Retrospective analysis of the occurrence of secondary pulmonary hypertension in patients with viral pneumonia based on ultrasound examination of the heart in patients with viral pneumonia in the context of the COVID-19 pandemic

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Potential for inhibition of checkpoint kinases 1/2 in pulmonary fibrosis and secondary pulmonary hypertension

BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic lung disease characterised by exuberant tissue remodelling and associated with high unmet medical needs. Outcomes are even worse when IPF results in secondary pulmonary hypertension (PH). Importantly, exaggerated resistance to cell death, excessive proliferation and enhanced synthetic capacity are key endophenotypes of both fibroblasts and pulmonary artery smooth muscle cells, suggesting shared molecular pathways. Under persistent injury, sustained activation of the DNA damage response (DDR) is integral to the preservation of cells survival and their capacity to proliferate. Checkpoint kinases 1 and 2 (CHK1/2) are key components of the DDR. The objective of this study was to assess the role of CHK1/2 in the development and progression of IPF and IPF+PH.Methods and resultsIncreased expression of DNA damage markers and CHK1/2 were observed in lungs, remodelled pulmonary arteries and isolated fibroblasts from IPF patients and animal models. Blockade of CHK1/2 expression or activity-induced DNA damage overload and reverted the apoptosis-resistant and fibroproliferative phenotype of disease cells. Moreover, inhibition of CHK1/2 was sufficient to interfere with transforming growth factor beta 1-mediated fibroblast activation. Importantly, pharmacological inhibition of CHK1/2 using LY2606368 attenuated fibrosis and pulmonary vascular remodelling leading to improvement in respiratory mechanics and haemodynamic parameters in two animal models mimicking IPF and IPF+PH.ConclusionThis study identifies CHK1/2 as key regulators of lung fibrosis and provides a proof of principle for CHK1/2 inhibition as a potential novel therapeutic option for IPF and IPF+PH.

Implanting the HeartMate 6 (total artificial heart)

The HeartMate 3 is a ventricular assist device that supports the heart with a centrifugal continuous flow. It contains a fully levitated rotor to minimize hemolysis and was initially designed as an apical intrapericardial implant. It can be used as a bridge to a transplant, to recovery, or to destination therapy. After we excise the ventricles, we implant 2 HeartMate 3 devices as a total artificial heart (HeartMate 6). The patient was 35 years old when the devices were implanted and had been diagnosed with Yamaguchi syndrome (apical hypertrophic cardiomyopathy) at 13 years of age. Being listed for a transplant was not an option due to secondary pulmonary hypertension. Furthermore, the conventional method of apically implanting a left ventricular assist device was not possible due to the underlying pathology. A HeartMate 6 implant as a bridge to transplant therapy was planned. Additionally, a CardioMEMS HF System was implanted to monitor the pulmonary artery pressure. The video tutorial provides step-by-step instructions for implanting 2 HeartMate 3 devices as a total artificial heart.

Development of Predictive Risk Models for All-cause Mortality in Pulmonary Hypertension using Machine Learning

BackgroundPulmonary hypertension, a progressive lung disorder with symptoms such as breathlessness and loss of exercise capacity, is highly debilitating and has a negative impact on the quality of life. In this study, we examined whether a multi-parametric approach using machine learning can improve mortality prediction.MethodsA population-based territory-wide cohort of pulmonary hypertension patients from January 1, 2000 to December 31, 2017 were retrospectively analyzed. Significant predictors of all-cause mortality were identified. Easy-to-use frailty indexes predicting primary and secondary pulmonary hypertension were derived and stratification performances of the derived scores were compared. A factorization machine model was used for the development of an accurate predictive risk model and the results were compared to multivariate logistic regression, support vector machine, random forests, and multilayer perceptron.ResultsThe cohorts consist of 2562 patients with either primary (n=1009) or secondary (n=1553) pulmonary hypertension. Multivariate Cox regression showed that age, prior cardiovascular, respiratory and kidney diseases, hypertension, number of emergency readmissions within 28 days of discharge were all predictors of all-cause mortality. Easy-to-use frailty scores were developed from Cox regression. A factorization machine model demonstrates superior risk prediction improvements for both primary (precision: 0.90, recall: 0.89, F1-score: 0.91, AUC: 0.91) and secondary pulmonary hypertension (precision: 0.87, recall: 0.86, F1-score: 0.89, AUC: 0.88) patients.ConclusionWe derived easy-to-use frailty scores predicting mortality in primary and secondary pulmonary hypertension. A machine learning model incorporating multi-modality clinical data significantly improves risk stratification performance.