Performance of the Automated Neuropsychological Assessment Metrics (ANAM) in detecting cognitive impairment in heart failure patients.

OBJECTIVE

Evaluate capacity of the Automated Neuropsychological Assessment Metrics (ANAM) to detect cognitive impairment (CI) in heart failure (HF) patients.

BACKGROUND

CI is a key prognostic marker in HF. Though the most widely used cognitive screen in HF, the Mini-Mental State Examination (MMSE) is insufficiently sensitive. The ANAM has demonstrated sensitivity to cognitive domains affected by HF, but has not been assessed in this population.

METHODS

Investigators administered the ANAM and MMSE to 57 HF patients, compared against a composite model of cognitive function.

RESULTS

ANAM efficiency (p < .05) and accuracy scores (p < .001) successfully differentiated CI and non-CI. ANAM efficiency and accuracy scores classified 97.7% and 93.0% of non-CI patients, and 14.3% and 21.4% with CI, respectively.

CONCLUSIONS

The ANAM is more effective than the MMSE for detecting CI, but further research is needed to develop a more optimal cognitive screen for routine use in HF patients.