Apathy-Related Symptoms Appear Early in Parkinson's Disease

Impaired facial emotion recognition in relation to social behaviours in de novo Parkinson's disease

Facial emotion recognition (FER) is a crucial component of social cognition and is essential in social-interpersonal behaviour regulation. Although FER impairment is well-established in advanced PD, data about FER at the time of diagnosis and its relationship with social behavioural problems in daily life are lacking. The aim was to examine FER at the time of PD diagnosis compared to a matched healthy control (HC) group and to associate FER with indices of social behavioural problems. In total, 142 de novo, treatment-naïve PD patients and 142 HC were included. FER was assessed by the Ekman 60 faces test (EFT). Behavioural problems in PD patients were assessed using the Dysexecutive Questionnaire (DEX-self and DEX-proxy) and the Apathy Evaluation Scale (AES-self). PD patients had significantly lower EFT-total scores (p = .001) compared to HC, with worse recognition of Disgust (p = .001) and Sadness (p = .016). Correlational analyses yielded significant correlations between AES-self and both EFT-total (rs = .28) and Fear (rs = .22). Significant negative correlations were found between DEX-proxy and both EFT-total (rs = -.28) and Anger (rs = -.26). Analyses of DEX-subscales showed that proxy ratings were significantly higher than patient-ratings for the Social Conventions subscale (p = .047). This DEX-proxy subscale had the strongest correlation with EFT-total (rs = -.29). Results show that de novo PD patients already show impaired FER compared to HC. In addition, lower FER is linked to self-reported apathy and proxy-reported social-behavioural problems, especially concerning social conventions. These findings validate the importance of the inclusion of social cognition measures in the neuropsychological assessment even in early PD.

Virtual Reality Intervention for Managing Apathy in People With Cognitive Impairment: Systematic Review

Background

Apathy is common in people with cognitive impairment. It leads to different consequences, such as more severe cognitive deficits, rapid functional decline, and decreased quality of life. Virtual reality (VR) interventions are increasingly being used to manage apathy in individuals with cognitive impairment. However, reports of VR interventions are scattered across studies, which has hindered the development and use of the interventions.

Objective

This study aimed to systematically review existing evidence on the use of VR interventions for managing apathy in people with cognitive impairment with regard to the effectiveness, contents, and implementation of the interventions.

Methods

The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines were followed. The PubMed, Embase, CINAHL, and PsycINFO databases were systematically searched for experimental studies published up to March 13, 2022, that reported the effects of VR interventions on apathy in older adults with cognitive impairment. Hand searching and citation chasing were conducted. The results of the included studies were synthesized by using a narrative synthesis. Their quality was appraised by using the Effective Public Health Practice Project quality assessment tool. However, because the VR interventions varied in duration, content, and implementation across studies, a meta-analysis was not conducted.

Results

A total of 22 studies were identified from the databases, of which 6 (27%) met the inclusion criteria. Of these 6 studies, 2 (33%) were randomized controlled trials, 1 (17%) was a controlled clinical trial, and 3 (50%) were quasi-experimental studies. Individual studies showed significant improvement in apathy and yielded within-group medium to large effect sizes. The level of immersion ranged from low to high. Minor adverse effects were reported. The VR content mostly included natural scenes, followed by city views and game-based activities. A background soundtrack was often used with natural scenes. Most (5/6, 83%) of the studies were conducted in a residential care setting and were implemented by health care professionals or researchers. Safety precautions were taken in most (5/6, 83%) of the studies.

Conclusions

Although preliminary evidence shows that VR interventions may be effective and feasible for alleviating apathy in people with cognitive impairment, the methodological limitations in the included studies make it difficult to reach a firm conclusion on these points. The implementation of the interventions was highlighted and discussed. More rigorous studies are encouraged.

Trial Registration

PROSPERO International Prospective Register of Systematic Reviews CRD42021268289; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021268289

Cardiovascular/Stroke Risk Stratification in Parkinson's Disease Patients Using Atherosclerosis Pathway and Artificial Intelligence Paradigm: A Systematic Review

Parkinson’s disease (PD) is a severe, incurable, and costly condition leading to heart failure. The link between PD and cardiovascular disease (CVD) is not available, leading to controversies and poor prognosis. Artificial Intelligence (AI) has already shown promise for CVD/stroke risk stratification. However, due to a lack of sample size, comorbidity, insufficient validation, clinical examination, and a lack of big data configuration, there have been no well-explained bias-free AI investigations to establish the CVD/Stroke risk stratification in the PD framework. The study has two objectives: (i) to establish a solid link between PD and CVD/stroke; and (ii) to use the AI paradigm to examine a well-defined CVD/stroke risk stratification in the PD framework. The PRISMA search strategy selected 223 studies for CVD/stroke risk, of which 54 and 44 studies were related to the link between PD-CVD, and PD-stroke, respectively, 59 studies for joint PD-CVD-Stroke framework, and 66 studies were only for the early PD diagnosis without CVD/stroke link. Sequential biological links were used for establishing the hypothesis. For AI design, PD risk factors as covariates along with CVD/stroke as the gold standard were used for predicting the CVD/stroke risk. The most fundamental cause of CVD/stroke damage due to PD is cardiac autonomic dysfunction due to neurodegeneration that leads to heart failure and its edema, and this validated our hypothesis. Finally, we present the novel AI solutions for CVD/stroke risk prediction in the PD framework. The study also recommends strategies for removing the bias in AI for CVD/stroke risk prediction using the PD framework.