The 10/66 Dementia Research Group's fully operationalised DSM-IV dementia computerized diagnostic algorithm, compared with the 10/66 dementia algorithm and a clinician diagnosis: a population validation study
2008

Validation of a Computerized Dementia Diagnosis Algorithm

Sample size: 2909 publication 10 minutes Evidence: moderate

Author Information

Author(s): Prince Martin J, de Rodriguez Juan Llibre, Noriega L, Lopez A, Acosta Daisy, Albanese Emiliano, Arizaga Raul, Copeland John RM, Dewey Michael, Ferri Cleusa P, Guerra Mariella, Huang Yueqin, Jacob KS, Krishnamoorthy ES, McKeigue Paul, Sousa Renata, Stewart Robert J, Salas Aquiles, Sosa Ana Luisa, Uwakwa Richard

Primary Institution: King's College London

Hypothesis

Can a computerized algorithm for diagnosing dementia based on DSM-IV criteria be validated against clinician diagnoses in a population-based study?

Conclusion

The DSM-IV criterion may be specific but is incompletely sensitive to clinically relevant dementia cases, while the 10/66 dementia diagnosis is broader and more sensitive.

Supporting Evidence

  • The DSM-IV algorithm confirmed 86.7% of severe dementia cases.
  • The 10/66 algorithm identified 100% of severe cases.
  • Clinician diagnoses agreed better with the 10/66 dementia diagnosis than with the DSM-IV algorithm.
  • 71% of clinically diagnosed cases met the memory impairment criterion for DSM-IV.
  • 85% of clinically diagnosed cases met the social and occupational impairment criterion.

Takeaway

This study created a computer program to help doctors diagnose dementia and found that it sometimes misses less severe cases, while another method catches more cases.

Methodology

The study used a computerized algorithm based on DSM-IV criteria and validated it against clinician diagnoses in a population-based sample in Cuba.

Potential Biases

The study may have overestimated concordance due to the use of the same structured assessments for all diagnoses.

Limitations

The study's reliance on clinician diagnoses and the potential for overdiagnosis with the 10/66 algorithm may affect the results.

Participant Demographics

Participants were aged 65 and over from various catchment areas in Cuba.

Statistical Information

P-Value

p<0.001

Confidence Interval

95% CI 0.74–0.83

Statistical Significance

p<0.001

Digital Object Identifier (DOI)

10.1186/1471-2458-8-219

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