The Performance of Dual-Task Tests Can Be a Combined Neuro-Psychological and Motor Marker of Mild Cognitive Impairment, Depression and Dementia in Geriatric Patients-A Cross-Sectional Study

Association Between Depressive Symptoms, Cognitive Status, and the Dual-Task Performance Index in Older Adults: A Cross-Sectional Study

The Performance Index (P-Index) is a measure for evaluating mobility-related dual-task performance in older adults. The identification of specific clinicodemographic factors predictive of P-Index scores, however, remains unclear. This cross-sectional study analyzed data from 120 community-dwelling older adults (average age 71.3 ± 11.23 years) to explore clinicodemographic variables that influence P-Index scores during the instrumented timed up and go test. Unadjusted analyses suggested several factors, including age, gender, body mass index, Mini-Mental Status Examination scores, functional reach test performance, history of falls, ethnicity, Geriatric Depression Scale scores, alcohol consumption, and educational levels, as potential predictors of P-Index. However, adjusted multinomial multiple regression analysis revealed Geriatric Depression Scale and Mini-Mental Status Examination scores as the exclusive independent predictors of P-Index classifications, segmented into high, intermediate, or low (percentiles ≤ 25, 26-74, or ≥ 75, respectively). A significant association was observed between the manifestation of depressive symptoms, lower Mini-Mental Status Examination scores, and reduced cognitive-motor performance. The findings implicate depressive symptoms and low cognitive performance as substantial impediments to optimal dual-task mobility within this cohort. Further studies are warranted to examine the efficacy of cognitive stimulation and antidepressant therapy, in augmenting mobility-related dual-task performance among older adults.

Mild cognitive impairment identification based on motor and cognitive dual-task pooled indices

OBJECTIVE

This study investigates the possibility of adopting motor and cognitive dual-task (MCDT) approaches to identify subjects with mild cognitive impairment (MCI) and subjective cognitive impairment (SCI).

METHODS

The upper and lower motor performances of 44 older adults were assessed using the SensHand and SensFoot wearable system during three MCDTs: forefinger tapping (FTAP), toe-tapping heel pin (TTHP), and walking 10 m (GAIT). We developed five pooled indices (PIs) based on these MCDTs, and we included them, along with demographic data (age) and clinical scores (Frontal Assessment Battery (FAB) scores), in five logistic regression models.

RESULTS

Models which consider cognitively normal adult (CNA) vs MCI subjects have accuracies that range from 67% to 78%. The addition of clinical scores stabilised the accuracies, which ranged from 85% to 89%. For models which consider CNA vs SCI vs MCI subjects, there are great benefits to considering all three regressors (age, FAB score, and PIs); the overall accuracies of the three-class models range between 50% and 59% when just PIs and age are considered, whereas the overall accuracy increases by 18% when all three regressors are utilised.

CONCLUSION

Logistic regression models that consider MCDT PIs and age have been effective in distinguishing between CNA and MCI subjects. The inclusion of clinical scores increased the models' accuracy. Particularly high performances in distinguishing among CNA, SCI, and MCI subjects were obtained by the TTHP PI. This study suggests that a broader framework for MCDTs, which should encompass a greater selection of motor tasks, could provide clinicians with new appropriate tools.

Falls at the Geriatric Hospital Ward in the Context of Risk Factors of Falling Detected in a Comprehensive Geriatric Assessment

It is only by knowing the most common causes of falls in the hospital that appropriate and targeted fall prevention measures can be implemented. This study aimed to assess the frequency of falls in a hospital geriatrics ward and the circumstances in which they occurred and evaluate the parameters of the comprehensive geriatric assessment (CGA) correlating with falls. We considered medical, functional, and nutritional factors associated with falls and built multivariable logistic regression analysis models. A total of 416 (median age 82 (IQR 77-86) years, 77.4% women) hospitalizations in the geriatrics ward were analyzed within 8 months. We compared the results of a CGA (including health, psycho-physical abilities, nutritional status, risk of falls, frailty syndrome, etc.) in patients who fell and did not fall. Fourteen falls (3.3% of patients) were registered; the rate was 4.4 falls per 1000 patient days. They most often occurred in the patient's room while changing position. Falls happened more frequently among people who were more disabled, had multimorbidity, were taking more medications (certain classes of drugs in particular), had Parkinson's disease and diabetes, reported falls in the last year, and were diagnosed with orthostatic hypotension. Logistic regression determined the significant independent association between in-hospital falls and a history of falls in the previous 12 months, orthostatic hypotension, Parkinson's disease, and taking statins, benzodiazepines, and insulin. Analysis of the registered falls that occurred in the hospital ward allowed for an analysis of the circumstances in which they occurred and helped to identify people at high risk of falling in a hospital, which can guide appropriate intervention and act as an indicator of good hospital care.