Predictive Modeling of Secondary Pulmonary Hypertension in Left Ventricular Diastolic Dysfunction
Predictive Modeling of Secondary Pulmonary Hypertension in Left Ventricular Diastolic Dysfunction
复制标题
左心室舒张功能不全继发性肺动脉高压的预测模型
DOI：
10.1101/2020.04.23.20073601
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发表时间：
2021
影响因子：
4
通讯作者：
Schiavazzi, Daniele E.
中科院分区：
文献类型：
--
作者：
Harrod, Karlyn K.;Rogers, Jeffrey L.;Feinstein, Jeffrey A.;Marsden, Alison L.;Schiavazzi, Daniele E.
舒张功能障碍是一种常见的病理，发生在约三分之一的心力衰竭患者中。这种情况可能与心输出量或体循环压力的显著降低无关，因此比收缩期疾病更难诊断。左心室舒张受损或僵硬度增加导致上游肺动脉压增加，被归类为继发性或II组肺动脉高压（2018 Nice分类）。这可能导致右心室后负荷增加，从而导致右心室衰竭。因此，肺动脉压升高是舒张性心力衰竭（有时称为射血分数保留性心力衰竭，HFpEF）的重要临床指标，与相关死亡率显著相关。然而，该量的准确测量通常通过侵入性导管插入术和症状发作后获得。在这项研究中，我们使用微分代数循环模型的血流动力学一致性来预测其他可能无创的临床数据中成人患者的肺动脉压。我们调查了几个方面的问题，包括模型输出的能力，以代表一个足够宽的病理谱，模型的参数的可识别性，和预测的肺动脉压的准确性。我们还发现，使用同化的模型参数作为特征的分类器是免费的缺失数据的问题，并能够检测肺动脉高压具有足够高的精度。对于一个队列的82例患者患有不同程度的心力衰竭的严重程度，我们表明，收缩压，舒张压和楔肺压可以估计平均在8，6和6毫米汞柱，分别。我们还表明，在一般情况下，增加数据的可用性导致改进的预测。
Diastolic dysfunction is a common pathology occurring in about one third of patients affected by heart failure. This condition may not be associated with a marked decrease in cardiac output or systemic pressure and therefore is more difficult to diagnose than its systolic counterpart. Compromised relaxation or increased stiffness of the left ventricle induces an increase in the upstream pulmonary pressures, and is classified as secondary or group II pulmonary hypertension (2018 Nice classification). This may result in an increase in the right ventricular afterload leading to right ventricular failure. Elevated pulmonary pressures are therefore an important clinical indicator of diastolic heart failure (sometimes referred to asheart failure with preserved ejection fraction, HFpEF), showing significant correlation with associated mortality. However, accurate measurements of this quantity are typically obtained through invasive catheterization and after the onset of symptoms. In this study, we use the hemodynamic consistency of a differential-algebraic circulation model to predict pulmonary pressures in adult patients from other, possibly non-invasive, clinical data. We investigate several aspects of the problem, including the ability of model outputs to represent a sufficiently wide pathologic spectrum, the identifiability of the model's parameters, and the accuracy of the predicted pulmonary pressures. We also find that a classifier using the assimilated model parameters as features is free from the problem of missing data and is able to detect pulmonary hypertension with sufficiently high accuracy. For a cohort of 82 patients suffering from various degrees of heart failure severity, we show that systolic, diastolic, and wedge pulmonary pressures can be estimated on average within 8, 6, and 6 mmHg, respectively. We also show that, in general, increased data availability leads to improved predictions.
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DOI：
10.1016/s0735-1097(83)80278-2
发表时间：
1983-01-01
影响因子：
24
作者：
GORDON, EP;SCHNITTGER, I;POPP, RL
通讯作者：
POPP, RL
影响因子：
64.8
作者：
E. M. Wright
通讯作者：
E. M. Wright
计算机模拟研究
DOI：
--
发表时间：
2021
期刊：
Encyclopedic Dictionary of Archaeology
影响因子：
--
作者：
D. Kanto;M. Salo;R. Happonen;T. Vahlberg;J. Kanto
通讯作者：
J. Kanto
影响因子：
24
作者：
Lam, Carolyn S. P.;Roger, Veronique L.;Rodeheffer, Richard J.;Borlaug, Barry A.;Enders, Felicity T.;Redfield, Margaret M.
通讯作者：
Redfield, Margaret M.
DOI：
10.1016/0141-5425(87)90094-x
发表时间：
1987-01-01
期刊：
JOURNAL OF BIOMEDICAL ENGINEERING
影响因子：
--
作者：
CAPPELLO, A;CEVENINI, G;AVANZOLINI, G
通讯作者：
AVANZOLINI, G