Evidence map›Paper›PMID 27825146›Full record

ReviewCells, tissues, organs2016

Regenerative and Rehabilitative Medicine: A Necessary Synergy for Functional Recovery from Volumetric Muscle Loss Injury.

Sarah M Greising, Christopher L Dearth, Benjamin T Corona

Abstract readReview
In one paragraph

Review in Cells, tissues, organs, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed
–field-weighted citation impact
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

40 citing papers in PubMed.

  1. Article
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  15. Article
  16. Article
  17. Tissue Engineered 3D Constructs for Volumetric Muscle Loss.Annals of biomedical engineering · 2024
    Review
  18. Review
  19. Review
  20. Extruded alginate tubes with myogenic potential.bioRxiv : the preprint server for biology · 2024
    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

3 authors.

Sarah M Greising
Christopher L Dearth
Benjamin T Corona

Funding

NSAIDs and the Role of COX2 in Biologic Scaffold-Mediated Tissue ReconstructionR03EB018889 · NIBIB · HENRY M. JACKSON FDN FOR THE ADV MIL/MED · PI DEARTH, CHRISTOPHER L · 2015 to 2018
$155k
NIBIB NIH HHS R03 EB018889
6 · The paper itself

Abstract

Volumetric muscle loss (VML) is a complex and heterogeneous problem due to significant traumatic or surgical loss of skeletal muscle tissue. The consequences of VML are substantial functional deficits in joint range of motion and skeletal muscle strength, resulting in life-long dysfunction and disability. Traditional physical medicine and rehabilitation paradigms do not address the magnitude of force loss due to VML and related musculoskeletal comorbidities. Recent advancements in regenerative medicine have set forth encouraging and emerging therapeutic options for VML injuries. There is significant potential that combined rehabilitative and regenerative therapies can restore limb and muscle function following VML injury in a synergistic manner. This review presents the current state of the VML field, spanning clinical and preclinical literature, with particular focus on rehabilitation and regenerative medicine in addition to their synergy. Moving forward, multidisciplinary collaboration between clinical and research fields is encouraged in order to continue to improve the treatment of VML injuries and specifically address the encompassing physiology, pathology, and specific needs of this patient population. This is a work of the US Government and is not subject to copyright protection in the USA. Foreign copyrights may apply. Published by S. Karger AG, Basel.

Indexed as

Recovery of FunctionRegenerative MedicineHumansMuscle, SkeletalMuscle StrengthMuscular DiseasesRegeneration

Identifiers

PMID27825146
PMCPMC5553044

What OpenQuestion holds

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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.