Sunday September 15, 2019

30% Higher Risk Of Heart Failure Linked with Malaria

The findings were presented at the ESC Congress 2019 together with the World Congress of Cardiology in Paris

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Malaria, Heart failure, disease
FILE - A female Aedes aegypti mosquito is shown in this Center for Disease Control photograph. VOA

Malaria infection is linked to 30 per cent higher risk of heart failure, a new research has warned.

The mosquito-borne infection affects more than 219 million people worldwide each year, according to the 2018 statistics of the World Health Organization (WHO).

“We have seen an increase in the incidence of malaria cases and what is intriguing is that we have seen the same increase in cardiovascular disease in the same regions,” said the first author of the study, Philip Brainin, a postdoctoral research fellow at the Herlev-Gentofte University Hospital in Denmark.

“Even though we have taken preventive measures to decrease the malaria numbers, it remains a major burden,” Brainin said.

Mission Delhi, STEMI, Heart Attack
The Mission Delhi aims to provide care to STEMI, a very serious type of heart attack, patients. Pixabay

The researchers used Danish nationwide registries to identify patients with a history of malaria infection between January 1994 and January 2017. The mean age of patients in the study was 34 and 58 per cent of the subjects were male.

Around 4,000 malaria cases were identified, with 40 per cent having plasmodium falciparum, a parasite transmitted through mosquito bites that is responsible for the majority of severe malaria cases in humans.

The 11-year follow-up of patients revealed 69 cases of heart failure, which were very high as compared to the general population, and 68 cases of cardiovascular death, which were considered within normal range.

“These patients had a 30 per cent increased likelihood of developing heart failure over the follow-up time,” Brainin said.

More research will be needed to further validate the findings, but recent studies have found that malaria could be a contributor to functional and structural changes in the myocardium, which is the muscle tissue of the heart.

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Experimental studies have also shown that malaria may affect the blood pressure regulatory system causing hypertension, which is a contributor to heart failure.

Malaria can also affect vascular pathways that cause inflammation in the heart, which could lead to fibrosis and then heart failure.

According to the European Society of Cardiology (ESC), a combination of high blood pressure, diabetes, obesity, and coronary artery disease are among the most common risk factors for heart failure.

The findings were presented at the ESC Congress 2019 together with the World Congress of Cardiology in Paris.

Among the high malaria burden countries, India has made substantial progress in disease control. The malaria burden has declined by over 80 per cent — malaria cases came down to 0.39 million in 2018 from 2.03 million cases in 2000. Malaria deaths in India have declined by over 90 per cent — from 932 deaths in 2000 to 85 in 2018, according to Indian Council of Medical Research. (IANS)

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Researchers Can Now Detect Heart Failure with 100% Accuracy with the Help of Artificial Intelligence

Conversely, their new model uses a combination of advanced signal processing and machine learning tools on raw ECG signals, delivering 100 per cent accuracy

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Artificial Intelligence Bot
Artificial Intelligence Bot. Pixabay

With the help of Artificial Intelligence(AI), researchers have developed a neural network approach that can accurately identify congestive heart failure with 100 per cent accuracy through analysis of just one raw electrocardiogram (ECG) heartbeat.

Congestive heart failure (CHF) is a chronic progressive condition that affects the pumping power of the heart muscles. Associated with high prevalence, significant mortality rates and sustained healthcare costs, clinical practitioners and health systems urgently require efficient detection processes.

The researchers have worked to tackle these important concerns by using Convolutional Neural Networks (CNN) – hierarchical neural networks highly effective in recognising patterns and structures in data.

“We trained and tested the CNN model on large publicly available ECG datasets featuring subjects with CHF as well as healthy, non-arrhythmic hearts. Our model delivered 100 per cent accuracy: by checking just one heartbeat we are able detect whether or not a person has heart failure,” said study researcher Sebastiano Massaro, Associate Professor at the University of Surrey in the UK.

artificial intelligence, nobel prize
“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society.” VOA

“Our model is also one of the first known to be able to identify the ECG’ s morphological features specifically associated to the severity of the condition,” Massaro said.

Published in Biomedical Signal Processing and Control Journal, the research drastically improves existing CHF detection methods typically focused on heart rate variability that, whilst effective, are time-consuming and prone to errors.

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Conversely, their new model uses a combination of advanced signal processing and machine learning tools on raw ECG signals, delivering 100 per cent accuracy.

“With approximately 26 million people worldwide affected by a form of heart failure, our research presents a major advancement on the current methodology,” said study researcher Leandro Pecchia from the University of Warwick. (IANS)