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Record W1141899667 · doi:10.1007/s11999-015-4526-0

Implant Design Variations in Reverse Total Shoulder Arthroplasty Influence the Required Deltoid Force and Resultant Joint Load

2015· article· en· W1141899667 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2015
Typearticle
Languageen
FieldMedicine
TopicShoulder Injury and Treatment
Canadian institutionsHand and Upper Limb ClinicWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMedicineArthroplastyDeltoid curveJoint (building)Joint arthroplastyShoulder jointShoulder ProsthesisArthroplasty replacementOrthopedic surgeryImplantOrthodonticsProsthesis designSurgeryPhysical therapyProsthesisStructural engineering

Abstract

fetched live from OpenAlex

BACKGROUND: Reverse total shoulder arthroplasty (RTSA) is widely used; however, the effects of RTSA geometric parameters on joint and muscle loading, which strongly influence implant survivorship and long-term function, are not well understood. By investigating these parameters, it should be possible to objectively optimize RTSA design and implantation technique. QUESTIONS/PURPOSES: The purposes of this study were to evaluate the effect of RTSA implant design parameters on (1) the deltoid muscle forces required to produce abduction, and (2) the magnitude of joint load and (3) the loading angle throughout this motion. We also sought to determine how these parameters interacted. METHODS: Seven cadaveric shoulders were tested using a muscle load-driven in vitro simulator to achieve repeatable motions. The effects of three implant parameters-humeral lateralization (0, 5, 10 mm), polyethylene thickness (3, 6, 9 mm), and glenosphere lateralization (0, 5, 10 mm)-were assessed for the three outcomes: deltoid muscle force required to produce abduction, magnitude of joint load, and joint loading angle throughout abduction. RESULTS: Increasing humeral lateralization decreased deltoid forces required for active abduction (0 mm: 68% ± 8% [95% CI, 60%-76% body weight (BW)]; 10 mm: 65% ± 8% [95% CI, 58%-72 % BW]; p = 0.022). Increasing glenosphere lateralization increased deltoid force (0 mm: 61% ± 8% [95% CI, 55%-68% BW]; 10 mm: 70% ± 11% [95% CI, 60%-81% BW]; p = 0.007) and joint loads (0 mm: 53% ± 8% [95% CI, 46%-61% BW]; 10 mm: 70% ± 10% [95% CI, 61%-79% BW]; p < 0.001). Increasing polyethylene cup thickness increased deltoid force (3 mm: 65% ± 8% [95% CI, 56%-73% BW]; 9 mm: 68% ± 8% [95% CI, 61%-75% BW]; p = 0.03) and joint load (3 mm: 60% ± 8% [95% CI, 53%-67% BW]; 9 mm: 64% ± 10% [95% CI, 56%-72% BW]; p = 0.034). CONCLUSIONS: Humeral lateralization was the only parameter that improved joint and muscle loading, whereas glenosphere lateralization resulted in increased loads. Humeral lateralization may be a useful implant parameter in countering some of the negative effects of glenosphere lateralization, but this should not be considered the sole solution for the negative effects of glenosphere lateralization. Overstuffing the articulation with progressively thicker humeral polyethylene inserts produced some adverse effects on deltoid muscle and joint loading. CLINICAL RELEVANCE: This systematic evaluation has determined that glenosphere lateralization produces marked negative effects on loading outcomes; however, the importance of avoiding scapular notching may outweigh these effects. Humeral lateralization's ability to decrease the effects of glenosphere lateralization was promising but further investigations are required to determine the effects of combined lateralization on functional outcomes including range of motion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.233
Threshold uncertainty score0.684

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.195
GPT teacher head0.439
Teacher spread0.243 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it