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This study proposes the Pairwise Attention Enhancement (PAE) model to address the limitations of the Vision Transformer (ViT). While the ViT effectively models global relationships between image patches, it encounters challenges in medical image analysis where fine-grained local features are crucial. Although the ViT excels at capturing global interactions within the entire image, it may potentially underperform due to its inadequate representation of local features such as color, texture, and edges. The proposed PAE model enhances local features by calculating cosine similarity between the attention maps of training and reference images and integrating attention maps in regions with high similarity. This approach complements the ViT's global capture capability, allowing for a more accurate reflection of subtle visual differences. Experiments using Clock Drawing Test data demonstrated that the PAE model achieved a precision of 0.9383, recall of 0.8916, F1-Score of 0.9133, and accuracy of 92.69%, showing a 12% improvement over API-Net and a 1% improvement over the ViT. This study suggests that the PAE model can enhance performance in computer vision fields where local features are crucial by overcoming the limitations of the ViT. [ABSTRACT FROM AUTHOR]

AbstractBackground and Objectives: In geriatrics and dementia care, early diagnosis is crucial. We developed a dementia screening model using drawing features from clock drawing tests (CDT) and investigated the features contributing to the discrimination of dementia and its screening performance. Methods: This study included 129 older adults attending a dementia outpatient clinic. We obtained information on the diagnosis of dementia and CDT data from medical records and quantified 12 types of drawing features according to the Freedman scoring system. Based on the dementia diagnosis information, participants were assigned to two groups: 58 in the dementia diagnosis group and 71 in the non-diagnosis group. Using Boruta, an iterative feature selection algorithm, and a support vector machine, a machine learning method, we analyzed the drawing features contributing to dementia discrimination and evaluated discrimination performance. Results: Five types of drawing features were selected as contributors to discrimination, including “numbers in the correct position,” “minute target number indicated,” and “hand in correct proportion.” These features exhibited a discriminating sensitivity of 0.74 ± 0.16 and specificity of 0.74 ± 0.18 for detecting dementia. Conclusion: This study demonstrated a method for identifying individuals likely to be diagnosed with dementia among patients attending a dementia outpatient clinic using drawing features. The knowledge of drawing features contributing to dementia differentiation may assist healthcare practitioners in clinical reasoning and provide novel insights for clinical practice. In the future, we plan to develop a primary screening for dementia based on machine learning using CDT. [ABSTRACT FROM AUTHOR]

Abstract Identifying high-risk patients for developing postoperative delirium (POD) is essential for optimizing the medical field’s human and financial resources through specialty-relevant geriatric assessments that can aid in establishing prehabilitation strategies. This study aims to identify geriatric screening tools to predict preoperative delirium and explore the high-risk elderly patients undergoing oral maxillofacial surgery. A comprehensive geriatric assessment encompassing 23 instruments was used to evaluate inpatients undergoing surgery under general anaesthesia, preoperatively and postoperatively. Selective intraoperative and postoperative variables were also assessed for their relation to POD occurrence. This prospective study included 90 patients (mean age 79.0 years) from August 2022 to August 2023. The POD rate in this cohort was (8.9% n = 8). The Clock-Drawing Test (CDT) was significantly associated with POD occurrence (p = 0.005). Significant associations were found between POD occurrence and operation type (p = 0.018), duration (p = 0.026), length of stay ( p = 0.002), and postoperative hemoglobin levels (p = 0.027). This study highlights the importance of comprehensive geriatric assessments in predicting POD in elderly patients. Future research should build on these findings to enhance preoperative care strategies and improve outcomes. Trial registration: German Register of Clinical Studies, DRKSID DRKS00028614.

Abstract Background Mobile device-based cognitive screening has the potential to overcome the limitations in diagnostic precision and efficiency that characterize conventional pen and paper cognitive screening. Several mobile device-based cognitive testing platforms have demonstrated usability, but the usability of take-home mobile device-based cognitive screening in typical adult primary care patients requires further investigation. Methods This study set out to test the usability of a prototype mobile device-based cognitive screening test in older adult primary care patients across a range of cognitive performance. Participants completed the St. Louis University Mental Status Examination (SLUMS) and then used a study-supplied mobile device application at home for 5 days. The application presented 7 modules lasting approximately 15 min. Participants completed the System Usability Scale (SUS) after using the application. Results A total of 51 individuals participated, with a median (IQR) age of 81 (74–85) years. Cognitive impairment (SLUMS score

Background: Mobile device-based cognitive screening has the potential to overcome the limitations in diagnostic precision and efficiency that characterize conventional pen and paper cognitive screening. Several mobile device-based cognitive testing platforms have demonstrated usability, but the usability of take-home mobile device-based cognitive screening in typical adult primary care patients requires further investigation. Methods: This study set out to test the usability of a prototype mobile device-based cognitive screening test in older adult primary care patients across a range of cognitive performance. Participants completed the St. Louis University Mental Status Examination (SLUMS) and then used a study-supplied mobile device application at home for 5 days. The application presented 7 modules lasting approximately 15 min. Participants completed the System Usability Scale (SUS) after using the application. Results: A total of 51 individuals participated, with a median (IQR) age of 81 (74–85) years. Cognitive impairment (SLUMS score < 27) was present in 30 (59%) of participants. The mean (95% Confidence Interval [CI]) SUS score was 76 (71–81), which indicates good usability. Usability scores were similar across ranges of cognitive impairment. A Lower SLUMS score predicted early withdrawal from the study with an area under the receiver operating characteristic curve (95% CI) of 0.78 (0.58–0.97). Conclusion: Take-home mobile device-based cognitive testing is a usable strategy for many older adult primary care patients. Depending on patient preferences and abilities, it could be part of a flexible cognitive testing and follow-up strategy that includes mobile device-based testing in healthcare settings and pen-and-paper cognitive testing. [ABSTRACT FROM AUTHOR]

BACKGROUND: The Rey-Osterrieth Complex Figure Test (ROCFT) and the Clock Drawing Test (CDT) are commonly used in clinical practice. The ROCFT measures constructional praxis, visual perception, and visuospatial learning and memory, and the CDT assesses for visuospatial, constructional, and executive difficulties. Several neurological disorders are associated with visuospatial and visuo-constructional impairments, yet reliable normative data accounting for sociodemographic and acculturative variables are scarce for Hispanics living in the U.S. OBJECTIVE: To generate normative data for the ROCFT and CDT in a Spanish-speaking adult population living in the U.S. METHODS: The sample consisted of 245 cognitively healthy adults recruited from several states in the U.S. Each participant was administered the ROCFT and CDT as part of a larger cognitive battery. The ROCFT and CDT were normed using a Bayesian approach. Age, age2, education, sex, acculturation, and language proficiency were included as predictors in the analyses. RESULTS: ROCFT performance was associated with education and age, particularly as they interacted with Spanish language proficiency and time spent in the U.S. Education was significantly associated with recall abilities and a lower memory recall on the ROCFT. Age was found to vary depending on a person's bilingual abilities. Sex did not emerge as a predictor of performance, and it did not interact significantly with other variables. CONCLUSION: This is the first study to include acculturation and language proficiency variables in the creation of norms for the assessment of visuo-constructional abilities. This study will have a large impact on the practice of neuropsychology in the U.S. [ABSTRACT FROM AUTHOR]

Background: The Clock Drawing Test (CDT) is used to screen for Alzheimer's disease and other dementia disorders. Normative scores on the version from the Montreal Cognitive Assessment (MoCA) do not exist in the Nordic countries. Objective: To examine the normative scores of the CDT among adults aged 70 years and older. Methods: We included 4,023 cognitively healthy persons aged 70–97 years from a population survey in Norway. They were examined with the CDT, which has a total score between zero and three. A multiple multinominal regression model was applied with a CDT score as the dependent categorical variable and estimated the probabilities of scoring a particular score, stratified by age, sex, and education. These probabilities correspond to an expected proportion of the normative population scoring at, or below a given percentile. Results: None scored zero, 2.1% scored one, 14.9% scored two, and 83% scored three. Higher age, female sex and fewer years of schooling were associated with poorer performance. Scores of zero and one deviated from the normative score regardless of age, sex and education. A score of two was within the norm for a female older than 81 and a male older than 85. Conclusions: The majority (83%) of people 70 years and older had a score of three on the CDT. Lower age, male sex, and higher education were associated with a better performance. Scores of zero and one were below the normative score. Except for the very old, a score of two was also well below the normative score. [ABSTRACT FROM AUTHOR]

• The Clock Drawing Test (CDT) is a useful risk stratification tool for older emergency department patients presenting with non-specific complaints. • The CDT can be used as predictor for 30-day mortality and hospital length of stay. • The early identification of individuals at risk may help to attribute resources, support disposition decisions, and may ultimately lead to improved quality of care. Cognitive impairment (CI) is common among older patients presenting to the emergency department (ED). The failure to recognize CI at ED presentation constitutes a high risk of additional morbidity, mortality, and functional decline. The Clock Drawing Test (CDT) is a well-established cognitive screening test. In patients presenting to the ED with non-specific complaints (NSCs), we aimed to investigate the usability of the CDT and its prognostic value regarding length of hospital stay (LOS) and mortality. Secondary analysis of the Basel Non-specific Complaints (BANC) trial, a prospective delayed type cross-sectional study with a 30-day follow-up. In three EDs, patients presenting with NSCs were enrolled. The CDT was administered at enrollment. In the 1,278 patients enrolled, median age was 81 [74, 87] years and 782 were female (61.19%). A valid CDT was obtained in 737 (57.7%) patients. In patients without a valid CDT median LOS was higher (29 [9, 49] days vs. 22 [9, 45] days), and 30-day mortality was significantly higher than in patients with a valid CDT (n = 45 (8.32%) vs. n = 39 (5.29%)). Of all valid CDTs, 154 clocks (20.9%) were classified as normal, 55 (7.5%) as mildly deficient, 297 (40.3%) as moderately deficient, and 231 (31.3%) as severely deficient. Mortality and LOS increased along with the CDT deficits (p = 0.012 for 30-day mortality; p < 0.001 for LOS). The early identification of patients with CI may lead to improved patient management and resource allocation. The CDT could be used as a risk stratification tool for older ED patients presenting with NSCs, as it is a predictor for 30-day mortality and LOS. [Display omitted] [ABSTRACT FROM AUTHOR]

The common requirement to set the time to "10 past 11" on the Clock Drawing Test is intended to elicit a stimulus bound response (SBR), in which the responder is "pulled" to the salient stimulus "10," resulting in hands set at "10 before 11." SBRs are considered markers of executive dysfunction, although this assumption has not yet been validated. We compared SBR and other time-setting errors on inhibitory control tests, hypothesizing that they represent related constructs. The role of semantic dysfunction in the formation of those errors was also investigated. We examined baseline test performance of participants with Mild Cognitive Impairment or a history of depression, and control participants, enrolled in a dementia prevention study. Among 258 participants, we identified clocks with SBRs (n = 16), other time errors (n = 22), or no errors at all (n = 42). Performance between the groups with SBRs and other time-setting errors did not differ on any of the executive tests, and both error groups performed significantly worse than the No Error group on the semantic tests. Control for covariates further supported semantic and executive components in time-setting errors. Both semantic and inhibitory control deficits may underlie time representation errors in general. [ABSTRACT FROM AUTHOR]

Objectives: Cognitive impairment is a prevalent non-motor symptom of Parkinson's disease (PD), significantly impacting patient quality of life. The Clock Drawing Test (CDT) evaluates cognitive abilities, including planning, organization, and executive functions such as attention, memory, and visuospatial skills. This study aimed to determine the sensitivity of the CDT in diagnosing cognitive impairment in PD. Methods: We reviewed the records of 44 PD patients (16 female, 28 male) diagnosed with dementia (30 patients) or mild cognitive impairment (14 patients) between 2018 and 2022. These patients were compared to 106 visitors to the neurological outpatient clinic, serving as a control group. A separate researcher assessed the patients' CDT scores, maintaining confidentiality of all other patient data except age and education level. Results: Among the 44 PD patients, two with mild cognitive impairment were rated as normal, while all PD dementia cases were identified solely through the CDT. In the healthy control group, 72 out of 106 individuals reported no cognitive complaints, whereas 34 individuals (32.1%) reported cognitive complaints as assessed by a blind investigator. The CDT demonstrated a positive predictive value of 55.3% and a negative predictive value of 97.3%. Sensitivity was calculated at 95.5%, and specificity was 67.9%. Conclusion: The findings suggest that the CDT is sensitive in detecting cognitive impairment in PD patients with cognitive deficits. While the CDT serves as an effective rapid screening tool, high scores indicate the absence of cognitive impairment, but low scores alone are insufficient for a definitive diagnosis of dementia. Comprehensive neurological evaluation and detailed cognitive assessment remain essential for confirming dementia diagnoses. [ABSTRACT FROM AUTHOR]

Featured Application: The implementation of targeted interventions focusing on specific cognitive domains affected by depression and cognitive impairment, ultimately enhancing the overall cognitive health and well-being of older adults. This study examined the cognitive performance of older adults aged 60 and above using the Montreal Cognitive Assessment (MoCA) test and DigiMoCA, a digital tool for cognitive screening administered by means of a smart speaker, to investigate whether the additional variables utilised by DigiMoCA allow for the identification of significant differences between individuals with depressive symptoms and those with mild cognitive impairment, which are not detected using the original MoCA test. A total of 73 senior adults located in Northwestern Spain, 22 male and 51 female, participated in this study. Subjects were divided into four groups based on the presence of depressive symptoms and mild cognitive impairment, with the aim of analysing the results of each dimension of the MoCA and DigiMoCA tests and assessing the additional insights provided by the digital administration tool. The results indicate significant differences among groups. Individuals with depressive symptoms exhibited poorer performance in forward number span, attention, and clock drawing compared to healthy controls. Furthermore, individuals with depressive symptoms and mild cognitive impairment exhibited significantly worse memory and orientation compared to those with cognitive impairment alone. Correlations revealed that a greater severity of depressive symptoms was associated with poorer performance across cognitive domains, including visuospatial skills, attention, language, memory, and phonemic verbal fluency. This study also illustrated how the exploitation of additional variables systematically captured by digital instruments, such as completion times or response delays to individual interactions, may facilitate the early identification of cognitive and depressive conditions, providing initial evidence about the importance of integrating advanced digital tools in cognitive assessment to inspire the development of more effective, personalised interventions. [ABSTRACT FROM AUTHOR]

The Clock Drawing Test (CDT) is a professional examination that can detect cognitive impairments, such as Parkinson’s and Alzheimer’s diseases, based on scoring criteria. The pooling layers of a convolutional neural network (CNN) compress features by reducing dimensionality, which tends to focus on a single dominant element. This can be detrimental to compressing information in CDT images, where all elements are significant features. Therefore, in this study, we developed a model that utilizes features obtained from multiple channels to focus on all the elements within an image using channel and spatial attention. We utilized supervised contrastive learning to classify patient and control groups solely from CDT images. The features obtained from the multiple channels of the MCC-net were used to compute contrastive loss and learn representations of the data. Subsequently, a classifier was trained to learn the decision boundaries between the data. When the MCC-net was trained for binary classification, the accuracy, sensitivity, specificity, and area under the curve reached their maximum values of 0.9718, 0.8358, 0.9789, and 0.9700, respectively. As far as our knowledge extends, this study represents the first instance of utilizing supervised contrastive learning, acquiring features from multiple channels, for classifying CDT images, and we achieved superior performance compared to other models. Furthermore, the model visualized the attention clock elements to provide evidence for the inference results and presents the potential of utilizing artificial intelligence to classify CDT images.

Abstract Background Disease-modifying treatments for Alzheimer’s disease highlight the need for early detection of cognitive decline. However, at present, most primary care providers do not perform routine cognitive testing, in part due to a lack of access to practical cognitive assessments, as well as time and resources to administer and interpret the tests. Brief and sensitive digital cognitive assessments, such as the Digital Clock and Recall (DCR™), have the potential to address this need. Here, we examine the advantages of DCR over the Mini-Mental State Examination (MMSE) in detecting mild cognitive impairment (MCI) and mild dementia. Methods We studied 706 participants from the multisite Bio-Hermes study (age mean ± SD = 71.5 ± 6.7; 58.9% female; years of education mean ± SD = 15.4 ± 2.7; primary language English), classified as cognitively unimpaired (CU; n = 360), mild cognitive impairment (MCI; n = 234), or probable mild Alzheimer’s dementia (pAD; n = 111) based on a review of medical history with selected cognitive and imaging tests. We evaluated cognitive classifications (MCI and early dementia) based on the DCR and the MMSE against cohorts based on the results of the Rey Auditory Verbal Learning Test (RAVLT), the Trail Making Test-Part B (TMT-B), and the Functional Activities Questionnaire (FAQ). We also compared the influence of demographic variables such as race (White vs. Non-White), ethnicity (Hispanic vs. Non-Hispanic), and level of education (≥ 15 years vs.

Abstract Background Post-stroke neurocognitive disorder, though common, is often overlooked by clinicians. Moreover, although the Montreal Cognitive Assessment (MoCA) has proven to be a valid screening test for neurocognitive disorder, even more time saving tests would be preferred. In our study, we aimed to determine the diagnostic accuracy of the Clock Drawing Test (CDT) for post-stroke neurocognitive disorder and the association between the CDT and MoCA. Methods This study is part of the Norwegian Cognitive Impairment After Stroke study, a multicentre prospective cohort study following patients admitted with acute stroke. At the three-month follow-up, patients were classified with normal cognition, mild neurocognitive disorder, or major neurocognitive disorder according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition criteria. Any neurocognitive disorder compromised both mild- and major neurocognitive disorder. The CDT at the three-month assessment was given scores ranging from 0 to 5. Patients able to complete the CDT and whose cognitive status could be classified were included in analyses. The CDT diagnostic accuracy for post-stroke neurocognitive disorder was identified using receiver operating characteristic curves, sensitivity, specificity, positive predictive value, and negative predictive value. The association between the MoCA and CDT was analysed with Spearman’s rho. Results Of 554 participants, 238 (43.0%) were women. Mean (SD) age was 71.5 (11.8) years, while mean (SD) National Institutes of Health Stroke Scale score was 2.6 (3.7). The area under the receiver operating characteristic curve of the CDT for major neurocognitive disorder and any neurocognitive disorder was 0.73 (95% CI, 0.68–0.79) and 0.68 (95% CI, 0.63–0.72), respectively. A CDT cutoff of

This study proposes the Pairwise Attention Enhancement (PAE) model to address the limitations of the Vision Transformer (ViT). While the ViT effectively models global relationships between image patches, it encounters challenges in medical image analysis where fine-grained local features are crucial. Although the ViT excels at capturing global interactions within the entire image, it may potentially underperform due to its inadequate representation of local features such as color, texture, and edges. The proposed PAE model enhances local features by calculating cosine similarity between the attention maps of training and reference images and integrating attention maps in regions with high similarity. This approach complements the ViT’s global capture capability, allowing for a more accurate reflection of subtle visual differences. Experiments using Clock Drawing Test data demonstrated that the PAE model achieved a precision of 0.9383, recall of 0.8916, F1-Score of 0.9133, and accuracy of 92.69%, showing a 12% improvement over API-Net and a 1% improvement over the ViT. This study suggests that the PAE model can enhance performance in computer vision fields where local features are crucial by overcoming the limitations of the ViT.

Abstract Background Decline in olfaction may occur after general anesthesia, but the exact incidence and underlying physiopathology remain scarcely investigated. Olfactory dysfunction arises with aging and is known to be linked to cognitive impairment. In this pilot study, we evaluated the incidence of immediate postoperative decline in olfaction and its association with a preoperative cognitive test, performance at Clock Drawing Test (CDT), in a group of older patients. Methods This pilot study is a sub-analysis of a prospective observational study. Patients ≥ 65 years old and scheduled for elective non-cardiac surgery under sevoflurane-based anesthesia were enrolled. CDT was part of the preoperative evaluation. We assessed olfaction on the day before and the day after surgery (between 16 and 26 h postoperatively) using the Sniffin’ Sticks 12-item identification test, which consists of pen-like devices displaying 12 different odors. Postoperative decline in olfaction was defined as a decrease of at least 1 standard deviation in the olfactory score. Results We included a total of 93 patients, among whom 19 (20.4%) presented a postoperative decline in olfaction. The incidence of postoperative decline in olfaction was higher in the “CDT low-score” (score ≤ 5/8) group (11/34, 32.4%) than in the “CDT high-score” (score ≥ 6/8) group (8/58, 13.6%) (P = 0.030). Despite adjusting for confounding variables, CDT score remained independently associated with immediate postoperative decline in olfactory identification function (OR 0.67, 95% CI 0.48 to 0.94, P = 0.022). Conclusions Postoperative decline in olfaction occurred in 20.4% of older patients and was associated with poor preoperative performance at CDT. Trial registration This study was retrospectively registered on https://clinicaltrials.gov/ under the NCT04700891 number (principal investigator: Victoria Van Regemorter), in December 2020.

Objective: We investigated the diagnostic accuracy of the Clock Drawing Test (CDT) in discriminating Mild Cognitive Impairment (MCI) and dementia from normal cognition. Additionally, its clinical utility in predicting the transition from normal cognition to MCI and dementia over the course of several years was explored. Method: In total, 1037 older adults (633 women) who completed the CDT in a baseline assessment were drawn from the population-based HELIAD cohort. Among these, 848 participants were identified as cognitively normal, 142 as having MCI and 47 with dementia during the baseline assessment. Of these individuals, 565 attended the follow-up assessment (mean interval: 3.21 years). ROC curve and binary logistic regression analyses were performed. Results: The CDT exhibited good diagnostic accuracy for the discrimination between dementia and normal cognition (AUC =.879, SN =.813, SP =.778, LR+ = 3.66, LR- =.240, <.001, d = 1.655) and acceptable diagnostic accuracy for the discrimination between dementia and MCI (AUC=.761, SN=.750, SP=.689, LR+ = 2.41, LR- =.362, p <.001, d = 1.003). We found limited diagnostic accuracy, however, for the discrimination between MCI and normal cognition (AUC =.686, SN =.764, SP =.502, LR+ = 1.53, LR- =.470, p <.001, d =.685). Moreover, the CDT significantly predicted the transition from normal cognition to dementia [Exp(B)= 1.257, p =.022], as well as the transition from MCI to normal cognition [Exp(B) = 1.334, p =.023] during the longitudinal investigation. Conclusions: The CDT is a neuropsychological test with acceptable diagnostic accuracy for the discrimination of dementia from MCI and normal cognition. Furthermore, it has an important predictive value for the transition from normal cognition to dementia and from MCI to normal cognition. [ABSTRACT FROM AUTHOR]

This study examined the cognitive performance of older adults aged 60 and above using the Montreal Cognitive Assessment (MoCA) test and DigiMoCA, a digital tool for cognitive screening administered by means of a smart speaker, to investigate whether the additional variables utilised by DigiMoCA allow for the identification of significant differences between individuals with depressive symptoms and those with mild cognitive impairment, which are not detected using the original MoCA test. A total of 73 senior adults located in Northwestern Spain, 22 male and 51 female, participated in this study. Subjects were divided into four groups based on the presence of depressive symptoms and mild cognitive impairment, with the aim of analysing the results of each dimension of the MoCA and DigiMoCA tests and assessing the additional insights provided by the digital administration tool. The results indicate significant differences among groups. Individuals with depressive symptoms exhibited poorer performance in forward number span, attention, and clock drawing compared to healthy controls. Furthermore, individuals with depressive symptoms and mild cognitive impairment exhibited significantly worse memory and orientation compared to those with cognitive impairment alone. Correlations revealed that a greater severity of depressive symptoms was associated with poorer performance across cognitive domains, including visuospatial skills, attention, language, memory, and phonemic verbal fluency. This study also illustrated how the exploitation of additional variables systematically captured by digital instruments, such as completion times or response delays to individual interactions, may facilitate the early identification of cognitive and depressive conditions, providing initial evidence about the importance of integrating advanced digital tools in cognitive assessment to inspire the development of more effective, personalised interventions.

Background: Decline in olfaction may occur after general anesthesia, but the exact incidence and underlying physiopathology remain scarcely investigated. Olfactory dysfunction arises with aging and is known to be linked to cognitive impairment. In this pilot study, we evaluated the incidence of immediate postoperative decline in olfaction and its association with a preoperative cognitive test, performance at Clock Drawing Test (CDT), in a group of older patients. Methods: This pilot study is a sub-analysis of a prospective observational study. Patients ≥ 65 years old and scheduled for elective non-cardiac surgery under sevoflurane-based anesthesia were enrolled. CDT was part of the preoperative evaluation. We assessed olfaction on the day before and the day after surgery (between 16 and 26 h postoperatively) using the Sniffin' Sticks 12-item identification test, which consists of pen-like devices displaying 12 different odors. Postoperative decline in olfaction was defined as a decrease of at least 1 standard deviation in the olfactory score. Results: We included a total of 93 patients, among whom 19 (20.4%) presented a postoperative decline in olfaction. The incidence of postoperative decline in olfaction was higher in the "CDT low-score" (score ≤ 5/8) group (11/34, 32.4%) than in the "CDT high-score" (score ≥ 6/8) group (8/58, 13.6%) (P = 0.030). Despite adjusting for confounding variables, CDT score remained independently associated with immediate postoperative decline in olfactory identification function (OR 0.67, 95% CI 0.48 to 0.94, P = 0.022). Conclusions: Postoperative decline in olfaction occurred in 20.4% of older patients and was associated with poor preoperative performance at CDT. Trial registration: This study was retrospectively registered on https://clinicaltrials.gov/ under the NCT04700891 number (principal investigator: Victoria Van Regemorter), in December 2020. [ABSTRACT FROM AUTHOR]

Alzheimer's disease is an incurable disorder that accounts for up to 70% of all dementia cases. While the prevalence of Alzheimer's disease and other types of dementia has increased by more than 160% in the last 30 years, the rates of undetected cases remain critically high. The present work aims to address the underdetection of Alzheimer's disease by proposing four logistic regression models that can be used as a foundation for community-based screening tools that do not require the participation of medical professionals. Our models make use of individual clock drawing errors as well as complementary patient data that is highly available and easily collectible. All models were controlled for age, education, and gender. The discriminative ability of the models was evaluated by area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow test, and calibration plots were used to assess calibration. Finally, decision curve analysis was used to quantify clinical utility. We found that among 10 possible CDT errors, only 3 were informative for the detection of Alzheimer's disease. Our base regression model, containing only control variables and clock drawing errors, produced an AUC of 0.825. The other three models were built as extensions of the base model with the step-wise addition of three groups of complementary data, namely cognitive features (semantic fluency score), genetic predisposition (family history of dementia), and cardio-vascular features (BMI, blood pressure). The addition of verbal fluency scores significantly improved the AUC compared to the base model (0.91 AUC). However, further additions did not make a notable difference in discriminatory power. All models showed good calibration. In terms of clinical utility, the derived models scored similarly and greatly outperformed the base model. Our results suggest that the combination of clock symmetry and clock time errors plus verbal fluency scores may be a suitable candidate for developing accessible screening tools for Alzheimer's disease. However, future work should validate our findings in larger and more diverse datasets. [ABSTRACT FROM AUTHOR]

Background: Neurotropism of the hepatitis C virus (HCV) can be the source of subtle neuropsychological symptoms in non-cirrhotic patients. Age is a risk factor for cognitive impairment (CI). Thus, asymptomatic elderly people who carry HCV might be at a greater risk of CI. Education can influence test performance. Objectives: (1) To verify whether elderly people with HCV performed poorer than controls on cognitive tests. (2) To analyze how education affects performance. (3) To verify whether the extent of the effect of education on performance depends on the group (HCV vs. controls) and the type of cognitive test. Methods: Asymptomatic HCV carriers older than 60 years (n = 41) were matched with 41 corresponding controls. All participants performed the following tests: Mini-Cog, Mini Mental State Examination, clock drawing test (CDT), and verbal fluency. Results: (1) There were no significant differences in cognitive performance between the two groups. (2) Higher education was always associated with better performance. (3) There was a significant group difference in the slopes of the regression lines between years of education and CDT performance. No differences were found for the other three tests. Conclusion: Considering the scores on the CDT, the rate of improvement in performance when schooling increases is higher in HCV carriers. [ABSTRACT FROM AUTHOR]

Objectives: The clock drawing test (CDT) is a widely used cognitive screening test. However, CDT performance is affected by education. This study examined an alternative, the Papadum test, designed for people with low levels of education/literacy. The association between education and test performance, correlation between CDT and Papadum test, and diagnostic accuracy of both CDT and Papadum tests were examined. Method: 89 healthy literate adults and 59 literate adults (all Bengali speaking) with a diagnosis of mild-moderate dementia from hospitals in Kolkata, India undertook the CDT and the Papadum test. Results: Education had a significant association with the CDT but not with the Papadum test. Across the whole sample there was a significant correlation between CDT and Papadum, but not within separate groups of healthy controls and patients. Diagnostic accuracy for the Papadum test was similar to that for CDT. Conclusions: Results highlight the strong influence that education has on CDT performance indicating that it is not suitable for those with low levels of literacy. The Papadum test could provide a viable alternative as a screening tool to the CDT for use with people who are illiterate or have low levels of education. Further validation studies are required. [ABSTRACT FROM AUTHOR]

Background: The clock drawing test (CDT) and the Mini Mental State Examination (MMSE) are frequently used screening instruments for cognitive impairment, however, the precise contribution of the CDT to the MMSE is largely unknown. Methods: We studied patients with subjective cognitive impairment (SCI, n = 481), mild cognitive impairment (MCI, n = 628) and Alzheimer's disease (AD, n = 1099). Discrimination between patients was examined with multiple logistic regression, adjusted for age, sex, and education. Four groups were constructed based on a normal/abnormal MMSE (cut‐off <24/30) versus normal/abnormal CDT (cut‐off ≤2/3). Visually rated medial temporal lobe atrophy (MTA) on CT was used as parameter of neurodegeneration. Results: The CDT significantly contributed to the MMSE in discriminating SCI from both MCI and AD patients. Our four group analyses showed that of those patients with a normal MMSE and incorrectly classified as SCI, an abnormal CDT could significantly identify 10.0% as MCI and 13.2% as AD. Among those with an abnormal MMSE, the percentage AD patients shifted from 53.1% to 82.1% due to an abnormal CDT. Presence of an abnormal CDT was significantly related to MTA increase, regardless of the MMSE score. Conclusion: The CDT is an important additional screening tool to the MMSE. An abnormal CDT with a normal MMSE is an indicator for cognitive impairment. An abnormal CDT in combination with an abnormal MMSE can be considered as an indicator of disease progression. Key points: The clock drawing test (CDT) is widely used as a screening tool for cognitive impairment, often in combination with the Mini Mental State Examination (MMSE), however, very few studies focus on the specific contribution of the CDT when the MMSE is known.To our knowledge, our study is the first to examine the additional value of the CDT to the MMSE in a large elderly memory clinic population to differentiate patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD) from those with subjective cognitive impairment (SCI). We focus on the clinical use of both tests using predefined cut‐off scores.When patients have an MMSE of 24 or higher, and are thus classified as having no cognitive impairment by the MMSE, the CDT can significantly identify close to 25% as having either MCI or AD. When the MMSE is below 24, the combination with an abnormal CDT yielded a percentage of 82% AD.When the MMSE is known, an abnormal CDT can give additional information on progression along the SCI‐MCI‐AD trajectory. We therefore recommend the CDT as a highly relevant, quick and easy to administrate screening tool. [ABSTRACT FROM AUTHOR]

The prevalence of dementia is currently increasing worldwide. This syndrome produces a deterioration in cognitive function that cannot be reverted. However, an early diagnosis can be crucial for slowing its progress. The Clock Drawing Test (CDT) is a widely used paper-and-pencil test for cognitive assessment in which an individual has to manually draw a clock on a paper. There are a lot of scoring systems for this test and most of them depend on the subjective assessment of the expert. This study proposes a computer-aided diagnosis (CAD) system based on artificial intelligence (AI) methods to analyze the CDT and obtain an automatic diagnosis of cognitive impairment (CI). This system employs a preprocessing pipeline in which the clock is detected, centered and binarized to decrease the computational burden. Then, the resulting image is fed into a Convolutional Neural Network (CNN) to identify the informative patterns within the CDT drawings that are relevant for the assessment of the patient's cognitive status. Performance is evaluated in a real context where patients with CI and controls have been classified by clinical experts in a balanced sample size of 3 2 8 2 drawings. The proposed method provides an accuracy of 7 5. 6 5 % in the binary case-control classification task, with an AUC of 0. 8 3. These results are indeed relevant considering the use of the classic version of the CDT. The large size of the sample suggests that the method proposed has a high reliability to be used in clinical contexts and demonstrates the suitability of CAD systems in the CDT assessment process. Explainable artificial intelligence (XAI) methods are applied to identify the most relevant regions during classification. Finding these patterns is extremely helpful to understand the brain damage caused by CI. A validation method using resubstitution with upper bound correction in a machine learning approach is also discussed. [ABSTRACT FROM AUTHOR]

Many clock drawing test (CDT) scoring systems focus on drawing results and lack drawing process assessments. This study created a CDT scoring procedure with drawing process assessment and explored its diagnostic value in screening for mild cognitive impairment (MCI) and early Alzheimer's disease (AD) from normal control (NC). We used logistic regression and receiver operating characteristic (ROC) curves to determine a new, sensitive scoring system for AD and MCI patients in a derivation cohort. The new scoring method was then compared to two common scoring systems and externally validated in a second cohort. We developed a new scoring system named CDT5, which contained one process assessment item: remember setting time without asking. Compared with two published scoring systems, CDT5 had better discriminatory power in distinguishing AD patients from NCs in derivation (area under the ROC curve [area under the curve, AUC] =.890) and validation (AUC =.867) cohorts. Three scoring systems had poor diagnostic accuracy at discriminating MCI patients from controls, with CDT5 being the most sensitive (78.57%). Adding the drawing process in CDT helps accurately detect patients with early AD, but its role in identifying patients with MCI needs to be further explored. [ABSTRACT FROM AUTHOR]

The clock drawing test (CDT) is a widely recognized neurocognitive test for executive and visuospatial functions. However, no normative data exist for Generation Z young adults (born on or after 1997). The widespread use of digital displays among this generation may impair performance on the analog CDT. Young Generation Z adults with at least 12 years of education, who were evaluated at the Israel Defense Forces (IDF) outpatient neurology clinic between 2021 and 2022, completed a CDT using the Manos-Wu method and drew a digital clock. Patients with possible cognitive impairment were excluded. Three hundred Generation Z patients were recruited, with a mean age of 19.7 ± 1.2 years. 171 (57.0 %) were female. Mean CDT score was 8.1 ± 2.5 out of 10 (Manos & Wu). A lower CDT score was associated with younger age (p = 0.031). No association was found with chief complaint, presence of ADHD diagnosis, gender, or postsecondary education. Digital clock drawing (4/4 digits) was successful in 100 % of patients. Generation Z adults demonstrate lower CDT scores than previously reported for older generations. The CDT may require revision to maintain its specificity for this population. Developing an alternative, digital-based tool for cognitive screening in young generations could be advisable. [Display omitted] • Many Generation Z young adults reportedly struggle with reading analog clocks. • The performance of Generation Z on the Clock Drawing Test (CDT) is not well studied. • We report poor than expected CDT scores in cognitively normal young adults. • Younger individuals tended to have lower CDT scores. • A subsample achieved perfect scores (100 %) on a digital clock drawing. [ABSTRACT FROM AUTHOR]

BackgroundVisuospatial dysfunction and cognitive impairment are common in Parkinson’s disease (PD), which draw increasing attention in the current literature. But clinicians still lack rapid, effective and unified cognitive battery for visuospatial assessment.ObjectiveA new approach was studied to explore the feasibility of using mobile application software (APP) to evaluate visuospatial dysfunction in patients with PD and compared with traditional assessment tools. We aimed to verify the threshold score of the APP for early diagnosis.Materials and methodsA total of 41 patients with PD underwent assessments using several test modules including Digit Symbol Test (DST), Visual Organization Test (VOT), Facial Recognition Test (FRT), Vocabulary Memory Test (VMT) of this APP, as well as Clock Drawing Test (CDT), Cube Copying Test (CCT) and the Mini-Mental State Examination (MMSE) for comparison. Among the 41 PD patients, 30 individuals were found to have visuospatial dysfunction based on CDT score

Objectives: Frailty has been suggested to take part in the recently demonstrated link between olfactory dysfunction and overall mortality risk. Preoperative assessment of frailty is essential to detect the most vulnerable patients scheduled for surgery. The aim of this study was to evaluate whether olfactory dysfunction is a reliable predictor of preoperative frailty and postoperative outcome. Design: This was a single-center prospective observational study conducted between July and October 2020 in Brussels, Belgium. Setting And Participants: 155 preoperative patients aged from 65 years old and scheduled for elective non-cardiac surgery. Measurements: Olfactory function was examined using the Sniffin' Sticks 12-item identification test. Frailty was assessed using the Edmonton Frail Scale (EFS) and handgrip strength. The clock drawing test (CDT) from the EFS was also analyzed separately to evaluate cognitive function. Patients were followed for postoperative complications and mortality over one year. Results: Olfactory dysfunction was significantly associated with the EFS score, anosmic patients having a higher median EFS score than normosmic patients (6[4–7] vs 4[2–5], p =.025). Anosmic patients had an increased odds of being frail after adjusting for possible confounding factors (OR: 6.19, 95% CI: 1.65–23.20, p =.007) and were more at risk of poor postoperative outcome (including complications and death) (OR: 4.33, 95% CI: 1.28–14.67, p =.018). Conclusions: Olfactory dysfunction is associated with preoperative frailty determined by the EFS and with poor post-surgical outcome at one-year. [ABSTRACT FROM AUTHOR]

This article aims to at analyze and point out the importance of the use of the Clock Drawing Test for cognitive screening in special education and rehabilitation with reference to early identification and adequate intervention for children and adults at risk, as well as to prevent the occurrence and intensification of disabilities. Through the simplicity of the test administration and scoring, as well as the great value of qualitative data based on the observation of participants’ behavior while performing the given task this test has gained popularity in research and clinical practice. On the other hand, in order to perform the given task, it is necessary to activate complex cognitive functions such asvisuospatial/visuoconstructive skills and executive functioning. Given the difficulties in performing, the Clock Drawing Test may be indicative of a potential cognitive inefficiencies in the specifieddomains and/or executive dysfunctions, such as those related to the temporoparietal and frontal lobe structures. In this regard, the present article aims to present and discuss the utility of the Clock Drawing Test in children of different ages and types of developmental challenges (attention deficit hyperactivity disorder, learning disabilities) as well as in adults with multiple sclerosis, traumatic brain injury and dementia.

ABSTRACT Cognitive decline can be screened by the clock drawing test (CDT), which has several versions. Objective: This survey aimed to analyze the correlation between two simple methods for scoring the CDT. Methods: This cross-sectional study was nested in the Elo-Creati cohort from Passo Fundo, Brazil and comprised 404 subjects. Two raters underwent previous training and scored the subjects’ CDT according to both the Pfizer and Shulman systems. The inter-observer and intra-observer concordance within each method was analyzed with the Spearman’s rank correlation coefficient, as well as the concordance of the scores between the two methods. Age and scholarity were also correlated with the scores. Results: Most of the participants were women (93.8%) and Caucasian (84.6%), with a mean age of 66.9 (±7.8) years and a scholarity of 10.9 years (±5.6). There was significant inter-observer (Pfizer: r=0.739, p£0.001; Shulman: r=0.727, p£0.001) and intra-observer correlation (Pfizer: rater 1, r=0.628, p≤0.001; rater 2, r=0.821, p≤0.001; Shulman: rater 1, r=0.843, p≤0.001; rater 2: r=0.819; p≤0.001). Intra-observer correlation was also observed comparing Pfizer and Shulman methods (rater 1: r=0.744; p≤0.001; rater 2: r=0.702; p≤0.001). There was weak correlation of the scores with scholarity (Pfizer: r=0.283, p£0.001; Shulman: r=0.244, p£0.001) and age (Pfizer: r=-0.174, p£0.001; Shulman: r=-0.170, p£0.001). More participants were classified with decreased cognition through the Pfizer system (rater 1: 44.3 vs. 26.5%; rater 2: 42.1 vs. 16.3%; p≤0.001). Conclusions: For this population, our results suggest that the Pfizer system of scoring CDT is more suitable for screening cognitive decline.

Alzheimer’s disease is an incurable disorder that accounts for up to 70% of all dementia cases. While the prevalence of Alzheimer’s disease and other types of dementia has increased by more than 160% in the last 30 years, the rates of undetected cases remain critically high. The present work aims to address the underdetection of Alzheimer’s disease by proposing four logistic regression models that can be used as a foundation for community-based screening tools that do not require the participation of medical professionals. Our models make use of individual clock drawing errors as well as complementary patient data that is highly available and easily collectible. All models were controlled for age, education, and gender. The discriminative ability of the models was evaluated by area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow test, and calibration plots were used to assess calibration. Finally, decision curve analysis was used to quantify clinical utility. We found that among 10 possible CDT errors, only 3 were informative for the detection of Alzheimer’s disease. Our base regression model, containing only control variables and clock drawing errors, produced an AUC of 0.825. The other three models were built as extensions of the base model with the step-wise addition of three groups of complementary data, namely cognitive features (semantic fluency score), genetic predisposition (family history of dementia), and cardio-vascular features (BMI, blood pressure). The addition of verbal fluency scores significantly improved the AUC compared to the base model (0.91 AUC). However, further additions did not make a notable difference in discriminatory power. All models showed good calibration. In terms of clinical utility, the derived models scored similarly and greatly outperformed the base model. Our results suggest that the combination of clock symmetry and clock time errors plus verbal fluency scores may be a suitable candidate for developing accessible screening tools for Alzheimer’s disease. However, future work should validate our findings in larger and more diverse datasets.

Purpose: The purposes of this study were to determine if (1) certain demographic characteristics (potential predictors) of participants, and (2) clock-drawing test results (as a screening test for cognitive impairment) were associated with fecal immunochemical test (FIT) sample collection errors.Methods: Patients scheduled for an upcoming colonoscopy were asked to collect stool samples using 5 different FITs. Patients completed a questionnaire that included the clock-drawing test. Errors included mistakes or omissions in recording the stool collection date and errors in stool collection. Each clock drawing was scored by 2 reviewers using 2 established methods.Results: Of the 1,448 participants with a clock drawing, 63% were female with a mean age of 63 years. In this population there were 83% White, 6% Black, and 24% Hispanic persons. Cognitive impairment was found in 292 patients by the Mendes-Santos method. Kappa coefficient for the 2 clock-drawing scores was 0.79 (P <.001). The multivariable generalized linear mixed model for FIT collection errors indicated being female (adjusted odds ratio [AOR], 1.64; 95% CI, 1.09-2.48), having an 8th grade or less education (AOR, 3.40; 95% CI, 1.87-6.18), and having an abnormal Mendes-Santos method clock score (AOR, 1.65; 95% CI, 1.08-2.54) were associated with significantly more errors.Conclusion: Among the participants who do not have dementia, FIT collection errors were made not only by those who had abnormal clock drawing, but also, by those with normal clock drawings. Subjects being female, having 8th grade education or less, and having an abnormal clock drawing scored by Mendes-Santos's method were associated with FIT collection errors. [ABSTRACT FROM AUTHOR]

This was a quantitative, retrospective, correlational, cross-sectional study that aimed to provide normative CDT (Clock-Drawing Test) data for older adults, taking into account different age groups and educational levels. The sample included 235 older adults distributed among five age groups and four levels of education. The instruments were Sociodemographic Data Sheet, the Mini-Mental State Examination (MMSE), the Geriatric Depression Scale reduced version (GDS-15), the Semantic Verbal Fluency Task (TFVS), and the CDT. Descriptive statistics, Pearson's correlation, and univariate analysis (one-way ANOVA) with Scheffe post hoc were used. The CDT scores showed significant associations with age, years of schooling, MMSE, TFVS, and GDS-15. There was a difference in performance in CDT when considering age groups. The present study was able to provide normative values for CDT in a sample of older adults in southern Brazil that were influenced by age, education, depressive symptoms, and verbal fluency. [ABSTRACT FROM AUTHOR]

Background: Hippocampal calcification (HC), highly prevalent in older people, has not attracted attention until recently. Despite its potential effects on cognition and behaviour, and its possible impact on the diagnosis and severity of dementia, it has not been investigated. This study aimed to evaluate the prevalence of HC and its influence on cognition and behavioural symptoms in patients with dementia. Methods: Data from consecutive patients who visited a medical centre for dementia, for the first time between April 2016 and September 2018, were extracted and analysed. These data included the patients' demographics, the presence of HC and hippocampal thickness as measured on computed tomography, the diagnosis of dementia and its type, cognitive function measured using the Mini‐Mental State Examination and the Clock Drawing Test, and the chief complaints or symptoms prompting the visit. Results: A high incidence of HC (85/267 patients) was observed. There was no significant difference in the ages of patients with and without HC. Patients with HC had higher cognitive function than those without HC at their first visit. This result was contrary to our expectations as it was not explained by the chief complaints recorded at the first visit. Conclusions: Our study showed a high prevalence of HC in older patients with dementia. Patients with HC had better cognitive function than did those without HC during their first hospital visit. This study suggests that HC may not affect the cognitive functions related to dementia. However, further research is needed to evaluate the long‐term consequences of dementia with HC. [ABSTRACT FROM AUTHOR]

Aim: Although clinicians primarily diagnose dementia based on a combination of metrics such as medical history and formal neuropsychological tests, recent work using linguistic analysis of narrative speech to identify dementia has shown promising results. We aim to build upon research by Thomas JA & Burkardt HA et al. (J Alzheimers Dis. 2020;76:905–2) and Alhanai et al. (arXiv:1710.07551v1. 2020) on the Framingham Heart Study (FHS) Cognitive Aging Cohort by 1) demonstrating the predictive capability of linguistic analysis in differentiating cognitively normal from cognitively impaired participants and 2) comparing the performance of the original linguistic features with the performance of expanded features. Methods: Data were derived from a subset of the FHS Cognitive Aging Cohort. We analyzed a sub-selection of 98 participants, which provided 127 unique audio files and clinical observations (n = 127, female = 47%, cognitively impaired = 43%). We built on previous work which extracted original linguistic features from transcribed audio files by extracting expanded features. We used both feature sets to train logistic regression classifiers to distinguish cognitively normal from cognitively impaired participants and compared the predictive power of the original and expanded linguistic feature sets, and participants’ Mini-Mental State Examination (MMSE) scores. Results: Based on the area under the receiver-operator characteristic curve (AUC) of the models, both the original (AUC = 0.882) and expanded (AUC = 0.883) feature sets outperformed MMSE (AUC = 0.870) in classifying cognitively impaired and cognitively normal participants. Although the original and expanded feature sets had similar AUC, the expanded feature set showed better positive and negative predictive value [expanded: positive predictive value (PPV) = 0.738, negative predictive value (NPV) = 0.889; original: PPV = 0.701, NPV = 0.869]. Conclusions: Linguistic analysis has been shown to be a potentially powerful tool for clinical use in classifying cognitive impairment. This study expands the work of several others, but further studies into the plausibility of speech analysis in clinical use are vital to ensure the validity of speech analysis for clinical classification of cognitive impairment.

Abstract Background The Clock Drawing Test (CDT) and Rey–Osterrieth Complex Figure Test (RCFT) are widely used as a part of neuropsychological test batteries to assess cognitive function. Our objective was to confirm the prediction accuracies of the RCFT-copy and CDT for cognitive impairment (CI) using convolutional neural network algorithms as a screening tool. Methods The CDT and RCFT-copy data were obtained from patients aged 60–80 years who had more than 6 years of education. In total, 747 CDT and 980 RCFT-copy figures were utilized. Convolutional neural network algorithms using TensorFlow (ver. 2.3.0) on the Colab cloud platform ( www.colab.research.google.com ) were used for preprocessing and modeling. We measured the prediction accuracy of each drawing test 10 times using this dataset with the following classes: normal cognition (NC) vs. mildly impaired cognition (MI), NC vs. severely impaired cognition (SI), and NC vs. CI (MI + SI). Results The accuracy of the CDT was better for differentiating MI (CDT, 78.04 ± 2.75; RCFT-copy, not being trained) and SI from NC (CDT, 91.45 ± 0.83; RCFT-copy, 90.27 ± 1.52); however, the RCFT-copy was better at predicting CI (CDT, 77.37 ± 1.77; RCFT, 83.52 ± 1.41). The accuracy for a 3-way classification (NC vs. MI vs. SI) was approximately 71% for both tests; no significant difference was found between them. Conclusions The two drawing tests showed good performance for predicting severe impairment of cognition; however, a drawing test alone is not enough to predict overall CI. There are some limitations to our study: the sample size was small, all the participants did not perform both the CDT and RCFT-copy, and only the copy condition of the RCFT was used. Algorithms involving memory performance and longitudinal changes are worth future exploration. These results may contribute to improved home-based healthcare delivery.

Aims: Reduced pre-operative cognitive functioning in older adults is a risk factor for postoperative complications, but it is unknown if preoperative digitally-acquired clock drawing test (CDT) cognitive screening variables, which allow for more nuanced examination of patient performance, may predict lengthier hospital stay and greater cost of hospital care. This issue is particularly relevant for older adults undergoing transcatheter aortic valve replacement (TAVR), as this surgical procedure is chosen for intermediate-risk older adults needing aortic replacement. This proof of concept research explored if specific latency and graphomotor variables indicative of planning from digitally-acquired command and copy clock drawing would predict post-TAVR duration and cost of hospitalization, over and above age, education, American Society of Anesthesiologists (ASA) physical status classification score, and frailty. Methods: Form January 2018 to December 2019, 162 out of 190 individuals electing TAVR completed digital clock drawing as part of a hospital wide cognitive screening program. Separate hierarchical regressions were computed for the command and copy conditions of the CDT and assessed how a-priori selected clock drawing metrics (total time to completion, ideal digit placement difference, and hour hand distance from center; included within the same block) incrementally predicted outcome, as measured by R2 change significance values. Results: Above and beyond age, education, ASA physical status classification score, and frailty, only digitally-acquired CDT copy performance explained significant variance for length of hospital stay (9.5%) and cost of care (8.9%). Conclusions: Digital variables from clock copy condition provided predictive value over common demographic and comorbidity variables. We hypothesize this is due to the sensitivity of the copy condition to executive dysfunction, as has been shown in previous studies for subtypes of cognitive impairment. Individuals undergoing TAVR procedures are often frail and executively compromised due to their cerebrovascular disease. We encourage additional research on the value of digitally-acquired clock drawing within different surgery types. Type of cognitive impairment and the value of digitally-acquired CDT command and copy parameters in other surgeries remain unknown.

Neuropsychological assessment using the Boston Process Approach (BPA) suggests that an analysis of the strategy or the process by which tasks and neuropsychological tests are completed, and the errors made during test completion convey much information regarding underlying brain and cognition and are as important as overall summary scores. Research over the last several decades employing an analysis of process and errors has been able to dissociate between dementia patients diagnosed with Alzheimer's disease, vascular dementia associated with MRI-determined white matter alterations, and Parkinson's disease; and between mild cognitive impairment subtypes. Nonetheless, BPA methods can be labor intensive to deploy. However, the recent availability of digital platforms for neuropsychological test administration and scoring now enables reliable, rapid, and objective data collection. Further, digital technology can quantify highly nuanced data previously unobtainable to define neurocognitive constructs with high accuracy. In this paper, a brief review of the BPA is provided. Studies that demonstrate how digital technology translates BPA into specific neurocognitive constructs using the Clock Drawing Test, Backward Digit Span Test, and a Digital Pointing Span Test are described. Implications for using data driven artificial intelligence-supported analytic approaches enabling the creation of more sensitive and specific detection/diagnostic algorithms for putative neurodegenerative illness are also discussed. [ABSTRACT FROM AUTHOR]

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Objectives: This study aimed to clarify the diagnostic performance and neural basis of the Clock Drawing Test (CDT) combining free‐ and pre‐drawn methods. Methods: This retrospective study included 165 participants (91 with Alzheimer disease [AD], 52 with amnestic mild cognitive impairment [aMCI], and 22 healthy controls [HC]), who were divided into four groups according to their free‐ and pre‐drawn CDT scores: group 1, could do both; group 2, impaired in both; group 3, impaired in pre‐drawn CDT; and group 4, impaired in free‐drawn CDT. The diagnostic performances of the free‐drawn, pre‐drawn, and combination methods were compared using receiver operating characteristics analysis; in voxel‐based morphometry analysis, the gray matter (GM) volume of groups 2–4 were compared with that of group 1. Results: The area under the curve of the combination method was greater than that of the free‐ or pre‐drawn method alone when comparing AD with HC or aMCI. Group 2 had a significantly smaller GM volume in the bilateral temporal lobes than group 1. Group 3 had a trend toward smaller GM volumes in the right temporal lobe when a liberal threshold was applied. Group 4 had significantly smaller GM volumes in the left temporal lobe than group 1. Conclusions: This study suggests that the combination method may be able to screen for a wider range of brain dysfunction. Combined use of free‐ and pre‐drawn CDT may be useful for screening for AD and its early detection and treatment. Key points: The diagnostic performance and neural basis of the combination of free‐ and pre‐drawn Clock Drawing Test (CDT) were investigated in the Alzheimer disease [AD] continuum.The combination method is more sensitive than each method alone as a screening test for AD.The combination can screen for a wider range of brain dysfunction than each method alone. [ABSTRACT FROM AUTHOR]

Background: Cognitive impairment is common and disabling in Parkinson's disease (PD). Cognitive testing can be time consuming in the clinical setting. One rapid test to detect cognitive impairment in non-PD populations is the Clock Drawing Test (CDT), which calls upon the brain's executive and visuospatial abilities to draw a clock designating a certain time. Objective: Test the hypothesis that PD participants would perform worse on CDT compared to controls and that CDT would correlate with other measures of cognition. Methods: This study evaluated two independent CDT scoring systems and differences in CDT performance between PD (N = 97) and control (N = 54) participants using a two-sample t-test. Pearson's correlations were conducted between the CDT and tests of sleepiness (Epworth Sleepiness Scale) and vigilance (Psychomotor Vigilance Test); executive function (Trails B-A); and global cognition (Montreal Cognitive Assessment). Receiver operating characteristic curves were used to determine cut points on the CDT that identify individuals who need additional cognitive testing. Results: PD participants had worse performance on CDT compared to controls. The CDT was correlated with executive function (Trails B-A) and global cognition (Montreal Cognitive Assessment). The CDT correlated with vigilance (Psychomotor Vigilance Task) only in healthy controls. However, the CDT was not correlated with measures of sleepiness (Epworth Sleepiness Scale) in either group. A cut point of 9 on the Rouleau scale and 18 on the Mendez scale identified PD participants with cognitive impairment. Conclusion: The CDT is a rapid clinical cognitive assessment that is feasible in PD and correlates with other measures of cognition. [ABSTRACT FROM AUTHOR]