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Povzetek: Background Loneliness is a state in which an individual feels socially isolated due to deficiencies in the quantity or quality of social relationships and interaction. To date very little is known about loneliness in Parkinson's disease (PD) and focal/segmental craniocervical dystonia (FSCD). Objectives To explore whether level of loneliness is disease-specific by comparing PD, FCSD and healthy controls (HCs), and to define predictors of loneliness in both PD and FSCD. Methods Eighty-two people with PD, 63 people with FSCD and 50 HC were surveyed. The UCLA Loneliness Scale was used to assess loneliness. Various non-motor symptoms, psychosocial variables and measures of subjective well-being were assessed and used as potential predictors of loneliness. Results There was no significant difference in reported levels of loneliness between people with PD and matched HCs, and between people with PD and people with FSCD, but people with FSCD reported higher levels of loneliness than HCs (p = 0.018). Perceived stigma predicted loneliness in both disease groups (p < 0.001). Additionally, non-motor symptoms (p = 0.006), lack of optimism (p = 0.015) and practical social support (p = 0.006) predicted loneliness in people with PD. Patients with PD and FSCD with higher perceived stigma levels felt lonelier (p < 0.001), as did female patients with PD (p = 0.004), younger patients with FSCD (p = 0.007) and older patients with PD (p = 0.023). Conclusions We identified important predictors of loneliness in PD and FSCD. The identified age- and gender-specific differences in loneliness in people with PD and FSCD contribute to our better understanding of this complex and not yet fully understood concept.
Ključne besede: loneliness, Parkinson's disease, focal/segmental craniocervical dystonia, optimism and stigma
Objavljeno v DiRROS: 04.12.2025; Ogledov: 18; Prenosov: 9
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Povzetek: Introduction. In the advanced stages of Parkinson’s disease (PD), when standard drug adjustments fail to sufficiently improve patients’ quality of life, device-aided therapies (DATs) such as deep brain stimulation (DBS), continuous subcutaneous apomorphine infusion (CSAI), levodopa-carbidopa intestinal gel infusion (LCIG), levodopa-carbidopa-entacapone intestinal gel infusion, or continuous subcutaneous foslevodoa-foscarbidopa infusion are beneficial in the long run. However, sometimes patients need to switch or combine DATs due to either adverse events or loss of efficacy. Aim of study. The aim of this article was to summarise the existing data on the long-term efficacy and adverse events of DATs, and to review the data on the rationale and efficacy for switching or combining DATs in advanced PD. State of the art. A total of 50 studies on the long-term efficacy of DBS (N = 28), LCIG (N = 12), CSAI (N = 10) and 13 studies on switching and combining DATs were included in this review. Although the DATs show a favourable long-term effect on the main motor and non-motor symptoms of PD they all feature specific adverse events that need to be considered when deciding which DAT to offer to a particular patient. Occasionally, switching or combining DATs is recommended, e.g. if the first DAT shows inadequate symptom control, or due to adverse events. The choice of the second DAT depends above all on the main problems of the first DAT being correctly recognised. Clinical implications. DATs are a safe and long-term effective option for the treatment of advanced PD. Switching and/or combining DATs is recommended for patients in whom the first treatment option is not optimal. Future directions. Future studies are warranted to address the unresolved issues related to long-term efficacy, side effect profile and switching and combination of DATs in multicentric studies and using advanced analytical approaches such as machine learning.
Ključne besede: advanced Parkinson’s Disease, device-aided therapies, long-term effect of device-aided therapies
Objavljeno v DiRROS: 02.12.2025; Ogledov: 53; Prenosov: 24
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Povzetek: Background: Freezing of gait (FoG) is one of the most debilitating motor symptoms in Parkinson’s disease (PD). It often leads to falls and reduces quality of life due to the risk of injury and loss of independence. Several types of wearable sensors have emerged as promising tools for the detection of FoG in clinical and real-life settings. Objective: The main objective of this systematic review was to critically evaluate the current usability of wearable sensor technologies for FoG detection in PD patients. The focus of the study is on sensor types, sensor combinations, placement on the body and the applications of such detection systems in a naturalistic environment. Methods: PubMed, IEEE Explore and ACM digital library were searched using a search string of Boolean operators that yielded 328 results, which were screened by title and abstract. After the screening process, 43 articles were included in the review. In addition to the year of publication, authorship and demographic data, sensor types and combinations, sensor locations, ON/OFF medication states of patients, gait tasks, performance metrics and algorithms used to process the data were extracted and analyzed. Results: The number of patients in the reviewed studies ranged from a single PD patient to 205 PD patients, and just over 65% of studies have solely focused on FoG + PD patients. The accelerometer was identified as the most frequently utilized wearable sensor, appearing in more than 90% of studies, often in combination with gyroscopes (25.5%) or gyroscopes and magnetometers (20.9%). The best overall sensor configuration reported was the accelerometer and gyroscope setup, achieving nearly 100% sensitivity and specificity for FoG detection. The most common sensor placement sites on the body were the waist, ankles, shanks and feet, but the current literature lacks the overall standardization of optimum sensor locations. Real-life context for FoG detection was the focus of only nine studies that reported promising results but much less consistent performance due to increased signal noise and unexpected patient activity. Conclusions: Current accelerometer-based FoG detection systems along with adaptive machine learning algorithms can reliably and consistently detect FoG in PD patients in controlled laboratory environments. The transition of detection systems towards a natural environment, however, remains a challenge to be explored. The development of standardized sensor placement guidelines along with robust and adaptive FoG detection systems that can maintain accuracy in a real-life environment would significantly improve the usefulness of these systems.
Ključne besede: Parkinson’s disease, wearable sensors, freezing of gait, symptoms
Objavljeno v DiRROS: 24.11.2025; Ogledov: 100; Prenosov: 54
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