Evidence map›Paper›PMID 40308521›Full record

ArticleVideo journal of sports medicine

Bridge-Enhanced Anterior Cruciate Ligament Restoration: Surgical Technique.

Elizabeth Bond, Kevin A Wu, Frederic Baker Mills, Ryan O'Donnell, Grant Cochran, Brian C Lau

Abstract read
In one paragraph

Article in Video journal of sports medicine. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Elizabeth BondDuke Sports Science Institute, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0002-1343-5658
Kevin A WuDuke Sports Science Institute, Durham, North Carolina, USA.
Frederic Baker MillsDuke Sports Science Institute, Durham, North Carolina, USA.
Ryan O'DonnellSt Lukes University Health Network, Bethlehem, Pennsylvania, USA.
Grant CochranDuke Sports Science Institute, Durham, North Carolina, USA.
Brian C LauDuke Sports Science Institute, Durham, North Carolina, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Anterior cruciate ligament (ACL) repair has historically had poor outcomes and fell out of favor in the 1980s with the majority of surgeons opting to do an ACL reconstruction instead due to the high failure rate. The Bridge-Enhanced ACL Restoration or BEAR technique utilizes a de-cellularized, bovine-derived, type I collagen implant to aid in the ACL repair. The device is implanted to augment the healing of the ACL. Indications: The BEAR technique is indicated to augment ACL repair in cases of complete rupture where there is a residual tibial stump of sufficient length and good tissue quality. Results: In our experience to date, patients undergoing an ACL repair with BEAR recover range of motion quickly and have less quadriceps atrophy and less postoperative swelling than those undergoing ACL reconstruction requiring autograft harvest. We will continue to follow up our patient cohort to assess for re-rupture rate as they return to sport. Conclusion: The BEAR technique is a promising development that enables ACL repair as an alternative option to reconstruction. This article describes our approach including tips and tricks to successfully perform this procedure. Patient Consent Disclosure Statement: The author(s) attests that consent has been obtained from any patient(s) appearing in this publication. If the individual may be identifiable, the author(s) has included a statement of release or other written form.

Indexed as

ACL repairACL tearknee

Identifiers

PMID40308521
PMCPMC11752531

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.