Abstract 99: Prep2: A Refined Algorithm for Predicting REcovery Potential of Upper Limb Function After Stroke

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Cathy M Stinear ◽  
Winston D Byblow ◽  
Marie-Claire Smith ◽  
Suzanne J Ackerley ◽  
P Alan Barber
Keyword(s):  
Upper Limb ◽  
Right Hemisphere ◽  
Economic Benefits ◽  
Good Prognosis ◽  
Asymmetry Index ◽  
Shoulder Abduction ◽  
Limb Function ◽  
Upper Limb Function ◽  
Recovery Potential ◽  
Capacity For Consent

Independence after stroke depends on the recovery of motor function, but this is difficult to accurately predict for individual patients. We have previously described an algorithm for predicting potential for recovery of upper limb function for individual patients after stroke. The Predict REcovery Potential (PREP) algorithm begins with a bedside assessment of paretic shoulder abduction and finger extension strength (SAFE score out of 10), followed by transcranial magnetic stimulation (TMS), and magnetic resonance imaging (MRI), as required. Patients are predicted to have potential for an Excellent, Good, Limited or Poor recovery of upper limb function within 12 weeks. The algorithm was developed with data from 40 patients with first-ever ischaemic stroke. This study evaluated and refined the algorithm with a larger, more heterogeneous cohort. Inclusion criteria were confirmed stroke (ischaemic or haemorrhagic), new upper limb motor symptoms, and age at least 18 years. Previous stroke, thrombolysis and thrombectomy were allowed. Exclusion criteria were cerebellar stroke, contraindications to TMS and MRI for those patients who required these tests, and reduced capacity for consent. The Action Research Arm Test was used to measure paretic upper limb function 12 weeks post-stroke. A sample of 192 patients was recruited within 3 days of stroke (106 men, mean age 72 y, 100 right hemisphere), and 157 patients completed the 12 week assessment. The algorithm was refined by combining the SAFE score with age (<80, ≥80 years) to more accurately distinguish between patients with an Excellent or Good prognosis; and by revising the MRI asymmetry index threshold from 0.15 to 0.125 to more accurately distinguish between patients with a Limited or Poor prognosis. These revisions improved accuracy from 59% to 75%. With the revised algorithm, the proportion of patients who need TMS is reduced from over half to around one third. The revised algorithm is therefore more accurate and more efficient. Alternative versions of the PREP2 algorithm will also be presented, which can be used when TMS and/or MRI are unavailable. The potential clinical and economic benefits of implementing the PREP2 algorithm will be discussed.

Abstract 112: Predicting REcovery Potential of Upper Limb Function After Stroke to Increase Rehabilitation Efficiency

Stroke ◽  
2016 ◽  
Vol 47 (suppl_1) ◽  
Author(s):  
Cathy M Stinear ◽  
Suzanne J Ackerley ◽  
Winston D Byblow ◽  
P A Barber ◽  
Anna McRae ◽  
...  
Keyword(s):  
Upper Limb ◽  
Diffusion Tensor ◽  
Shoulder Abduction ◽  
Limb Function ◽  
Limb Weakness ◽  
Implementation Phase ◽  
Upper Limb Function ◽  
Therapy Program ◽  
Recovery Potential ◽  
Two Phases

Introduction: The PREP algorithm combines clinical assessment [Shoulder Abduction Finger Extension (SAFE) score], transcranial magnetic stimulation (TMS) and diffusion-tensor imaging to predict potential for upper limb recovery following stroke. Patients’ recovery potential is predicted to be Complete, Notable, Limited or None. Hypothesis: The PREP algorithm may be used in a ‘real world’ clinical setting to set individual rehabilitation goals. Methods: This study recruited 194 patients with upper limb weakness within 3 days of stroke. Assessments were made at baseline and 12 weeks by assessors blinded to PREP algorithm prediction. The initial benchmarking phase recruited 85 patients and PREP algorithm information was not shared with clinical teams or patients. The results were used to refine the algorithm and guide implementation in three ways. First, patients with a SAFE score > 7, predicted to have Complete upper limb recovery, were given a self-directed therapy program. Second, patients with a SAFE score of 5-7 could be given a Notable recovery prognosis, without requiring TMS. Third, 19% of patients exceeded their predicted upper limb recovery, so this possibility was conveyed to patients and clinical teams. The implementation phase recruited 109 patients, and PREP algorithm predictions were shared with patients and clinical teams. Results: Interim analyses (n = 135) find that the PREP algorithm correctly predicted upper limb function at 12 weeks for 85% of patients. Implementation of the algorithm decreased length of stay by 7 days (95%CI 2 - 15 days, p < 0.05) and increased the proportion of patients discharged home from the acute stroke unit from 28% to 49% (p < 0.01). Implementation also decreased upper limb therapy dose (p < 0.01), yet patient outcomes were similar between the two phases. Primary endpoint analysis will be complete in November 2015. Conclusions: Making predictions about the potential for recovery of upper limb function, and setting individual rehabilitation goals accordingly, may increase the efficiency of post-stroke rehabilitation.

scholarly journals Measures of Interjoint Coordination Post-stroke Across Different Upper Limb Movement Tasks

2021 ◽  
Vol 8 ◽  
Author(s):  
Anne Schwarz ◽  
Janne M. Veerbeek ◽  
Jeremia P. O. Held ◽  
Jaap H. Buurke ◽  
Andreas R. Luft
Keyword(s):  
Upper Limb ◽  
Elbow Flexion ◽  
Shoulder Abduction ◽  
Kinematic Parameters ◽  
Limb Function ◽  
Interjoint Coordination ◽  
Upper Limb Function ◽  
Shoulder Flexion ◽  
Flexion Extension ◽  
Median Slope

Background: Deficits in interjoint coordination, such as the inability to move out of synergy, are frequent symptoms in stroke subjects with upper limb impairments that hinder them from regaining normal motor function. Kinematic measurements allow a fine-grained assessment of movement pathologies, thereby complementing clinical scales, like the Fugl–Meyer Motor Assessment of the Upper Extremity (FMMA-UE). The study goal was to investigate the effects of the performed task, the tested arm, the dominant affected hand, upper limb function, and age on spatiotemporal parameters of the elbow, shoulder, and trunk. The construct validity of the metrics was examined by relating them with each other, the FMMA-UE, and its arm section.Methods: This is a cross-sectional observational study including chronic stroke patients with mild to moderate upper limb motor impairment. Kinematic measurements were taken using a wearable sensor suit while performing four movements with both upper limbs: (1) isolated shoulder flexion, (2) pointing, (3) reach-to-grasp a glass, and (4) key insertion. The kinematic parameters included the joint ranges of shoulder abduction/adduction, shoulder flexion/extension, and elbow flexion/extension; trunk displacement; shoulder–elbow correlation coefficient; median slope; and curve efficiency. The effects of the task and tested arm on the metrics were investigated using a mixed-model analysis. The validity of metrics compared to clinically measured interjoint coordination (FMMA-UE) was done by correlation analysis.Results: Twenty-six subjects were included in the analysis. The movement task and tested arm showed significant effects (p &lt; 0.05) on all kinematic parameters. Hand dominance resulted in significant effects on shoulder flexion/extension and curve efficiency. The level of upper limb function showed influences on curve efficiency and the factor age on median slope. Relations with the FMMA-UE revealed the strongest and significant correlation for curve efficiency (r = 0.75), followed by shoulder flexion/extension (r = 0.68), elbow flexion/extension (r = 0.53), and shoulder abduction/adduction (r = 0.49). Curve efficiency additionally correlated significantly with the arm subsection, focusing on synergistic control (r = 0.59).Conclusion: The kinematic parameters of the upper limb after stroke were influenced largely by the task. These results underpin the necessity to assess different relevant functional movements close to real-world conditions rather than relying solely on clinical measures.Study Registration: clinicaltrials.gov, identifier NCT03135093 and BASEC-ID 2016-02075.

scholarly journals Does Transcranial Magnetic Stimulation Have an Added Value to Clinical Assessment in Predicting Upper-Limb Function Very Early After Severe Stroke?

2018 ◽  
Vol 32 (8) ◽  
pp. 682-690 ◽  
Author(s):  
Maurits H. J. Hoonhorst ◽  
Rinske H. M. Nijland ◽  
Peter J. S. van den Berg ◽  
Cornelis H. Emmelot ◽  
Boudewijn J. Kollen ◽  
...  
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Upper Limb ◽  
Predictive Value ◽  
Magnetic Stimulation ◽  
Prognostic Value ◽  
Motor Evoked Potentials ◽  
Added Value ◽  
Shoulder Abduction ◽  
Limb Function ◽  
Upper Limb Function

Background. The added prognostic value of transcranial magnetic stimulation (TMS)-induced motor-evoked potentials (MEPs) to clinical modeling for the upper limb is still unknown early poststroke. Objective. To determine the added prognostic value of TMS of the adductor digiti minimi (TMS-ADM) to the clinical model based on voluntary shoulder abduction (SA) and finger extension (FE) during the first 48 hours and at 11 days after stroke. Methods. This was a prospective cohort study with 3 logistic regression models, developed to predict upper-limb function at 6 months poststroke. The first model showed the predictive value of SA and FE measured within 48 hours and at 11 days poststroke. The second model included TMS-ADM, whereas the third model combined clinical and TMS-ADM information. Differences between derived models were tested with receiver operating characteristic curve analyses. Results. A total of 51 patients with severe, first-ever ischemic stroke were included. Within 48 hours, no significant added value of TMS-ADM to clinical modeling was found ( P = .369). Both models suffered from a relatively low negative predictive value within 48 hours poststroke. TMS-ADM combined with SA and FE (SAFE) showed significantly more accuracy than TMS-ADM alone at 11 days poststroke ( P = .039). Conclusion. TMS-ADM showed no added value to clinical modeling when measured within first 48 hours poststroke, whereas optimal prediction is achieved by SAFE combined with TMS-ADM at 11 days poststroke. Our findings suggest that accuracy of predicting upper-limb motor function by TMS-ADM is mainly determined by the time of assessment early after stroke onset.

scholarly journals The Dynamic Thumb-in-Palm Pattern in Children with Spastic Cerebral Palsy and Its Effects on Upper Limb Function

Children ◽  
2020 ◽  
Vol 8 (1) ◽  
pp. 17
Author(s):  
Ja Young Choi ◽  
Dong-Wook Rha ◽  
Seon Ah Kim ◽  
Eun Sook Park
Keyword(s):  
Cerebral Palsy ◽  
Upper Limb ◽  
Multivariable Analysis ◽  
Spastic Cerebral Palsy ◽  
Type I ◽  
Upper Arm ◽  
Limb Function ◽  
Upper Limb Function ◽  
Limb Deformities ◽  
Arm Function

The thumb-in-palm (TIP) pattern is one of the most common upper limb deformities in cerebral palsy (CP). This study was designed to investigate the effect of the dynamic TIP pattern on upper limb function in children with spastic CP. This prospective observational study included a total of 106 children with CP with dynamic TIP. The House TIP classification while grasping small or large objects, Melbourne Assessment of Unilateral Upper Limb Function (MUUL), Shriners Hospital Upper Extremity Evaluation (SHUEE), Zancolli classification for wrist–finger flexor deformity, and degree of swan neck deformity were assessed. Type I was the most common and highest functioning House TIP classification type. However, there were no significant differences in upper arm function between types II, III, and IV. The three components of the SHUEE showed stronger association with MUUL than House TIP and Zancolli classifications. After multivariable analysis, functional use of the wrist–finger and the thumb played a more significant role than the dynamic alignment of the thumb. In conclusion, the House TIP classification is useful to describe the TIP pattern. The SHUEE thumb assessment is a useful tool for reflecting upper arm function. The upper arm function was related more with the associated wrist flexor deformity than dynamic TIP.

Robotic Assessment of Upper Limb Function in a Nonhuman Primate Model of Chronic Stroke

2021 ◽  
Author(s):  
Yining Chen ◽  
Meredith C. Poole ◽  
Shelby V. Olesovsky ◽  
Allen A. Champagne ◽  
Kathleen A. Harrison ◽  
...  
Keyword(s):  
Upper Limb ◽  
Nonhuman Primate ◽  
Chronic Stroke ◽  
Nonhuman Primate Model ◽  
Limb Function ◽  
Primate Model ◽  
Upper Limb Function
Sign in / Sign up

Export Citation Format

Share Document