Department of Physiology, HeartOtago, School of Biomedical Sciences, University of Otago, Dunedin, 9054, New Zealand.
Department of Medicine, HeartOtago, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
Forensic Sci Med Pathol. 2022 Sep;18(3):333-342. doi: 10.1007/s12024-022-00478-1. Epub 2022 Apr 28.
Heart mass can be predicted from heart volume as measured from post-mortem computed tomography (PMCT), but with limited accuracy. Although related to heart mass, age, sex, and body dimensions have not been included in previous studies using heart volume to estimate heart mass. This study aimed to determine whether heart mass estimation can be improved when age, sex, and body dimensions are used as well as heart volume. Eighty-seven (24 female) adult post-mortem cases were investigated. Univariable predictors of heart mass were determined by Spearman correlation and simple linear regression. Stepwise linear regression was used to generate heart mass prediction equations. Heart mass estimate performance was tested using median mass comparison, linear regression, and Bland-Altman plots. Median heart mass (P = 0.0008) and heart volume (P = 0.008) were significantly greater in male relative to female cases. Alongside female sex and body surface area (BSA), heart mass was univariably associated with heart volume in all cases (R = 0.72) and in male (R = 0.70) and female cases (R = 0.64) when segregated. In multivariable regression, heart mass was independently associated with age and BSA (R adjusted = 0.46-0.54). Addition of heart volume improved multivariable heart mass prediction in the total cohort (R adjusted = 0.78), and in male (R adjusted = 0.74) and female (R adjusted = 0.74) cases. Heart mass estimated from multivariable models incorporating heart volume, age, sex, and BSA was more predictive of actual heart mass (R = 0.75-0.79) than models incorporating either age, sex, and BSA only (R = 0.48-0.57) or heart volume only (R = 0.64-0.73). Heart mass can be more accurately predicted from heart volume measured from PMCT when combined with the classical predictors, age, sex, and BSA.
心脏质量可以根据死后计算机断层扫描（PMCT）测量的心脏体积进行预测，但准确性有限。尽管与心脏质量有关，但年龄、性别和身体尺寸在以前使用心脏体积估计心脏质量的研究中并未包括在内。本研究旨在确定当使用心脏体积以及年龄、性别和身体尺寸作为预测因子时，心脏质量的估计是否可以得到改善。对 87 例（24 例为女性）成年死后病例进行了研究。通过 Spearman 相关和简单线性回归确定心脏质量的单变量预测因子。使用逐步线性回归生成心脏质量预测方程。使用中位数质量比较、线性回归和 Bland-Altman 图测试心脏质量估计性能。与女性相比，男性的心脏质量中位数（P=0.0008）和心脏体积中位数（P=0.008）显著更高。除了女性性别和体表面积（BSA）外，在所有病例（R=0.72）和男性病例（R=0.70）和女性病例（R=0.64）中，心脏质量与心脏体积也存在单变量关联。在多变量回归中，心脏质量与年龄和 BSA 独立相关（R 调整=0.46-0.54）。在总队列中，心脏体积的加入改善了多变量心脏质量预测（R 调整=0.78），在男性（R 调整=0.74）和女性（R 调整=0.74）病例中也是如此。从多变量模型中估算的心脏质量，该模型包含心脏体积、年龄、性别和 BSA，比仅包含年龄、性别和 BSA（R=0.48-0.57）或仅包含心脏体积（R=0.64-0.73）的模型更能准确预测实际心脏质量（R=0.75-0.79）。当与经典预测因子年龄、性别和 BSA 相结合时，从 PMCT 测量的心脏体积中可以更准确地预测心脏质量。
