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A new tool calculates which medicines are more likely to cause adverse anticholinergic effects, according to work by a team led by the University of Exeter.

“Use of medicines with anticholinergic effects can have significant harmful effects, for example falls and confusion, which are avoidable, we urgently need to reduce the harmful side effects as this can leads to hospitalization and death,” said Chris Fox, at the University of Exeter, and one of the study authors. “This new tool provides a promising avenue towards a more tailored personalized medicine approach, of ensuring the right person gets a safe and effective treatment whilst avoiding unwanted anticholinergic effects.”

Such complications can occur from many prescription and over-the-counter drugs that affect the brain by blocking the neurotransmitter acetylcholine. These medicines include some for bladder disorders, depression, stomach ailments, and Parkinson’s disease. They are most commonly taken by older people.

The paper was recently published in Age and Ageing.

Anticholinergic side effects include confusion, blurred vision, dizziness, falls, and a decline in brain function. Anticholinergic effects may also increase risks of falls and may be associated with an increase in mortality. They have also been linked to a higher risk of dementia when used long term.

This team created a new online tool, the International Anticholinergic Cognitive Burden Tool (IACT), that uses natural language processing and chemical structure analysis to identify medications that have anticholinergic effect. The researchers say their tool is the first to incorporate a machine learning technique to develop an automatically updated tool available on a website portal.

A drug’s anticholinergic burden is assessed by assigning a score based on reported adverse events and aligning closely with the chemical structure of the drug being considered for prescription, resulting in a more accurate and up-to-date scoring system than any previous system. Ultimately, after further research and modelling with real world patient data the tool developed could help to support prescribing reducing risks from common medicines.

The team surveyed 110 health professionals, including pharmacists and prescribing nurses.  Of this group, 85 percent said they would use a tool to assess risk of anticholinergic side effects, if available. The team also gathered usability feedback to help improve the tool further.

Saber Sami, at the University of East Anglia, said, “Our tool is the first to use innovative artificial intelligence technology in measures of anticholinergic burden—ultimately, once further research has been conducted the tool should support pharmacists and prescribing health professionals in finding the best treatment for patients.”

The research team includes collaboration with AKFA University Medical School, Uzbekistan, and the Universities of East Anglia, Aston, Kent and Aberdeen.

“I have been working in this area for over 20 years. Anti-cholinergic side-effects can be very debilitating for patients. We need better ways to assess these side-effects,” said Ian Maidment, from Aston University, and one of the co-authors.

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