Podium 10
Tracks
Breakout 2
| Saturday, September 7, 2024 |
| 2:45 PM - 3:15 PM |
| Dobson 2 |
Speaker
Dr Prasath Jayakaran
School of Physiotherapy, University Of Otago
Postural control in children with strabismus: A longitudinal investigation on sensory weighting
Presentation Abstract
Background and purpose: Appropriate visual input is crucial in the early years of life to develop effective postural control, by coordinating the body’s three sensory systems – namely visual, vestibular, and somatosensory systems. Strabismus (misalignment of eyes) is a relatively common childhood ophthalmic disorder that can impact on the development of effective postural control. This longitudinal study aimed to investigate changes in sensory weighting for postural control over time in children with and without strabismus.
Methods: Twenty-four children with strabismus (study group) and 22 matched control participants (control group) completed the Sensory Organization Test (SOT), BOT® Balance subscale, and Paediatric Balance Scale at three time points (baseline, 6 and 12 months). SOT of the NeuroCom Smart Equitest® was the primary outcome measure that systematically manipulated the available sensory information on six sensory testing conditions. The key variables of interest were the percentage measure of balance (Equilibrium Score) for each of the six-conditions and a weighted summary score of all the six conditions (Composite Score). The BOT (0-24) and PBS (0-54) consist of a series of balance assessment tasks which were scored numerically on the items and reduced to a summary score.
Results: A significant group effect (between-participants, p<0.001; F statistic ranging between 71.83 and 2701.76) was found for ES of the SOT condition 3 (sway-referenced surround – manipulating the visual information) and condition 4 (sway-referenced support – manipulating peripheral somatosensory information) and composite score when adjusted for age and baseline measures.
Conclusion: The sensory weighting for postural control changes over time in children as they develop, and this reweighting phenomenon is different between children with and without strabismus.
Implications: Findings highlight the importance of considering the difference in sensory weighting in children with strabismus and incorporate sensory reorganisation exercises in any part of rehabilitation when working with people with strabismus.
Methods: Twenty-four children with strabismus (study group) and 22 matched control participants (control group) completed the Sensory Organization Test (SOT), BOT® Balance subscale, and Paediatric Balance Scale at three time points (baseline, 6 and 12 months). SOT of the NeuroCom Smart Equitest® was the primary outcome measure that systematically manipulated the available sensory information on six sensory testing conditions. The key variables of interest were the percentage measure of balance (Equilibrium Score) for each of the six-conditions and a weighted summary score of all the six conditions (Composite Score). The BOT (0-24) and PBS (0-54) consist of a series of balance assessment tasks which were scored numerically on the items and reduced to a summary score.
Results: A significant group effect (between-participants, p<0.001; F statistic ranging between 71.83 and 2701.76) was found for ES of the SOT condition 3 (sway-referenced surround – manipulating the visual information) and condition 4 (sway-referenced support – manipulating peripheral somatosensory information) and composite score when adjusted for age and baseline measures.
Conclusion: The sensory weighting for postural control changes over time in children as they develop, and this reweighting phenomenon is different between children with and without strabismus.
Implications: Findings highlight the importance of considering the difference in sensory weighting in children with strabismus and incorporate sensory reorganisation exercises in any part of rehabilitation when working with people with strabismus.
Biography
Prasath has a primary interest in the rehabilitation of individuals with physical disability. Prasath completed his doctoral studies in 2012 on postural control in lower limb amputations. He has since completed two postdoctoral fellowships, first at Brunel University, London (one year), followed by another at the School of Physiotherapy, University of Otago (three years) where he was involved in projects investigating gait and balance, with application to people with pain and disability. He is currently a Senior Lecturer at the School of Physiotherapy.
Current research interests:
- Sensory-motor re-organization across the lifespan
- Supporting people to live well with Parkinson's
Mr Ben Scrivener
Research Physiotherapist
University of Auckland
Can physiotherapists predict walking recovery after stroke?
Presentation Abstract
Background:
Regaining independent walking after a stroke is significant for patients and their families, as it affects both rehabilitation and discharge planning. Patients and families report wanting information about walking recovery. However, the degree to which physiotherapists can accurately provide predictions on walking recovery is unknown.
Purpose:
The aim was to explore whether physiotherapists can accurately predict, at 1-week post-stroke, whether and when their patient will achieve independent walking after stroke.
Methods:
Adults with lower-limb weakness and unable to walk independently were recruited within 5 days of stroke from two Aotearoa hospitals. Clinical assessments were completed at 1 week. At 1-week post-stroke, the treating physiotherapist was asked to predict whether their patient would walk independently by 4, 6, 9, 12, 16, or 26 weeks post-stroke. Physiotherapists rated their confidence in their predictions on a 6-point Likert scale. Functional Ambulation Category (FAC) assessment was completed at each timepoint to determine time by which independent walking was achieved, defined as FAC ≥ 4. Binary logistic regressions were conducted with physiotherapist accuracy as the dependent variable and confidence, years of stroke-specific experience, stroke severity, patient age, lower limb strength and 1-week FAC as independent variables.
Results:
We included 91 patients (median age 71y) and 37 physiotherapists (median 2y stroke-specific experience, range 0 – 14y). Physiotherapists correctly predicted whether independent walking was achieved by 26 weeks for 80/91 (88%) participants. Predictions of time taken to achieve independent walking were accurate for 39/91 (43%), optimistic for 28/91 (31%) and pessimistic for 24/91 (26%). Prediction accuracy was not related to physiotherapist confidence in their predictions or years of experience (both p > 0.4).
Conclusion:
Physiotherapists can accurately predict whether a patient will walk independently after stroke but not when they will achieve this.
Implications:
Validated walking prediction tools may assist physiotherapists in rehabilitation and discharge planning.
Regaining independent walking after a stroke is significant for patients and their families, as it affects both rehabilitation and discharge planning. Patients and families report wanting information about walking recovery. However, the degree to which physiotherapists can accurately provide predictions on walking recovery is unknown.
Purpose:
The aim was to explore whether physiotherapists can accurately predict, at 1-week post-stroke, whether and when their patient will achieve independent walking after stroke.
Methods:
Adults with lower-limb weakness and unable to walk independently were recruited within 5 days of stroke from two Aotearoa hospitals. Clinical assessments were completed at 1 week. At 1-week post-stroke, the treating physiotherapist was asked to predict whether their patient would walk independently by 4, 6, 9, 12, 16, or 26 weeks post-stroke. Physiotherapists rated their confidence in their predictions on a 6-point Likert scale. Functional Ambulation Category (FAC) assessment was completed at each timepoint to determine time by which independent walking was achieved, defined as FAC ≥ 4. Binary logistic regressions were conducted with physiotherapist accuracy as the dependent variable and confidence, years of stroke-specific experience, stroke severity, patient age, lower limb strength and 1-week FAC as independent variables.
Results:
We included 91 patients (median age 71y) and 37 physiotherapists (median 2y stroke-specific experience, range 0 – 14y). Physiotherapists correctly predicted whether independent walking was achieved by 26 weeks for 80/91 (88%) participants. Predictions of time taken to achieve independent walking were accurate for 39/91 (43%), optimistic for 28/91 (31%) and pessimistic for 24/91 (26%). Prediction accuracy was not related to physiotherapist confidence in their predictions or years of experience (both p > 0.4).
Conclusion:
Physiotherapists can accurately predict whether a patient will walk independently after stroke but not when they will achieve this.
Implications:
Validated walking prediction tools may assist physiotherapists in rehabilitation and discharge planning.
Biography
Ben is a Research Physiotherapist and Professional Teaching Fellow in the Department of Medicine, at the University of Auckland. His clinical and research interests include: stroke patient and family experiences of care, predicting recovery after stroke, and neurophysiological assessment for stroke and functional neurological disorders.
Many thanks to our sponsors
If you need help at any stage, please contact us:
+64 21 0271 7606
events@twelveconferences.nz
