Real-Time Assessment of Fatigue in Patients With Multiple Sclerosis: How Does It Relate to Commonly Used Self-Report Fatigue Questionnaires?

Arch Phys Med Rehabil

Department of Rehabilitation Medicine, MOVE Research Institute, VU University Medical Center, Amsterdam, The Netherlands; Department of Neurorehabilitation, Reade Center of Rehabilitation and Rheumatology, Amsterdam, The Netherlands; Department of Physical Therapy and Human Movement Sciences, Northwestern University, Evanston, IL.

Published: November 2016

Objectives: (1) To assess real-time patterns of fatigue; (2) to assess the association between a real-time fatigue score and 3 commonly used questionnaires (Checklist Individual Strength [CIS] fatigue subscale, Modified Fatigue Impact Scale (MFIS), and Fatigue Severity Scale [FSS]); and (3) to establish factors that confound the association between the real-time fatigue score and the conventional fatigue questionnaires in patients with multiple sclerosis (MS).

Design: Cross-sectional study.

Setting: MS-specialized outpatient facility.

Participants: Ambulant patients with MS (N=165) experiencing severe self-reported fatigue.

Interventions: Not applicable.

Main Outcome Measures: A real-time fatigue score was assessed by sending participants 4 text messages on a particular day (How fatigued do you feel at this moment?; score range, 0-10). Latent class growth mixed modeling was used to determine diurnal patterns of fatigue. Regression analyses were used to assess the association between the mean real-time fatigue score and the CIS fatigue subscale, MFIS, and FSS. Significant associations were tested for candidate confounders (eg, disease severity, work status, sleepiness).

Results: Four significantly different fatigue profiles were identified by the real-time fatigue score, namely a stable high (n=79), increasing (n=57), stable low (n=16), and decreasing (n=13). The conventional questionnaires correlated poorly (r<.300) with the real-time fatigue score. The Epworth Sleepiness Scale significantly reduced the regression coefficient between the real-time fatigue score and conventional questionnaires, ranging from 15.4% to 35%.

Conclusions: Perceived fatigue showed 4 different diurnal patterns in patients with MS. Severity of sleepiness is an important confounder to take into account in the assessment of fatigue.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.apmr.2016.04.019DOI Listing

Publication Analysis

Top Keywords

real-time fatigue
20
fatigue score
20
fatigue
15
association real-time
12
patients multiple
8
multiple sclerosis
8
patterns fatigue
8
assess association
8
fatigue subscale
8
real-time
7

Similar Publications

Basic Science and Pathogenesis.

Alzheimers Dement

December 2024

Department of Neurosurgery, Clinical Neuroscience Research Center, Tulane University School of Medicine, New Orleans, LA, USA.

Background: SARS-CoV-2 causes a variety of neurological sequelae in COVID-19 survivors, including fatigue and cognitive dysfunction. Endothelial dysfunction is the unifying and central mechanism of COVID-19 illness and a major risk factor for vascular dementia (VaD). Endothelial dysfunction stems, in part, from an imbalance between nitric oxide (NO) generated by the endothelial nitric oxide synthase (eNOS) and reactive oxidant species produced by uncoupled-eNOS.

View Article and Find Full Text PDF

Objective: This study investigated the effects of electroacupuncture (EA) on muscle hardness changes induced by exercise, using ultrasound real-time tissue elastography (RTE).

Materials And Methods: Healthy men were included in 2 experiments. Experiment 1 had 11, and Experiment 2 had 10.

View Article and Find Full Text PDF

A Highly Stable Electrochemical Sensor Based on a Metal-Organic Framework/Reduced Graphene Oxide Composite for Monitoring the Ammonium in Sweat.

Biosensors (Basel)

December 2024

Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen 518107, China.

The demand for non-invasive, real-time health monitoring has driven advancements in wearable sensors for tracking biomarkers in sweat. Ammonium ions (NH) in sweat serve as indicators of metabolic function, muscle fatigue, and kidney health. Although current ion-selective all-solid-state printed sensors based on nanocomposites typically exhibit good sensitivity (~50 mV/log [NH]), low detection limits (LOD ranging from 10 to 10 M), and wide linearity ranges (from 10 to 10 M), few have reported the stability test results necessary for their integration into commercial products for future practical applications.

View Article and Find Full Text PDF

Constructing an electrochemical sensor with screen-printed electrodes incorporating TiCT-PDA-AgNPs for lactate detection in sweat.

Talanta

December 2024

Institute of Chemical Biology and Nanomedicine (ICBN), State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha, 410082, China. Electronic address:

Sweat lactate levels are closely related to an individual's physiological state and serve as critical indicators for assessing exercise intensity, muscle fatigue, and certain pathological conditions. Screen-printed electrodes (SPEs) offer a promising avenue for the development of low-cost, high-performance wearable devices for electrochemical sweat analysis. The material composition of SPEs significantly impacts their detection sensitivity and stability.

View Article and Find Full Text PDF

Data-driven natural computational psychophysiology in class.

Cogn Neurodyn

December 2024

School of Biomedical Engineering, Southern Medical University, Guangzhou, 510515 China.

The assessment of mental fatigue (MF) and attention span in educational and healthcare settings frequently relies on subjective scales or methods such as induced-task interruption tools. However, these approaches are deficient in real-time evaluation and dynamic definitions. To address this gap, this paper proposes a Continuous Quantitative Scale (CQS) that allows for the natural and real-time measurement of MF based on group-synchronized electroencephalogram (EEG) data.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!