Sensitivity and specificity of the Bamberg Dementia Screening Test's (BDST) full and short versions: brief screening instruments for geriatric patients that are suitable for infectious environments

"Try to Build This Bunny as Fast as Possible without Using Red or Pink Bricks": How Simple Assembly Tasks Might Aid in Detecting People with Mild Cognitive Impairment and Dementia

(1) Background: Dementia and mild cognitive impairment (MCI) are still underdiagnosed in the general population. Impaired odor identification has been identified as an early marker of MCI and dementia. We aim to investigate whether short tasks, in which simple forms must be assembled from single building blocks based on a template or while considering specific re-strictions, could increase the diagnostic quality of established cognitive screening tests in detecting MCI or dementia. (2) Methods: A brief assembly test, where participants had to assemble simple animal shapes from Lego® Duplo® building blocks, the Frontal Assessment Battery, and the Mini-Mental State Exam (MMSE) were administered to a consecutive series of 197 patients (89 with mild dementia, 62 with mild cognitive impairment, and 46 without cognitive impairment) referred for neuropsychological testing. (3) Results: Both participants with dementia and with MCI performed badly in the assembly tasks. The assembly tasks and the Frontal Assessment Battery were substantially correlated. Complementing MMSE scores with the assembly tasks improved the diagnostic accuracy of individuals with dementia and MCI. (4) Conclusions: People with suspected dementia or MCI may already benefit from simple assembly tasks. Although these tests require little additional time, they can notably increase sensitivity for dementia or MCI.

"Mmm, Smells like Coffee!": How a Brief Odor Identification Test Could Help to Identify People with Mild Cognitive Impairment and Dementia

(1) Background: Dementia and mild cognitive impairment (MCI) are still underdiagnosed in the general population. Impaired odor identification has been identified as an early marker of MCI and dementia. We aimed to compare the additional diagnostic value of two odor identification tests to a cognitive screening test in detecting MCI or dementia. (2) Methods: The Sniffin' Sticks odor identification test (SS-OIT), a brief odor identification test (B-OIT) requiring the identification of coffee scent, and the Mini-Mental State Exam (MMSE) were administered to a consecutive series of 174 patients (93 with dementia, 42 with mild cognitive impairment, and 39 without cognitive impairment) referred for neuropsychological testing. (3) Results: Both participants with dementia and with MCI exhibited impairments in odor identification. The SS-OIT and the B-OIT were substantially correlated. Complementing MMSE scores with the SS-OIT or the B-OIT similarly improved the diagnostic accuracy of individuals with dementia and MCI. (4) Conclusions: People with suspected dementia or MCI may already benefit from brief odor identification tests. Although these tests require little additional time, they can notably increase sensitivity for dementia or MCI.

Telephone Interview for Cognitive Status (TICS): Italian adaptation, psychometrics and diagnostics

BACKGROUND

Telephone-based cognitive screening (TBCS) is crucial to telehealth care of neurological patients, prevention campaigns, and epidemiological studies on cognitive impairment. The Telephone Interview for Cognitive Status (TICS) is one of the most widespread and psychometrically/diagnostically sound TBCS test, with several versions developed worldwide (e.g., with and without a delayed recall item). In Italy, only attempts of adaptation and preliminary evidence of its statistical features have been provided so far. This study thus aimed at (1) developing an Italian version of the TICS and assessing its (2) psychometric and (3) diagnostic properties.

METHODS

A back-translated and culturally adapted version of the TICS was developed. Three-hundred and sixty-five healthy individuals from different regions of Italy (147 males, 216 females; age: 53.2 ± 16 years; education: 13 ± 4.5 years) were administered the TICS and the Italian telephone-based Mini-Mental State Examination (Itel-MMSE). Validity was tested by convergence and at the structure level, whereas reliability as internal consistency, test-retest, and inter-rater. Diagnostic accuracy, item difficulty, and discrimination were also examined.

RESULTS

The TICS featured a single component and its score converged with that of the Itel-MMSE (rs = .37). Reliability was excellent as inter-rater (ICC = .94), good as test-retest (ICC = .78), and acceptable as internal consistency (Cronbach's α = .63). Accuracy was high as tested against the Itel-MMSE (AUC = .83) and did not improve when adding the delayed recall. Backward subtraction was the most difficult and discriminative task.

DISCUSSION

The Italian TICS is a valid, reliable, and diagnostically accurate TBCS test. The original format of the TICS can be thus adopted in both clinical and research settings.

|tPRiors |: a tool for prior elicitation and obtaining posterior distributions of true disease prevalence

BACKGROUND

Tests have false positive or false negative results, which, if not properly accounted for, may provide misleading apparent prevalence estimates based on the observed rate of positive tests and not the true disease prevalence estimates. Methods to estimate the true prevalence of disease, adjusting for the sensitivity and the specificity of the diagnostic tests are available and can be applied, though, such procedures can be cumbersome to researchers with or without a solid statistical background. This manuscript introduces a web-based application that integrates statistical methods for Bayesian inference of true disease prevalence based on prior elicitation for the accuracy of the diagnostic tests. This tool allows practitioners to simultaneously analyse and visualize results while using interactive sliders and output prior/posterior plots.

METHODS - IMPLEMENTATION

Three methods for prevalence prior elicitation and four core families of Bayesian methods have been combined and incorporated in this web tool. |tPRiors| user interface has been developed with R and Shiny and may be freely accessed on-line.

RESULTS

|tPRiors| allows researchers to use preloaded data or upload their own datasets and perform analysis on either single or multiple population groups clusters, allowing, if needed, for excess zero prevalence. The final report is exported in raw parts either as.rdata or.png files and can be further analysed. We utilize a real multiple-population and a toy single-population dataset to demonstrate the robustness and capabilities of |tPRiors|.

CONCLUSIONS

We expect |tPRiors| to be helpful for researchers interested in true disease prevalence estimation and who are keen on accounting for prior information. |tPRiors| acts both as a statistical tool and a simplified step-by-step statistical framework that facilitates the use of complex Bayesian methods. The application of |tPRiors| is expected to aid standardization of practices in the field of Bayesian modelling on subject and multiple group-based true prevalence estimation.

Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer's Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

BACKGROUND

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer's disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD.

OBJECTIVE

We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test.

METHODS

Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent.

RESULTS

A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260).

CONCLUSION

MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.