This is the protocol for a review and there is no abstract. The objectives are as follows:
To determine the diagnostic accuracy of the informant based questionnaire IQCODE, in detection of all cause (undifferentiated) dementia in community-dwelling adults.
(Where data are available) we will describe the following.
The diagnostic accuracy of IQCODE at various pre-specified thresholds. We recognize that various thresholds or “cut-off” scores have been used to define IQCODE screen positive states. We will describe the properties of IQCODE for the following cut-off scores (rounded where necessary): 3.6; 3.5; 3.4, 3.3. If data are available for IQCODE scores not in the pre-specified list, we will describe all IQCODE scores greater than 3.6 or less than 3.3 together. These thresholds have been chosen to represent the range of cut-offs that are commonly used in practice and research; we have been inclusive in our choice of cut-off to maximize available data for review.
Accuracy of IQCODE for diagnosis of the commonest specific dementia subtype - Alzheimer’s dementia.
Effects of heterogeneity (see below) on the reported diagnostic accuracy of IQCODE.
The focused study question, restricting review to cross-sectional studies in a community setting is designed to remove potential heterogeneity relating to study design and setting. Other sources of heterogeneity in dementia studies such as treatment; intervention or duration of follow-up are not applicable to a cross-sectional study in an unselected population and will not be considered outwith inclusion/exclusion criteria. The properties of a tool describe behaviour of the instrument under particular circumstances. Thus for our assessment of potential sources of heterogeneity (where data allow), we will collect data on features of the study population namely age; features of the index test namely language of administration and IQCODE format; features of the reference standard namely diagnostic criteria used and diagnostic methodology. Analysis of heterogeneity will be performed by adding these prespecified co-variates to the bivariate model. Operational definitions are given in the section Data collection and analysis and Investigations of heterogeneity below.