Objective: Patients with dementia may be at high risk for psychiatric adver
se drug reactions (ADRs). A Bayesian approach was developed for the assessm
ent of changes in cognition and behaviour suspected as being related to psy
chotropic medications.
Design: This was a prospective observational study. A Bayesian model calcul
ated the posterior probability (PsP) in favour of psychotropic drugs being
the cause of the psychiatric adverse events detected. Bayesian results were
cross-validated by comparison with an expert clinician and 2 other clinici
ans using a causality visual analogue scale (VAS).
Setting and Patients: The setting was a cognitive support unit in a long te
rm care facility associated with a teaching hospital. 107 (97 males and 10
females) cognitively impaired institutionalised elderly patients (mean age
+/- SD = 78 +/- 7, range 59 to 98 years) were monitored for 3 months for ch
anges in cognition and behaviour.
Results: 13 behavioural events (6 agitation, 4 confusion and 3 cognitive de
cline) were detected. Bayesian analysis implicated lorazepam, levomepromazi
ne (methotrimeprazine) plus oxazepam perphenazine and zopiclone as causing
4 of 13 behavioural events. Bayesian results were correlated to the VAS res
ults of the expert rater (r = 0.78, p = 0.002) and less so to the other cli
nicians (r = 0.68, p = 0.01; r = 0.49, p = not significant). The expert rat
er identified the same 4 cases as being most likely to have been drug induc
ed. Bayesian results indicated that drug-induced psychiatric events occurre
d in 3.7% of patients and the drug-attributable risk was 5.4% over 3 months
.
Conclusions: The Bayesian approach identified psychiatric ADRs in high agre
ement with an expert rating. These results suggest that drug-induced cognit
ive and behavioural symptoms are an important source of reversible morbidit
y in patients with dementia.