Evidence map›Paper›PMID 28979667›Full record

ReviewAmerican journal of translational research2017

Hormonal therapy in traumatic spinal cord injury.

Parker E Ludwig, Arun A Patil, Andrea J Chamczuk, Devendra K Agrawal

Abstract readReview
In one paragraph

Review in American journal of translational research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing 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

26 citing papers in PubMed.

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  19. Pathophysiology and Therapeutic Approaches for Spinal Cord Injury.International journal of molecular sciences · 2022
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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

4 authors.

Parker E LudwigDepartment of Clinical and Translational Science, Creighton University School of MedicineOmaha, NE, USA.
Arun A PatilDepartment of Clinical and Translational Science, Creighton University School of MedicineOmaha, NE, USA.
Andrea J ChamczukDepartment of Neurosurgery, Creighton University School of MedicineOmaha, NE, USA.
Devendra K AgrawalDepartment of Clinical and Translational Science, Creighton University School of MedicineOmaha, NE, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traumatic spinal cord injuries are major health problems and the underlying pathophysiological events and treatment strategies are currently under investigation. In this article, we critically reviewed the literature investigating the effects of estrogen, progesterone, and human chorionic gonadotropin on spinal cord damage or preservation following traumatic spinal cord injury. The National Library of Medicine database was searched through December 2016 using PubMed for articles addressing the clinical relevance of the hormones to improve neural structural integrity following traumatic spinal cord injury. It was found that each of these hormones, through varied mechanisms, could serve to reduce the harmful effects associated with spinal cord injury, and could aid in restoring some function to the injured spinal cord in the animal models. The most striking effects were seen in the reduction of inflammation commonly linked to injury of the central nervous system. The effects of human chorionic gonadotropin administration following spinal cord injury have received far less attention than those of either estrogen or progesterone, and additional inquiry could be of general benefit. In this article, we discussed the outstanding questions and suggested future directions for further investigation.

Indexed as

Estrogenhuman chorionic gonadotropininflammationprogesteroneremyelinationspinal cord injury

Identifiers

PMID28979667
PMCPMC5622236

What OpenQuestion holds

Textmetadata
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.