What aspects of rehabilitation provision contribute to self-reported met needs for rehabilitation one year after stroke - amount, place, operator or timing?

BACKGROUND AND OBJECTIVE: To a large extent, people who have suffered a stroke report unmet needs for rehabilitation. The purpose of this study was to explore aspects of rehabilitation provision that potentially contribute to self-reported met needs for rehabilitation 12 months after stroke with consideration also to severity of stroke. METHODS: The participants (n = 173) received care at the stroke units at the Karolinska University Hospital, Sweden. Using a questionnaire, the dependent variable, self-reported met needs for rehabilitation, was collected at 12 months after stroke. The independent variables were four aspects of rehabilitation provision based on data retrieved from registers and structured according to four aspects: amount of rehabilitation, service level (day care rehabilitation, primary care rehabilitation and home-based rehabilitation), operator level (physiotherapist, occupational therapist, speech therapist) and time after stroke onset. Multivariate logistic regression analyses regarding the aspects of rehabilitation were performed for the participants who were divided into three groups based on stroke severity at onset. RESULTS: Participants with moderate/severe stroke who had seen a physiotherapist at least once during each of the 1st, 2nd and 3rd-4th quarters of the first year (OR 8.36, CI 1.40-49.88 P = 0.020) were more likely to report met rehabilitation needs. CONCLUSION: For people with moderate/severe stroke, continuity in rehabilitation (preferably physiotherapy) during the first year after stroke seems to be associated with self-reported met needs for rehabilitation.

Automating condition monitoring of vegetation on railway trackbeds and embankments

Vegetation growing on railway trackbeds and embankments present potential problems. The presence of vegetation threatens the safety of personnel inspecting the railway infrastructure. In addition vegetation growth clogs the ballast and results in inadequate track drainage which in turn could lead to the collapse of the railway embankment. Assessing vegetation within the realm of railway maintenance is mainly carried out manually by making visual inspections along the track. This is done either on-site or by watching videos recorded by maintenance vehicles mainly operated by the national railway administrative body. A need for the automated detection and characterisation of vegetation on railways (a subset of vegetation control/management) has been identified in collaboration with local railway maintenance subcontractors and Trafikverket, the Swedish Transport Administration (STA). The latter is responsible for long-term planning of the transport system for all types of traffic, as well as for the building, operation and maintenance of public roads and railways. The purpose of this research project was to investigate how vegetation can be measured and quantified by human raters and how machine vision can automate the same process. Data were acquired at railway trackbeds and embankments during field measurement experiments. All field data (such as images) in this thesis work was acquired on operational, lightly trafficked railway tracks, mostly trafficked by goods trains. Data were also generated by letting (human) raters conduct visual estimates of plant cover and/or count the number of plants, either on-site or in-house by making visual estimates of the images acquired from the field experiments. Later, the degree of reliability of(human) raters’ visual estimates were investigated and compared against machine vision algorithms. The overall results of the investigations involving human raters showed inconsistency in their estimates, and are therefore unreliable. As a result of the exploration of machine vision, computational methods and algorithms enabling automatic detection and characterisation of vegetation along railways were developed. The results achieved in the current work have shown that the use of image data for detecting vegetation is indeed possible and that such results could form the base for decisions regarding vegetation control. The performance of the machine vision algorithm which quantifies the vegetation cover was able to process 98% of the im-age data. Investigations of classifying plants from images were conducted in in order to recognise the specie. The classification rate accuracy was 95%.Objective measurements such as the ones proposed in thesis offers easy access to the measurements to all the involved parties and makes the subcontracting process easier i.e., both the subcontractors and the national railway administration are given the same reference framework concerning vegetation before signing a contract, which can then be crosschecked post maintenance.A very important issue which comes with an increasing ability to recognise species is the maintenance of biological diversity. Biological diversity along the trackbeds and embankments can be mapped, and maintained, through better and robust monitoring procedures. Continuously monitoring the state of vegetation along railways is highly recommended in order to identify a need for maintenance actions, and in addition to keep track of biodiversity. The computational methods or algorithms developed form the foundation of an automatic inspection system capable of objectively supporting manual inspections, or replacing manual inspections.

Monitoring vegetation on railway embankments : supporting maintenance decisions

The national railway administrations in Scandinavia, Germany, and Austria mainly resort to manual inspections to control vegetation growth along railway embankments. Manually inspecting railways is slow and time consuming. A more worrying aspect concerns the fact that human observers are often unable to estimate the true cover of vegetation on railway embankments. Further human observers often tend to disagree with each other when more than one observer is engaged for inspection. Lack of proper techniques to identify the true cover of vegetation even result in the excess usage of herbicides; seriously harming the environment and threating the ecology. Hence work in this study has investigated aspects relevant to human variationand agreement to be able to report better inspection routines. This was studied by mainly carrying out two separate yet relevant investigations.First, thirteen observers were separately asked to estimate the vegetation cover in nine imagesacquired (in nadir view) over the railway tracks. All such estimates were compared relatively and an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05). Bearing in difference between the observers, a second follow-up field-study on the railway tracks was initiated and properly investigated. Two railway segments (strata) representingdifferent levels of vegetationwere carefully selected. Five sample plots (each covering an area of one-by-one meter) were randomizedfrom each stratumalong the rails from the aforementioned segments and ten images were acquired in nadir view. Further three observers (with knowledge in the railway maintenance domain) were separately asked to estimate the plant cover by visually examining theplots. Again an analysis of variance resulted in a significant difference on the observers’ cover estimates (p<0.05) confirming the result from the first investigation.The differences in observations are compared against a computer vision algorithm which detects the "true" cover of vegetation in a given image. The true cover is defined as the amount of greenish pixels in each image as detected by the computer vision algorithm. Results achieved through comparison strongly indicate that inconsistency is prevalent among the estimates reported by the observers. Hence, an automated approach reporting the use of computer vision is suggested, thus transferring the manual inspections into objective monitored inspections

Unfulfilled rehabilitation needs and dissatisfaction with care 12 months after a stroke : an explorative observational study

BACKGROUND: People who have suffered a stroke commonly report unfulfilled need for rehabilitation. Using a model of patient satisfaction, we examined characteristics in individuals that at 3 months after stroke predicted, or at 12 months were associated with unmet need for rehabilitation or dissatisfaction with health care services at 12 months after stroke. METHODS: The participants (n = 175) received care at the stroke units at the Karolinska University Hospital, Sweden. The dependent variables "unfulfilled needs for rehabilitation" and "dissatisfaction with care" were collected using a questionnaire. Stroke severity, domains of the Stroke Impact Scale (SIS), the Sense of Coherence scale (SOC) and socio demographic factors were used as independent variables in four logistic regression analyses. RESULTS: Unfulfilled needs for rehabilitation at 12 months were predicted by strength (SIS) (odds ratio (OR) 7.05) at three months, and associated with hand function (SIS) (OR 4.38) and poor self-rated recovery (SIS) (OR 2.46) at 12 months. Dissatisfaction with care was predicted by SOC (OR 4.18) and participation (SIS) (OR 3.78), and associated with SOC (OR 3.63) and strength (SIS) (OR 3.08). CONCLUSIONS: Thirty-three percent of the participants reported unmet needs for rehabilitation and fourteen percent were dissatisfied with the care received. In order to attend to rehabilitation needs when they arise, rehabilitation services may need to be more flexible in terms of when rehabilitation is provided. Long term services with scheduled re-assessments and with more emphasis on understanding the experiences of both the patients and their social networks might better be able to provide services that attend to patients' needs and aid peoples' reorientation; this would apply particularly to those with poor coping capacity.

Usual clinical practice for early supported discharge after stroke with continued rehabilitation at home : an observational comparative study

Introduction: Based on randomised controlled trials, evidence exists that early supported discharge (ESD) from the hospital with continued rehabilitation at home has beneficial effects after stroke; however, the effects of ESD service in regular clinical practice have not been investigated. The purpose of the current study was to compare ESD service with conventional rehabilitation in terms of patient outcomes, caregiver burden at 3 and 12 months and the use and costs of healthcare during the first year after stroke. Material and methods: This study was a subgroup analysis of a longitudinal observational study of patients who received care in the stroke unit at Karolinska University Hospital in Sweden. Patients who met the inclusion criteria for ESD in previous experimental studies were included. The patients were referred to available rehabilitation services at discharge, and comparisons between those who received ESD service (the ESD group, n = 40) and those who received conventional rehabilitation (the NoESD group, n = 110) were performed with regard to independence in activities of daily living (ADL), the frequency of social activities, life satisfaction, and caregiver burden and the use and costs of healthcare during the first year after stroke. Results: At 3 and 12 months, no differences were observed with regard to patient outcomes; however, ESD was associated with a lower caregiver burden (p = 0.01) at 12 months. The initial length of stay (LOS) at the hospital was 8 days for the ESD group and 15 days for the NoESD group (p = 0.02). The median number of outpatient rehabilitation contacts was 20.5 for the ESD group (81% constituting ESD service) and 3 for the NoESD group (p<0.001). There was no difference between the groups with regard to overall healthcare costs. Conclusions: ESD service in usual clinical practice renders similar health benefits as conventional rehabilitation but a different pattern of resource use and with released capacity in acute stroke care.