Fatigue Profiles in Patients with Multiple Sclerosis are Based on Severity of Fatigue and not on Dimensions of Fatigue

Fatigue related to Multiple Sclerosis (MS) is considered a multidimensional symptom, manifesting in several dimensions such as physical, cognitive, and psychosocial fatigue. This study investigated in 264 patients with severe primary MS-related fatigue (median MS duration 6.8 years, mean age 48.1 years, 75% women) whether subgroups can be distinguished based on these dimensions. Subsequently, we tested whether MS-related

Improving the Action Research Arm test: a unidimensional hierarchical scale

The Action Research Arm (ARA) test is a performance test of upper extremity motor function which consists of 19 items divided into four hierarchical subtests. This multidimensionality has not yet been tested empirically. To investigate the dimensionality of the ARA test. Cross-sectional study involving a sample of 63 chronic stroke patients. A Mokken scale analysis was performed. The Mokken scale analysis revealed one strong unidimensional scale containing all 19 items, of which the scalability coefficient H was 0.79, while H per item ranged from 0.69 to 0.86. The reliability coefficient rho equalled 0.98, indicating a very high internal consistency. A subset of 15 out of 19 items showed an invariant hierarchical item-ordering. The ARA test is a unidimensional scale. The use of subtests, as proposed in the original description of the instrument, is not supported by the present findings. The 15-item scale presented here can be used for adaptive testing, i.e. using only a selected subset of items based on prior knowledge about the patient's abilities, thus minimizing testing tim

Physical and Cognitive Functioning After 3 Years Can Be Predicted Using Information From the Diagnostic Process in Recently Diagnosed Multiple Sclerosis

Objective\ud To predict functioning after 3 years in patients with recently diagnosed multiple sclerosis (MS).\ud \ud Design\ud Inception cohort with 3 years of follow-up. At baseline, predictors were obtained from medical history taking, neurologic examination, and magnetic resonance imaging (MRI).\ud \ud Setting\ud Neurology outpatient clinic.\ud \ud Participants\ud Patients with MS (N=156); 146 with complete follow-up.\ud \ud Interventions\ud Not applicable.\ud \ud Main Outcome Measures\ud Inability to walk at least 500m, impaired dexterity, cognitive impairments, incontinence, inability to drive a car or use public transportation, social dysfunction, and reliance on a disability pension.\ud \ud Results\ud Clinical prediction rules were constructed for the models that were well calibrated (sufficient agreement between predicted and observed outcomes, based on visual inspection of calibration curves) and that showed sufficient discrimination (area under the receiver operation characteristic curve >.70) after internal bootstrap validation. The models for the inability to walk at least 500m, impaired dexterity, and cognitive impairments were well calibrated. Discrimination was sufficient for all 7 models, except the one predicting social dysfunction (.67). The inability to walk at least 500m was predicted by the perceived ability to walk, impairment of the cerebellar tract, and the number of MRI lesions in the spinal cord. Impaired dexterity was predicted by the perceived ability to use the hands, impairments of the pyramidal, cerebellar, and sensory tracts, and the T2-weighted infratentorial lesion load. Cognitive impairment was predicted by age, gender, the perceived ability to concentrate, and the T2-weighted supratentorial lesion load.\ud \ud Conclusions\ud Inability to walk at least 500m, impaired dexterity, and cognitive impairments can be predicted with predictors that are derived from medical history taking, neurologic examination, and MRI shortly after a definite diagnosis of MS has been made.\ud \u

Measuring subluxation of the hemiplegic shoulder: Reliability of a method

Objective: Subluxation of the shoulder after stroke can be measured according to the method described by Van Langenberghe and Hogan. Methods: To evaluate the reliability of this method, the shoulder radiographs of 25 patients were available for this study. Two independent raters each assessed these radiographs twice. Results: The intrarater reliability was good: percentage of agreement was 88 and 84%, weighted κ, 0.69 [95% confidence interval (CI), 0.38-1 0] and 0.78 (95% CI, 0.60-0.95) for raters 1 and 2, respectively. The interrater reliability was poor: percentage of agree ment was 36 and 28%, κ, 0.11 (95% CI, 0.0-0.31) and 0.09 (95% CI, 0.0-0.23) in sessions 1 and 2, respectively. Subsequently the original method was adjusted by com bining two categories (no subluxation and beginning subluxation) into one (“no clin ically important subluxation”). Conclusions: After this adjustment of the categories, the interrater reliability improved [percentage of agreement, 72%, and κ, 0.49 (95% CI, 0.18-0.80)], but did not reach acceptable values

Minimal changes in health status questionnaires: distinction between minimally detectable change and minimally important change

Changes in scores on health status questionnaires are difficult to interpret. Several methods to determine minimally important changes (MICs) have been proposed which can broadly be divided in distribution-based and anchor-based methods. Comparisons of these methods have led to insight into essential differences between these approaches. Some authors have tried to come to a uniform measure for the MIC, such as 0.5 standard deviation and the value of one standard error of measurement (SEM). Others have emphasized the diversity of MIC values, depending on the type of anchor, the definition of minimal importance on the anchor, and characteristics of the disease under study. A closer look makes clear that some distribution-based methods have been merely focused on minimally detectable changes. For assessing minimally important changes, anchor-based methods are preferred, as they include a definition of what is minimally important. Acknowledging the distinction between minimally detectable and minimally important changes is useful, not only to avoid confusion among MIC methods, but also to gain information on two important benchmarks on the scale of a health status measurement instrument. Appreciating the distinction, it becomes possible to judge whether the minimally detectable change of a measurement instrument is sufficiently small to detect minimally important changes

Treating patients with hemiplegic shoulder pain

Studies on the efficacy of available methods of treatment for hemiplegic shoulder pain are reviewed in an attempt to identify the most effective treatment for this problem. Because of the poor quality of the 14 selected studies, no definite conclusion can be drawn about the most effective method of treatment. However, functional electrical stimulation and intra-articular triamcinolone acetonide injections seem to be the most promising treatment option

Physical behaviour is weakly associated with physical fatigue in persons with multiple sclerosis-related fatigue

Background: Fatigue affects 80% of persons with multiple sclerosis and is associated with daily physical functioning. Both fatigue and physical behaviour are multidimensional concepts. Objective: To study the association between the dimensions of physical behaviour and multiple sclerosis- related fatigue. Methods: Cross-sectional analysis of 212 persons with multiple sclerosis. Participants were severely fatigued, with a Fatigue Severity Scale median (interquartile range): 5.4 (4.8-5.9) and were minimally to moderately neurologically impaired, based on the Expanded Disability Status Scale: 2.5 (2.0-3.5), 73% had relapsing-remitting multiple sclerosis. Fatigue was measured by questionnaires (i.e. Checklist Individual Strength, Modified Fatigue Impact Scale), and the dimensions subjective, physical, cognitive and psychological fatigue were distinguished. Physical behaviour was measured using an Actigraph GT3X+, and outcomes were categorized into the dimensions of activity amount, activity intensity, day pattern, and distribution of activities. Results: The physical behaviour dimensions were significantly associated with only the physical fatigue dimension (omnibus F-test: 3.96; df1 = 4, df2 = 207; p = 0.004). Additional analysis showed that the amount of activity (unstandardized beta coefficient (β) = -0.16; 95% confidence interval (CI) -0.27 to -0.04; p = 0.007), activity intensity (β = -0.18; 95% CI -0.31 to -0.06; p = 0.004) and day pattern of activity (β = -0.17; 95% CI, -0.28 to -0.06; p = 0.002) were the physical behaviour dimensions that were significantly associated with physical fatigue. Conclusion: Physical behaviour is weakly associated with physical fatigue and is not associated with other dimensions of fatigue