Rodero Cristobal, Baptiste Tiffany M G, Barrows Rosie K, Keramati Hamed, Sillett Charles P, Strocchi Marina, Lamata Pablo, Niederer Steven A
Cardiac Electro-Mechanics Research Group (CEMRG), National Heart and Lung Institute, Imperial College London, London, United Kingdom.
Cardiac Electro-Mechanics Research Group (CEMRG), Department of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Prog Biomed Eng (Bristol). 2023 Jul 1;5(3):032004. doi: 10.1088/2516-1091/acdc71. Epub 2023 Jun 22.
Computational models of the heart are now being used to assess the effectiveness and feasibility of interventions through clinical trials (ISCTs). As the adoption and acceptance of ISCTs increases, best practices for reporting the methodology and analysing the results will emerge. Focusing in the area of cardiology, we aim to evaluate the types of ISCTs, their analysis methods and their reporting standards. To this end, we conducted a systematic review of cardiac ISCTs over the period of 1 January 2012-1 January 2022, following the preferred reporting items for systematic reviews and meta-analysis (PRISMA). We considered cardiac ISCTs of human patient cohorts, and excluded studies of single individuals and those in which models were used to guide a procedure without comparing against a control group. We identified 36 publications that described cardiac ISCTs, with most of the studies coming from the US and the UK. In of the studies, a validation step was performed, although the specific type of validation varied between the studies. ANSYS FLUENT was the most commonly used software in of ISCTs. The specific software used was not reported in of the studies. Unlike clinical trials, we found a lack of consistent reporting of patient demographics, with of the studies not reporting them. Uncertainty quantification was limited, with sensitivity analysis performed in only of the studies. In of the ISCTs, no link was provided to provide easy access to the data or models used in the study. There was no consistent naming of study types with a wide range of studies that could potentially be considered ISCTs. There is a clear need for community agreement on minimal reporting standards on patient demographics, accepted standards for ISCT cohort quality control, uncertainty quantification, and increased model and data sharing.
心脏的计算模型目前正被用于通过临床试验（ISCTs）评估干预措施的有效性和可行性。随着ISCTs的采用和接受程度不断提高，报告方法和分析结果的最佳实践将会出现。聚焦于心脏病学领域，我们旨在评估ISCTs的类型、其分析方法及其报告标准。为此，我们按照系统评价和荟萃分析的首选报告项目（PRISMA），对2012年1月1日至2022年1月1日期间的心脏ISCTs进行了系统评价。我们考虑了人类患者队列的心脏ISCTs，并排除了对个体的研究以及那些使用模型指导手术但未与对照组进行比较的研究。我们确定了36篇描述心脏ISCTs的出版物，其中大部分研究来自美国和英国。在一些研究中进行了验证步骤，尽管不同研究之间验证的具体类型有所不同。ANSYS FLUENT是大多数ISCTs中最常用的软件。在一些研究中未报告所使用的具体软件。与临床试验不同，我们发现患者人口统计学信息的报告缺乏一致性，有一些研究未报告这些信息。不确定性量化有限，只有一些研究进行了敏感性分析。在一些ISCTs中，未提供链接以便轻松访问研究中使用的数据或模型。对于研究类型没有一致的命名，有广泛的研究可能被视为ISCTs。显然需要就患者人口统计学的最低报告标准、ISCT队列质量控制的公认标准、不确定性量化以及增加模型和数据共享达成社区共识。
