Objectives: Although subjective cognitive complaints (SCC) are an integral component of the diagnostic criteria for mild cognitive impairment (MCI), previous findings indicate they may not accurately reflect cognitive ability. Within the Alzheimer’s Disease Neuroimaging Initiative, we investigated longitudinal change in the discrepancy between self- and informant-reported SCC across empirically derived subtypes of MCI and normal control (NC) participants. Methods: Data were obtained for 353 MCI participants and 122 “robust” NC participants. Participants were classified into three subtypes at baseline via cluster analysis: amnestic MCI, mixed MCI, and cluster-derived normal (CDN), a presumptive false-positive group who performed within normal limits on neuropsychological testing. SCC at baseline and two annual follow-up visits were assessed via the Everyday Cognition Questionnaire (ECog), and discrepancy scores between self- and informant-report were calculated. Analysis of change was conducted using analysis of covariance. Results: The amnestic and mixed MCI subtypes demonstrated increasing ECog discrepancy scores over time. This was driven by an increase in informant-reported SCC, which corresponded to participants’ objective cognitive decline, despite stable self-reported SCC. Increasing unawareness was associated with cerebrospinal fluid Alzheimer’s disease biomarker positivity and progression to Alzheimer’s disease. In contrast, CDN and NC groups over-reported cognitive difficulty and demonstrated normal cognition at all time points. Conclusions: MCI participants’ discrepancy scores indicate progressive underappreciation of their evolving cognitive deficits. Consistent over-reporting in the CDN and NC groups despite normal objective cognition suggests that self-reported SCC do not predict impending cognitive decline. Results demonstrate that self-reported SCC become increasingly misleading as objective cognitive impairment becomes more pronounced. (JINS, 2018, 24, 842–853)

Subjective cognitive complaints are a criterion for the diagnosis of mild cognitive impairment (MCI), despite their uncertain relationship to objective memory performance in MCI. We aimed to examine self-reported cognitive complaints in subgroups of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) MCI cohort to determine whether they are a valuable inclusion in the diagnosis of MCI or, alternatively, if they contribute to misdiagnosis. Subgroups of MCI were derived using cluster analysis of baseline neuropsychological test data from 448 ADNI MCI participants. Cognitive complaints were assessed via the Everyday Cognition (ECog) questionnaire, and discrepancy scores were calculated between self- and informant-report. Cluster analysis revealed Amnestic and Mixed cognitive phenotypes as well as a third Cluster-Derived Normal subgroup (41.3%), whose neuropsychological and cerebrospinal fluid (CSF) Alzheimer’s disease (AD) biomarker profiles did not differ from a “robust” normal control group. This cognitively intact phenotype of MCI participants overestimated their cognitive problems relative to their informant, whereas Amnestic MCI participants with objective memory impairment underestimated their cognitive problems. Underestimation of cognitive problems was associated with positive CSF AD biomarkers and progression to dementia. Overall, there was no relationship between self-reported cognitive complaints and objective cognitive functioning, but significant correlations were observed with depressive symptoms. The inclusion of self-reported complaints in MCI diagnostic criteria may cloud rather than clarify diagnosis and result in high rates of misclassification of MCI. Discrepancies between self- and informant-report demonstrate that overestimation of cognitive problems is characteristic of normal aging while underestimation may reflect greater risk for cognitive decline. (JINS, 2014, 20, 1–12)

Regression-based normative techniques account for variability in test performance associated with multiple predictor variables and generate expected scores based on algebraic equations. Using this approach, we show that estimated IQ, based on oral word reading, accounts for 1–9% of the variability beyond that explained by individual differences in age, sex, race, and years of education for most cognitive measures. These results confirm that adding estimated “premorbid” IQ to demographic predictors in multiple regression models can incrementally improve the accuracy with which regression-based norms (RBNs) benchmark expected neuropsychological test performance in healthy adults. It remains to be seen whether the incremental variance in test performance explained by estimated “premorbid” IQ translates to improved diagnostic accuracy in patient samples. We describe these methods, and illustrate the step-by-step application of RBNs with two cases. We also discuss the rationale, assumptions, and caveats of this approach. More broadly, we note that adjusting test scores for age and other characteristics might actually decrease the accuracy with which test performance predicts absolute criteria, such as the ability to drive or live independently. (JINS, 2009, 15, 1012–1022.)

The frequency and determinants of abnormal test performance by normal individuals are critically important to clinical inference. Here we compare two approaches to predicting rates of abnormal test performance among healthy individuals with the rates actually shown by 327 neurologically normal adults aged 18–92 years. We counted how many participants produced abnormal scores, defined by three different cutoffs with test batteries of varied length, and the number of abnormal scores they produced. Observed rates generally were closer to predictions based on a series of Monte Carlo simulations than on the binomial model. They increased with the number of tests administered, decreased as more stringent cutoffs were used to identify abnormality, varied with the degree of correlation among test scores, and depended on individual differences in age, education, race, sex, and estimated premorbid IQ. Adjusting scores for demographic variables and premorbid IQ did not reduce rates of abnormal performance. However, it eliminated the contribution of these variables to rates of abnormal test performance. These findings raise fundamental questions about the nature and interpretation of abnormal test performance by normal, healthy adults. (JINS, 2008, 14, 436–445.)

Thyroglossal duct remnants presenting as a lump in the neck are usually called thyroglossal cysts. Meticulous dissection of the cyst and duct, along with the body of the hyoid bone (Sistrunk’s operation) is necessary to avoid recurrence. The authors have reviewed the histology of 61 consecutive specimens diagnosed preoperatively as thyroglossal cysts and have found that a true cyst exists in only 46 per cent of cases.

The magnitude and origin of audiometric air-bone gaps in the range 3 kHz to 8 kHz was investigated in 20 normal subjects. The average gap ranged from a minimum of about 3 dB at 3 kHz to a maximum of about 19 dB at 6 kHz. Approximately 5 dB of the gap at high frequencies is caused by excess air-radiated sound from the bone vibrator. A larger error appears to result from discrepancies between the air and bone conduction standards to which audiometers are calibrated. These errors may influence diagnosis and we recommend that bone conduction tests at frequencies greater than 4 kHz are avoided. These findings have implications for medico-legal work where small air-bone gaps have diagnostic significance.