title: Diagnosis of dementia from the history and aetiology schedule.
abstract: OBJECTIVE
  To provide a computerised method of diagnosing organic brain syndrome from history data without the use of mental state data.
  
  
  METHODS
  Interview dataset from participants in a community study of the incidence of dementia was used to form a training sample and validation sample. The algorithm was developed on the training sample and tested on the validation sample.
  
  
  RESULTS
  Performance in the training and validation samples was very similar. The algorithm shows monotonically increasing probability of being diagnosed with dementia as a function of the proposed level of diagnostic confidence. At the proposed cut point it has sensitivity 94% and specificity 84% for detecting concurrent psychiatrist's diagnosis of dementia.
  
  
  CONCLUSIONS
  The method provides a good agreement with psychiatrist's diagnosis, and the results in the validation sample show little shrinkage. The method will prove useful in studies where it has proved impossible to collect mental state information on all the study participants.
authors.affiliation: Trent Institute for Health Services Research, Medical School, University Hospital, UK. michael.dewey@nottingham.ac.uk
authors.forename: M E
authors.initials: ME
authors.lastname: Dewey
authors.forename: J R
authors.initials: JR
authors.lastname: Copeland
mesh_terms: D000368:Aged; D000465:Algorithms; D003704:Dementia / Q000175:diagnosis* / Q000523:psychology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D015577:Geriatric Assessment; D006801:Humans; D008297:Male; D016347:Medical Records Systems, Computerized; D015588:Observer Variation; D011594:Psychometrics