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Background: The Addenbrooke's Cognitive Examination-Revised (ACE-R) is an accessible cognitive tool that supports the early detection of mild cognitive impairment (MCI), Alzheimer's disease (AD), and behavioral variant frontotemporal dementia (bvFTD). Objective: To investigate the diagnostic efficacy of the ACE-R in MCI, AD, and bvFTD through the identification of novel coefficients for differentiation between these diseases. Methods: We assessed 387 individuals: 102 mild AD, 37 mild bvFTD, 87 with amnestic MCI patients, and 161 cognitively unimpaired controls. The Mokken scaling technique facilitated the extraction out of the 26 ACE-R items that exhibited a common latent trait, thereby generating the Mokken scales for the AD group and the MCI group. Subsequently, we performed logistic regression, integrating each Mokken scales with sociodemographic factors, to differentiate between AD and bvFTD, as well as between AD or MCI and control groups. Ultimately, the Receiver Operating Characteristic curve analysis was employed to assess the efficacy of the coefficient's discrimination. Results: The AD-specific Mokken scale (AD-MokACE-R) versus bvFTD exhibited an Area Under the Curve (AUC) of 0.922 (88% sensitivity and specificity). The AD-MokACE-R versus controls achieved an AUC of 0.968 (93% sensitivity, 94% specificity). The MCI-specific scale (MCI-MokACE-R) versus controls demonstrated an AUC of 0.859 (78% sensitivity, 79% specificity). Conclusions: The ACE-R's capacity is enhanced through statistical methods and demographic integration, allowing for accurate differentiation between AD and bvFTD, as well as between MCI and controls. This new method not only reinforces its clinical value in early diagnosis but also surpasses traditional approaches noted in prior studies. [ABSTRACT FROM AUTHOR]

Radiological interpretations, while essential, are not infallible and are best understood as expert opinions formed through the evaluation of available evidence. Acknowledging the inherent possibility of error is crucial, as it frames the discussion on improving diagnostic accuracy and patient care. A comprehensive review of error classifications highlights the complexity of diagnostic errors, drawing on recent frameworks to categorize them into perceptual and cognitive errors, among others. This classification underpins an analysis of specific error types, their prevalence, and implications for clinical practice. Additionally, we address the psychological impact of radiological practice, including the effects of mental health and burnout on diagnostic accuracy. The potential of artificial intelligence (AI) in mitigating errors is discussed, alongside ethical and regulatory considerations in its application. This research contributes to the body of knowledge on radiological errors, offering insights into preventive strategies and the integration of AI to enhance diagnostic practices. It underscores the importance of a nuanced understanding of errors in radiology, aiming to foster improvements in patient care and radiological accuracy. [ABSTRACT FROM AUTHOR]

Objective There are scarce data comparing Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP) in social cognition (SC). We aimed to compare patients with PSP and PD in SC. Methods We included three groups: PD (n  = 18), PSP (n  = 20) and controls (n  = 23). Participants underwent neuropsychological exams, including the mini-version of the Social and Emotional Assessment, which is composed of the facial emotion recognition test (FERT) and the modified faux-pas (mFP) test, which assesses Theory of Mind (ToM). Results Patients with PD scored lower than controls in the FERT, but not in the mFP test. Patients with PSP performed worse than controls in both the mFP and FERT. PD and PSP groups did not differ in the FERT, but PSP performed worse than PD in the mFP test. The mFP test distinguished PSP from PD with 89% accuracy. Conclusion The assessment of ToM may contribute to the differentiation between PD and PSP. [ABSTRACT FROM AUTHOR]

Background: The ACE‐R is an accurate and brief cognitive battery for the detection of mild dementia, especially for the discrimination between Alzheimer's disease (AD) and frontotemporal dementia. The aim of this study was to develop a new logarithm based on discriminative items of the ACE‐R combined with relevant demographic characteristics that may interfere on cognition. Method: The ACE‐R was administered to 102 patients with mild dementia due to probable AD and 161 controls from two Brazilian research centers. All individuals were submitted to the Mattis Dementia Rating Scale (DRS) and the ACE‐R. The performance of the patients was compared and analyzed. Mokken scaling analysis was applied to identify the latent trait on the AD Group. Multivariate logistic regression and ROC curve analysis were carried out. Result: Mean ± SD total scores in the ACE‐R were 70.2 ± 10.8 in AD and 85.1 ± 8.2 in controls. AD Mokken ACE‐R (AMokACE‐R) comprises 12 items measuring the same latent concept. Logistic regression with cross‐validation pointed that AMokACE‐R + Years of education + ACE‐R items Orientation (time) and Memory (name and address recall) share importance as independent variables (p<0.05). The proposed logarithm reached an area under the curve of 0.968, with 93% sensitivity, 94% specificity, 90% PPV and 95% NPV. Conclusion: The new logarithm using the ACE‐R items achieved high diagnostic accuracy in identifying mild AD versus controls. Furthermore, the final ROC curves showed the superiority of the model proposed in relation to the analysis of the subscales individually, as the literature previously reported. Further analysis in larger samples, with biomarkers or pathological confirmation, are necessary to confirm these findings. [ABSTRACT FROM AUTHOR]

Introduction Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) are frequent causes of dementia and, therefore, instruments for differential diagnosis between these two conditions are of great relevance. Objective To investigate the diagnostic accuracy of Addenbrooke's Cognitive Examination-Revised (ACE-R) for differentiating AD from bvFTD in a Brazilian sample. Methods The ACE-R was administered to 102 patients who had been diagnosed with mild dementia due to probable AD, 37 with mild bvFTD and 161 cognitively healthy controls, matched according to age and education. Additionally, all subjects were assessed using the Mattis Dementia Rating Scale and the Neuropsychiatric Inventory. The performance of patients and controls was compared by using univariate analysis, and ROC curves were calculated to investigate the accuracy of ACE-R for differentiating AD from bvFTD and for differentiating AD and bvFTD from controls. The verbal fluency plus language to orientation plus name and address delayed recall memory (VLOM) ratio was also calculated. Results The optimum cutoff scores for ACE-R were <80 for AD, <79 for bvFTD, and <80 for dementia (AD + bvFTD), with area under the receiver operating characteristic curves (ROC) (AUC) >0.85. For the differential diagnosis between AD and bvFTD, a VLOM ratio of 3.05 showed an AUC of 0.816 (Cohen's d  = 1.151; p  < .001), with 86.5% sensitivity, 71.4% specificity, 72.7% positive predictive value, and 85.7% negative predictive value. Conclusions The Brazilian ACE-R achieved a good diagnostic accuracy for differentiating AD from bvFTD patients and for differentiating AD and bvFTD from the controls in the present sample. [ABSTRACT FROM AUTHOR]

Objective To investigate the accuracy of the Social and Emotional Assessment-short version (Mini-SEA) to differentiate subgroups of behavioral variant of frontotemporal dementia (bvFTD) and Alzheimer's disease (AD) defined according to executive performance. Methods bvFTD (n = 21), AD (n = 20), and healthy controls (HC, n = 23) underwent the Mini-SEA, comprising the Facial Emotion Recognition Test (FERT) and the faux-pas test. AD and bvFTD patients were classified according to their performance in the Frontal Assessment Battery into dysexecutive and nondysexecutive subgroups. Results The area under the curve (AUC) values for the faux-pas test were 0.87 (dysexecutive-bvFTD vs. dysexecutive-AD) and 0.96 (non-dysexecutive-bvFTD vs. nondysexecutive-AD). The AUC values for FERT were 0.99 (dysexecutive-bvFTD vs. dysexecutive-AD) and 0.65 (nondysexecutive-bvFTD vs. nondysexecutive-AD); the AUC values for the Mini-SEA (total-score) were 0.95 (dysexecutive-bvFTD vs. dysexecutive-AD) and 0.88 (nondysexecutive-bvFTD vs. nondysexecutive-AD). Discussion Social Cognition tests accurately distinguish bvFTD from AD regardless of the executive profile. [ABSTRACT FROM AUTHOR]

Objective: Cognitive tests of inhibitory control show variable results for the differential diagnosis between behavioural variant of Frontotemporal Dementia (bvFTD) and Alzheimer's disease (AD). We compared the diagnostic accuracies of tests of inhibitory control and of a behavioural questionnaire, to distinguish bvFTD from AD. Methods: Three groups of participants were enrolled: 27 bvFTD patients, 25 AD patients, and 24 healthy controls. Groups were matched for gender, education, and socio-economic level. Participants underwent a comprehensive neuropsychological assessment of inhibitory control, including Hayling Test, Stroop, the Five Digits Test (FDT) and the Delay Discounting Task (DDT). Caregivers completed the Barratt Impulsiveness Scale 11th version (BIS-11). Results: bvFTD and AD groups showed no difference in the tasks of inhibitory control, while the caregiver questionnaire revealed that bvFTD patients were significantly more impulsive (BIS-11: bvFTD 76.1+9.5, AD 62.9+13, p <.001). Conclusions: Neuropsychological tests of inhibitory control failed to distinguish bvFTD from AD. On the contrary, impulsivity caregiver-completed questionnaire provided good distinction between bvFTD and AD. These results highlight the current limits of cognitive measures of inhibitory control for the differential diagnosis between bvFTD and AD, whereas questionnaire information appears more reliable and in line with clinical diagnostics. [ABSTRACT FROM AUTHOR]