Evidence map›Paper›PMID 23531014›Full record

ReviewAnnals of the New York Academy of Sciences2013

Accelerating locomotor recovery after incomplete spinal injury.

Brian K Hillen, James J Abbas, Ranu Jung

Abstract readReview
In one paragraph

Review in Annals of the New York Academy of Sciences, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Article
  11. Targeted, activity-dependent spinal stimulation produces long-lasting motor recovery in chronic cervical spinal cord injury.Proceedings of the National Academy of Sciences of the United States of America · 2015
    Article
  12. 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.

Brian K HillenDepartment of Biomedical Engineering, Florida International University, Miami, FL 33174, USA.
James J Abbas
Ranu Jung

Funding

CRCNS: Modeling Neuromusculoskeletal Alterations after Spinal Cord InjuryR01NS054282 · NINDS · ARIZONA STATE UNIVERSITY-TEMPE CAMPUS · PI JUNG, RANU · 2005 to 2008
$1.3M
NINDS NIH HHS R01 NS054282NINDS NIH HHS R01-NS054282
6 · The paper itself

Abstract

A traumatic spinal injury can destroy cells, irreparably damage axons, and trigger a cascade of biochemical responses that increase the extent of injury. Although damaged central nervous system axons do not regrow well naturally, the distributed nature of the nervous system and its capacity to adapt provide opportunities for recovery of function. It is apparent that activity-dependent plasticity plays a role in this recovery and that the endogenous response to injury heightens the capacity for recovery for at least several weeks postinjury. To restore locomotor function, researchers have investigated the use of treadmill-based training, robots, and electrical stimulation to tap into adaptive activity-dependent processes. The current challenge is to maximize the degree of functional recovery. This manuscript reviews the endogenous neural system response to injury, and reviews data and presents novel analyses of these from a rat model of contusion injury that demonstrates how a targeted intervention can accelerate recovery, presumably by engaging processes that underlie activity-dependent plasticity.

Indexed as

AccelerationAnimalsContusionsDisease Models, AnimalHumansLocomotionModels, BiologicalNerve RegenerationRatsRecovery of FunctionSpinal Cord InjuriesSpinal Injuries

Identifiers

PMID23531014
PMCPMC3616515

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.