Evidence map›Paper›PMID 35845616›Full record

ArticleShoulder & elbow2022

Clinical outcomes and structural integrity rate of arthroscopic augmented rotator cuff repairs using extracellular porcine matrix patch.

Paolo Consigliere, Alessio Bernasconi, Richard Dimock, A Ali Narvani

Abstract read
In one paragraph

Article in Shoulder & elbow, 2022. 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
–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

3 citing papers in PubMed.

  1. Article
  2. Review
  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

4 authors.

Paolo ConsigliereWythenshawe Hospital, Manchester University NHS FT, Manchester UK.ORCID https://orcid.org/0000-0003-4282-1539
Alessio BernasconiDepartment of Public Health, University Federico II of Naples.
Richard DimockDepartment of Trauma and Orthopaedics, Ashford & St Peters NHS FT, Chertsey, UK.
A Ali NarvaniDepartment of Trauma and Orthopaedics, Ashford & St Peters NHS FT, Chertsey, UK.ORCID https://orcid.org/0000-0001-9000-4504

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Structural failure rate in rotator cuff repairs is still high. The purpose of the study is to assess the structural integrity of a series of augmented rotator cuff repairs with porcine matrix patch and report the functional outcomes. Methods: Between 2014 and 2017, 44 consecutive patients underwent arthroscopic double-row repair of medium to massive rotator cuff tears with extracellular porcine dermal matrix augmentation. At one-year follow-up, magnetic resonance imaging scan was performed to assess the integrity of the repair. Oxford Shoulder Score (OSS), Constant Score (CS) and Visual Analogue Scale pain score, together with range of motion were used to assess patients. Results: Patients mean age was 68 (53-82); mean follow-up was 17.2 (12-24) months. On magnetic resonance imaging scans, seven rotator cuff repair failures (15.9%) were observed: tear size was an independent predictor of re-rupture at one-year follow-up. Clinical scores showed a statistically significant improvement at three months and until final follow-up ( Conclusion: Observed structural failure rate of 15.9% is lower than those reported in the literature for standard rotator cuff repair of medium to massive tears in similar cohorts to ours. Extracellular matrix augmentation for rotator cuff repair was shown to be a safe and reliable support to the repairs and patients recovered good shoulder function.

Indexed as

augmented rotator cuff repairhealingpatchesRotator cuff repairtendon biologytendon biomechanics

Identifiers

PMID35845616
PMCPMC9284254

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.