Inter-rater reliability of the Foot Posture Index (FPI-6) in the assessment of the paediatric foot

Abstract Background Reliability is an integral component of clinical assessment and necessary for establishing baseline data, monitoring treatment outcomes and providing robust research findings. In the podiatric literature traditional measures of foot assessment have been shown to be largely unreliable. The Foot Posture Index (FPI-6) is a clinical tool used in the assessment of foot and to date, there is limited research published which evaluates the reliability of this tool in children and adolescents. Method Thirty participants aged 5 - 16 years were recruited for the research. Two raters independently recorded the FPI-6 score for each participant. Results Almost perfect agreement between the two raters was identified following weighted kappa analysis (Kw = 0.86). Conclusion The FPI-6 is a quick, simple and reliable clinical tool which has demonstrated excellent inter-rater reliability when used in the assessment of the paediatric foot.</p

Response to letter regarding article, "patient-reported measures provide unique insights into motor function after stroke".

Background and PurposePatient-reported outcome measures have been found useful in many disciplines but have received limited evaluation after stroke. The current study investigated the relationship that patient-reported measures have with standard impairment and disability scales after stroke.MethodsPatients with motor deficits after stroke were scored on standard assessments including NIH Stroke Scale (NIHSS), modified Rankin Scale (mRS), and Fugl-Meyer motor scale (FM), and on two patient-reported measures, the hand function domain of the Stroke Impact Scale (SIS), which documents difficulty of hand motor usage, and the amount of use portion of the Motor Activity Log (MAL), which records amount of arm motor usage.ResultsThe 43 participants had mild disability (median mRS=2), moderate motor deficits (FM=46 ± 22), and mild cognitive/language deficits. The two patient-reported outcome measures, SIS and MAL, were sensitive to the presence of arm motor deficits. Of 21 patients classified as having minimal or no impairment or disability by the NIHSS or mRS (score of 0-1), 15 (71%) reported difficulty with hand movements by the SIS score or reduced arm use by the MAL score. Furthermore, of 14 patients with a normal exam, 10 (71%) reported difficulty with hand movements or reduction in arm use.ConclusionsPatient-reported measures were a unique source of insight into clinical status in the current population. Motor deficits were revealed in a majority of patients classified by standard scales as having minimal or no disability, and in a majority of patients classified as having no deficits

Biomarkers of Rehabilitation Therapy Vary According To Stroke Severity

Biomarkers that capture treatment effects could improve the precision of clinical decision making for restorative therapies. We examined the performance of candidate structural, functional,and angiogenesis-related MRI biomarkers before and after a 3-week course of standardized robotic therapy in 18 patients with chronic stroke and hypothesized that results vary significantly according to stroke severity. Patients were 4.1 ± 1 months poststroke, with baseline arm Fugl-Meyer scores of 20–60. When all patients were examined together, no imaging measure changed over time in a manner that correlated with treatment-induced motor gains. However, when also considering the interaction with baseline motor status, treatment-induced motor gains were significantly related to change in three functional connectivity measures: ipsilesional motor cortex connectivity with (1) contralesional motor cortex (p = 0 003), (2) contralesional dorsal premotor cortex (p = 0 005), and (3) ipsilesional dorsal premotor cortex (p = 0 004). In more impaired patients, larger treatment gains were associated with greater increases in functional connectivity, whereas in less impaired patients larger treatment gains were associated with greater decreases in functional connectivity. Functional connectivity measures performed best as biomarkers of treatment effects after stroke. The relationship between changes in functional connectivity and treatment gains varied according to baseline stroke severity. Biomarkers of restorative therapy effects are not one-size-fits-all after stroke

Role of Corpus Callosum Integrity in Arm Function Differs Based on Motor Severity After Stroke

While the corpus callosum (CC) is important to normal sensorimotor function, its role in motor function after stroke is less well understood. This study examined the relationship between structural integrity of the motor and sensory sections of the CC, as reflected by fractional anisotropy (FA), and motor function in individuals with a range of motor impairment level due to stroke. Fifty-five individuals with chronic stroke (Fugl-Meyer motor score range 14 to 61) and 18 healthy controls underwent diffusion tensor imaging and a set of motor behavior tests. Mean FA from the motor and sensory regions of the CC and from corticospinal tract (CST) were extracted and relationships with behavioral measures evaluated. Across all participants, FA in both CC regions was significantly decreased after stroke (p \u3c 0.001) and showed a significant, positive correlation with level of motor function. However, these relationships varied based on degree of motor impairment: in individuals with relatively less motor impairment (Fugl-Meyer motor score \u3e 39), motor status correlated with FA in the CC but not the CST, while in individuals with relatively greater motor impairment (Fugl-Meyer motor score ≤ 39), motor status correlated with FA in the CST but not the CC. The role interhemispheric motor connections play in motor function after stroke may differ based on level of motor impairment. These findings emphasize the heterogeneity of stroke, and suggest that biomarkers and treatment approaches targeting separate subgroups may be warranted

Test–retest Reliability and Minimal Detectable Change of Corticospinal Tract Integrity in Chronic Stroke

Diffusion tensor imaging (DTI) can be used to index white matter integrity of the corticospinal tract (CST) after stroke; however, the psychometric properties of DTI‐based measures of white matter integrity are unknown. The purpose of this study was to examine test–retest reliability as determined by intraclass correlation coefficients (ICC) and calculate minimal detectable change (MDC) of DTI‐based measures of CST integrity using three different approaches: a Cerebral Peduncle approach, a Probabilistic Tract approach, and a Tract Template approach. Eighteen participants with chronic stroke underwent DTI on the same magnetic resonance imaging scanner 4 days apart. For the Cerebral Peduncle approach, a researcher hand drew masks at the cerebral peduncle. For the Probabilistic Tract approach, tractography was seeded in motor areas of the cortex to the cerebral peduncle. For the Tract Template approach, a standard CST template was transformed into native space. For all approaches, the researcher performing analyses was blind to participant number and day of data collection. All three approaches had good to excellent test–retest reliability for fractional anisotropy (FA; ICCs \u3e0.786). Mean diffusivity, axial diffusivity, and radial diffusivity were less reliable than FA. The ICC values were highest and MDC values were the smallest for the most automated approach (Tract Template), followed by the combined manual/automated approach (Probabilistic Tract) then the manual approach (Cerebral Peduncle). The results of this study may have implications for how DTI‐based measures of CST integrity are used to define impairment, predict outcomes, and interpret change after stroke

AnAbEL: Towards empowering people living with dementia in ambient assisted living

Ambient assisted living aims to support the well-being of people with special needs by offering assistive solutions. Systems focused on dementia increase the autonomy of people living with dementia by monitoring their activities. Topics such as activity recognition and specific solutions such as reminders and tracking users by Global Positioning System offer great advances in user safety and help them preserve a healthier lifestyle. However, these solutions are often addressed to secondary parties, providing them activity logs or alerts, but excluding the main user, the person living with dementia. Although the primary users are taken into consideration at some design stages using user-centred design frameworks, the final products tend to not fully address user needs. This paper presents an ambient intelligent system aimed at reducing this limitation by providing reminders and advice to the person living with dementia in the first instance. The system still involves caregivers if unusual or unhealthy behaviour continues. The solution is deployed in order to be validated by professionals from London city boroughs who work in housing and dementia related services, with an emphasis on enhancing healthy lifestyles by empowering the user in the early stages of dementia with autonomy. Through continued activity monitoring in real-time, the system can provide reminders and warnings to users to keep healthy routines. Continuous monitoring provides user behaviour tracking, and the context-aware logic used involves caregivers through alerts when necessary to ensure user safety. This article describes the process followed in developing the system, and covers previous concerns and practical feedback from health professionals over the deployment of the system in a real environment. Our approach also includes a novel indoor localization system to distinguish users and allows a more specific delivery of services in multi-occupancy scenarios

Application of the Lomb-Scargle Periodogram to Investigate Heart Rate Variability during Haemodialysis

Short-term cardiovascular compensatory responses to perturbations in the circulatory system caused by haemodialysis can be investigated by the spectral analysis of heart rate variability, thus providing an important variable for categorising individual patients' response, leading to a more personalised treatment. This is typically accomplished by resampling the irregular heart rate to generate an equidistant time series prior to spectral analysis, but resampling can further distort the data series whose interpretation can already be compromised by the presence of artefacts. The Lomb-Scargle periodogram provides a more direct method of spectral analysis as this method is specifically designed for large, irregularly sampled, and noisy datasets such as those obtained in clinical settings. However, guidelines for preprocessing patient data have been established in combination with equidistant time-series methods and their validity when used in combination with the Lomb-Scargle approach is missing from literature. This paper examines the effect of common preprocessing methods on the Lomb-Scargle power spectral density estimate using both real and synthetic heart rate data and will show that many common techniques for identifying and editing suspect data points, particularly interpolation and replacement, will distort the resulting power spectrum potentially misleading clinical interpretations of the results. Other methods are proposed and evaluated for use with the Lomb-Scargle approach leading to the main finding that suspicious data points should be excluded rather than edited, and where required, denoising of the heart rate signal can be reliably accomplished by empirical mode decomposition. Some additional methods were found to be particularly helpful when used in conjunction with the Lomb-Scargle periodogram, such as the use of a false alarm probability metric to establish whether spectral estimates are valid and help automate the assessment of valid heart rate records, potentially leading to greater use of this powerful technique in a clinical setting.The authors would like to thank Mel Morris and iTrend Medical Research Ltd. for funding the iTrend research programme

Toward an integrative understanding of social behavior: new models and new opportunities.

Social interactions among conspecifics are a fundamental and adaptively significant component of the biology of numerous species. Such interactions give rise to group living as well as many of the complex forms of cooperation and conflict that occur within animal groups. Although previous conceptual models have focused on the ecological causes and fitness consequences of variation in social interactions, recent developments in endocrinology, neuroscience, and molecular genetics offer exciting opportunities to develop more integrated research programs that will facilitate new insights into the physiological causes and consequences of social variation. Here, we propose an integrative framework of social behavior that emphasizes relationships between ultimate-level function and proximate-level mechanism, thereby providing a foundation for exploring the full diversity of factors that underlie variation in social interactions, and ultimately sociality. In addition to identifying new model systems for the study of human psychopathologies, this framework provides a mechanistic basis for predicting how social behavior will change in response to environmental variation. We argue that the study of non-model organisms is essential for implementing this integrative model of social behavior because such species can be studied simultaneously in the lab and field, thereby allowing integration of rigorously controlled experimental manipulations with detailed observations of the ecological contexts in which interactions among conspecifics occur