Evidence map›Paper›PMID 40015472›Full record

ArticleJournal of shoulder and elbow surgery2025

Suture debris from high-tensile sutures contributes significantly to particle-induced tissue response in shoulder arthroplasty.

John P Scanaliato, Deborah J Hall, Songyun Liu, Gregory P Nicholson, Grant E Garrigues, Robin Pourzal

Abstract read
In one paragraph

Article in Journal of shoulder and elbow surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

John P ScanaliatoDepartment of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA; Midwest Orthopaedics at Rush, Chicago, IL, USA. Electronic address: john.scanaliato@gmail.com.
Deborah J HallDepartment of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA.
Songyun LiuDepartment of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA.
Gregory P NicholsonDepartment of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA; Midwest Orthopaedics at Rush, Chicago, IL, USA.
Grant E GarriguesDepartment of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA; Midwest Orthopaedics at Rush, Chicago, IL, USA.
Robin PourzalDepartment of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA.

Funding

Corrosion Induced Hip Implant Failure: Synergistic Interactions of Patient, Material, Design, and Surgical FactorsR56AR070181 · NIAMS · RUSH UNIVERSITY MEDICAL CENTER · PI LUNDBERG, HANNAH JEAN, MATHEW, MATHEW THOPPIL · 2022 to 2022
$677k
NIAMS NIH HHS R56 AR070181
6 · The paper itself

Abstract

HYPOTHESIS AND

backgroundPolyethylene (PE) wear debris has long been known to be important for the development of osteolysis and aseptic loosening in total joint replacements. Evaluation of shoulder hemiarthroplasty (HA) specimens provided a unique opportunity to study the histopathologic response when a PE-bearing surface was absent. We hypothesized that HAs would exhibit no significant inflammatory periprosthetic tissue response due to the absence of significant numbers of wear particles from the articulation.

methodsWe analyzed 13 shoulder HAs. The explants were examined for damage to the bearing surface and taper damage using a stereomicroscope. The periprosthetic tissues were examined histologically for wear debris and cellular biological response. Fourier Transform Infrared spectroscopy imaging and scanning electron microscopy with energy dispersive x-ray spectroscopy were used to characterize debris, if present, within tissue samples.

resultsThe average patient age at the time of implantation was 57.2 ± 7.3, and the average time in situ was 34.1 ± 29.4 months. The metal-bearing surface damage was primarily mild, with an average score of 1.5 ± 0.7. The same was true for taper damage on both humeral stem and head tapers, with average scores of 1.7 ± 0.5 and 1.7 ± 0.9, respectively. The histopathological analysis revealed the considerable presence of metal debris in 11 (91.7%), cement debris in 4 (33.3%), and suture debris in 11 (83.3%) cases. Scanning electron microscopy/energy dispersive x-ray spectroscopy revealed titanium alloy debris to be the most dominant type of metal particle present, while Fourier Transform Infrared spectroscopy imaging scans suggested polyester to be the most commonly occurring type of suture debris. Particles were mostly found within and around macrophages. The mean macrophage score was 3.1 ± 0.8, and the mean foreign-body giant cell score was 2.3 ± 1.1. There was, on average, no significant lymphocyte or neutrophil presence, except for a single septic case. DISCUSSION AND

conclusionThis surgically retrieved shoulder HA cohort exhibited a considerable macrophage and foreign-body giant cell response within the periprosthetic environment. Interestingly, given the low amount of damage to metallic surfaces and the absence of a PE bearing, the tissue response does not appear to be driven by wear particles from the metal-bearing surface or taper junctions but rather from suture and, to a much lesser degree, cement and metal debris. Overall, these findings highlight the potential impact that high-tensile suture material, frequently used in high quantities around shoulder arthroplasty, may have on the periprosthetic environment and identify these materials as a potential driver of osteolysis.

Indexed as

Arthroplasty, Replacement, ShoulderShoulder JointShoulder ProsthesisSuturesAgedFemaleHumansMaleMicroscopy, Electron, ScanningMiddle AgedPolyethyleneProsthesis FailureSpectroscopy, Fourier Transform InfraredPolyethylenearthroplastyfailedhemiarthroplastymacrophageosteolysisshoulderSuture debriswear debris

Identifiers

PMID40015472
PMCPMC12068988

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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.