Evidence map›Paper›PMID 39640878›Full record

ReviewJournal of orthopaedics2025

A systematic review of surgical outcomes of ulnar collateral ligament rupture in the elbow treated with various techniques.

Ben Nagy, Jacob Alexander, Jiayong Liu

Abstract readReview
In one paragraph

Review in Journal of orthopaedics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Ben NagyUniversity of Toledo Medical Center, Department of Orthopaedic Surgery, USA.
Jacob AlexanderUniversity of Toledo Medical Center, Department of Orthopaedic Surgery, USA.
Jiayong LiuUniversity of Toledo Medical Center, Department of Orthopaedic Surgery, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

When comparing different techniques, there is limited evidence on return-to-play rates and complication rates following ulnar collateral ligament (UCL) surgery. This systematic review aims to assess the outcomes of various UCL surgery techniques. A systematic search of PubMed, Google Scholar, and EMBASE up to May 2024 was performed. Outcome measures included return-to-play rates and postoperative complication rates from relevant articles. Data was analyzed using a chi-square analysis to determine statistical significance. Internal bracing repair demonstrated a return-to-play rate of 93.2 % at the same or higher level of competition, outperforming the rates of 80.5 % for the modified Jobe technique and 82.3 % for docking reconstruction. The docking technique exhibited a minor postoperative complication rate of 2.35 %, significantly lower than the rates of 8.59 % and 8.08 % for modified Jobe and internal bracing techniques, respectively. The modified Jobe technique had a major postoperative complication rate of 1.16 %, while internal bracing had a rate of 3.01 %. The use of internal bracing for anchor repairs demonstrated a statistically significant higher return-to-play rate at the same or elevated levels of competition compared to the reconstruction techniques analyzed. Notably, the docking technique exhibited a significantly lower rate of minor postoperative complications when contrasted with both the modified Jobe and internal bracing methods. Furthermore, the modified Jobe technique was associated with a significantly reduced incidence of major postoperative complications compared to the internal bracing approach.

Indexed as

DockingModified jobeOutcomesRepair with internal bracingUlnar collateral ligament (UCL) rupture

Identifiers

PMID39640878
PMCPMC11616627

What OpenQuestion holds

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Registered trials

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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.