Name: measuring the motor aspect of cancer-related fatigue using a handheld dynamometer
Uploaded: 2020-02-20T14:00:00
Description: Watch this Scientific Journal Video about Measuring the Motor Aspect of Cancer-Related Fatigue using a Handheld Dynamometer at JoVE.com

This study is fully supported by the Division of Intramural Research of the National Institute of Nursing Research of the NIH, Bethesda, Maryland.

The current study (NCT00852111) was approved by the Institutional Review Board (IRB) of the National Institutes of Health (NIH). Participants enrolled in this study were 18 years of age or older, diagnosed with non-metastatic prostate cancer with or without prior prostatectomy, and scheduled to receive external beam radiation therapy at the Radiation Oncology Clinic of the NIH Clinical Center. Potential participants were excluded if they had a progressive disease that could cause significant fatigue, had psychiatric dise...

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Here, we provide three different methods for measuring the physical dimension of CRF. Motor fatigue tests using handheld dynamometers are simple and easily adaptable for clinical use. Since many variations of the test exist in the literature, our goal was to provide standardized methods to administer these tests and decrease the need for extensive in-person trainings for clinicians.
Although the fatigue tests outlined in this study demonstrate good test-retest reliability7</s...

Cancer-related fatigue (CRF) is an prevalent and debilitating symptom that is reported by up to 80% of cancer patients1. The National Comprehensive Cancer Network (NCCN) defines CRF as a persistent sense of physical, emotional, and cognitive exhaustion1. The main differentiating characteristics of CRF are the disproportionality to recent activity and the inability of CRF to be relieved by rest1. As a result, CRF severely impacts patients&#39; participation in daily activities and their health-related quality of life1.
The current assessment of CRF relies primarily on self-report questionnaires2. As a result, symptom severity which is measured using self-reports is subject to recall and reporting biases and can be influenced by the specific questionnaire and cutoff scores used to assess CRF3. As a multidimensional construct, the physical dimension of CRF has been shown to correlate with daily activity changes and a need for daytime naps4, whereas the influence of CRF on physical functioning is less explored. To this date, CRF remains an underdiagnosed and undertreated symptom with no well-defined underlying mechanism or treatment option1. To better understand this debilitating condition, there is an increasing need to measure CRF and its dimensions objectively and quantitatively.
Physical fatigue refers to an inability to maintain the required force during sustained contractile activity5. The subsequent compromised daily functioning as a result of not being able to carry out daily tasks (e.g., carrying grocery bags, lifting and holding an object) greatly affects the health-related quality of life, especially in older adults, and contributes to future injuries6,7. Various tools have been developed to quantify physical impairment including physical performance tests, such as the 6 min walk test (6MWT) and sit-to-stand test (STS), as well as wearable physical activity monitors, such as actigraphy devices and fitness trackers8,9,10. Physical performance tests such as 6MWT and STS are easy to administer and do not require special equipment10. However, the reliability and success of such tests require clinician training and logistical requirements such as a 30 m corridor10. Wearable activity monitors allow for automated data collection and longitudinal symptom monitoring11. However, these activity monitors often need to be worn for multiple days, and patient compliance can be an issue11. In addition, the large amount of data collected using activity monitors can be challenging to process, making it difficult to derive clinically meaningful information11.
The handheld dynamometer, or instrumented handgrip device with computer-assisted data acquisition, is a portable apparatus that measures grip strength. Handheld dynamometry has been used to test motor fatigue and impairment in disease conditions that typically involve the motor system including motor neurons and muscular problems12. Recent work has demonstrated an association between self-reported subjective CRF scores and motor fatigue measured using a handgrip static fatigue test13. Handgrip fatigue tests are particularly suitable for clinical use due to their reliability and time efficiency, requiring a few minutes to complete14,15. Furthermore, handgrip fatigue tests can be pre-programed, ensuring data reproducibility7. Administering the handgrip test requires minimal training on the part of the test administrator and can be easily implemented in a clinical setting given a standardized protocol. Using self-reported fatigue questionnaires in conjunction with the handgrip fatigue test should provide additional tools for clinicians to screen, monitor, and manage fatigue symptoms in cancer patients.
The lack of standardized consensus methods has limited the adoption of the handgrip fatigue test in the clinics16. In this current work, we outline three different methods to use the handheld dynamometer to quantify motor fatigue objectively. The utility of each method should be tested in each cancer population to ensure it accurately distinguishes between fatigued and non-fatigued subjects. We also outline methods to calculate the fatigue index for each handgrip fatigue test. The goal of this work is to provide a comprehensive toolkit to supplement self-reported questionnaires and to standardize CRF physical performance measurement accurately and objectively.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Quantitative Muscle Assessment application (QMA)</td>
			<td>Aeverl Medical</td>
			<td>QMA 4.6</td>
			<td>Data acquisition software. NOTE: other brands/models can be used as long as the software records force over time.</td>
		</tr>
		<tr>
			<td>QMA distribution box</td>
			<td>Aeverl Medical</td>
			<td>DSTBX</td>
			<td>Software distribution box which connects the handgrip to the software.</td>
		</tr>
		<tr>
			<td>Baseline hand dynamometer with analog output</td>
			<td>Aeverl Medical</td>
			<td>BHG</td>
			<td>Instrumented handgrip device with computer assisted data acquisition. NOTE: other brands/models can be used as long as the instrument measures force over time</td>
		</tr>
	</tbody>
</table>

measuring the motor aspect of cancer-related fatigue using a handheld dynamometer

Cancer-related fatigue (CRF) is commonly reported by patients both during and after receiving treatment for cancer. Current CRF diagnoses rely on self-report questionnaires which are subject to report and recall biases. Objective measurements using a handheld dynamometer, or handgrip device, have been shown in recent studies to correlate significantly with subjective self-reported fatigue scores. However, variations of both the handgrip fatigue test and fatigue index calculations exist in the literature. The lack of standardized methods limits the utilization of the handgrip fatigue test in the clinical and research settings. In this study, we provide detailed methods for administering the physical fatigue test and calculating the fatigue index. These methods should supplement existing self-reported fatigue questionnaires and help clinicians assess fatigue symptom severity in an objective and quantitative manner.

Representative force (kg) versus time (s) traces are shown in Figure 1. During the static fatigue test, subjects typically reach maximal strength (Fmax) within 2&#8211;3 s23. Self-reported fatigue in subjects was measured based on previous studies3. The absence of Fmax (&#177;10% MVIC) within 3 s indicates insufficient effort23. To prevent this issue, verbal encouragement should be provided. Both su...

Watch this Scientific Journal Video about Measuring the Motor Aspect of Cancer-Related Fatigue using a Handheld Dynamometer at JoVE.com

Measuring the Motor Aspect of Cancer-Related Fatigue using a Handheld Dynamometer

Simple and accessible methods were developed to measure the motor aspect of cancer-related fatigue objectively and quantitatively. We describe, in detail, ways to administer the physical fatigue test using a simple handgrip device as well as methods to calculate fatigue indices.

Cancer-related fatigue (CRF) is commonly reported by patients both during and after receiving treatment for cancer. Current CRF diagnoses rely on ...

Cancer related fatigue severely impacts patients health related quality of life. Currently, researchers and clinicians rely on self reported questionnaires to diagnose this debilitating symptom. Methods outlined in this work help to standardize physical fatigue measurement in an accurate and objective manner.This technique is fairly simple and easily adaptable for clinical use. Protocols provided in the current work will decrease the need for in person trainings for clinicians. Demonstrating these procedures will be Jeniece Regan, Sarah Alshawi Josephine Liwang and Jamell Joseph, postback fellows from our lab.In a quiet room, set up a chair with armrests. Turn on the handheld dynamometer. When prompted, press the button to accept the calibration prompt.Ensure the devices resting on a flat surface during calibration. The handle device is sensitive to mechanical force. It is important to handle the device with care.Sit the subject in an upright position, with their feet in full contact with the floor. And hips as far back as the chair supports. Ensure the subject's hip and knee angles are close to 90 degrees.And shoulders are a neutral abduction adduction and neutrally rotated. Ensure the subject's elbow is flexed at 90 degrees and the wrist is unsupported. Instruct the subject to grasp the dynamometer with the dorsal Intermediate phalanges facing forward.Adjust the grip position to the subjects hand size. And then record the grip position. It is important to remember to ensure the proper seating and grip position throughout the tests.Using a standardized script for each subject, explained that for this test, the subject will squeeze as hard as they can for five seconds. It is important to ensure that subjects maintain their maximal voluntary isometric contraction or MVIC during the static fatigue test. Count down three, two, one, Go.On Go, start the program by clicking the Go button on the dynamometer.Repeat the MVIC test twice more for a total of three trials with 30-second rest between trials. Using a standardized script, instruct the subject to exert full effort for the whole 35 seconds of this test. Count down three, two, one, Go.On Go, start the program by clicking the Go button on the dynamometer.For 35 seconds, use a standardized script to encourage the subject to squeeze hard. End the test after 35 seconds. Prepare a transparency overlay for the dynamometer screen.Draw a horizontal line on the transparency that represents the target value, 50%of the subjects MVIC. Draw a second line 10%below the target value. Ensure the subject can see the screen and the 50%MVIC line.Instruct the subject to maintain the target value for as long as possible. Count down three two, one, Go.On Go, start the program by clicking the Go button on the dynamometer. When the force declines by 10%from the target value for more than five seconds, stop the test.Set the metronome to one beat per second. Then start the metronome. Instruct the subject that they will be performing a maximal squeeze every second for a duration of 30 seconds.In time with the metronome, count down three, two, one Go.On Go, start the program by clicking the Go button on the dynamometer. Stop the test after 30 seconds. This study provides three different methods for measuring cancer related fatigue.The dynamometer data can be used to calculate fatigue indices. Static fatigue, index version one represents the difference between the actual force generated and the hypothetical force in the absence of fatigue. Version two represents the decline in force from the first five seconds to the last five seconds.While both versions detect the differences between fatigued and non fatigued subjects, version one resulted in better discrimination and a higher test to retest reliability. Version one is recommended for measuring fatigue in patients with Cancer. For the sub maximal fatigue index, performance is calculated as the total work.Non fatigued subjects exhibited higher endurance and total work performed than fatigued subjects. While this test is typically not used to calculate voter fatigue ability, it is included because it is often used to induce fatigue and it better approximates daily tasks. The dynamic fatigue index represents the decline in the intermittent contractile force from the first five seconds to the last five seconds.It also capture the difference between fatigued and non fatigued subjects. But the difficulty of it adhering to a consistent rhythm, introduces variability. Furthermore, while it has good test retest reliability, in prior studies, it did not demonstrate sufficient discriminative power.Following this procedure, subjective fatigue can be measured using a self report questionnaire. The contribution of physical fatigue to the overall sense of tiredness can be further investigated using this procedure. Furthermore, physical fatigue data can be collected over time to examine longitudinal treatment effects.Clinicians will be be able to objectively measure cancer related fatigue. In addition, researchers will be able to explore possible pathogenic mechanisms that underlies debilitating symptom.

Research

JoVE Journal

Cancer Research

Ultrasonographic Evaluation of Breast Cancer-related Lymphedema

Lymphedema is one of the most common complications after breast cancer surgery. There are many diagnostic tools for lymphedema, but no standard method yet ...

A Mouse Model of Fatigue Induced by Peripheral Irradiation

Cancer-related fatigue (CRF) is a distressing and costly condition that often affects patients receiving cancer treatments, including radiation therapy. ...

A Comprehensive Procedure to Evaluate the In Vitro Performance of the Putative Hemangioblastoma Neovascularization Using the Spheroid Sprouting Assay

A Comprehensive Procedure to Evaluate the In Vitro Performance of the Putative Hemangioblastoma Neovascularization Using the Spheroid Sprouting Assay

The inactivation of the von Hippel-Lindau (VHL) tumor suppressor gene plays a crucial role in the development of hemangioblastomas (HBs) within the human ...

Modeling Osteosarcoma Using Li-Fraumeni Syndrome Patient-derived Induced Pluripotent Stem Cells

Li-Fraumeni syndrome (LFS) is an autosomal dominant hereditary cancer disorder. Patients with LFS are predisposed to a various type of tumors, including ...

Evaluating the Role of Mitochondrial Function in Cancer-related Fatigue

Fatigue is a common and debilitating condition that affects most cancer patients. To date, fatigue remains poorly characterized with no diagnostic test to ...

Measuring Bone Remodeling and Recreating the Tumor-Bone Microenvironment Using Calvaria Co-culture and Histomorphometry

Bone is a connective tissue constituted of osteoblasts, osteocytes, and osteoclasts and a mineralized extracellular matrix, which gives it its strength ...

Characterize Disease-related Mutants of RAF Family Kinases by Using a Set of Practical and Feasible Methods

The rapidly accelerated fibrosarcoma (RAF) family kinases play a central role in cell biology and their dysfunction leads to cancers and developmental ...

In Vitro Establishment of a Genetically Engineered Murine Head and Neck Cancer Cell Line using an Adeno-Associated Virus-Cas9 System

The use of primary normal epithelial cells makes it possible to reproducibly induce genomic alterations required for cellular transformation by ...

Monitoring eIF4F Assembly by Measuring eIF4E-eIF4G Interaction in Live Cells

Formation of the eIF4F complex has been shown to be the key downstream node for the convergence of signalling pathways that often undergo&#160;oncogenic ...

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Many cancers are characterized by chromosomal translocations which result in the expression of oncogenic fusion transcription factors. Typically, these ...