Evidence map›Paper›PMID 35990575›Full record

ArticleAnnals of joint2021

Preclinical Models of Elbow Injury and Pathology.

Michael A David, Aaron M Chamberlain, Spencer P Lake

Open access · diamondAbstract read
In one paragraph

Article in Annals of joint, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. 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 at 1 institution in 1 country.

Michael A DavidMechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO.
Aaron M ChamberlainOrthopaedic Surgery, Washington University in St. Louis, St. Louis, MO.
Spencer P LakeMechanical Engineering and Materials Science, Washington University in St. Louis, St. Louis, MO.
Washington University in St. Louis · US

Funding

Physical and Biological Treatment Strategies to Prevent Post-Traumatic Joint ContractureR01AR071444 · NIAMS · WASHINGTON UNIVERSITY · PI LAKE, SPENCER PARK · 2017 to 2022
$1.7M
NIAMS NIH HHS R01 AR071444
6 · The paper itself

Abstract

The human elbow is a complex joint that is essential for activities of daily living requiring the upper extremities; however, this complexity generates significant challenges when considering its response to injury and management of treatment. The current understanding of elbow injury and pathologies lags behind that of other joints and musculoskeletal tissues. Most research on the elbow joint is mainly focused on the late-stage disease states when irreversible damage has occurred. Consequentially, the specific contribution and relative time course of different elbow tissues in disease progression, as well as optimized approaches for treating such conditions, remains largely unknown. Given the challenge of studying elbow pathologies in humans, preclinical models can serve as ideal alternatives. However, a limited number of preclinical models exist to investigate elbow injury and pathology. This review highlights significant clinical elbow diseases and the preclinical models currently available to recapitulate these diseases, while also providing recommendations for the development of future preclinical models. Overall, this review will serve as a guide for preclinical models studying injuries and pathologies of the elbow, with the long-term goal of developing novel intervention strategies to improve the treatment of elbow diseases in human patients.

Indexed as

elbowinjurypathologypreclinical models

Identifiers

PMID35990575
PMCPMC9390859
OpenAlexW3025574725

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.