Evidence map›Paper›PMID 34166628›Full record

ArticleJournal of the American Medical Directors Association2021

Assessing Additional Characteristics of Muscle Function With Digital Handgrip Dynamometry and Accelerometry: Framework for a Novel Handgrip Strength Protocol.

Ryan McGrath, Grant R Tomkinson, Brian C Clark, Peggy M Cawthon, Matteo Cesari, Soham Al Snih, Donald A Jurivich, Kyle J Hackney

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of the American Medical Directors Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.5field-weighted citation impact, top 6% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 34 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Prevalence and Trends of Handgrip Strength Asymmetry in the United States.Advances in geriatric medicine and research · 2023
    Article
  15. Article
  16. Article
  17. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 8 institutions in 3 countries.

Ryan McGrathDepartment of Health, Nutrition, and Exercise Sciences, North Dakota State University, Fargo, ND, USA; Fargo VA Healthcare System, Fargo, ND, USA. Electronic address: ryan.mcgrath@ndsu.edu.
Grant R TomkinsonDepartment of Education, Health and Behavior Studies, University of North Dakota, Grand Forks, ND, USA; Alliance for Research in Exercise, Nutrition and Activity (ARENA), School of Health Sciences, University of South Australia, Adelaide, Australia.
Brian C ClarkOhio Musculoskeletal and Neurological Institute, Ohio University, Athens, OH, USA; Department of Biomedical Sciences, Ohio University, Athens, OH, USA; Department of Geriatric Medicine, Ohio University, Athens, OH, USA.
Peggy M CawthonCalifornia Pacific Medical Center Research Institute, San Francisco Coordinating Center, San Francisco, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA.
Matteo CesariGeriatric Unit, IRCCS Istituti Clinici Scientifici Maugeri, Milano, Italy; Department of Clinical Sciences and Community Health, Università di Milano, Milano, Italy.
Soham Al SnihDivision of Rehabilitation Sciences, University of Texas Medical Branch, Galveston, TX, USA.
Donald A JurivichDepartment of Geriatrics, University of North Dakota, Grand Forks, ND, USA.
Kyle J HackneyDepartment of Health, Nutrition, and Exercise Sciences, North Dakota State University, Fargo, ND, USA.
California Pacific Medical Center · USFargo VA Health Care System · USIstituti Clinici Scientifici Maugeri · ITNorth Dakota State University · USOhio University · USThe University of Texas Medical Branch at Galveston · USUniversity of North Dakota · USUniversity of South Australia · AU

Funding

Neural mechanisms of dynapeniaR01AG044424 · NIA · OHIO UNIVERSITY ATHENS · PI CLARK, BRIAN C · 2014 to 2018
$1.4M
NIA NIH HHS R01 AG044424
6 · The paper itself

Abstract

Maximal handgrip strength (HGS) is a convenient and reliable, but incomplete, assessment of muscle function. Although low HGS is a powerful predictor of poor health, several limitations to maximal HGS exist. The predictive value of HGS is restricted because low HGS is associated with a wide range of unspecified health conditions, and other characteristics of muscle function aside from strength capacity are not evaluated. Current HGS protocol guidelines emphasize the ascertainment of maximal force, which is only a single muscle function characteristic. Muscle function is intrinsically multivariable, and assessing other attributes in addition to strength capacity will improve screenings for age-related disabilities and diseases. Digital handgrip dynamometers and accelerometers provide unique opportunities to examine several aspects of muscle function beyond strength capacity, while also maintaining procedural ease. Specifically, digital handgrip dynamometry and accelerometry can assess the rate of force development, submaximal force steadiness, fatigability, and task-specific tremoring. Moreover, HGS protocols can be easily refined to include an examination of strength asymmetry and bilateral strength. Therefore, evaluating muscle function with new HGS technologies and protocols may provide a more comprehensive assessment of muscle function beyond maximal strength, without sacrificing feasibility. This Special Article introduces a novel framework for assessing multiple attributes of muscle function with digital handgrip dynamometry, accelerometry, and refinements to current HGS protocols. Such framework may aid in the discovery of measures that better predict and explain age-related disability, biological aging, and the effects of comorbid diseases that are amenable to interventions. These additional HGS measures may also contribute to our understanding of concepts such as resilience. Using sophisticated HGS technologies that are currently available and modernizing protocols for developing a new muscle function assessment may help transform clinical practice by enhancing screenings that will better identify the onset and progression of the disabling process.

Indexed as

AgingHand StrengthAccelerometryHumansMusclesMuscle StrengthAginggeriatric assessmentmuscle strengthmuscle weaknessphysical functional performancesarcopenia

Identifiers

PMID34166628
PMCPMC8557115
OpenAlexW3175133315

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.