
==== Front
Eur J Phys Rehabil Med
Eur J Phys Rehabil Med
EJPRM
European Journal of Physical and Rehabilitation Medicine
1973-9087
1973-9095
Edizioni Minerva Medica

38958692
8463
10.23736/S1973-9087.24.08463-6
Article
Validity and reliability of the chronic composite XA, an upper limb motor assessment using Active Range of Motion in patients with chronic stroke
JAMAL Karim 1 2 *
BUTET Simon 1
MAITRE Blandine 1
GRACIES Jean-Michel 3 4
HAMEAU Sophie 1 2
LEVEQUE LE BRAS Émilie 1
BAUDE Marjolaine 3 4
CORDILLET Sébastien 1
BONAN Isabelle 1 5
1Department of Physical and Rehabilitation Medicine, University Hospital of Rennes, Rennes, France; 2Clinical Investigation Center INSERM 1414, University Hospital of Rennes, Rennes, France; 3Service de Rééducation Neurolocomotrice, HU Henri Mondor, Créteil, France; 4UR BIOTN, Université Paris Est Créteil (UPEC), Créteil, France; 5University of Rennes, CNRS, Inria, Inserm, IRISA UMR 6074, EMPENN ERL U 1228, Rennes, France
* Corresponding author: Karim Jamal, Department of Physical and Rehabilitation Medicine, University Hospital of Rennes, France. E-mail: karim.jamal@univ-rennes.fr
Authors’ contributions: All authors read and approved the final version of the manuscript.

28 8 2024
8 2024
60 4 559566
31 5 2024
19 4 2024
15 2 2024
2024 THE AUTHORS
https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives (CC BY-NC-ND) 4.0 License.
BACKGROUND

Upper limb (UL) spastic paresis has been classically evaluated with assessments of passive movements with limited functional validity. The aim of this study was to assess whether a composite measure of active range of motion (AROM, or XA) is valid and reliable in chronic post-stroke spastic paresis.

AIM

The primary objective was to investigate the validity and reliability of a composite score, comprising multiple XA measurements, to assess UL spastic paresis in patients in chronic stages post-stroke. In addition to this, an exploratory analysis was conducted to identify which muscles should be optimally included in this composite score.

DESIGN

A psychometric proprieties study.

SETTING

Physical and Rehabilitation Medicine Department.

POPULATION

twenty-eight chronic post-stroke participants with spastic paresis.

METHODS

Composite UL XA measurement in twenty-eight chronic post-stroke participants (age=59±11 years; delay post-stroke=29±37 months) with spastic paresis was repeated twice about 40 days apart in a standardized body position. Concurrent and construct validity was evaluated exploring correlation with the Fugl-Meyer Assessment Upper Extremity (FMA-UE), Action Research Arm Test (ARAT), and grip strength (JAMAR™). Reliability was assessed by calculating intraclass correlation coefficients (ICC). Regarding the exploratory analysis, a linear regression analysis was performed to examine the value of including various muscles.

RESULTS

Composite XA against the resistance of elbow, wrist and finger flexors showed strong correlation with FMA-UE and ARAT (r=0.88; P<0.001 and r=0.82; P<0.001 respectively) and a weak association with grip strength (r=0.43; P=0.03). Test-retest reliability was excellent (ICC=0.92). However, the most effective regression model also included XA against the resistance of shoulder adductors as well as forearm pronator (adjusted R2=0.85; AIC=170).

CONCLUSIONS

The present study provided satisfactory psychometric data for the upper limb composite active movement (CXA), derived from the Five Step Assessment. For overall measurement of UL mobility after stroke, we strongly recommend including shoulder and forearm muscles to the score.

CLINICAL REHABILITATION IMPACT

Composite XA is a valid and reliable measure of upper limb motor function in chronic post-stroke patients and could be used in clinical practice and research.

Key words:

Stroke
Upper extremity
Psychometrics
Reproducibility of results
Muscle spasticity
La Fondation pour la Recherche sur les AVC and l’Institut de Neurosciences Cliniques de Rennes
==== Body
pmcAssessment of motor function in post-stroke patients is challenging due to abnormal motor control with both synergistic patterns and inappropriate co-contractions.1-3 This results in reduced capacity for active movements due to an imbalance of forces between agonist and antagonist muscles4 and in functional and participation limitations.4-6 Assessments of active range of motion (AROM) in the upper limb (UL) seem to be an appropriate way to provide a functionally relevant approach.7 Assessments of active range of motion (AROM) in the UL appear to be a suitable method for providing a functionally relevant approach. It takes into account joint mobility, flexibility, and the muscular strength required for specific movements,8 making it well-suited for efficient clinical evaluation.9, 10 However, the utilization of AROM tests to evaluate mobility in clinical practice has been relatively limited and scarce in the spastic paresis literature. On the other hand, the kinematic measurement of upper-limb movement offers objective metrics, although it is constrained by factors such as equipment costs, which hinder its clinical applicability.11 Conversely, several scales are considered valid assessments, including the Fugl-Meyer Assessment Upper-Extremity, the Modified Frenchay Scale, and the Wolf Motor Function Test, due to their good psychometric properties.12-14 However, these scales may be time-consuming in clinical practice.7

Gracies et al.7, 15, 16 have developed for some years a new scale named “Five-Step Assessment,” an expansion of the previously developed Tardieu Scale,17 which was created to quantify various forms of resistance to movement from selected muscle groups, measuring in particular the resistance to passive slow movements (angle of arrest, XV1) passive fast movements (angle of catch, XV3) and maximal active efforts (angle of match, XA). The Five Step Assessment thus includes an evaluation of active range of motion against selected antagonists, in a standardized body position. For a given antagonist muscle, the maximum active range of motion obtained, referred to as XA in degrees, is determined by the angle of match between the torque developed by the agonist muscle during a maximal effort and both passive (spastic myopathy) and active (spastic co-contraction) resistances of the antagonist in the standardized body position. Interestingly, XA against the resistance of most muscles was found to be highly reliable in a preliminary study.18 Composite XA (CXA) scores were recently used in large-scale multicentric international clinical research aiming to evaluate the efficacy of Guided Self-rehabilitation Contracts combined with botulinum injections15 or of botulinum injections alone.7 In these studies, correlation of CXA with the Modified Frenchay Scale for the UL and the 10-meter walking speed for the lower limb was shown. However, it is important to further test the validity and reliability of such a composite assessment.

From the first composite score proposed in Bayle et al.,7 which encompassed only distal muscles, Gracies et al.15 have then expanded CXA toward a more comprehensive version “full CXA” incorporating shoulder extensors and pronator teres. Here, we aim to revisit the potential contribution of adding further muscles of the shoulder and forearm commonly impacted by stroke19 into the composite score, particularly those included in the full CXA.

Therefore, the primary objective of this study was to evaluate the validity and reliability (relative and absolute) of the “distal” composite score proposed by Bayle et al.7 in chronic post-stroke patients with spastic UL paresis. In addition to this, an exploratory analysis was to investigate the value of including additional muscles in the composite score, in particular shoulder extensors/adductors and forearm pronator, through regression analysis.

Materials and methods

Participants

This prospective cohort study used data from a randomized controlled trial investigating the effect of neurofeedback on UL recovery after stroke (NeuroFB-AVC), registered at Clinicaltrials.gov (NCT03766113). All participants gave written informed consent and the study protocol was approved by the local ethics committee. Only the screening and baseline data of the trial were included in this study. Patients were included if they were adults, less than 80 years of age, in the chronic phase after stroke, i.e. over 6 months following a first unilateral supratentorial stroke, and had moderately disabling UL spastic paresis as defined by a Fugl-Meyer Assessment Upper Extremity (FMA-UE) score between 22 and 53 out of 66.20 To ensure homogeneity for functional MRI analysis, participants with multiple strokes or strokes involving the posterior fossa were excluded from the NeuroFB-AVC study.

Procedure

The patients underwent systematic assessments at the screening visit and then at Visit 1 of the study (baseline) before being included in the neurofeedback study. Only these two visits were considered for the psychometric analysis in the present study. Both evaluations consisted in the assessment of the composite score of active range of motion (CXA) against the resistance of specific antagonist muscles and FMA-UE, as well as the Action Research Arm Test (ARAT), and grip strength (JAMAR™). The time between the two visits varied from two to eight weeks although study participants were in chronic phase and thus supposed to be stable on all clinical data. The same assessor evaluated each participant during the two visits. Study participants received no additional rehabilitation beyond routine physiotherapy between the two visits.

Outcomes measures

Composite score of active range of motion (CXA)

The assessment of active movement XA against the resistance of prespecified antagonists was performed according to the measurement modalities described by Gracies et al.7, 15 For a given antagonist, XA was defined as the maximum active range of motion against its resistance (passive and active), measured in degrees. For example, for XA of the elbow flexors, active extension of the elbow was measured in a standardized seated position with a goniometer, using as reference angle a zero that is always the theoretical minimum stretch position of the elbow flexors (Figure 1).

Figure 1 —Practical implementation of XA measurement of the elbow flexors (A), the wrist flexors (B) and the extrinsic finger flexors (C).

CXA was performed as described by Bayle et al.7 as the sum of the active range of motion obtained at three levels as follows: CXA=XA for elbow flexors + XA for wrist flexors + XA for extrinsic finger flexors. As part of the original study, XA of the shoulder extensors and adductors, forearm pronator, and supinators were also evaluated. The assessment tested the pronator quadratus with the elbow in the flexed position.

FMA-UE

Motor impairment of the UL was assessed using the Fugl-Meyer Assessment Upper Extremity (FMA-UE).20 This scale comprises 33 items ordinally scored by the examiner between 0 (movement not performed) and 2 (movement performed perfectly), for a maximum total of 66. The FMA-UE scale has long been validated and proven reliable.21, 22

ARAT

The Action Research Arm Test (ARAT) has also been used to evaluate the activity limitations of the UL by analyzing ability to manipulate a set of objects varying in shape, size, and weight.23 The scale comprises 19 items divided into 4 subscales (grasping, gripping, pinching, and gross motor movement). The ordinal rating varies from 0 to 3 for each item, for a maximum score of 57. The ARAT is a validated scale with excellent reliability.24

Grip strength (JAMAR™)

The Jamar™ hand dynamometer (Lafayette Instrument Company, USA) is a reliable and valid measuring tool25, 26 that has been used to measure the maximal grip strength (in kg) on the paretic side.

Statistical analysis

All statistical analyses were performed using RStudio v.1.3.959 statistical software.27 The level of significance was set at 0.05.

Validity

To assess convergent validity, correlations between the CXA and FMA-UE, ARAT, and grip strength (JAMAR™) were explored using Pearson’s correlation or Spearman’s correlation, depending on the conditions of normality. Validity assessment was performed using the baseline data. The coefficient of correlation (r) was defined according to the following guidelines: ≤0.20=very weak, >0.20-0.40, weak >0.40-0.70, moderate >0.70-0.90, strong and >0.90=very strong.28

Reliability

The relative intra-rater-reliability (stricto sensu test-retest) of the CXA was analyzed between the screening and baseline visit using the intraclass correlation coefficient for a single random rater (ICC2,1). ICC estimates were interpreted based on the following criteria: <0.5, poor, 0.5-0.75, moderate, 0.75-0.9 good; and >0.9 excellent reliability.29 Absolute reliability was determine using the standard error of measurement with the following equation: SEM=SD √(1-ICC) and the minimum detectable change (MDC) with the following equation: MDC 95=1.96 X SEM X√2.

Agreement between the two visits for each outcome was assessed using the Bland-Altman plot method by plotting the mean test-retest scores on the x-axis and the test–retest difference on the y-axis. The 95%CI of the mean difference, represented by boundary lines, illustrates the magnitude of the systematic difference. Graphical interpretation was useful for identifying systematic changes between visits and for illustrating heteroscedasticity, with increasing/decreasing variability and increasing mean test-retest scores.

Contribution of shoulder extensors and adductors and forearm supinators and pronators

The study assessed the additional value of incorporating XA measurements of shoulder extensors and adductors, forearm supinators, and pronators. This evaluation included correlating motor impairment of the UL (FMA-UE) with XA against the resistance of these muscle groups. Additionally, correlations were analyzed between XA measurements. Linear regression was utilized to evaluate the contribution of these muscle groups to active motor function. We selected the muscle combination by joint from the original CXA that yielded the best model. Further, we examined the impact of adding more shoulder and forearm muscles commonly affected by stroke to the composite score. The model incorporated variables sequentially to minimize the Akaike Information Criterion (AIC) and maximize the adjusted R.2, 30 Autocorrelation in regression residuals was assessed using the Durbin-Watson (DW) Test statistic, and multicollinearity was examined using the variance inflation factor (VIF).31, 32 Convergent validity between the best model based on FMA-UE and ARAT was established using either Pearson’s or Spearman’s correlation, based on normality conditions. Finally, the reliability of the best model was assessed.

Results

Participants

Thirty-four participants were included in the screening phase of the study. After consent withdrawal, twenty-eight patients were included in the present psychometric study (Figure 2). The sociodemographic and clinical characteristics of patients are displayed in Table I.

Figure 2 —Flow chart of the study.

Table I —Clinical characteristics of study participants.

Characteristics	Participants (N.=28)	
Male/female	19/9	
Age (years) (mean; SD)	59±11	
Ischemic/hemorrhagic	17/11	
Delay-post (months) (mean; SD)	29±37	
Delay between sessions (days) (mean; SD)	40±21	
FMA-UE (/66) (mean; SD)	37.8±11.6	
CXA (degrees) (mean; SD)	411±78.9	
XA shoulder extensors (degrees) (mean; SD)	94.89±36	
XA shoulder adductors (degrees) (mean; SD)	86.61±32	
XA elbow flexors (degrees) (mean; SD)	158.36±17	
XA forearm pronator (degrees) (mean; SD)	143.86±38	
XA forearm supinators (degrees) (mean; SD)	152.36±36	
XA wrist flexors (degrees) (mean; SD)	119.32±34	
XA extrinsic finger flexors (degrees) (mean; SD)	133.43±44	
JAMAR (kg) (mean; SD)	5.8±7.6	
ARAT (/57) (mean; SD)	21.4±18.4	
ARAT: Action Research Arm Test; CXA: composite active range of motion; FMA-UE: Fugl-Meyer-Assessment Upper-Extremity; N.: number of participants; SD: standard deviation.

Validity

Strong correlations were found between CXA and FMA-UE (r=0.88; P<0.001; Figure 3A), between CXA and ARAT (r=0.82; P<0.001; Figure 3B) and to a lesser level with grip strength (r=0.43; P=0.03) (Figure 3C).

Figure 3 —Correlation between CXA (XA for elbow flexors + XA for wrist flexors + XA for extrinsic finger flexors) and FMA-UE (A), ARAT (B), JAMAR (C).

Reliability

Reliability of CXA was excellent, with an ICC of 0.92 (95% CI, 0.85-0.96; Table II). The Bland-Altman plot showed a bias of -10.8° with 95% limits of agreement between -75.6° and 53.9° (Figure 4). The overall standard error of measurement (SEM) for CXA was 23°. The MDC was 64°. Reliability of ICC for the XA of the shoulder extensors and adductors and forearm pronator was excellent (ICC-XA of shoulder extensors 0.94; 95% CI, 0.88-0.97), ICC of XA of shoulder adductors 0.93 (95% CI (0.87; 0.97); XA of forearm pronator (0.91 (95% CI (0.82; 0.95). Reliability was good for XA of the forearm supinators (0.78; 95% CI, 0.59-0.89).

Table II —Relative and absolute reliability of the CXA, full CXA (including XA of the shoulder adductors and the XA of the forearm pronators), XA shoulder (extensors and adductors), XA elbow flexors, forearm pronators and supinators, XA wrist flexors and XA extrinsic finger flexors.

Variables	ICC (95%CI)	SEM	MDC	
CXA	0.92 (0.85; 0.96)	23.08	63.97	
Full CXA	0.94 (0.89; 0.96)	31.24	86.59	
XA shoulder extensors	0.94 (0.88; 0.97)	9.72	26.94	
XA shoulder adductors	0.93 (0.87; 0.97)	8.32	23.07	
XA elbow flexors	0.78 (0.59; 0.89)	7.12	19.72	
XA forearm pronator	0.91 (0.82; 0.95)	10.5	29.11	
XA forearm supinators	0.78 (0.59; 0.89)	18.55	51.43	
XA wrist flexors	0.86 (0.76;0.94)	13.09	36.28	
XA extrinsic finger flexors	0.88 (0.76;0.94)	15.93	44.14	
ICC: Intraclass Correlation Coefficient; SEM: standard error of measurement, MDC: minimal detectable change.

Figure 4 —Bland-Altman’s plots of test-retest differences (vertical scale) relative to mean test-retest value (horizontal scale) of the CXA (XA for elbow flexors + XA for wrist flexors + XA for extrinsic finger flexors). The black solid line represents zero difference, while the red solid line represents the difference found in the study. The dotted red lines indicate the 95% limits of agreement.

Contribution of shoulder extensors and adductors and of forearm pronators and supinators

Significant correlations were observed between FMA-UE and XA measurements of shoulder extensors and adductors, as well as with XA of the forearm pronator and supinators (P<0.001) (Table III).

Table III —Contribution of shoulder extensors an adductors and of forearm pronators and supinators.

Variables		FMA-UE	
XA shoulder extensors	Pearson‘s r	0.74	
P value	<0.001	
XA shoulder adductors	Pearson’s r	0.72	
P value	<0.001	
XA elbow flexors	Pearson’s r	0.57	
P value	0.001	
XA forearm pronator	Pearson’s r	0.76	
P value	<0.001	
XA forearm supinators	Pearson’s r	0.65	
P value	<0.001	
XA wrist flexors	Pearson’s r	0.78	
P value	<0.001	
XA extrinsic finger flexors	Pearson’s r	0.72	
P value	<0.001	

Additionally, correlations were noted among various XA measurements (Supplementary Digital Material 1: Supplementary Table I). Notably, the DW test statistic values, nearing 2, suggested no evidence of autocorrelation, while the VIF<5 indicated no significant multicollinearity between the XA measurements (Supplementary Digital Material 2: Supplementary Table II). The linear regression model including CXA showed an adjusted R2 of 0.77 with an AIC of 181. Including shoulder extensors and adductors improved the regression model, especially with the XA of the shoulder adductors (adjusted R2=0.83 with an AIC=174). Focusing on the elbow, the model with XA of the forearm pronator was optimal in according to the a priori set criteria (adjusted R2=0.85, AIC=170; Table IV). The new CXA showed a significant correlation with both FMA-UE (r=0.92; P<0.001) and ARAT (r=0.82; P<0.001) and its reliability was excellent at 0.94 (95% CI (0.89; 0.96), with a SEM of 31° and a MDC of 86°.

Table IV —Linear regression.

Model	XA incorporated	R	R2	Adjusted R2	AIC	F	df1	df2	P	
1	XA wrist flexors XA extrinsic finger flexors XA elbow flexors	0.89	0.79	0.77	181	31.1	3	24	<0.001	
2	XA wrist flexors
XA extrinsic finger flexors
XA elbow flexors
XA shoulder extensors	0.91	0.83	0.80	178	28.6	4	23	<0.001	
3	XA wrist flexors
XA extrinsic finger flexors
XA elbow flexors
XA shoulder adductors	0.92	0.85	0.83	174	33.8	4	23	<0.001	
4	XA shoulder adductors
XA wrist flexors
XA extrinsic finger flexors
XA forearm supinators	0.93	0.86	0.84	172	37.2	4	23	<0.001	
5	XA shoulder adductors
XA wrist flexors
XA extrinsic finger flexors
XA forearm pronator	0.93	0.87	0.85	170	39.5	4	23	<0.001	

Discussion

The initial composite score comprising active range of motion against the resistance of elbow, wrist and fingers flexors7 has excellent test-retest reliability and concurrent validity as against activity scores such as the Fugl-Meyer assessment and the ARAT. This score is adapted to the assessment of spastic paresis and rapidly obtained. Adding XA against the shoulder extensors, adductors and forearm pronator improves the model to a level where 87% of the FMA-UE variability is explained.

Reliability and correlations of composite active range of motion with activity scores

Thus, this composite score seems to well reflect the motor limitations in UL spastic paresis after stroke. The correlations found in the present monocentric study are stronger than those found from large international multicenter trial data in Bayle et al.,7 who studied the relationship between CXA and the Modified Frenchay Scale (MFS13). On the other hand, we found a weak correlation between CXA and grip strength. This result can be easily explained by the fact that finger extensors do not constitute a common antagonist to hand function in hemiparesis, as opposed to finger flexors and wrist and elbow flexors.19

In terms of the relative reliability of this composite score, the present findings are comparable to those of Baude et al.18 who investigated the intra- (stricto sensu test-retest) and inter-reliability of the active range of motion (XA) against the major UL antagonists measured in 18 participants with chronic spastic hemiparesis. This study complements the psychometric data by providing the absolute reliability of the CXA with a standard error of measurement of 23° and the MDC of 64°. These results will be of future clinical and research interest. Indeed, a gain of more than 64° in the total CXA score must be observed during a clinical procedure in order to conclude that there is a significant clinical difference in the UL active capacity and thus to be able to demonstrate the efficacy of a given therapy. While the composite score seems to effectively capture motor limitations in spastic paresis of the upper limbs following a stroke and allows for a rapid and thorough assessment, a more granular joint evaluation and the utilization of MDC per joint are recommended for more precise localized treatment. Moreover, although CXA proves to be a valid and reliable tool, it should be employed in conjunction with the other components of the Five-Step Assessment as part of a comprehensive evaluation of UL spastic paresis in clinical practice.

Extending CXA to shoulder muscles and forearm pronators

However, this composite score fails to consider shoulder and forearm antagonists to UL function. Therefore, the second step of the present study was to explore the value of including the performance against additional potentially important antagonists in the score.15 We thus included shoulder and forearm muscles, as these potential antagonists to function19 are crucial to release active capacities of the upper limb, particular in reaching and hand orientation efforts. The present findings demonstrate that incorporating shoulder extensors and adductors, enhances the model, bringing it to explain 83% to 85% of FMA-UE variability.

Moreover, the addition of the forearm pronator yields the best model, explaining 87% of FMA-UE variability), in line with the version proposed by Gracies et al.15 The MDC increases a bit from that of the initial CXA limited to finger, wrist and elbow flexors, but this obviously relates to the additional muscles. Thus, we favor adding XA against the shoulder adductors and extensors and the forearm pronator in the composite score.

Despite finding no evidence of autocorrelation or multicollinearity, and despite the clinical rationale behind including muscles commonly affected by stroke,19 it’s important to recognize that this analysis remains exploratory due to the limited sample size. Consequently, it is advisable to validate this study with a larger cohort.

Limitations of the study

The cohort size was limited, with only 28 participants. Because the data were drawn from a larger study, the number of subjects included was dependent on the number of subjects participating in the original study. Also, the findings only pertain to patients with moderate UL motor impairment. Indeed, the inclusion criteria of the original study was a FMA-UE score between 22 and 53 out of 66.20 In addition, the evaluation of this novel clinical assessment was performed here in chronic stroke subjects, which does not allow generalization to acute and subacute phases after stroke. Therefore, inclusion of participants at an earlier stage of stroke in future studies would be relevant. Finally, inter-rater reliability was not assessed in this study. This should be tested in future studies, as well as other psychometric data such as responsiveness or the minimal clinically important difference, which would allow identifying clinical differences that would be meaningful based on patient subjectivity with respect to quality of life in particular.

Conclusions

The present study provided satisfactory psychometric data for the UL CXA, derived from the Five Step Assessment. For overall measurement of UL mobility after stroke, we strongly recommend including shoulder and forearm muscles to the score. We recommend using this composite active movement measurement in the assessment of UL spastic paresis in clinical practice.

Supplementary Digital Material 1

Supplementary Table I

Correlations were noted among various XA measurements.

Supplementary Digital Material 2

Supplementary Table II

Linear regression

Conflicts of interest: The authors certify that there is no conflict of interest with any financial organization regarding the material discussed in the manuscript.

Funding: This research was funded by a grant from La Fondation pour la Recherche sur les AVC and l’Institut de Neurosciences Cliniques de Rennes.
==== Refs
References

1 Baude M Nielsen JB Gracies JM . The neurophysiology of deforming spastic paresis: A revised taxonomy. Ann Phys Rehabil Med 2019;62 :426–30. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=30500361&dopt=Abstract 10.1016/j.rehab.2018.10.004 30500361
2 Chae J Yang G Park BK Labatia I . Muscle weakness and cocontraction in upper limb hemiparesis: relationship to motor impairment and physical disability. Neurorehabil Neural Repair 2002;16 :241–8. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12234087&dopt=Abstract 10.1177/154596830201600303 12234087
3 Yelnik AP Simon O Parratte B Gracies JM . How to clinically assess and treat muscle overactivity in spastic paresis. J Rehabil Med 2010;42 :801–7. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=20878038&dopt=Abstract https://doi.org/10.2340/16501977-0613 20878038
4 Khan F Amatya B Bensmail D Yelnik A . Non-pharmacological interventions for spasticity in adults: an overview of systematic reviews. Ann Phys Rehabil Med 2019;62 :265–73. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=29042299&dopt=Abstract 10.1016/j.rehab.2017.10.001 29042299
5 Doan QV Brashear A Gillard PJ Varon SF Vandenburgh AM Turkel CC Relationship between disability and health-related quality of life and caregiver burden in patients with upper limb poststroke spasticity. PM R 2012;4 :4–10. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=22200567&dopt=Abstract 10.1016/j.pmrj.2011.10.001 22200567
6 Broussy S Saillour-Glenisson F García-Lorenzo B Rouanet F Lesaine E Maugeais M Sequelae and Quality of Life in Patients Living at Home 1 Year After a Stroke Managed in Stroke Units. Front Neurol 2019;10 :907. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=31496987&dopt=Abstract 10.3389/fneur.2019.00907 31496987
7 Bayle N Maisonobe P Raymond R Balcaitiene J Gracies JM . Composite active range of motion (CXA) and relationship with active function in upper and lower limb spastic paresis. Clin Rehabil 2020;34 :803–11. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=32336148&dopt=Abstract 10.1177/0269215520911970 32336148
8 Parikh RJ Sutaria JM Ahsan M Nuhmani S Alghadir AH Khan M . Effects of myofascial release with tennis ball on spasticity and motor functions of upper limb in patients with chronic stroke: A randomized controlled trial. Medicine (Baltimore) 2022;101 :e29926. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=35945719&dopt=Abstract 10.1097/MD.0000000000029926 35945719
9 Beebe JA Lang CE . Absence of a proximal to distal gradient of motor deficits in the upper extremity early after stroke. Clin Neurophysiol 2008;119 :2074–85. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=18571981&dopt=Abstract 10.1016/j.clinph.2008.04.293 18571981
10 Beebe JA Lang CE . Active range of motion predicts upper extremity function 3 months after stroke. Stroke 2009;40 :1772–9. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=19265051&dopt=Abstract 10.1161/STROKEAHA.108.536763 19265051
11 Eftekhar P Li MH Semple MJ Richardson D Brooks D Mochizuki G Investigation of the Kinematic Upper-Limb Movement Assessment (KUMA): A Pilot Study. Physiother Can 2022;74 :316–23. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=37325208&dopt=Abstract 10.3138/ptc-2019-0023 37325208
12 Berglund K Fugl-Meyer AR . Upper extremity function in hemiplegia. A cross-validation study of two assessment methods. Scand J Rehabil Med 1986;18 :155–7. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=3810081&dopt=Abstract 10.2340/16501977198618155157 3810081
13 Laclergue Z Ghédira M Gault-Colas C Billy L Gracies JM Baude M . Reliability of the Modified Frenchay Scale for the Assessment of Upper Limb Function in Adults With Hemiparesis. Arch Phys Med Rehabil 2023;104 :1596–605. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=37121532&dopt=Abstract 10.1016/j.apmr.2023.04.003 37121532
14 Wolf SL Catlin PA Ellis M Archer AL Morgan B Piacentino A . Assessing Wolf motor function test as outcome measure for research in patients after stroke. Stroke 2001;32 :1635–9. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11441212&dopt=Abstract 10.1161/01.STR.32.7.1635 11441212
15 Gracies JM Francisco GE Jech R Khatkova S Rios CD Maisonobe P ENGAGE Study Group. Guided Self-rehabilitation Contracts Combined With AbobotulinumtoxinA in Adults With Spastic Paresis. J Neurol Phys Ther 2021;45 :203–13. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=34039905&dopt=Abstract 10.1097/NPT.0000000000000359 34039905
16 Gracies JM Bayle N Vinti M Alkandari S Vu P Loche CM Five-step clinical assessment in spastic paresis. Eur J Phys Rehabil Med 2010;46 :411–21. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=20927007&dopt=Abstract 20927007
17 Gracies JM Marosszeky JE Renton R Sandanam J Gandevia SC Burke D . Short-term effects of dynamic lycra splints on upper limb in hemiplegic patients. Arch Phys Med Rehabil 2000;81 :1547–55. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=11128888&dopt=Abstract 10.1053/apmr.2000.16346 11128888
18 Baude M Loche CM Gault-Colas C Pradines M Gracies JM . Intra- and inter-raters reliabilities of a stepped clinical assessment of chronic spastic paresis in adults. Ann Phys Rehabil Med 2015;58 :4–5. 10.1016/j.rehab.2015.07.016
19 Mayer NH Esquenazi A Childers MK . Common patterns of clinical motor dysfunction. Muscle Nerve Suppl 1997;6 :S21–35. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=9826981&dopt=Abstract 10.1002/(SICI)1097-4598(1997)6+<21::AID-MUS4>3.0.CO;2-L 9826981
20 Hoonhorst MH Nijland RH van den Berg JS Emmelot CH Kollen BJ Kwakkel G . How Do Fugl-Meyer Arm Motor Scores Relate to Dexterity According to the Action Research Arm Test at 6 Months Poststroke? Arch Phys Med Rehabil 2015;96 :1845–9. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=26143054&dopt=Abstract 10.1016/j.apmr.2015.06.009 26143054
21 Gladstone DJ Danells CJ Black SE . The fugl-meyer assessment of motor recovery after stroke: a critical review of its measurement properties. Neurorehabil Neural Repair 2002;16 :232–40. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=12234086&dopt=Abstract 10.1177/154596802401105171 12234086
22 Duncan PW Propst M Nelson SG . Reliability of the Fugl-Meyer assessment of sensorimotor recovery following cerebrovascular accident. Phys Ther 1983;63 :1606–10. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=6622535&dopt=Abstract 10.1093/ptj/63.10.1606 6622535
23 Pike S Lannin NA Wales K Cusick A . A systematic review of the psychometric properties of the Action Research Arm Test in neurorehabilitation. Aust Occup Ther J 2018;65 :449–71. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=30306610&dopt=Abstract 10.1111/1440-1630.12527 30306610
24 Platz T Pinkowski C van Wijck F Kim IH di Bella P Johnson G . Reliability and validity of arm function assessment with standardized guidelines for the Fugl-Meyer Test, Action Research Arm Test and Box and Block Test: a multicentre study. Clin Rehabil 2005;19 :404–11. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=15929509&dopt=Abstract 10.1191/0269215505cr832oa 15929509
25 Bertrand AM Fournier K Wick Brasey MG Kaiser ML Frischknecht R Diserens K . Reliability of maximal grip strength measurements and grip strength recovery following a stroke. J Hand Ther 2015;28 :356–62, quiz 363. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=26206167&dopt=Abstract 10.1016/j.jht.2015.04.004 26206167
26 Sunderland A Tinson D Bradley L Hewer RL . Arm function after stroke. An evaluation of grip strength as a measure of recovery and a prognostic indicator. J Neurol Neurosurg Psychiatry 1989;52 :1267–72. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=2592969&dopt=Abstract 10.1136/jnnp.52.11.1267 2592969
27 RStudio Team. RStudio: Integrated Development for R. RStudio, PBC, Boston, MA; 2020 [Internet]. Available from http://www.rstudio.com/ [cited 2024, Jun 13].
28 Salkind NJ, Rasmussen K. Encyclopedia of measurement and statistics. Thousand Oaks, CA: SAGE Publications; 2007.
29 Koo TK Li MY . A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research. J Chiropr Med 2016;15 :155–63. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=27330520&dopt=Abstract 10.1016/j.jcm.2016.02.012 27330520
30 Burnham KP Anderson DR Huyvaert KP . AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons. Behav Ecol Sociobiol 2011;65 :23–35. 10.1007/s00265-010-1029-6
31 Alshurtan KS Aldhaifi SY Alshammari KA Alodayli OM Alqahtani KF Aldhaifi SY . Burnout Syndrome Among Critical Care Health Providers in Saudi Arabia. J Multidiscip Healthc 2024;17 :843–54. https://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=38434482&dopt=Abstract https://doi.org/10.2147/JMDH.S452294 38434482
32 Zuur AF Ieno EN Elphick CS . A protocol for data exploration to avoid common statistical problems. Methods Ecol Evol 2010;1 :3–14. 10.1111/j.2041-210X.2009.00001.x
