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Last Updated: Monday, 26 December 2005, 01:22 GMT
Asthma attack 'predictor' devised
Image of a girl with asthma
Predicting when attacks may occur can help tailor treatment
Researchers say they have found a way to predict asthma attacks using a mathematic model.

The findings may help asthmatics control their symptoms more effectively and improve the testing of new drugs.

The Nature paper authors were able to predict the likelihood of an asthma attack occurring over the next month by looking at peak flow readings.

These readings give doctors an idea of how well a person's lungs are working - low readings mean poorer function.

Essentially, they measure how fast a person can exhale air from the lungs.

'Chaos model'

The model the international team used is based on processes known as "chaos" which are applied to complex systems, such as the weather, that despite appearing random, actually are not and are dependent on the interaction of many individual components.

Indeed, the apparently random nature of the peak flow readings they looked at did conceal a hidden order in the 80 patients they studied over 18 months.

By looking at the fluctuations in airway function they were able to calculate the risk of severe asthma attacks occurring within 30 days.

It may be possible to carry out clinical trials of new anti-asthma treatments in a much more efficient way than has been done in the past
Researcher Professor Mike Silverman

This could mean big benefits for patients and experts alike, they said.

Researcher Professor Mike Silverman, from Leicester University, explained: "It may be possible to determine the risk of a severe attack of asthma in individual subjects, and to use the information to modify their treatment.

"You might want to step up their medication or give them a flu jab, for example.

"It may also be possible to carry out clinical trials of new anti-asthma treatments in a much more efficient way than has been done in the past."

Predictions

Currently, long observation periods are needed to accumulate sufficient attacks of asthma to be certain new drugs are better than previous forms of therapy.

With the chaos model, researchers would not need to wait for people to have an asthma attack, said Dr Silverman.

The model also revealed that in patients with more severe asthma, attacks tended to be more variable and random.

Dr Silverman said this might be because the airways become hypersensitive to even apparently minor environmental factors such as small amounts of pollutants or allergens.

The results also showed that an inhaler which is commonly used by asthmatics for relief can increase the instability of lung function, and increase the likelihood of an acute attack if it was used regularly.

Anything that will predict asthmatic attacks thereby allowing treatment to be given to prevent serious events occurring is a major step forward
Asthma expert Professor Tak Lee

Regular use of short-acting bronchodilators, or beta agonists, (four times daily with a long night time drug-free interval) increased the risk of asthma episodes.

But Professor Martyn Partridge, of Asthma UK, stressed that this was no cause for concern because regular use of these inhalers was an indicator that the asthma was not properly controlled and other treatments should be used.

Professor Tak Lee, an asthma expert at the Medical Research Council and Guy's Hospital, London, said: "There are around 5.2 million asthmatics in the country and half of them have severe asthma requiring frequent use of inhalers.

"The numbers of children with asthma have increased six fold in the last 30 years and six to seven people will die of asthma every 24 hours.

"The cost to the NHS is enormous - close to 890 million each year - so anything that will predict asthmatic attacks thereby allowing treatment to be given to prevent serious events occurring is a major step forward."

He recently published work showing that an increase in daytime asthma symptoms is the strongest predictor of an asthma attack that will require a course of steroid tablets - more so than night time symptoms or a fall in peak flow measurements.


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