Comparison of 2 informant questionnaire screening tools for dementia and mild cognitive impairment: AD8 and IQCODE.

BACKGROUND: Dementia and mild cognitive impairment (MCI) are underrecognized in community settings. This may be due in part to the lack of brief dementia screening tools available to clinicians. We compared 2 brief, informant-based screening tests: the AD8 and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) in a community-based neurology practice in the midwestern United States. METHODS: We examined 186 consecutive patients (44 controls, 13 with MCI, and 129 with dementia). Receiver operator characteristic curves were used to examine the ability of AD8 and IQCODE to discriminate between controls and MCI or dementia. Sensitivity, specificity, predictive values, and likelihood ratios were reported. RESULTS: AD8 differentiated healthy controls from MCI (P<0.001) or dementia (P<0.001), and MCI from dementia (P=0.008). The IQCODE differentiated controls and MCI from dementia (both P<0.001), and between controls and MCI (P=0.002). Both AD8 (AUC=0.953; 95% confidence interval, 0.92-0.99) and IQCODE (AUC=0.930, 95% confidence interval, 0.88-0.97) provided discrimination between controls and patients with dementia; however, the AD8 had superior sensitivity detecting dementia (99.2%) and MCI (100%) compared with the IQCODE (79.1% for dementia, 46.1% for MCI) with nonoverlapping confidence intervals. Using published cut-offs (AD8≥2, IQCODE≥3.4), only 1 case of dementia was missed with the AD8, whereas the IQCODE failed to detect dementia in 27 individuals. The AD8 detected MCI in all 13 individuals, whereas the IQCODE misclassified 7 individuals. CONCLUSIONS: Both the AD8 and IQCODE were able to detect dementia in a community setting. The AD8, however, was more successful than IQCODE in detecting MCI. If simple and efficient screening for early cognitive impairment is the goal, particularly in the early stages (e.g., for prevention trials or public screening), the combination of an informant interview (the AD8) and a brief performance measure could be considered as they meet the basic requirements of the Personalized Prevention Plan for Medicare beneficiaries.

A longitudinal study of transient epileptic amnesia.

OBJECTIVE: To study the underlying pathophysiology and the long-term prognosis of the syndrome of transient epileptic amnesia (STEA). BACKGROUND: STEA has been recently described as a distinct nosologic entity, in which memory impairment is the sole clinical manifestation of temporal lobe epilepsy. METHODS: Serial neuropsychologic examinations and electroencephalography (EEG) were performed on a patient with STEA, before and after treatment with antiepileptic drug for a 2-year study period. RESULTS: Initial neuropsychologic assessment revealed isolated mild-to-moderate impairment in anterograde verbal and visual memory. EEG showed intermittent sharp and spike discharges from both temporal regions, independently, consistent with an underlying seizure tendency. Treatment with extended-release carbamazepine 200 mg twice daily led to complete resolution of the memory difficulty, and the repeat neuropsychologic assessment and EEG were within normal limits. Two years after the treatment was initiated, the patient remained asymptomatic and a third neuropsychologic assessment was completely normal. CONCLUSIONS: The memory impairment in STEA does not originate from a progressive neurodegenerative mechanism, but rather from an underlying epileptic and therefore reversible etiology. When identified and treated, STEA carries no memory impairment at 2 years after diagnosis.

Source of low-frequency fluctuations in functional MRI signal.

PURPOSE: To investigate the source of native low-frequency fluctuations (LFF) in functional MRI (fMRI) signal. MATERIALS AND METHODS: Phase analysis was performed on tissue-segmented fMRI data acquired at systematically varying sampling rates. RESULTS: LFF in fMRI signal were both native and aliased in origin. Scanner instability did not contribute to native or aliased LFF. Aliased LFF arose from cardiorespiratory processes and head motion. Native LFF did not arise from cardiorespiratory processes, but did so, at least in part, from head motion. Motion correction reduced native LFF, but did not eliminate them. The residual native LFF in motion-corrected fMRI data showed a systematic phase difference among different tissue structures. The native LFF in fMRI signals of cerebral blood vessels and CSF were synchronous, and preceded those of gray and white matter, indicating that the vascular fluctuations lead the metabolic fluctuations. CONCLUSION: The primary physiologic source of native LFF in fMRI signal is vasomotion.

Rubral lateropulsion due to vertebral artery dissection in a patient with Klippel-Feil syndrome.

BACKGROUND: Neurologic deficits in patients with Klippel-Feil syndrome usually are attributed to direct compression of neuronal structures or hypoperfusion secondary to compression of the vertebral arteries by bony abnormalities. OBJECTIVE: To describe a 38-year-old woman with known Klippel-Feil syndrome who developed lateropulsion. RESULTS: The results of magnetic resonance imaging were consistent with rubrothalamic stroke. The cerebral angiogram confirmed vertebral artery dissection at the level of her previously observed bony abnormality. CONCLUSIONS: Hypermobility adjacent to fused vertebrae subjects the vertebral artery to increased shear forces. Thus, Klippel-Feil syndrome may be a predisposing factor for vertebral artery dissection. Moreover, to our knowledge, this case represents the second known case of rubral lateropulsion.

Model assessment and model building in fMRI.

Model quality is rarely assessed in fMRI data analyses and less often reported. This may have contributed to several shortcomings in the current fMRI data analyses, including: (1) Model mis-specification, leading to incorrect inference about the activation-maps, SPM[t] and SPM[F]; (2) Improper model selection based on the number of activated voxels, rather than on model quality; (3) Under-utilization of systematic model building, resulting in the common but suboptimal practice of using only a single, pre-specified, usually over-simplified model; (4) Spatially homogenous modeling, neglecting the spatial heterogeneity of fMRI signal fluctuations; and (5) Lack of standards for formal model comparison, contributing to the high variability of fMRI results across studies and centers. To overcome these shortcomings, it is essential to assess and report the quality of the models used in the analysis. In this study, we applied images of the Durbin-Watson statistic (DW-map) and the coefficient of multiple determination (R(2)-map) as complementary tools to assess the validity as well as goodness of fit, i.e., quality, of models in fMRI data analysis. Higher quality models were built upon reduced models using classic model building. While inclusion of an appropriate variable in the model improved the quality of the model, inclusion of an inappropriate variable, i.e., model mis-specification, adversely affected it. Higher quality models, however, occasionally decreased the number of activated voxels, whereas lower quality or inappropriate models occasionally increased the number of activated voxels, indicating that the conventional approach to fMRI data analysis may yield sub-optimal or incorrect results. We propose that model quality maps become part of a broader package of maps for quality assessment in fMRI, facilitating validation, optimization, and standardization of fMRI result across studies and centers. Hum. Brain Mapping 20:227-238, 2003.