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Applicability of automated MR-based diagnosing in a memory clinic

Applicability of automated MR-based diagnosing in a memory clinic

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00003199
Enrollment
120
Registered
2011-07-26
Start date
2011-08-01
Completion date
Unknown
Last updated
2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

F03 F06.7

Interventions

Group 1: Study part 1. We aim to compare the diagnostic accuracy achieved by an automated method against a gold standard diagnoses defined by clinical consensus based on all available data (e.g. medic

Sponsors

ZGGF
Lead Sponsor

Eligibility

Sex/Gender
All
Age
40 Years to No maximum

Inclusion criteria

Inclusion criteria: Part 1 - first time referral - age > 40 - Subjects with mild to moderate dementia (CDR of 1 or below). Part 2 - first time referral - age > 40 - CDR of 0.5 - Age and education corrected Z-score below -1.5 in at least one of the CERAD items

Exclusion criteria

Exclusion criteria: - Dementia that is definitely not caused by neurodegeneration (e.g. severe trauma, brain tumor). Cases for which that cause does not explain the cognitive impairment with certainty (e.g. disease progression despite isolated trauma) will remain in the study to include a representative spectrum. - Inability to provide informed consent.

Design outcomes

Primary

MeasureTime frame
Part 1: The overall aim is the evaluation of the clinical usefulness of the computer tool with respect to supporting the diagnostic process. Usefulness is here defined as the ability to reach a diagnostic decision with high reliability in a substantial fraction of the patients or at least the ability to rule out some possible diagnoses in a reliable manner in a substantial fraction of the patients. Reliable means here a predictive value for the true status which is high enough to allow to stop or at least reduce the further diagnostic process compared to the current work up. A secondary aim is to compare the diagnostic accuracy of the computer tool with that of an experienced clinician with respect to three aspects: Main diagnose, secondary diagnose and differentiation between main and secondary diagnose. Part 2: The aim is to demonstrate that the prognostic accuracy of the computer tool is at least as good as the accuracy of the clinician, i.e. to declare it as non-inferior.

Secondary

MeasureTime frame
Part 1: In the secondary analyses we compare the accuracy of the main diagnose with that of the gold standard in cross tabulations allowing a detailed picture of the types of confusions. The accuracy itself is compared by the overall accuracy, i.e. the exact rate of agreement, as well as by the five sensitivities. Confidence intervals for the differences will be computed. Part 2: In the secondary analysis the comparison will be based on the R² values when regressing the change in the score versus the output of each procedure. In a sensitivity analysis, the relation between the change and the output will be modelled by fractioned polynomials.

Countries

Germany

Contacts

Public ContactMichael Hüll

ZGGF

michael.huell@uniklinik-freiburg.de0049 761 270 70900

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 4, 2026