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A novel approach to the development of an antimuscarinic potency tool and measuring anticholinergic burden in older people

Project Description

A self-funded PhD studentship is available under the supervision of Dr Prasad Nishtala at the University of Bath. This is a collaborative project which will involve working with Dr Hamish Jamieson from the Big Data and Ageing Research Group at Christchurch. This research project provides an opportunity to combine big data analytics and advance translational research in ageing.
Anticholinergic medicines are frequently prescribed in older people. Anticholinergic load or burden is when there is more than one anticholinergic drug or drug with anticholinergic properties are co-administered. Numerous studies have reported that anticholinergic burden is a strong predictor of cognitive impairment and physical impairment and increased mortality in older people.
We propose to develop a novel antimuscarinic tool based on efficacy data derived from randomized clinical trials (RCTs). Clinicians can use this evidence-based tool to guide prescribing in older people. We will validate this tool in older people with complex care needs prescribed antimuscarinic medicines living in the community. We have access to interRAI data. The interRAI is a unique, internationally recognised and validated assessment tool for health and disability needs, used for all older people requiring health services in New Zealand. The interRAI assessments used for this study provides a comprehensive overview of the person’s physical, psychological, behavioural and social status.
The association between higher anticholinergic load and cognitive and functional decline in older people is well established. We propose to develop an evidence base tool to predict antimuscarinic potency would aid rational prescribing, thereby improving patient safety and outcomes. We propose to develop an "Antimuscarinic tool" that can be used to compare the potency of antimuscarinic medicines as well to calculate the total anticholinergic load of the patient’s entire medication profile. This would provide a useful clinical tool to guide prescribing in older people.

Funding Notes

Applicants should possess a Master’s degree (1st Class) qualification from disciplines of Statistics, Pharmacy or Medicine, preferably from a UK University.
Applicants are requested to submit their CV and a one-page expression of interest statement on how their research interests aligns with big data analytics and geriatric Pharmacoepidemiology. The documents should be emailed to Dr Prasad Nishtala ().
A formal application will be required if shortlisted.


1. Salahudeen MS, Nishtala PS. Examination and estimation of anticholinergic burden: Current Trends and Implications for Future Research. Drugs Aging. Accepted 2016.
2. Salahudeen MS, Hilmer SN, Nishtala PS. Comparison of anticholinergic risk scales and associations with adverse health outcomes in older people. Journal of American Geriatric Society, 2015; 63:85-90. [IF: 4.572]
3. Nishtala PS, Salahudeen MS, Hilmer SN. Anticholinergics: Theoretical and Clinical Overview, Expert Opinion in Drug Safety, 2016; 30:1-16.
4. Nishtala PS, Fois RA, McLachlan AJ, Bell JS, Kelly PJ, Chen TF. Anticholinergic activity of commonly prescribed medications and neuropsychiatric adverse events in older people. J. Clin. Pharmacol. 2009; 49; 1176-84.
5. Salahudeen MS, Duffull SB, Nishtala PS. Anticholinergic burden quantified by anticholinergic risk scales and adverse outcomes in older people: a systematic review. BMC Geriatrics, 2015; 15:31 [IF: 1.680]

How good is research at University of Bath in Allied Health Professions, Dentistry, Nursing and Pharmacy?

FTE Category A staff submitted: 54.20

Research output data provided by the Research Excellence Framework (REF)

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