Association between gait speed deterioration and EEG abnormalities.

Physical and cognitive decline at an older age is preceded by changes that accumulate over time until they become clinically evident difficulties. These changes, frequently overlooked by patients and health professionals, may respond better than fully established conditions to strategies designed to prevent disabilities and dependence in later life. The objective of this study was twofold; to provide further support for the need to screen for early functional changes in older adults and to look for an early association between decline in mobility and cognition. A cross-sectional cohort study was conducted on 95 active functionally independent community-dwelling older adults in Havana, Cuba. We measured their gait speed at the usual pace and the cognitive status using the MMSE. A value of 0.8 m/s was used as the cut-off point to decide whether they presented a decline in gait speed. A quantitative analysis of their EEG at rest was also performed to look for an associated subclinical decline in brain function. Results show that 70% of the sample had a gait speed deterioration (i.e., lower than 0.8 m/s), of which 80% also had an abnormal EEG frequency composition for their age. While there was no statistically significant difference in the MMSE score between participants with a gait speed above and below the selected cut-off, individuals with MMSE scores below 25 also had a gait speed<0.8 m/s and an abnormal EEG frequency composition. Our results provide further evidence of early decline in older adults-even if still independent and active-and point to the need for clinical pathways that incorporate screening and early intervention targeted at early deterioration to prolong the years of functional life in older age.

Relationship between gait parameters and cognitive indexes in adult aging.

PURPOSE: This study aimed to identify the most effective summary cognitive index predicted from spatio-temporal gait features (STGF) extracted from gait patterns. METHODS: The study involved 125 participants, including 40 young (mean age: 27.65 years, 50% women), and 85 older adults (mean age: 73.25 years, 62.35% women). The group of older adults included both healthy adults and those with Mild Cognitive Impairment (MCI). Participant´s performance in various cognitive domains was evaluated using 12 cognitive measures from five neuropsychological tests. Four summary cognitive indexes were calculated for each case: 1) the z-score of Mini-Mental State Examination (MMSE) from a population norm (MMSE z-score); 2) the sum of the absolute z-scores of the patients' neuropsychological measures from a population norm (ZSum); 3) the first principal component scores obtained from the individual cognitive variables z-scores (PCCog); and 4) the Mahalanobis distance between the vector that represents the subject's cognitive state (defined by the 12 cognitive variables) and the vector corresponding to a population norm (MDCog). The gait patterns were recorded using a body-fixed Inertial Measurement Unit while participants executed four walking tasks (normal, fast, easy- and hard-dual tasks). Sixteen STGF for each walking task, and the dual-task costs for the dual tasks (when a subject performs an attention-demanding task and walks at the same time) were computed. After applied Principal Component Analysis to gait measures (96 features), a robust regression was used to predict each cognitive index and individual cognitive variable. The adjusted proportion of variance (adjusted-R2) coefficients were reported, and confidence intervals were estimated using the bootstrap procedure. RESULTS: The mean values of adjusted-R2 for the summary cognitive indexes were as follows: 0.0248 for MMSE z-score, 0.0080 for ZSum, 0.0033 for PCCog, and 0.4445 for MDCog. The mean adjusted-R2 values for the z-scores of individual cognitive variables ranged between 0.0009 and 0.0693. Multiple linear regression was only statistically significant for MDCog, with the highest estimated adjusted-R2 value. CONCLUSIONS: The association between individual cognitive variables and most of the summary cognitive indexes with gait parameters was weak. However, the MDCog index showed a stronger and significant association with the STGF, exhibiting the highest value of the proportion of the variance that can be explained by the predictor variables. These findings suggest that the MDCog index may be a useful tool in studying the relationship between gait patterns and cognition.

Harmonized-Multinational qEEG norms (HarMNqEEG).

This paper extends frequency domain quantitative electroencephalography (qEEG) methods pursuing higher sensitivity to detect Brain Developmental Disorders. Prior qEEG work lacked integration of cross-spectral information omitting important functional connectivity descriptors. Lack of geographical diversity precluded accounting for site-specific variance, increasing qEEG nuisance variance. We ameliorate these weaknesses. (i) Create lifespan Riemannian multinational qEEG norms for cross-spectral tensors. These norms result from the HarMNqEEG project fostered by the Global Brain Consortium. We calculate the norms with data from 9 countries, 12 devices, and 14 studies, including 1564 subjects. Instead of raw data, only anonymized metadata and EEG cross-spectral tensors were shared. After visual and automatic quality control, developmental equations for the mean and standard deviation of qEEG traditional and Riemannian DPs were calculated using additive mixed-effects models. We demonstrate qEEG "batch effects" and provide methods to calculate harmonized z-scores. (ii) We also show that harmonized Riemannian norms produce z-scores with increased diagnostic accuracy predicting brain dysfunction produced by malnutrition in the first year of life and detecting COVID induced brain dysfunction. (iii) We offer open code and data to calculate different individual z-scores from the HarMNqEEG dataset. These results contribute to developing bias-free, low-cost neuroimaging technologies applicable in various health settings.

Las pruebas de desempeño físico en el pronóstico de desenlaces adversos en los ancianos / Physical performance tests in the prognosis of adverse outcomes in the elderly

Las pruebas de desempeño físico son mediciones objetivas del estado funcional de los ancianos, y se ha demostrado su eficacia para identificar cuáles de ellos son más susceptibles a la discapacidad. En este artículo se exponen las ventajas de implementar dichas pruebas en la práctica clínica geriátrica, las que son factibles en cualquier escenario, aún en condiciones de pocos recursos, debido a su sencillez, reproducibilidad y bajo costo; por lo que pueden ser más utilizadas para estratificar el riesgo de discapacidad en ancianos de cualquier comunidad

Physical performance tests are objective measurements of the functional state of the elderly, and their effectiveness has been demonstrated to identify who of them are more susceptible to disability. The advantages of implementing these tests in the geriatric clinical practice are exposed in this work, which are feasible in any scenario, even with few resources conditions, due to their simplicity, reproducibility and low cost; so that they can be more used to stratify the disability risk in aged patients of any community

Comorbilidad y desempeño en personas adultos mayores de La Habana, Cuba / Performance status and comorbidity in older personas, La habana-Cuba

Numerosos estudios han demostrado la utilidad de las mediciones Desempeño Físico (DF) para el diagnóstico de fragilidad y la predicción adecuada de la discapacidad en adultos mayores (AM). Objetivo: Describir el impacto que tienen las Enfermedades Cr¢nicas y la comorbilidad sobre variables del DF. Material y métodos: Investigación observacional descriptiva, de corte transversal, realizada en 329 Adultos Mayores del Municipio Plaza de la Revolución. Se realizaron entrevistas para conocer sus comorbilidades y se midió la Velocidad de la Marcha (VM), amplitud del paso promedio (APP) y Tiempo de Equilibrio (TE). Resultados: La poblaci¢n total tuvo en promedio una VM de 0.93m/s, una APP de 49cm, y un TE de 14.2 segundos. La VM en hipertensos fue 0.89 m/s (p: 0.012), la APP de 48 cm (p: 0.20), y un TE de 16.1 (p: 0.022). En diabéticos la VM fue de 0.87 m/s, la APP de cm y TE de 16.1 (p: 0.06). Se encontró que la VM sin comorbilidades fue de 0.97 m/s, con 1 comorbilidad 0.92 m/s y con 2 o m s comorbilidades fue de 50.8 cm, con 1 comorbilidad 49.6 cm y con 2 y m s comorbilidades 49.3 cm (p: 0.08); el TE sin comorbilidades fue de 13.8 segundos, con 1 comorbilidad 16.4 segundos y con 2 y m s comorbilidades 16.6 segundos (p: 0.003). Conclusiones: la hipertensi¢n y la diabetes est n asociadas a alteraciones en las mediciones DF en los AM así como el número de comorbilidades.

Numerous studies have demonstrated the usefulness of physical performance measurements (PPM) for the diagnosis of frailty and accurate prediction of disability in older adults. Objective: To describe the impact of chronic disease and comorbidity on variables of PPM. Material and Methods: descriptive observational, cross-sectional, conducted on 329 elderly from Municipio Plaza de la Revoluci¢n. They were interviewed to find out their comorbidities and measured gait speed (GS), average step amplitude (ASA) and balance time (BT). Results: total population had an average GS of 0.93 m/s, an ASA of 49 cm, and a BT of 14.2 seconds. The GS in hypertensives was 0.89 m/s (p: 0.012), 48 cm of ASA (p: 0.20), and a BT of 16.1 (p: 0.022). In diabetics the GS was 0.87 m/s, an ASA of 46 cm and BT of 16.1 (p: 0.06). We found that the GS in elderly without comorbidities was 0.97 m/s, with 1 comorbidity 0.92 m/s, and with 2 or more comorbidities 0.87 m/s (p: 0.05), the ASA without comorbidities was 50.8 cm, 49.6 cm witch 1 comorbidity and with 2 or more comorbidities 49.3 cm (p: 0.08), the BT without comorbidities was 13.8 seconds, 16.4 seconds in elderly with 1 comorbidity and with 2 or more comorbidities 16.6 seconds (p: 0.003). Conclusions: Hypertension and diabetes are associated with alterations in PPM as the number of comorbidities.