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Record W4417234383 · doi:10.3390/jcm14248769

High Prevalence of Osteopenia and Osteoporosis in Total Hip and Total Knee Arthroplasty Patients and Effects of Anti-Resorptive Agents on Bone Health Optimization: A Systematic Review and Meta-Analysis

2025· article· en· W4417234383 on OpenAlexaffabout
Ronald Man Yeung Wong, Pui Yan Wong, Joon Kiong Lee, Aasis Unnanuntana, Tanawat Amphansap, Peter R. Ebeling, Jacqueline Close, Gustavo Duque, Sheung Wai Law, Wing‐Hoi Cheung

Bibliographic record

VenueJournal of Clinical Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsPeriprostheticOsteoporosisOsteoarthritisOsteopeniaMeta-analysisArthroplastyConfidence intervalCalcarRandomized controlled trial

Abstract

fetched live from OpenAlex

Background: Osteoarthritis is a leading cause of chronic pain and long-term disability in adults, which commonly affects the hip and knee joints. Joint arthroplasties are one of the management strategies for end-stage osteoarthritis. Periprosthetic fractures after hip or knee arthroplasties have mortality rates comparable to hip fractures. Recent studies assessed bone health optimization and the use of anti-osteoporotic agents in elective hip and knee arthroplasty surgeries. This systematic review and meta-analysis aimed to determine the prevalence of osteoporosis before surgery and the effect of bone health optimization on periprosthetic fractures and revisions. Methods: A systematic search was carried out on three databases, including PubMed, Embase, and Web of Science. The keywords used were (Revision or Periprosthetic fracture) AND (osteop*) and (Total Knee* or Total Hip*). Studies that included subjects aged >50 years with investigated outcomes were included in the review. The quality of selected randomized controlled trials was assessed using the Cochrane Collaboration tool, and non-randomized studies were assessed using the Newcastle–Ottawa Scale. The review was not registered with the International Prospective Register of Systematic Reviews (PROSPERO). Results: A total of 2482 records were identified. Twenty-three studies were included, and eighteen were used for quantitative analysis. Pooled overall prevalence of osteopenia in patients undergoing total knee arthroplasty (TKA)/total hip arthroplasty (THA) surgery was 42.87% (95% confidence interval (CI) 32.65 to 53.09). Pooled overall prevalence of osteoporosis in patients undergoing TKA/THA surgery was 23.99% (95% CI 15.72 to 32.26). The overall mean difference was in favor of anti-resorptive treatment on periprosthetic BMD of the medial calcar region (Gruen zone 7) after THA (12.16% (95% CI 8.78 to 15.53, p < 0.00001). Pooled odds ratio of periprosthetic fracture was 1.27 (95% CI 1.08 to 1.48, p = 0.003) in favor of the control group compared to bisphosphonate treatment. The pooled hazard ratio for all-cause revisions after TKA/THA for both osteopenia and osteoporotic patients was 0.26 (95% CI 0.13 to 0.51, p = 0.0001, I2 76%), signifying an improvement with bisphosphonates. Limitations of this study include the heterogeneity and retrospective nature of the included studies, with the average level of evidence subject to bias. Conclusions: There was a high prevalence of osteopenia/osteoporosis amongst patients undergoing total knee and total hip arthroplasty at 66.86%. Whilst bone health optimization with bisphosphonates may decrease the risk of revisions, the risk of periprosthetic fracture appeared to increase. Further research will be required to evaluate the effects of bone health optimization on the risk of periprosthetic fracture and revisions, and the effects of anabolic agents on periprosthetic fractures.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.019
Threshold uncertainty score0.054

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.024
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0190.032
Bibliometrics0.0070.008
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.360
Teacher spread0.328 · 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 source (direct Gemma or distilled Codex), 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 routes2
Has abstractyes

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