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Record W4415243722 · doi:10.47176/mjiri.39.111

Functional Outcomes of Different Bearing Surfaces for Total Hip Arthroplasty: A Systematic Review and Meta-Analysis

2025· review· en· W4415243722 on OpenAlexaboutno aff
Amirhosein Sabaghian, Bahram Fadaee Dowlat, Seyyed Amir Yasin Ahmadi, Shayan Amiri

Bibliographic record

VenueMedical Journal of the Islamic Republic of Iran · 2025
Typereview
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsImplantBearing (navigation)Total hip arthroplastyTotal hip replacementBearing surfaceReduction (mathematics)

Abstract

fetched live from OpenAlex

Background: Total hip arthroplasty (THA) has changed significantly since its inception, with various bearing surfaces affecting clinical outcomes. This systematic review aimed to assess the functional results of various bearing surfaces in total hip arthroplasty using validated scoring systems. Methods: This systematic review was carried out in accordance with PRISMA guidelines, and the protocol was registered in PROSPERO under CRD42025634591. Studies were included based on predefined criteria for population, intervention type, and reported clinical outcomes. Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Harris Hip Score (HHS), and SF-12 were analyzed closely. Results: <0.001), suggesting better quality of life and improved functional outcomes. CoM showed slightly better WOMAC scores over MoM, but the difference was not statistically significant. The most common reason for revision was dislocation (36 cases), while osteolysis was the most common complication (43 cases). Conclusion: MoM implants demonstrated better quality of life and functional outcomes, but their use has declined due to safety concerns. Other implants may reduce complications related to metal ion release. These findings help surgeons choose THA implants by weighing benefits against long-term risks. Further research is necessary to refine implant selection criteria and long-term performance.

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.

How this classification was reachedexpand

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)0.003
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.696
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.063
GPT teacher head0.331
Teacher spread0.268 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueMedical Journal of the Islamic Republic of IranSame topicOrthopaedic implants and arthroplastyFrench-language works237,207