Parkinson’s disease (PD) has the second highest prevalence among neurodege - nerative diseases. In Colombia, PD population dynamics are currently unknown. Health records offer a unique resource to study frequency and multi-morbidity of chronic diseases. The aim of this research is to estimate prevalence and staging using administrative data (AD) provided by Health Maintenance Organizations (HMOs). A cross-sectional study was conducted using 2015 AD from two Colombian HMOs (4.312.928 beneficiaries, 9.01% of the affiliated Colombian population). PD prevalence and severity was estimated by age and sex. Prevalence was adjusted to WHO demographics. Age-adjusted PD prevalence was 205.89 per 100.000 inhabitants. Prevalence increment of 62.13% was found between those aged ≥40 years and those aged ≥50 years. Similarly, each extra decade (50-80+) represented an increment of 83.65%, 80.95%, and 35.10%. Between 40 and 89 years, males exhibited a significantly higher PD prevalence compared to females. Advanced PD was more frequent as age increased from 3.77% in the group between 40 to 49 years to 25.86% in those older than 89 years. More common related comorbidities were arterial hypertension, diabetes, and psychiatric disorders; the first two increased their frequency with age, and the last one maintained its prevalence across all age groups. AD sets are useful to estimate the prevalence and staging of PD. Prevalence of PD in Colombia is higher in men and increases with age, as well as disease severity.
In patients with Parkinson’s disease (PD), arm swing changes are common, even in the early stages, and these changes are usually evaluated subjectively by an expert. In this article, hypothesize that arm swing changes can be detected using a low-cost, cloud-based, wearable, sensor system that incorporates triaxial accelerometers. The aim of this work is to develop a low-cost, assistive diagnostic tool for use in quantifying the arm swing kinematics of patients with PD. Ten patients with PD and 11 age-matched, healthy subjects are included in the study. Four feature extraction techniques were applied: (i) Asymmetry estimation based on root mean square (RMS) differences between arm movements; (ii) posterior–anterior phase and cycle regularity through autocorrelation; (iii) tremor energy, established using Fourier transform analysis; and (iv) signal complexity through the fractal dimension by wavelet analysis. The PD group showed significant (p < 0.05) reductions in arm swing RMS values, higher arm swing asymmetry, higher anterior–posterior phase regularities, greater “high energy frequency” signals, and higher complexity in their XZ plane signals. Therefore, the novel, portable system provides a reliable means to support clinical practice in PD assessment.
Background. Gait alterations are hallmarks for the diagnosis and follow-up of patients with Parkinson’s disease (PD). In normal conditions, age could affect gait dynamics. Although it is known that objective assessment of gait is a valuable tool for diagnosis and follow-up of patients with PD, only few studies evaluate the effect of aging on the gait pattern of patients with PD. Objective. The purpose of this study was to assess differences in gait dynamics between PD patients and healthy subjects and to investigate the effects of aging on these differences using a low-cost RGB-D depth-sensing camera. Methods. 30 PD patients and 30 age-matched controls were recruited. Descriptive analysis was used for clinical variables, and Spearman’s rank correlation was used to correlate age and gait variables. The sample was distributed in age groups; then, Mann–Whitney U test was used for comparison of gait variables between groups. Results. PD patients exhibited prolonged swing () and stance times () and lower speed values () compared to controls. This was consistent in all age groups, except for the one between 76 and 88 years old, in which the controls were slower and had longer swing and stance times. These results were statically significant for the group from 60 to 66 years. Conclusion. Gait speed, swing, and stance times are useful for differentiating PD patients from controls. Quantitative gait parameters measured by an RGB-D camera can complement clinical assessment of PD patients. The analysis of these spatiotemporal variables should consider the age of the subject.
Introduction. Parkinson’s disease (PD) is one of the most prevalent age-related neurodegenerative disorders. The progression of PD produces an important disease burden in patients due to functional impairment, which also has repercussions on caregivers. In addition, it has become a challenge for health systems, especially in developing countries, which have limited resources. Multidisciplinary teams with a community approach have proved effective in high-income countries; however, there is no reported literature in low- and middle-income countries about this kind of initiative. Objective. This paper aims to document the experience of patients, caregivers, and experts in a community approach as an innovative model in a middle-income country. Methods. A quantitative descriptive research was conducted. The selection criteria were having a PD diagnosis, attending with a caregiver to Saturdays in Motion (SIM), or being a clinical expert invited to SIM. PD patients and their caregivers answered three surveys on their points of view with respect to SIM: SIM and their quality of life (QoL) and PDQ-39 and Zarit, whereas clinical experts completed two questions related to the SIM program. Descriptive statistics were used to summarize the results of the surveys and clinical tests. Results. Forty-eight, twenty-four, and twenty-one subjects answered surveys one, two, and three, respectively. In total, four clinical experts were interviewed. 87.9% of the patients consider that SIM activities improved their QoL. The most affected areas in PDQ-39 were those related to the social area. Around 66.6% of the caregivers reported a mild burden on Zarit and think that SIM enhances the PD patient’s QoL. Clinical experts highlighted the sense of community and empathy. Conclusion. Our preliminary experience shows a multidisciplinary model with a community approach which redefines the traditional relationship between patients, caregivers, and clinical experts. This aim of this initiative is that education and empowerment patients and caregivers reach a better perception of QoL.
In this chapter, we describe the aging process and, more specifically, the pathological aging, associated with neurodegenerative diseases and its relation with gait. Then, we explain the importance of using quantitative gait analysis techniques using wearables and other technologies to diagnose different conditions that can be complex to discriminate using only the physician naked-eye diagnosis. We analyze different approaches used for gait analysis using wearables and affordable devices like inertial units (IMU), accelerometers, and depth cameras like Microsoft Kinect or Intel’s RealSense, which have been available at least in an academic context but will be available for daily use in the near future.