Clinical and Population Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, School of Medicine, Faculty of Medicine and Health, University of Leeds, Leeds, LS2 9JT, UK; Leeds Institute for Data Analytics, University of Leeds, Leeds, LS2 9JT, UK.
Leeds Institute for Data Analytics, University of Leeds, Leeds, LS2 9JT, UK; School of Molecular and Cellular Biology, Faculty of Biological Sciences, University of Leeds, Leeds, LS2 9JT, UK.
EBioMedicine. 2023 Oct;96:104792. doi: 10.1016/j.ebiom.2023.104792. Epub 2023 Sep 21.
Knowledge of post-myocardial infarction (MI) disease risk to date is limited-yet the number of survivors of MI has increased dramatically in recent decades. We investigated temporally ordered sequences of all conditions following MI in nationwide electronic health record data through the application of process mining.
We conducted a national retrospective cohort study of all hospitalisations (145,670,448 episodes; 34,083,204 individuals) admitted to NHS hospitals in England (1st January 2008-31st January 2017, final follow-up 27th March 2017). Through process mining, we identified trajectories of all major disease diagnoses following MI and compared their relative risk (RR) and all-cause mortality hazard ratios (HR) to a risk-set matched non-MI control cohort using Cox proportional hazards and flexible parametric survival models.
Among a total of 375,669 MI patients (130,758 females; 34.8%) and 1,878,345 matched non-MI patients (653,790 females; 34.8%), we identified 28,799 unique disease trajectories. The accrual of multiple circulatory diagnoses was more common amongst MI patients (RR 4.32, 95% CI 3.96-4.72) and conferred an increased risk of death (HR 1.32, 1.13-1.53) compared with matched controls. Trajectories featuring neuro-psychiatric diagnoses (including anxiety and depression) following circulatory disorders were markedly more common and had increased mortality post MI (HR ranging from 1.11 to 1.73) compared with non-MI individuals.
These results provide an opportunity for early intervention targets for survivors of MI-such as increased focus on the psychological and behavioural pathways-to mitigate ongoing adverse disease trajectories, multimorbidity, and premature mortality.
British Heart Foundation; Alan Turing Institute.
目前对心肌梗死后（MI）疾病风险的了解有限，然而，近几十年来，MI 幸存者的数量急剧增加。我们通过应用流程挖掘技术，从全国性电子健康记录数据中调查了 MI 后所有疾病的时间顺序序列。
我们对英格兰 NHS 医院（2008 年 1 月 1 日至 2017 年 1 月 31 日期间的 145670448 例住院治疗，34083204 人）的所有住院治疗进行了一项全国性回顾性队列研究。通过流程挖掘，我们确定了 MI 后所有主要疾病诊断的轨迹，并使用 Cox 比例风险和灵活参数生存模型，将其相对风险（RR）和全因死亡率风险比（HR）与风险集匹配的非 MI 对照组进行了比较。
在总共 375669 例 MI 患者（130758 名女性；34.8%）和 1878345 名匹配的非 MI 患者（653790 名女性；34.8%）中，我们确定了 28799 种独特的疾病轨迹。在 MI 患者中，循环系统多种诊断的累积更为常见（RR 4.32，95%CI 3.96-4.72），并且与匹配的对照组相比，死亡风险增加（HR 1.32，1.13-1.53）。在循环系统疾病后出现神经精神诊断（包括焦虑和抑郁）的轨迹明显更为常见，并且与非 MI 个体相比，MI 后死亡率更高（HR 范围为 1.11 至 1.73）。
这些结果为 MI 幸存者提供了早期干预目标的机会，例如更加关注心理和行为途径，以减轻持续的不良疾病轨迹、多种合并症和过早死亡。
英国心脏基金会；艾伦·图灵研究所。
