RESUMO
Objectives: This study aims to investigate the cost incurred by people travelling to the neurology outpatient clinic of a large metropolitan hospital. As outpatients are a substantial portion of a hospital's demographic, we aimed to understand the patient experience of various commuters. Methods: We conducted an observational study collecting demographic details and travel information for how people attended the neurology clinic of Monash Medical Centre. Statistical analysis was performed using R. 165 participants were randomly selected and interviewed in-person. Data were collected via an anonymous questionnaire. The study was approved by the Monash Health Human Ethics Research Committee. Results: 155 responses were included in the analysis. Patients paid an average of $A16.64 to travel to Monash Medical Centre. Drivers paid on average $A16.70 and those taking public transport paid on average $A9.64, with the maximum cost overall being $A120.00. For patients driving to hospital, parking accounted for 60% of their travel costs. The average to Monash Medical centre was 20.82 km with the maximum being 190.88 km. Distance from hospital was correlated with a higher cost of travel (p<0.001, Spearman's rank correlation coefficient=0.48). There was also an inverse association between distance from hospital and socioeconomic status (p<0.001, Spearman's rank correlation coefficient=-0.26). Conclusion: Travelling to hospital can be a costly endeavour. Driving is the most popular form of transport, but a large portion of the cost involved is hospital parking. Further research should be conducted at other tertiary centres with larger samples.
RESUMO
Background: There is a growing interest in the topography of brain regions associated with disorders of consciousness. This has caused increased research output, yielding many publications investigating the topic with varying methodologies. The objective of this study was to ascertain the topographical regions of the brain most frequently associated with disorders of consciousness. Methods: We performed a cross-sectional text-mining analysis of disorders of consciousness studies. A text mining algorithm built in the Python programming language searched documents for anatomical brain terminology. We reviewed primary PubMed studies between January 1st 2000 to 8th February 2023 for the search query "Disorders of Consciousness." The frequency of brain regions mentioned in these articles was recorded, ranked, then built into a graphical network. Subgroup analysis was performed by evaluating the impact on our results if analyses were based on abstracts, full-texts, or topic-modeled groups (non-negative matrix factorization was used to create subgroups of each collection based on their key topics). Brain terms were ranked by their frequency and concordance was measured between subgroups. Graphical analysis was performed to explore relationships between the anatomical regions mentioned. The PageRank algorithm (used by Google to list search results in order of relevance) was used to determine global importance of the regions. Results: The PubMed search yielded 24,944 abstracts and 3,780 full texts. The topic-modeled subgroups contained 2015 abstracts and 283 full texts. Text Mining across all document groups concordantly ranked the thalamus the highest (Savage score = 11.716), followed by the precuneus (Savage score = 4.983), hippocampus (Savage score = 4.483). Graphical analysis had 5 clusters with the thalamus once again having the highest PageRank score (PageRank = 0.0344). Conclusion: The thalamus, precuneus and cingulate cortex are strongly associated with disorders of consciousness, likely due to the roles they play in maintaining awareness and involvement in the default mode network, respectively. The findings also suggest that other areas of the brain like the cerebellum, cuneus, amygdala and hippocampus also share connections to consciousness should be further investigated.
