）发生了复合结局。最终的、外部验证的、简洁的多变量模型包括预测因子：年龄、糖尿病、慢性阻塞性肺疾病、N 端脑钠肽前体和 CMR 变量，包括整体纵向应变、心肌梗死和心肌细胞外体积。在 20 个模型开发数据集的 20 次迭代中，外部验证模型的中位数校正后的 C 指数在开发队列中为 0.805（95%CI 0.793-0.829），在外部验证队列中为 0.793（0.766-0.820）。整个风险谱的校准都非常出色。为患者提供了一种风险计算器，可在 CMR 后 3 年内估计心力衰竭住院和全因死亡率的个体风险。
我们开发并外部验证了一个风险预测模型，该模型可为心力衰竭或心力衰竭风险患者提供准确的个体化住院风险和全因死亡率估计，在首次住院前。它可以用于指导那些风险增加的患者进行强化治疗和更密切的随访。
英国国家卫生研究院、古莱特实验室和罗氏诊断国际公司。
