Automated PDF highlighting to support faster curation of literature for Parkinson's and Alzheimer's disease

Neurodegenerative disorders such as Parkinson’s and Alzheimer’s disease are devastating and costly illnesses, a source of major global burden. In order to provide successful interventions for patients and reduce costs, both causes and pathological processes need to be understood. The ApiNATOMY project aims to contribute to our understanding of neurodegenerative disorders by manually curating and abstracting data from the vast body of literature amassed on these illnesses. As curation is labour-intensive, we aimed to speed up the process by automatically highlighting those parts of the PDF document of primary importance to the curator. Using techniques similar to those of summarisation, we developed an algorithm that relies on linguistic, semantic and spatial features. Employing this algorithm on a test set manually corrected for tool imprecision, we achieved a macro F1-measure of 0.51, which is an increase of 132% compared to the best bag-of-words baseline model. A user based evaluation was also conducted to assess the usefulness of the methodology on 40 unseen publications, which reveals that in 85% of cases all highlighted sentences are relevant to the curation task and in about 65% of the cases, the highlights are sufficient to support the knowledge curation task without needing to consult the full text. In conclusion, we believe that these are promising results for a step in automating the recognition of curation-relevant sentences. Refining our approach to pre-digest papers will lead to faster processing and cost reduction in the curation process

SF-36 includes less Parkinson Disease (PD)-targeted content but is more responsive to change than two PD-targeted health-related quality of life measures

To compare validity including responsiveness, and internal consistency reliability and scaling assumptions of a generic (SF-36) and Parkinson Disease (PD)-targeted (PDQ-39; PDQUALIF) health-related quality of life (HRQOL) measures. Ninety-six PD patients were administered for all HRQOL measures by telephonic interview at baseline and 18 months. Relative efficiency and responsiveness were compared relative to four external criteria (self-ratings of PD’s daily effects, global Quality of Life, PD symptom severity, and a depression screener). We examined whether PD-targeted measures explained unique variance beyond the SF-36 by regressing criterion variables on HRQOL scales/items. Adequacy of PD-targeted measures’ original scaling was explored by item-scale correlations. Relative efficiency estimates were similar for generic and PD-targeted measures across all criteria. Responsiveness analyses showed that the SF-36 yielded large (>0.8) effect sizes (ES) for three of eight scales for each of two criterion variables, compared to only one large ES for any scale in either PD-targeted measure. Adjusted R 2 increased from 14 to 27% in regression models that included PD-targeted items compared to models with only SF-36 scales. Item-scale correlations showed significant cross-loading of items across scales of the PD-targeted measures. SF-36 responsiveness was better than that of two PD-targeted measures, yet those measures had content that significantly explains PD patients’ HRQOL

Physical inactivity in Parkinson’s disease

Patients with Parkinson’s disease (PD) are likely to become physically inactive, because of their motor, mental, and emotional symptoms. However, specific studies on physical activity in PD are scarce, and results are conflicting. Here, we quantified daily physical activities in a large cohort of PD patients and another large cohort of matched controls. Moreover, we investigated the influence of disease-related factors on daily physical activities in PD patients. Daily physical activity data of PD patients (n = 699) were collected in the ParkinsonNet trial and of controls (n = 1,959) in the Longitudinal Aging Study Amsterdam (LASA); data were determined using the LAPAQ, a validated physical activity questionnaire. In addition, variables that may affect daily physical activities in PD were recorded, including motor symptoms, depression, disability in daily life, and comorbidity. Patients were physically less active; a reduction of 29% compared to controls (95% CI, 10–44%). Multivariate regression analyses demonstrated that greater disease severity, gait impairment, and greater disability in daily living were associated with less daily physical activity in PD (R2 = 24%). In this large study, we show that PD patients are about one-third less active compared to controls. While disease severity, gait, and disability in daily living predicted part of the inactivity, a portion of the variance remained unexplained, suggesting that additional determinants may also affect daily physical activities in PD. Because physical inactivity has many adverse consequences, work is needed to develop safe and enjoyable exercise programs for patients with PD