scholarly journals Machine learning-guided phenotyping of dilated cardiomyopathy and treatment of heart failure by antisense oligonucleotides: the future has begun

2021 ◽  
Vol 42 (2) ◽  
pp. 139-142
Author(s):  
Filippo Crea
Keyword(s):  
Machine Learning ◽  
Heart Failure ◽  
Dilated Cardiomyopathy ◽  
Antisense Oligonucleotides ◽  
The Future

Myocardial Blood Flow Response to Pacing Tachycardia and to Dipyridamole Infusion in Patients With Dilated Cardiomyopathy Without Overt Heart Failure

Circulation ◽  
1995 ◽  
Vol 92 (4) ◽  
pp. 796-804 ◽  
Author(s):  
Danilo Neglia ◽  
Oberdan Parodi ◽  
Michela Gallopin ◽  
Gianmario Sambuceti ◽  
Assuero Giorgetti ◽  
...  
Keyword(s):  
Heart Failure ◽  
Blood Flow ◽  
Myocardial Blood Flow ◽  
Dilated Cardiomyopathy ◽  
Blood Flow Response ◽  
Flow Response

scholarly journals Homogeneous 2D and 3D alignment of cardiomyocyte in dilated cardiomyopathy revealed by intravital heart imaging

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kiyoshi Masuyama ◽  
Tomoaki Higo ◽  
Jong-Kook Lee ◽  
Ryohei Matsuura ◽  
Ian Jones ◽  
...  
Keyword(s):  
Heart Failure ◽  
Dilated Cardiomyopathy ◽  
Cardiac Dysfunction ◽  
Three Dimensional ◽  
Single Layer ◽  
Specific Pattern ◽  
Two Dimensional ◽  
Heart Imaging ◽  
Novel Method ◽  
2D And 3D

AbstractIn contrast to hypertrophic cardiomyopathy, there has been reported no specific pattern of cardiomyocyte array in dilated cardiomyopathy (DCM), partially because lack of alignment assessment in a three-dimensional (3D) manner. Here we have established a novel method to evaluate cardiomyocyte alignment in 3D using intravital heart imaging and demonstrated homogeneous alignment in DCM mice. Whilst cardiomyocytes of control mice changed their alignment by every layer in 3D and position twistedly even in a single layer, termed myocyte twist, cardiomyocytes of DCM mice aligned homogeneously both in two-dimensional (2D) and in 3D and lost myocyte twist. Manipulation of cultured cardiomyocyte toward homogeneously aligned increased their contractility, suggesting that homogeneous alignment in DCM mice is due to a sort of alignment remodelling as a way to compensate cardiac dysfunction. Our findings provide the first intravital evidence of cardiomyocyte alignment and will bring new insights into understanding the mechanism of heart failure.

scholarly journals Clinical applications of artificial intelligence and machine learning in cancer diagnosis: looking into the future

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Muhammad Javed Iqbal ◽  
Zeeshan Javed ◽  
Haleema Sadia ◽  
Ijaz A. Qureshi ◽  
Asma Irshad ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Cancer Diagnosis ◽  
Disease Risk ◽  
Clinical Applications ◽  
Optimal Decision ◽  
Great Promise ◽  
Time Range ◽  
Base System ◽  
The Future

AbstractArtificial intelligence (AI) is the use of mathematical algorithms to mimic human cognitive abilities and to address difficult healthcare challenges including complex biological abnormalities like cancer. The exponential growth of AI in the last decade is evidenced to be the potential platform for optimal decision-making by super-intelligence, where the human mind is limited to process huge data in a narrow time range. Cancer is a complex and multifaced disorder with thousands of genetic and epigenetic variations. AI-based algorithms hold great promise to pave the way to identify these genetic mutations and aberrant protein interactions at a very early stage. Modern biomedical research is also focused to bring AI technology to the clinics safely and ethically. AI-based assistance to pathologists and physicians could be the great leap forward towards prediction for disease risk, diagnosis, prognosis, and treatments. Clinical applications of AI and Machine Learning (ML) in cancer diagnosis and treatment are the future of medical guidance towards faster mapping of a new treatment for every individual. By using AI base system approach, researchers can collaborate in real-time and share knowledge digitally to potentially heal millions. In this review, we focused to present game-changing technology of the future in clinics, by connecting biology with Artificial Intelligence and explain how AI-based assistance help oncologist for precise treatment.

Long-term follow-up of cardiac resynchronization therapy patients with non-ischemic dilated cardiomyopathy assessed by radionuclide angiography

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
C Valzania ◽  
R Bonfiglioli ◽  
F Fallani ◽  
J Frisoni ◽  
M Biffi ◽  
...  
Keyword(s):  
Heart Failure ◽  
Dilated Cardiomyopathy ◽  
Radionuclide Angiography ◽  
Cardiac Resynchronization ◽  
Resynchronization Therapy ◽  
Long Term Follow Up ◽  
Non Ischemic Dilated Cardiomyopathy ◽  
Lv Ejection Fraction

Abstract Background While the beneficial effects of cardiac resynchronization therapy (CRT) have been widely investigated soon after CRT implantation, relatively few data are available on long-term clinical outcomes of CRT recipients. Aim To investigate long-term outcomes of CRT patients with non-ischemic dilated cardiomyopathy stratified as responders and non-responders according to radionuclide angiography. Methods Consecutive heart failure patients with non-ischemic dilated cardiomyopathy undergoing CRT implantation at our University Hospital between 2007 and 2013 were enrolled. All patients were assessed with equilibrium Tc99 radionuclide angiography at baseline and after 3 months of CRT. Left ventricular (LV) ejection fraction was computed on the basis of relative end-diastolic and end-systolic counts, and intraventricular dyssynchrony was derived by Fourier phase analysis. Response to CRT was defined by an absolute increase in LV ejection fraction (LVEF) ≥5% at 3-month follow-up. Clinical outcome was assessed after 10 years through hospital records review. Results Forty-seven patients (83% men, 63±11 years) were included in the study. At 3 months, 25 (53%) patients were identified as CRT responders according to LVEF increase (from 26±8 to 38±12%, p<0.001). In these patients, LV dyssynchrony decreased from 59±30° to 29±18° (p<0.001). Twenty-two (47%) patients were defined as non-responders. No significant changes in LVEF and LV dyssynchrony (50±30° vs. 38±19°, p=0.07) were observed in non-responders. At long-term follow-up (11±2 years), all-cause and cardiac mortality rates were 24% and 12% in responders vs. 32% and 27% in non-responders, respectively (p=ns). Heart transplantation was performed in 3 patients. One (4%) patient among CRT responders compared with 6 (27%) patients among non-responders died of worsening heart failure (p=0.03). Conclusions Although late overall mortality of non-ischemic CRT recipients was not significantly different between mid-term responders and non-responders, CRT responders were at lower risk of worsening heart failure death. Funding Acknowledgement Type of funding source: None

scholarly journals Temporal trends in outcome and patient characteristics in dilated cardiomyopathy, data from the Swedish Heart Failure Registry 2003–2015

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Helen Sjöland ◽  
Jonas Silverdal ◽  
Entela Bollano ◽  
Aldina Pivodic ◽  
Ulf Dahlström ◽  
...  
Keyword(s):  
Heart Failure ◽  
Dilated Cardiomyopathy ◽  
Temporal Trends ◽  
Physical Symptoms ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Continuous Change ◽  
Ventricular Ejection Fraction ◽  
Increased Risk ◽  
Over Time

Abstract Background Temporal trends in clinical composition and outcome in dilated cardiomyopathy (DCM) are largely unknown, despite considerable advances in heart failure management. We set out to study clinical characteristics and prognosis over time in DCM in Sweden during 2003–2015. Methods DCM patients (n = 7873) from the Swedish Heart Failure Registry were divided into three calendar periods of inclusion, 2003–2007 (Period 1, n = 2029), 2008–2011 (Period 2, n = 3363), 2012–2015 (Period 3, n = 2481). The primary outcome was the composite of all-cause death, transplantation and hospitalization during 1 year after inclusion into the registry. Results Over the three calendar periods patients were older (p = 0.022), the proportion of females increased (mean 22.5%, 26.4%, 27.6%, p = 0.0001), left ventricular ejection fraction was higher (p = 0.0014), and symptoms by New York Heart Association less severe (p < 0.0001). Device (implantable cardioverter defibrillator and/or cardiac resynchronization) therapy increased by 30% over time (mean 11.6%, 12.3%, 15.1%, p < 0.0001). The event rates for mortality, and hospitalization were consistently decreasing over calendar periods (p < 0.0001 for all), whereas transplantation rate was stable. More advanced physical symptoms correlated with an increased risk of a composite outcome over time (p = 0.0043). Conclusions From 2003 until 2015, we observed declining mortality and hospitalizations in DCM, paralleled by a continuous change in both demographic profile and therapy in the DCM population in Sweden, towards a less affected phenotype.

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