Gregorio Sorrentino1, Patrizio Sale2, Claudio Solaro3, Alessia Rabini4, Cesare G Cerri5, Giorgio Ferriero6. 1. Bicocca University, Milan, Italy. 2. Rehabilitation Unit, Department of Neuroscience, University of Padua, Padua, Italy. 3. Mons. Luigi Novarese Rehabilitation Center, Moncrivello, Vercelli, Italy. 4. Division of Physical Medicine and Rehabilitation, Department of Geriatrics, Neurosciences, and Orthopedics, Agostino Gemelli University Hospital, Sacred Heart Catholic University, Rome, Italy. 5. School of Physical and Rehabilitation Medicine, Bicocca University of Milan, Milan, Italy. 6. Department of Physical Medicine and Rehabilitation, Scientific Institute for Research and Care of Lissone, Istituti Clinici Scientifici Maugeri, Lissone, Monza-Brianza, Italy - giorgio.ferriero@icsmaugeri.it.
Abstract
INTRODUCTION: Stroke may result in decreased trunk muscle strength and limited trunk coordination, frequently determining loss of autonomy due to the trunk impairment. Furthermore, sitting balance has been repeatedly identified as an important predictor of motor and functional recovery after stroke. Given the importance of the trunk, it is therefore mandatory that validated tools be available to assess its performance. A systematic review of the currently available clinical measurement tools to assess trunk performance after stroke has been carried out. EVIDENCE ACQUISITION: We searched the PubMed database from January 2006 to April 2017 to select articles which reported or included a clinical measure of trunk performance used in an adult stroke population. The data collected were integrated with the results of a previous review published in 2006. A total of 302 articles were identified, of which 19 were eligible for inclusion. EVIDENCE SYNTHESIS: Numerous clinical tools have been validated to assess trunk performance after stroke, including the Trunk Control Test, the Trunk Impairment Scale, the Postural Assessment Scale for Stroke, the Ottawa Sitting Scale, the Modified Functional Reach Test, the Function In Sitting Test, the Physical Ability Scale, the Trunk Recovery Scale, the Balance Assessment in Sitting and Standing Positions, and the and Sitting-Rising Test. CONCLUSIONS: Several scales and tests have been demonstrated to be valid for assessing trunk performance in stroke. Some of these have already been refined by Rasch analysis to increase their psychometric characteristics. Further psychometric analysis of these tools in large and different samples is, however, still needed.
INTRODUCTION:Stroke may result in decreased trunk muscle strength and limited trunk coordination, frequently determining loss of autonomy due to the trunk impairment. Furthermore, sitting balance has been repeatedly identified as an important predictor of motor and functional recovery after stroke. Given the importance of the trunk, it is therefore mandatory that validated tools be available to assess its performance. A systematic review of the currently available clinical measurement tools to assess trunk performance after stroke has been carried out. EVIDENCE ACQUISITION: We searched the PubMed database from January 2006 to April 2017 to select articles which reported or included a clinical measure of trunk performance used in an adult stroke population. The data collected were integrated with the results of a previous review published in 2006. A total of 302 articles were identified, of which 19 were eligible for inclusion. EVIDENCE SYNTHESIS: Numerous clinical tools have been validated to assess trunk performance after stroke, including the Trunk Control Test, the Trunk Impairment Scale, the Postural Assessment Scale for Stroke, the Ottawa Sitting Scale, the Modified Functional Reach Test, the Function In Sitting Test, the Physical Ability Scale, the Trunk Recovery Scale, the Balance Assessment in Sitting and Standing Positions, and the and Sitting-Rising Test. CONCLUSIONS: Several scales and tests have been demonstrated to be valid for assessing trunk performance in stroke. Some of these have already been refined by Rasch analysis to increase their psychometric characteristics. Further psychometric analysis of these tools in large and different samples is, however, still needed.
Authors: John M Looft; Robert Sjoholm; Andrew H Hansen; Stuart Fairhurst; Greg Voss; Clifford A Dellamano; Jason Egginton; Christine Olney; Gary Goldish Journal: J Spinal Cord Med Date: 2021-03-11 Impact factor: 2.040