Mapping Translational Bottlenecks in Periprosthetic Osteolysis Research: A Bibliometric Correlation Analysis

Mapping Translational Bottlenecks in Periprosthetic Osteolysis Research: A Bibliometric Correlation Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Mapping Translational Bottlenecks in Periprosthetic Osteolysis Research: A Bibliometric Correlation Analysis Jifeng Jing, Shuo Cheng, Yu Wang, Shimin Hao, Souradeep Sahu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8617314/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Periprosthetic osteolysis (PPO) remains the leading cause of late-term failure in total joint arthroplasty. While bibliometric studies have mapped research trends, they have not systematically quantified the translational efficiency of different research themes toward reducing revision rates and prolonging implant survival. This study aimed to map the evolving research trends and identify translational bottlenecks in PPO research (2000–2025) by constructing a novel “clinical translational funnel” model, which quantifies the association strength between research themes and key clinical endpoints via an innovative keyword correlation analysis. Methods We retrieved 3,858 publications from the Web of Science Core Collection. VOSviewer and CiteSpace were used for co-occurrence, burst detection, timeline, and collaboration analyses. A novel keyword correlation strength calculation method was developed to categorize keywords into four translational tiers and quantify their associative strength with “revision” and “implant survival.” Results The analysis revealed a clear paradigm shift from basic pathology (2000–2010) to clinical risk management (2018–2025). Associative strength with “implant survival” attenuated sharply from the clinical/technical tier (e.g., “fixation”: strength = 35) to near-zero in molecular tiers. Key translational bottlenecks were identified, including the “titanium particle paradox” (high experimental use but low clinical relevance) and Western-centric collaboration patterns. Conclusion PPO management has transitioned toward a preventive, engineering-driven paradigm. Optimizing prosthetic fixation and wear-resistant materials represents the most efficient pathway to prolong implant survival. The proposed “translational funnel” model and keyword correlation method offer a data-driven framework for prioritizing clinically impactful research and reallocating resources to overcome identified bottlenecks. Periprosthetic osteolysis Bibliometric analysis Translational analytics Implant performance Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Introduction Total joint arthroplasty (TJA), particularly total hip arthroplasty (THA) and total knee arthroplasty (TKA), is the gold standard for reconstructing severe joint dysfunction and treating end-stage arthritis. Global TJA volume is surging: projections indicate US THA and TKA procedures will increase by 284% and 401%, respectively, by the 2040 [ 1 ]; German TKA volume is expected to reach 225,957 by 2050 [ 2 ]; and China’s annual growth rates for THA and TKA were 16.67% and 27.43%, respectively, between 2012 and 2019 [ 3 ]. Amid this surgical volume surge, periprosthetic osteolysis (PPO) and subsequent late-stage aseptic loosening (AL) have become increasingly prominent, emerging as leading causes of prosthetic failure and revision surgery [ 4 , 5 ]. US revision burdens for THA and TKA are projected to rise by 42% and 149%, respectively, by 2040, with revision surgery associated with higher costs [ 6 ], with revision surgery associated with higher costs [ 7 ] and suboptimal functional recovery [ 8 ]. Consequently, elucidating the pathological mechanisms underlying PPO and developing effective strategies to extend prosthesis longevity and reduce revision burden have become urgent research priorities in orthopedics. This challenge extends beyond hip and knee arthroplasty, emerging as a critical concern in other joint replacements, including the shoulder and ankle [ 9 – 11 ]. Against this backdrop, multidisciplinary research on PPO has witnessed exponential growth, yet a coherent knowledge framework remains underdeveloped [ 12 ]. While interdisciplinary investigations—such as wear particle-induced immune responses, mechanisms of imbalanced bone metabolism, and novel anti-osteolytic biomaterials—continue to generate innovative outcomes [ 13 , 14 ], research efforts remain fragmented and research foci evolve rapidly [ 15 ]. There is an urgent need for a comprehensive quantitative analysis of the field to map the research landscape and prioritize critical pathways for transformative breakthroughs [ 16 ]. Bibliometrics, grounded in mathematical and statistical methodologies, provides a rigorous framework for analyzing scholarly output and mapping the evolution of research fields. By quantifying multi-dimensional data—including publication volume, authorship networks, citation patterns, and keyword associations—it has become an indispensable tool for identifying emerging frontiers and structural dynamics within specialized disciplines [ 12 , 17 – 19 ]. Beyond descriptive mapping, bibliometrics can critically assess the academic influence of institutions and journals, informing strategic research resource allocation [ 20 – 22 ]. However, existing bibliometric studies on PPO have primarily focused on hotspots and collaboration networks [ 23 ]. They fail to quantitatively answer which research tiers (from molecular mechanisms to engineering solutions) can effectively translate into reducing revision rates and prolonging implant survival. This gap hinders evidence-based research resource allocation [ 24 ]. To address this, we developed a novel keyword correlation analysis and constructed a “clinical translational funnel” model to quantify theme-clinical endpoint association, identifying translational bottlenecks [ 25 ]. Materials and Methods Data Sources and Search Strategy A systematic search was conducted in the Web of Science Core Collection (SCI-EXPANDED and SSCI) on July 30, 2025, to identify PPO-related publications (2000–2025) [ 26 ]. Developed based on the PICO framework, the search strategy included core concepts ("periprosthetic osteolysis", "arthroplasty", "wear debris") and excluded non-relevant fields (e.g., dentistry, oncology, spinal surgery) via the NOT operator [ 27 ]. Detailed criteria are presented in Table 1 . The final query yielded 3,872 records, and 3,858 publications (3,598 research articles, 260 reviews) were included after rigorous manual screening. Table 1 Search Strategy in Web of Science Core Collection Step Query #1 TS=(("periprosthetic osteolysis" OR "PPO" OR "aseptic loosening" OR "wear debris" OR "metal ions") AND ("arthroplasty" OR "joint replacement" OR "hip replacement" OR "knee replacement")) #2 TS=("dental" OR "tumor" OR "infection" OR "spine" OR "spinal" OR "vertebral" OR "disc" OR "disk" OR "cervical" OR "lumbar") #3 WC=("Veterinary Sciences" OR "Oncology" OR "Dentistry") #4 PY=(2000–2025) AND DT=(Article OR Review) AND LA=(English) #5 DT=("Proceedings Paper" OR "Early Access") Final (#1 NOT #2 NOT #3) AND #4 NOT #5 Screening Process: The 3,858 publications that passed manual screening constituted the final dataset for all subsequent bibliometric analyses. Inclusion and Exclusion Criteria Inclusion Criteria Focus on the mechanisms, prevention, or treatment of periprosthetic osteolysis (PPO). Contain empirical data or be systematic reviews. Published between January 1, 2000, and July 14, 2025. Exclusion Criteria Irrelevant to the research theme: Studies on septic loosening, dental/spinal implants, or tumor metastasis-related bone loss; publications whose primary content does not address PPO mechanisms. Invalid study models: Animal studies investigating mechanisms without validation in human cells or tissues. Unavailable literature: Non-English publications; articles with inaccessible full text; unpublished preprints. Excluded document types: Non-research literature (e.g., conference abstracts, patents, commentaries, errata); duplicate records with incomplete data. Data Extraction Bibliometric attributes, content features, and keyword data (author keywords and Keywords Plus®) were extracted from all included publications. Co-citation networks and topic evolution were analyzed via VOSviewer 1.6.20 and CiteSpace 6.4.R1. [ 28 , 29 ]. Data Analysis Bibliometric data were organized and preprocessed using Microsoft Excel. Scientific knowledge mapping was performed using both VOSviewer and CiteSpace. Descriptive and Evolutionary Bibliometric Analysis VOSviewer was used to generate visualizations of keyword co-occurrence, journal publication distribution, and document co-citation. The H-index was incorporated to assess the academic influence of major research institutions [ 22 ]. CiteSpace was applied to perform co-citation analysis (identifying key literature with a betweenness centrality threshold of > 0.1), burst detection (implementing the Kleinberg algorithm with γ = 0.5 and a minimum duration of 2 years), cluster validation (using a homogeneity criterion of silhouette value > 0.7 and a structural significance criterion of modularity Q > 0.3), timeline and time slice analyses (2000–2025) to reveal evolutionary trajectories of research paradigms, as well as institutional co-occurrence and journal dual-map overlay analyses [ 25 ]. Translational Associative Strength Analysis ("Clinical Translational Funnel" Model) To evaluate the translational proximity of different research themes to clinical outcomes in PPO, a translational association analysis was developed based on direct keyword co-occurrence patterns. Clinical Endpoint Definitions Three clinically meaningful keywords were selected as anchor endpoints: revision (surgical failure), survival (long-term implant retention), and implant (technical application). Association Strength Calculation Direct co-occurrence counts between these anchor endpoints and all high-frequency keywords (occurrences ≥ 50) were extracted from the bibliometric co-occurrence matrix. Association strength was quantified as raw co-occurrence counts and normalized by keyword frequency for comparative analysis. Translational Tier Classification Based on the PPO pathological cascade, keywords were categorized into four translational tiers: Clinical/Technical Tier: Direct clinical interventions (e.g., fixation, prosthesis design); Wear/Materials Tier: Problem manifestations and solutions (e.g., polyethylene wear, material properties); Pathological/Cellular Tier: Biological responses (e.g., inflammation, osteoclast activation); Molecular/Model Tier: Basic mechanisms and experimental tools (e.g., NF- κB , in vitro models). Quantitative outcomes of this classification are presented in the Results (Table 1 ). Outcome Metrics For each tier, we calculated: (a) mean association strength with revision and survival endpoints, (b) translational efficiency ratio (clinical associations/total occurrences), and (c) identified "translational bridges"—keywords strongly linked to both clinical endpoints (co-occurrence > 5 with each endpoint). Detailed computational procedures and validation methods are provided in Supplemental Methods S1. Results Research Landscape of Periprosthetic Osteolysis This study conducted a systematic bibliometric analysis of literature related to PPO between 2000 and 2025 based on the Web of Science Core Collection database (SCI-EXPANDED and SSCI). Through a rigorous screening process (excluding 10 irrelevant articles and 4 duplicate records), a total of 3,858 eligible publications were ultimately included, comprising 3,598 research articles and 260 reviews. Annual Publication Trends (Fig. 1 ): After a steady phase (2000–2004, avg. 93 articles/year), PPO-related publications surged 35.2% in 2005 (142 articles) and grew rapidly through 2013, peaking temporarily at 206 articles (5.34% of total). An adjustment period followed (2014–2016, avg. 161.6 articles/year), succeeded by sustained growth until 2020’s historical high of 210 articles (5.44% of total). From 2021 to 2024, the annual output averaged 178.7 articles. Note: 2025 data (95 articles) is undercounted as database coverage only extends to July. Citation analysis (Fig. 2 ) indicated that the total number of citations reached 107,765, of which 91,502 were non-self-citations; the average number of citations per article was 27.94, and the H-index was 117, reflecting strong academic influence and potential clinical value of the field. Distribution of research areas (Fig. 3 , Table 2) revealed that the publications spanned 90 distinct disciplines. Orthopaedics (65.44%), Surgery (27.29%), and Biomedical Engineering (15.06%) constituted the core clusters directly related to clinical practice. Biomaterials Science (10.75%), Sport Sciences (4.92%), and Materials Science (2.54%) underpinned interdisciplinary clinical innovation. The sum of the top five categories exceeded 100% (123.5%), reflecting the interdisciplinary nature of the field, as articles are frequently indexed under multiple subject headings. (Table 2). Top 10 Web of Science Research Categories in Periprosthetic Osteolysis Publications (2000–2025). • Web of Science Categories Record Count % of 3,858 Orthopedics 2525 65.448 Surgery 1053 27.294 Engineering Biomedical 581 15.06 Materials Science Biomaterials 415 10.757 Sport Sciences 190 4.925 Materials Science Multidisciplinary 98 2.54 Medicine General Internal 88 2.281 Rheumatology 87 2.255 Medicine Research Experimental 75 1.944 Pharmacology Pharmacy 66 1.711 Note : a. Data source: Web of Science Core Collection (Total publications: 3,858); b. Since a single publication can be assigned to multiple research areas, the sum of research area counts exceeds the total number of publications (hence the sum of percentages > 100%); c. Retrieval date: July 14, 2025. Journal Distribution and Interdisciplinary Characteristics PPO research exhibited a characteristic "clinical-materials" dual-track distribution pattern (Fig. 4 ): leading orthopaedic journals (e.g., Journal of Bone and Joint Surgery, Clinical Orthopaedics and Related Research) focused on optimizing prosthetic revision techniques and controlling complications; specialized materials science journals (e.g., Acta Biomaterialia, Journal of Biomedical Materials Research Part A) concentrated on molecular mechanisms such as wear particle-induced osteoclast activation that underpin clinical material selection; cross-disciplinary platforms (e.g., Scientific Reports, PLOS ONE) facilitated translational research by enabling knowledge fusion across diverse fields. Research Hotspots and Theme Evolution Keyword Co-occurrence and Clustering Bibliometric analysis of PPO-related keywords was performed, constructing a co-occurrence network from 90 high-frequency terms (occurrence ≥ 50) with a density of 0.47 and modularity of 0.81. VOSviewer analysis identified five major clusters (Fig. 5 ): the red cluster (Clinical Outcomes) centered on total hip arthroplasty (445 occurrences) and revision (407 occurrences), with exceptionally high total link strength for follow-up (649 occurrences, TLS = 3069) and implant survival (212 occurrences, TLS = 1047), emphasizing long-term outcome assessment and failure management in clinical practice; the green cluster (Biological Mechanisms of Osteolysis) was anchored by osteolysis (577 occurrences, TLS = 2862) and aseptic loosening (412 occurrences, TLS = 1821), directly linking key nodes such as wear debris (379 occurrences, TLS = 1771), macrophages (141 occurrences), and NF-κB (70 occurrences, normalized citation value = 1.62), thereby delineating the central "wear debris → immune inflammation → osteolysis" pathway; the blue cluster (Material Wear) focused on prosthesis materials and wear behavior, built around wear (434 occurrences, TLS = 1995) and arthroplasty (899 occurrences, TLS = 3543), highlighting concerns regarding specific implants through strong co-occurrence among metal-on-metal implants (166 occurrences), cobalt (167 occurrences), and chromium (128 occurrences); the purple cluster (Prosthesis Components and Performance) revolved around component design and in vivo performance, with core terms including acetabular component (99 occurrences), femoral head (75 occurrences), and polyethylene wear (155 occurrences), reflecting a research emphasis on wear and functional integrity at the component level that directly impacts surgical planning. Complementary analysis via CiteSpace (Fig. 6 ) revealed five clinical-thematic dimensions: #0 Osteolytic Mechanisms (osteolysis), #1 Wear Mechanisms (corrosion), #2 Debris Types (polyethylene/titanium particles), #3 THA-MoM (acetabular component), and #4 TKA-PE (highly cross-linked polyethylene). These clusters collectively delineated a cascading pathway: "prosthesis design → wear → debris release → osteolysis → clinical optimization", with cross-validation by dual analytical tools consistently confirming the central role of wear debris within this pathological cascade, providing a clinical decision-making framework. Keyword Burst and Timeline Analysis Keyword burst detection revealed the dynamic evolution of research hotspots in PPO, clearly outlining three distinct phases (Fig. 7 ): Early Phase (2000–2010): Research efforts focused primarily on the core pathological initiation of the condition. Wear debris (strength = 24.77) and its associated bone resorption (strength = 10.08) emerged as the most prominent burst keywords. Investigations during this period successfully established the fundamental pathological framework of "wear debris → inflammatory response → osteolysis" [ 30 ], and delved into the physical characteristics and biological effects of prostheses (strength = 23.57) and polyethylene particles (strength = 9.4) [ 13 ], laying a theoretical foundation for subsequent clinical research; Middle Phase (2011–2017): The research frontier underwent a noticeable transition, shifting from downstream biological effects to upstream engineering solutions. The emergence of bearings (strength = 9.8) signaled a reorientation toward reducing wear generation through interface design and material innovation. Concurrently, in-depth studies on specific components such as femoral components (strength = 14.39) and fixation techniques like cement (strength = 13.03) indicated a progression from macroscopic pathological phenomena toward engineered details involving prosthetic micro-design, material properties, and fixation methodologies that directly improve clinical outcomes; Recent Phase (2018–2025): Research hotspots exhibited a robust trend toward clinical translation, with the strongest burst keywords all pointing to clinical applications and decision support. Outcomes (strength = 36.2) and risk management (strength = 25.81) became central themes, reflecting a pressing need for personalized prognostic evaluation and precise intervention. Aseptic loosening (strength = 30.89) received considerable attention as a critical clinical endpoint event, with related revision strategies (strength = 18.49) and enhancements in survivorship (strength = 11.47) forming major research topics. Timeline analysis further revealed (Fig. 8 ): wear debris was identified as the core etiological agent between 2000 and 2008; in-depth exploration of specific particle toxicity and signaling pathways and advancement of polyethylene material modification occurred between 2009 and 2016; since 2017, research has focused on clinical issues such as revision surgery, bone defect management, and risk factors, strengthening research related to knee arthroplasty to fill clinical research gaps. Translational Landscape Analysis: The "Clinical Translational Funnel" Building upon the thematic clusters and evolution identified above, a translational association analysis was conducted to quantitatively diagnose the proximity of diverse research themes to ultimate clinical goals. The results, encapsulated in the "Clinical Translational Funnel" model (Table 3 ), revealed a pronounced hierarchical structure in the research ecosystem. A marked gradient of clinical relevance was observed across four predefined translational tiers: the Clinical/Technical tier (fixation, THA, TKA, design) exhibited the strongest association with revision (mean association strength 33.2) and survival (10.4); the Wear/Materials tier (osteolysis, aseptic loosening, polyethylene wear) was next (revision 16.8, survival 6.1); the Pathological/Cellular tier (inflammation, bone loss, macrophages) and Molecular/Model tier ( NF-κB, in vitro, cytokines ) showed weak associations. A key finding was the identification of specific "translational bridges" (Metal-on-Metal, Polyethylene Wear) with strong association to revision and survival (strength = 16 each), anchoring translational efforts. A typical translational bottleneck was observed: titanium particles (a dominant experimental model, 71 occurrences) had minimal clinical relevance (strength = 1), while titanium as an engineering material retained survival association (strength = 6). This reflects that some basic research lacks progression to clinically actionable solutions (e.g., material modification, implant design). Finally, the data underscored the superior translational efficiency of preventive engineering interventions. The preventive material innovation Cross-linked Polyethylene demonstrated clear dual associations (revision = 12, survival = 4) [ 31 , 32 ], far exceeding the impact of targeting downstream molecular pathways like NF-κB [ 33 ]. Consequently, optimizing prosthesis design and surgical fixation techniques—themes with the strongest clinical linkages—emerged as the most evidence-supported strategy for extending implant longevity in clinical practice. Table 3 Attenuation of Clinical Relevance Across the Translational Funnel: Tier-Level Summary Translational Tier Representative Keywords No. Keywords Revision Assoc. Survival Assoc. I. Clinical/Technical Fixation, THA, TKA, Design 23 33.2 (2–69) 10.4 (0–38) II. Wear and Materials Osteolysis, Aseptic Loosening, Polyethylene Wear 25 16.8 (1–73) 6.1 (0–27) III. Pathological/Cellular Inflammation, Bone Loss, Macrophages 11 6.5 (1–17) 2.7 (0–10) IV. Molecular/Model NF-κB, In-vitro, Cytokines 10 1.1 (0–3) 0.5 (0–3) Key Translational Bridges Metal-on-Metal, Polyethylene Wear 2 16.0 9.5 Abbreviations: Assoc., association; THA, total hip arthroplasty; TKA, total knee arthroplasty. Data presentation: Values are presented as mean association strength (range). Calculation: The mean association strength for each tier was calculated by averaging the direct co-occurrence counts of all keywords within that tier with the anchor keywords “revision” or “implant survival”. The complete dataset is available in Supplementary Table S1. Range: Parentheses indicate the minimum and maximum association strength observed among keywords in that tier. Key Translational Bridges: The row “Metal-on-Metal, Polyethylene Wear” highlights keywords with exceptionally high mean association to both endpoints within the Wear/Materials tier, presented separately to underscore their translational pivot role. Keyword Count: Refers to the count of high-frequency keywords (total occurrences ≥50) classified into each tier. Knowledge Base and Interdisciplinary Knowledge Flow Document co-citation analysis delineated three phases in the knowledge evolution of PPO research: mechanical wear mechanism research represented by Gruen et al. [34] (laying the foundation for implant design) → immune-inflammatory axis research on particle-induced osteolysis represented by Green et al. [35] and Urban et al. [36] → standardized revision technology research represented by Kurtz et al. [37] (directly guiding clinical practice). Dual-map overlay analysis revealed three major interdisciplinary citation trajectories in PPO research (Figure 9) : the penetration of physics/materials/chemistry into biomechanics and molecular biology, providing a foundation for prosthetic material and interface design; high internal specialization of knowledge in molecular biology/immunology, which, while taking genetics as the core theoretical basis, has limited citation flow to application fields; clinical medicine, as the ultimate integrator, converges knowledge from applied clinical fields such as neurology/sports medicine/ophtalmology, integrating molecular biology (disease mechanisms), materials science (biomaterials), and sports rehabilitation (rehabilitation programs) to solve specific clinical problems. Discussion Quantitative Roadmap for Clinical Translation: The "Clinical Translational Funnel" The core innovation is the novel keyword correlation analysis, complementing traditional bibliometrics’ deficiency in translational evaluation [24]. It quantifies theme-clinical endpoint association, enabling objective judgment of clinically valuable research directions. Our results identified a major translational bottleneck: basic mechanism research has weak clinical relevance, while clinical engineering and wear-resistant material research strongly correlate with prosthesis survival [33]. This provides clear guidance for resource allocation. Notably, this method is based on existing bibliometric tool data, highly replicable and promotable. It can be applied to other medical fields, addressing the common “basic-clinical translation inefficiency” problem [38]. Research Paradigm Evolution: A Systematic Response to Translational Attenuation The 25-year paradigm shift in PPO research (basic pathology → engineering optimization → clinical management) represents a collective response to translational attenuation. The establishment of the early pathological framework laid the foundation for subsequent research, but the limitations of downstream drug intervention drove research to shift toward wear source control. The recent focus on clinical outcomes and risk assessment highlights the comprehensive alignment of research with clinical needs. This evolution indicates that the synergy between advanced materials and precise surgical techniques is key to PPO prevention and control, and the impact of the biomechanical environment on long-term implant survival emphasizes the importance of individualized engineering. Interdisciplinary Translational Gaps and Global Collaboration Imbalances "Silos" between disciplines are important sources of translational bottlenecks. Insufficient knowledge diffusion between materials science and clinical orthopaedics hinders the translation of emerging concepts such as immunomodulatory biomaterials into clinical applications. The core-periphery structure of global collaboration further exacerbates this problem: Western core institutions dominate the research agenda, potentially neglecting the specific clinical needs of regions such as Asia. Future efforts should establish interdisciplinary collaboration platforms and equitable global research alliances, integrating diverse clinical data to enhance the generalizability of research. Potential Limitations This study has certain limitations. First, the literature was only retrieved from the Web of Science Core Collection, which may have missed relevant research from other databases; second, keyword co-occurrence analysis relies on keywords annotated in the database, which may have subjective biases; finally, translational association strength is based on keyword co-occurrence and does not include the impact of factors such as research quality and sample size. These limitations provide directions for future research improvements. Conclusion This study revealed a PPO research paradigm shift from reactive pathological research to proactive engineering prevention (2000–2025). Key bottlenecks include basic-clinical translational gaps and imbalanced global collaboration. Future efforts need to break disciplinary and geographical silos. The path forward lies in advanced wear-resistant biomaterials combined with precise surgical fixation. We propose a three-pillar framework: two-way translational pipelines for intelligent biomaterials, equitable global research alliances, and preventive design in prosthetic systems. This transforms PPO research into a field proactively building lifelong joint health via materials science and surgical excellence. Declarations Ethics approval and consent to participate This bibliometric study used publicly available data and did not involve human participants or animal subjects. Ethical approval was therefore not required. Consent for publication Not applicable. Data availability The datasets analyzed during this study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding This work was supported by the National Natural Science Foundation of China (Grant No. 81971322). 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Arthritis Res Therapy 9(Suppl 1):S6. https://doi.org/10.1186/ar2170 Nam JS, Sharma AR, Jagga S, Lee DH, Sharma G, Nguyen LT et al (2017) Suppression of osteogenic activity by regulation of WNT and BMP signaling during titanium particle induced osteolysis. J Biomedical Mater Res Part A 105:912–926. https://doi.org/10.1002/jbm.a.36004 van Eck NJ, Waltman L (2010) Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 84:523–538. https://doi.org/10.1007/s11192-009-0146-3 Chen C, Hu Z, Liu S, Tseng H (2012) Emerging trends in regenerative medicine: a scientometric analysis in CiteSpace. Expert Opin Biol Ther 12:593–608. https://doi.org/10.1517/14712598.2012.674507 Noordin S, Masri B (2012) Periprosthetic osteolysis: genetics, mechanisms and potential therapeutic interventions. Can J Surg 55:408–417. https://doi.org/10.1503/cjs.003711 van Erp JHJ, Massier JRA, Halma JJ, Snijders TE, de Gast A (2020) 2-year results of an RCT of 2 uncemented isoelastic monoblock acetabular components: lower wear rate with vitamin E blended highly cross-linked polyethylene compared to ultra-high molecular weight polyethylene. Acta Orthop 91:254–259. https://doi.org/10.1080/17453674.2020.1730073 Afghanyar Y, Afghanyar B, Loweg L, Drees P, Gercek E, Dargel J et al (2024) Ten-year clinical and radiological outcomes with a vitamin E-infused highly cross-linked polyethylene acetabular cup. Bone Joint Open 5:825–831. https://doi.org/10.1302/2633-1462.510.BJO-2023-0179.R1 Qoreishi M, Panahi M, Dorodi O, Ghanbari N, Jousheghan SS (2022) Involvement of NF-kappaB/NLRP3 axis in the progression of aseptic loosening of total joint arthroplasties: a review of molecular mechanisms. Naunyn Schmiedebergs Arch Pharmacol 395:757–767. https://doi.org/10.1007/s00210-022-02232-4 Gruen TA, McNeice GM, Amstutz HC (2014) Modes of failure of cemented stem-type femoral components: a radiographic analysis of loosening. In: Banaszkiewicz PA, Kader DF (eds) Classic papers in orthopaedics. Springer-, London, pp 35–45. https://doi.org/10.1007/978-1-4471-5451-8_8 Green TR, Fisher J, Stone M, Wroblewski BM, Ingham E (1998) Polyethylene particles of a 'critical size' are necessary for the induction of cytokines by macrophages in vitro. Biomaterials 19:2297–2302. https://doi.org/10.1016/s0142-9612(98)00140-9 Urban RM, Jacobs JJ, Tomlinson MJ, Gavrilovic J, Black J, Peoc'h M (2000) Dissemination of wear particles to the liver, spleen, and abdominal lymph nodes of patients with hip or knee replacement. J Bone Joint Surg Am Volume 82:457–476. https://doi.org/10.2106/00004623-200004000-00002 Kurtz S, Ong K, Lau E, Mowat F, Halpern M (2007) Projections of primary and revision hip and knee arthroplasty in the United States from 2005 to 2030. J Bone Joint Surg Am Volume 89:780–785. https://doi.org/10.2106/JBJS.F.00222 Sugimoto CR, Ahn YY, Smith E, Macaluso B, Lariviere V (2019) Factors affecting sex-related reporting in medical research: a cross-disciplinary bibliometric analysis. Lancet 393:550–559. https://doi.org/10.1016/S0140-6736(18)32995-7 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8617314","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":583260797,"identity":"bccc9204-710c-4bf2-b194-222ff5e2c1d7","order_by":0,"name":"Jifeng Jing","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jifeng","middleName":"","lastName":"Jing","suffix":""},{"id":583260798,"identity":"1126076a-d1e0-4757-b8d7-f295959967c9","order_by":1,"name":"Shuo Cheng","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shuo","middleName":"","lastName":"Cheng","suffix":""},{"id":583260799,"identity":"854c2e80-62b0-45bf-8b0b-fb867ce96930","order_by":2,"name":"Yu Wang","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Wang","suffix":""},{"id":583260800,"identity":"1b9b12ed-dd9a-4989-a65a-d37ac610f060","order_by":3,"name":"Shimin Hao","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shimin","middleName":"","lastName":"Hao","suffix":""},{"id":583260801,"identity":"1b280a44-7818-4d83-af06-d7096a8814d9","order_by":4,"name":"Souradeep Sahu","email":"","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":false,"prefix":"","firstName":"Souradeep","middleName":"","lastName":"Sahu","suffix":""},{"id":583260802,"identity":"e21d5d6a-110a-4414-a15e-bc5b2d9f8076","order_by":5,"name":"Lei Guo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyUlEQVRIiWNgGAWjYBAC/hmMDQwMPGz8/MzMBx8QpUXiBkSL5Mx2tmQDorQYREBoyQ3necwEiNMi3dz24IcMn4TxYQYzBoYam2jCWmQOthv28LBJmB1mSHvAcCwtt4GgFonENgkeHrY6oJbjBowNh4nTIvkHaItxM2ObBHFaIhLbpIG2SBgwM7MRp0XiBlCLDFCLxGE2ZoMEYvzCPyP9meTbnmMS/P3nPz74UGNDWAsYMPYcgzASiFIOBj9qiFc7CkbBKBgFIw8AAJovOKclSLpUAAAAAElFTkSuQmCC","orcid":"","institution":"First Hospital of China Medical University","correspondingAuthor":true,"prefix":"","firstName":"Lei","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2026-01-16 11:02:57","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8617314/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8617314/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101762769,"identity":"f02a2594-3023-4a0e-bee4-01d4791ae048","added_by":"auto","created_at":"2026-02-03 11:28:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":379245,"visible":true,"origin":"","legend":"\u003cp\u003eAnnual trend in the number of publications from 2000 to July 14, 2025.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/d4bc59095026ed8c417195d5.png"},{"id":101762764,"identity":"8621c7c2-841e-4230-8644-54598ef13fd5","added_by":"auto","created_at":"2026-02-03 11:28:07","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":465940,"visible":true,"origin":"","legend":"\u003cp\u003ePublication output and citation impact over time (2000-2025).\u003c/p\u003e\n\u003cp\u003eNote: The blue line depicts the annual number of publications. The red line shows the cumulative number of citations received.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/5f9b51a0bceea462de067dff.png"},{"id":101762760,"identity":"ba7435af-0711-4db2-8f53-0c9cb8d22aec","added_by":"auto","created_at":"2026-02-03 11:28:07","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":380148,"visible":true,"origin":"","legend":"\u003cp\u003eResearch area distribution in periprosthetic osteolysis studies.\u003cbr\u003e\nNote: Bar chart: Frequency of research area assignments (Total assignments: 6,102 from 3,858 publications). Orange curve: Weighted proportion (logarithmic scale). Crossover index = 158.253% (Total assignments/Total publications).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/6687847ae60d71ad88729eed.png"},{"id":101880948,"identity":"9703ac6c-5206-4d3d-9295-7982eb5725ad","added_by":"auto","created_at":"2026-02-04 15:08:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":3405877,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of leading journals in periprosthetic osteolysis research (Journals with \u0026gt;10 publications, N=41).\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/769a40da6ab1609cf92b0538.png"},{"id":101762766,"identity":"190f4cde-cc01-4c45-966f-c81d60d9d43a","added_by":"auto","created_at":"2026-02-03 11:28:08","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":4386455,"visible":true,"origin":"","legend":"\u003cp\u003eKeyword co-occurrence network in periprosthetic osteolysis research\u003c/p\u003e\n\u003cp\u003eNote: a. Network generated from 90 high-frequency keywords (occurrence ≥ 50) using VOSviewer version 1.6.19 (density = 0.47, modularity = 0.81); b. Node size is proportional to keyword frequency, and edge thickness reflects co-occurrence strength; c. Clusters: Red—Clinical outcomes (e.g., revision, total hip arthroplasty), Green—Mechanisms (e.g., osteolysis, NF-κB), Blue—Wear (e.g., metal implants, debris), Yellow—Bone-implant interface (e.g., bone remodeling, titanium particles), Purple—Prosthesis fixation (e.g., acetabular cup, cementless); d. Key pathways: Aseptic loosening → Revision (link strength = 862), Wear particles → Osteolysis (link strength = 723).\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/a58c2a2c5aaaacd687133dad.png"},{"id":101762765,"identity":"19fd06e0-660d-4b92-9b1c-8e00779c0707","added_by":"auto","created_at":"2026-02-03 11:28:07","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2002911,"visible":true,"origin":"","legend":"\u003cp\u003eKeyword cluster network related to periprosthetic osteolysis research (generated by CiteSpace)\u003cbr\u003e\n\u003cstrong\u003eNote:\u003c/strong\u003eThe analysis identified five clinically oriented clusters: #0 Osteolysis (e.g., \u003cem\u003eosteolysis\u003c/em\u003e); #1 Wear mechanisms (e.g., \u003cem\u003ethird-body wear\u003c/em\u003e); #2 Debris types (e.g., \u003cem\u003epolyethylene particles\u003c/em\u003e); #3 THA-MoM (i.e., total hip arthroplasty-metal-on-metal; e.g., \u003cem\u003eacetabular component\u003c/em\u003e); #4 TKA-PE (i.e., total knee arthroplasty-polyethylene; e.g., \u003cem\u003ehighly cross-linked polyethylene\u003c/em\u003e).Arrows indicate the cascading pathway: #3 → #1 → #2 → #0.\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/2acde810843a1ee505011bdb.png"},{"id":101762762,"identity":"d27f9499-2223-42f4-9646-7603f0134abb","added_by":"auto","created_at":"2026-02-03 11:28:07","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1743435,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal evolution of keyword bursts in periprosthetic osteolysis research (2000--2025)\u003cbr\u003e\nNote: Top 20 keywords with the strongest citation bursts detected by CiteSpace. Evolutionary phases: I. Foundation (2000--2010) → II. Technical (2011--2017) → III. Precision Medicine (2018--2025).\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/83fed6747512c90536876235.png"},{"id":101880444,"identity":"cc5b3159-5ff8-4f31-a6f5-e420d991d42a","added_by":"auto","created_at":"2026-02-04 15:01:33","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":3987033,"visible":true,"origin":"","legend":"\u003cp\u003eTemporal evolution of keywords in periprosthetic osteolysis research (2000–2025).\u003cbr\u003e\nNote: a. Node size is proportional to keyword frequency; connecting lines reflect cross-time-period co-occurrence relationships (one count per co-occurrence in the same publication); b. Analysis tool: CiteSpace 6.3.R1 (time slicing: 2 years per segment; clustering algorithm: LLR).\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/6a536fadb69233d0ad729e99.png"},{"id":101762759,"identity":"40f1d4cd-ec34-4b49-b3c6-eca635aeb515","added_by":"auto","created_at":"2026-02-03 11:28:07","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":2268422,"visible":true,"origin":"","legend":"\u003cp\u003eInterdisciplinary knowledge flow in periprosthetic osteolysis research\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNote\u003c/strong\u003e: a. Dual-map overlay shows citation trajectories: purple path represents flow from physical sciences to biomechanics; yellow path indicates specialization within life sciences; gray path demonstrates integration through clinical medicine; b. Significant flows are defined as z \u0026gt; 1.65 (p \u0026lt; 0.05) with citation frequency \u0026gt; 1100; c. Discipline clusters are based on the Web of Science classification system.\u003c/p\u003e","description":"","filename":"image9.png","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/6ca628d31b29e3fb7371b6bd.png"},{"id":108805698,"identity":"a7050c01-c8af-42c7-9c73-4959cb684e7b","added_by":"auto","created_at":"2026-05-08 15:26:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":17602391,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8617314/v1/e9f97315-5488-490f-b4a0-1e5b92ea445f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mapping Translational Bottlenecks in Periprosthetic Osteolysis Research: A Bibliometric Correlation Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTotal joint arthroplasty (TJA), particularly total hip arthroplasty (THA) and total knee arthroplasty (TKA), is the gold standard for reconstructing severe joint dysfunction and treating end-stage arthritis. Global TJA volume is surging: projections indicate US THA and TKA procedures will increase by 284% and 401%, respectively, by the 2040 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]; German TKA volume is expected to reach 225,957 by 2050 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]; and China\u0026rsquo;s annual growth rates for THA and TKA were 16.67% and 27.43%, respectively, between 2012 and 2019 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmid this surgical volume surge, periprosthetic osteolysis (PPO) and subsequent late-stage aseptic loosening (AL) have become increasingly prominent, emerging as leading causes of prosthetic failure and revision surgery [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. US revision burdens for THA and TKA are projected to rise by 42% and 149%, respectively, by 2040, with revision surgery associated with higher costs [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], with revision surgery associated with higher costs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and suboptimal functional recovery [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Consequently, elucidating the pathological mechanisms underlying PPO and developing effective strategies to extend prosthesis longevity and reduce revision burden have become urgent research priorities in orthopedics. This challenge extends beyond hip and knee arthroplasty, emerging as a critical concern in other joint replacements, including the shoulder and ankle [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAgainst this backdrop, multidisciplinary research on PPO has witnessed exponential growth, yet a coherent knowledge framework remains underdeveloped [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. While interdisciplinary investigations\u0026mdash;such as wear particle-induced immune responses, mechanisms of imbalanced bone metabolism, and novel anti-osteolytic biomaterials\u0026mdash;continue to generate innovative outcomes [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], research efforts remain fragmented and research foci evolve rapidly [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. There is an urgent need for a comprehensive quantitative analysis of the field to map the research landscape and prioritize critical pathways for transformative breakthroughs [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBibliometrics, grounded in mathematical and statistical methodologies, provides a rigorous framework for analyzing scholarly output and mapping the evolution of research fields. By quantifying multi-dimensional data\u0026mdash;including publication volume, authorship networks, citation patterns, and keyword associations\u0026mdash;it has become an indispensable tool for identifying emerging frontiers and structural dynamics within specialized disciplines [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Beyond descriptive mapping, bibliometrics can critically assess the academic influence of institutions and journals, informing strategic research resource allocation [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, existing bibliometric studies on PPO have primarily focused on hotspots and collaboration networks [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. They fail to quantitatively answer which research tiers (from molecular mechanisms to engineering solutions) can effectively translate into reducing revision rates and prolonging implant survival. This gap hinders evidence-based research resource allocation [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. To address this, we developed a novel keyword correlation analysis and constructed a \u0026ldquo;clinical translational funnel\u0026rdquo; model to quantify theme-clinical endpoint association, identifying translational bottlenecks [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData Sources and Search Strategy\u003c/h2\u003e \u003cp\u003eA systematic search was conducted in the Web of Science Core Collection (SCI-EXPANDED and SSCI) on July 30, 2025, to identify PPO-related publications (2000\u0026ndash;2025) [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Developed based on the PICO framework, the search strategy included core concepts (\"periprosthetic osteolysis\", \"arthroplasty\", \"wear debris\") and excluded non-relevant fields (e.g., dentistry, oncology, spinal surgery) via the NOT operator [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Detailed criteria are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The final query yielded 3,872 records, and 3,858 publications (3,598 research articles, 260 reviews) were included after rigorous manual screening.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSearch Strategy in Web of Science Core Collection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuery\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTS=((\"periprosthetic osteolysis\" OR \"PPO\" OR \"aseptic loosening\" OR \"wear debris\" OR \"metal ions\") AND (\"arthroplasty\" OR \"joint replacement\" OR \"hip replacement\" OR \"knee replacement\"))\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTS=(\"dental\" OR \"tumor\" OR \"infection\" OR \"spine\" OR \"spinal\" OR \"vertebral\" OR \"disc\" OR \"disk\" OR \"cervical\" OR \"lumbar\")\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWC=(\"Veterinary Sciences\" OR \"Oncology\" OR \"Dentistry\")\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePY=(2000\u0026ndash;2025) AND DT=(Article OR Review) AND LA=(English)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e#5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDT=(\"Proceedings Paper\" OR \"Early Access\")\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFinal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(#1 NOT #2 NOT #3) AND #4 NOT #5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eScreening Process: The 3,858 publications that passed manual screening constituted the final dataset for all subsequent bibliometric analyses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eInclusion and Exclusion Criteria\u003c/h3\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eInclusion Criteria\u003c/h2\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eFocus on the mechanisms, prevention, or treatment of periprosthetic osteolysis (PPO).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eContain empirical data or be systematic reviews.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePublished between January 1, 2000, and July 14, 2025.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eExclusion Criteria\u003c/h3\u003e\n\u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eIrrelevant to the research theme: Studies on septic loosening, dental/spinal implants, or tumor metastasis-related bone loss; publications whose primary content does not address PPO mechanisms.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInvalid study models: Animal studies investigating mechanisms without validation in human cells or tissues.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUnavailable literature: Non-English publications; articles with inaccessible full text; unpublished preprints.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eExcluded document types: Non-research literature (e.g., conference abstracts, patents, commentaries, errata); duplicate records with incomplete data.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eData Extraction\u003c/h3\u003e\n\u003cp\u003eBibliometric attributes, content features, and keyword data (author keywords and Keywords Plus\u0026reg;) were extracted from all included publications. Co-citation networks and topic evolution were analyzed via VOSviewer 1.6.20 and CiteSpace 6.4.R1. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eBibliometric data were organized and preprocessed using Microsoft Excel. Scientific knowledge mapping was performed using both VOSviewer and CiteSpace.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDescriptive and Evolutionary Bibliometric Analysis\u003c/h3\u003e\n\u003cp\u003eVOSviewer was used to generate visualizations of keyword co-occurrence, journal publication distribution, and document co-citation. The H-index was incorporated to assess the academic influence of major research institutions [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. CiteSpace was applied to perform co-citation analysis (identifying key literature with a betweenness centrality threshold of \u0026gt;\u0026thinsp;0.1), burst detection (implementing the Kleinberg algorithm with γ\u0026thinsp;=\u0026thinsp;0.5 and a minimum duration of 2 years), cluster validation (using a homogeneity criterion of silhouette value\u0026thinsp;\u0026gt;\u0026thinsp;0.7 and a structural significance criterion of modularity Q\u0026thinsp;\u0026gt;\u0026thinsp;0.3), timeline and time slice analyses (2000\u0026ndash;2025) to reveal evolutionary trajectories of research paradigms, as well as institutional co-occurrence and journal dual-map overlay analyses [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eTranslational Associative Strength Analysis (\"Clinical Translational Funnel\" Model)\u003c/h3\u003e\n\u003cp\u003eTo evaluate the translational proximity of different research themes to clinical outcomes in PPO, a translational association analysis was developed based on direct keyword co-occurrence patterns.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eClinical Endpoint Definitions\u003c/h2\u003e \u003cp\u003eThree clinically meaningful keywords were selected as anchor endpoints: revision (surgical failure), survival (long-term implant retention), and implant (technical application).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAssociation Strength Calculation\u003c/h2\u003e \u003cp\u003eDirect co-occurrence counts between these anchor endpoints and all high-frequency keywords (occurrences\u0026thinsp;\u0026ge;\u0026thinsp;50) were extracted from the bibliometric co-occurrence matrix. Association strength was quantified as raw co-occurrence counts and normalized by keyword frequency for comparative analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eTranslational Tier Classification\u003c/h2\u003e \u003cp\u003eBased on the PPO pathological cascade, keywords were categorized into four translational tiers:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eClinical/Technical Tier: Direct clinical interventions (e.g., fixation, prosthesis design);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eWear/Materials Tier: Problem manifestations and solutions (e.g., polyethylene wear, material properties);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePathological/Cellular Tier: Biological responses (e.g., inflammation, osteoclast activation);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eMolecular/Model Tier: Basic mechanisms and experimental tools (e.g., NF-\u003cem\u003eκB\u003c/em\u003e, \u003cem\u003ein vitro\u003c/em\u003e models).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eQuantitative outcomes of this classification are presented in the Results (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Metrics\u003c/h2\u003e \u003cp\u003eFor each tier, we calculated: (a) mean association strength with revision and survival endpoints, (b) translational efficiency ratio (clinical associations/total occurrences), and (c) identified \"translational bridges\"\u0026mdash;keywords strongly linked to both clinical endpoints (co-occurrence\u0026thinsp;\u0026gt;\u0026thinsp;5 with each endpoint).\u003c/p\u003e \u003cp\u003eDetailed computational procedures and validation methods are provided in Supplemental Methods S1.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n\u003ch2\u003eResearch Landscape of Periprosthetic Osteolysis\u003c/h2\u003e\n\u003cp\u003eThis study conducted a systematic bibliometric analysis of literature related to PPO between 2000 and 2025 based on the Web of Science Core Collection database (SCI-EXPANDED and SSCI). Through a rigorous screening process (excluding 10 irrelevant articles and 4 duplicate records), a total of 3,858 eligible publications were ultimately included, comprising 3,598 research articles and 260 reviews.\u003c/p\u003e\n\u003cp\u003eAnnual Publication Trends (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e): After a steady phase (2000\u0026ndash;2004, avg. 93 articles/year), PPO-related publications surged 35.2% in 2005 (142 articles) and grew rapidly through 2013, peaking temporarily at 206 articles (5.34% of total). An adjustment period followed (2014\u0026ndash;2016, avg. 161.6 articles/year), succeeded by sustained growth until 2020\u0026rsquo;s historical high of 210 articles (5.44% of total). From 2021 to 2024, the annual output averaged 178.7 articles. Note: 2025 data (95 articles) is undercounted as database coverage only extends to July.\u003c/p\u003e\n\u003cp\u003eCitation analysis (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e) indicated that the total number of citations reached 107,765, of which 91,502 were non-self-citations; the average number of citations per article was 27.94, and the H-index was 117, reflecting strong academic influence and potential clinical value of the field.\u003c/p\u003e\n\u003cp\u003eDistribution of research areas (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;2) revealed that the publications spanned 90 distinct disciplines. Orthopaedics (65.44%), Surgery (27.29%), and Biomedical Engineering (15.06%) constituted the core clusters directly related to clinical practice. Biomaterials Science (10.75%), Sport Sciences (4.92%), and Materials Science (2.54%) underpinned interdisciplinary clinical innovation. The sum of the top five categories exceeded 100% (123.5%), reflecting the interdisciplinary nature of the field, as articles are frequently indexed under multiple subject headings.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e(Table\u0026nbsp;2). Top 10 Web of Science Research Categories in Periprosthetic Osteolysis Publications (2000\u0026ndash;2025).\u003c/em\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Taba\" border=\"1\"\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u0026bull; Web of Science Categories\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRecord Count\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e% of 3,858\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOrthopedics\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2525\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e65.448\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSurgery\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1053\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e27.294\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eEngineering Biomedical\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e581\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e15.06\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaterials Science Biomaterials\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e415\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.757\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSport Sciences\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e190\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e4.925\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMaterials Science Multidisciplinary\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.54\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedicine General Internal\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e88\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.281\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRheumatology\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.255\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMedicine Research Experimental\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e75\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.944\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePharmacology Pharmacy\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.711\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"3\"\u003e\u003cstrong\u003eNote\u003c/strong\u003e: a. Data source: Web of Science Core Collection (Total publications: 3,858); b. Since a single publication can be assigned to multiple research areas, the sum of research area counts exceeds the total number of publications (hence the sum of percentages\u0026thinsp;\u0026gt;\u0026thinsp;100%); c. Retrieval date: July 14, 2025.\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n\u003ch2\u003eJournal Distribution and Interdisciplinary Characteristics\u003c/h2\u003e\n\u003cp\u003ePPO research exhibited a characteristic \"clinical-materials\" dual-track distribution pattern (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e): leading orthopaedic journals (e.g., Journal of Bone and Joint Surgery, Clinical Orthopaedics and Related Research) focused on optimizing prosthetic revision techniques and controlling complications; specialized materials science journals (e.g., Acta Biomaterialia, Journal of Biomedical Materials Research Part A) concentrated on molecular mechanisms such as wear particle-induced osteoclast activation that underpin clinical material selection; cross-disciplinary platforms (e.g., Scientific Reports, PLOS ONE) facilitated translational research by enabling knowledge fusion across diverse fields.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n\u003ch2\u003eResearch Hotspots and Theme Evolution\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eKeyword Co-occurrence and Clustering\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBibliometric analysis of PPO-related keywords was performed, constructing a co-occurrence network from 90 high-frequency terms (occurrence\u0026thinsp;\u0026ge;\u0026thinsp;50) with a density of 0.47 and modularity of 0.81. VOSviewer analysis identified five major clusters (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e): the red cluster (Clinical Outcomes) centered on total hip arthroplasty (445 occurrences) and revision (407 occurrences), with exceptionally high total link strength for follow-up (649 occurrences, TLS\u0026thinsp;=\u0026thinsp;3069) and implant survival (212 occurrences, TLS\u0026thinsp;=\u0026thinsp;1047), emphasizing long-term outcome assessment and failure management in clinical practice; the green cluster (Biological Mechanisms of Osteolysis) was anchored by osteolysis (577 occurrences, TLS\u0026thinsp;=\u0026thinsp;2862) and aseptic loosening (412 occurrences, TLS\u0026thinsp;=\u0026thinsp;1821), directly linking key nodes such as wear debris (379 occurrences, TLS\u0026thinsp;=\u0026thinsp;1771), macrophages (141 occurrences), and \u003cem\u003eNF-\u0026kappa;B\u003c/em\u003e (70 occurrences, normalized citation value\u0026thinsp;=\u0026thinsp;1.62), thereby delineating the central \"wear debris \u0026rarr; immune inflammation \u0026rarr; osteolysis\" pathway; the blue cluster (Material Wear) focused on prosthesis materials and wear behavior, built around wear (434 occurrences, TLS\u0026thinsp;=\u0026thinsp;1995) and arthroplasty (899 occurrences, TLS\u0026thinsp;=\u0026thinsp;3543), highlighting concerns regarding specific implants through strong co-occurrence among metal-on-metal implants (166 occurrences), cobalt (167 occurrences), and chromium (128 occurrences); the purple cluster (Prosthesis Components and Performance) revolved around component design and in vivo performance, with core terms including acetabular component (99 occurrences), femoral head (75 occurrences), and polyethylene wear (155 occurrences), reflecting a research emphasis on wear and functional integrity at the component level that directly impacts surgical planning.\u003c/p\u003e\n\u003cp\u003eComplementary analysis via CiteSpace (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e6\u003c/span\u003e) revealed five clinical-thematic dimensions: #0 Osteolytic Mechanisms (osteolysis), #1 Wear Mechanisms (corrosion), #2 Debris Types (polyethylene/titanium particles), #3 THA-MoM (acetabular component), and #4 TKA-PE (highly cross-linked polyethylene).\u003c/p\u003e\n\u003cp\u003eThese clusters collectively delineated a cascading pathway: \"prosthesis design \u0026rarr; wear \u0026rarr; debris release \u0026rarr; osteolysis \u0026rarr; clinical optimization\", with cross-validation by dual analytical tools consistently confirming the central role of wear debris within this pathological cascade, providing a clinical decision-making framework.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKeyword Burst and Timeline Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKeyword burst detection revealed the dynamic evolution of research hotspots in PPO, clearly outlining three distinct phases (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e7\u003c/span\u003e): Early Phase (2000\u0026ndash;2010): Research efforts focused primarily on the core pathological initiation of the condition. Wear debris (strength\u0026thinsp;=\u0026thinsp;24.77) and its associated bone resorption (strength\u0026thinsp;=\u0026thinsp;10.08) emerged as the most prominent burst keywords. Investigations during this period successfully established the fundamental pathological framework of \"wear debris \u0026rarr; inflammatory response \u0026rarr; osteolysis\" [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e], and delved into the physical characteristics and biological effects of prostheses (strength\u0026thinsp;=\u0026thinsp;23.57) and polyethylene particles (strength\u0026thinsp;=\u0026thinsp;9.4) [\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e], laying a theoretical foundation for subsequent clinical research; Middle Phase (2011\u0026ndash;2017): The research frontier underwent a noticeable transition, shifting from downstream biological effects to upstream engineering solutions. The emergence of bearings (strength\u0026thinsp;=\u0026thinsp;9.8) signaled a reorientation toward reducing wear generation through interface design and material innovation. Concurrently, in-depth studies on specific components such as femoral components (strength\u0026thinsp;=\u0026thinsp;14.39) and fixation techniques like cement (strength\u0026thinsp;=\u0026thinsp;13.03) indicated a progression from macroscopic pathological phenomena toward engineered details involving prosthetic micro-design, material properties, and fixation methodologies that directly improve clinical outcomes; Recent Phase (2018\u0026ndash;2025): Research hotspots exhibited a robust trend toward clinical translation, with the strongest burst keywords all pointing to clinical applications and decision support. Outcomes (strength\u0026thinsp;=\u0026thinsp;36.2) and risk management (strength\u0026thinsp;=\u0026thinsp;25.81) became central themes, reflecting a pressing need for personalized prognostic evaluation and precise intervention. Aseptic loosening (strength\u0026thinsp;=\u0026thinsp;30.89) received considerable attention as a critical clinical endpoint event, with related revision strategies (strength\u0026thinsp;=\u0026thinsp;18.49) and enhancements in survivorship (strength\u0026thinsp;=\u0026thinsp;11.47) forming major research topics.\u003c/p\u003e\n\u003cp\u003eTimeline analysis further revealed (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e8\u003c/span\u003e): wear debris was identified as the core etiological agent between 2000 and 2008; in-depth exploration of specific particle toxicity and signaling pathways and advancement of polyethylene material modification occurred between 2009 and 2016; since 2017, research has focused on clinical issues such as revision surgery, bone defect management, and risk factors, strengthening research related to knee arthroplasty to fill clinical research gaps.\u003c/p\u003e\n\u003cp\u003eTranslational Landscape Analysis: The \"Clinical Translational Funnel\"\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n\u003cp\u003eBuilding upon the thematic clusters and evolution identified above, a translational association analysis was conducted to quantitatively diagnose the proximity of diverse research themes to ultimate clinical goals. The results, encapsulated in the \"Clinical Translational Funnel\" model (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), revealed a pronounced hierarchical structure in the research ecosystem.\u003c/p\u003e\n\u003cp\u003eA marked gradient of clinical relevance was observed across four predefined translational tiers: the Clinical/Technical tier (fixation, THA, TKA, design) exhibited the strongest association with revision (mean association strength 33.2) and survival (10.4); the Wear/Materials tier (osteolysis, aseptic loosening, polyethylene wear) was next (revision 16.8, survival 6.1); the Pathological/Cellular tier (inflammation, bone loss, macrophages) and Molecular/Model tier (\u003cem\u003eNF-\u0026kappa;B, in vitro, cytokines\u003c/em\u003e) showed weak associations.\u003c/p\u003e\n\u003cp\u003eA key finding was the identification of specific \"translational bridges\" (Metal-on-Metal, Polyethylene Wear) with strong association to revision and survival (strength\u0026thinsp;=\u0026thinsp;16 each), anchoring translational efforts. A typical translational bottleneck was observed: titanium particles (a dominant experimental model, 71 occurrences) had minimal clinical relevance (strength\u0026thinsp;=\u0026thinsp;1), while titanium as an engineering material retained survival association (strength\u0026thinsp;=\u0026thinsp;6). This reflects that some basic research lacks progression to clinically actionable solutions (e.g., material modification, implant design).\u003c/p\u003e\n\u003cp\u003eFinally, the data underscored the superior translational efficiency of preventive engineering interventions. The preventive material innovation Cross-linked Polyethylene demonstrated clear dual associations (revision\u0026thinsp;=\u0026thinsp;12, survival\u0026thinsp;=\u0026thinsp;4) [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e], far exceeding the impact of targeting downstream molecular pathways like \u003cem\u003eNF-\u0026kappa;B\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e]. Consequently, optimizing prosthesis design and surgical fixation techniques\u0026mdash;themes with the strongest clinical linkages\u0026mdash;emerged as the most evidence-supported strategy for extending implant longevity in clinical practice.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAttenuation of Clinical Relevance Across the Translational Funnel: Tier-Level Summary\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eTranslational Tier\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRepresentative Keywords\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNo. Keywords\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRevision Assoc.\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSurvival Assoc.\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eI. Clinical/Technical\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFixation, THA, TKA, Design\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e33.2\u0026nbsp;(2\u0026ndash;69)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10.4\u0026nbsp;(0\u0026ndash;38)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eII. Wear and Materials\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOsteolysis, Aseptic Loosening, Polyethylene Wear\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e25\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.8\u0026nbsp;(1\u0026ndash;73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.1\u0026nbsp;(0\u0026ndash;27)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIII. Pathological/Cellular\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInflammation, Bone Loss, Macrophages\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e11\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e6.5\u0026nbsp;(1\u0026ndash;17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2.7\u0026nbsp;(0\u0026ndash;10)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIV. Molecular/Model\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eNF-\u0026kappa;B, In-vitro, Cytokines\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e10\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e1.1\u0026nbsp;(0\u0026ndash;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.5\u0026nbsp;(0\u0026ndash;3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eKey Translational Bridges\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMetal-on-Metal, Polyethylene Wear\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e2\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e16.0\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e9.5\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec20\" class=\"Section3\"\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u003c/strong\u003e\u0026nbsp;Assoc., association; THA, total hip arthroplasty; TKA, total knee arthroplasty.\u003cbr /\u003e \u003cstrong\u003eData presentation:\u0026nbsp;\u003c/strong\u003eValues are presented as mean association strength (range).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCalculation:\u0026nbsp;\u003c/strong\u003eThe mean association strength for each tier was calculated by averaging the direct co-occurrence counts of all keywords within that tier with the anchor keywords \u0026ldquo;revision\u0026rdquo; or \u0026ldquo;implant survival\u0026rdquo;. The complete dataset is available in Supplementary Table S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRange:\u0026nbsp;\u003c/strong\u003eParentheses indicate the minimum and maximum association strength observed among keywords in that tier.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKey Translational Bridges:\u0026nbsp;\u003c/strong\u003eThe row \u0026ldquo;Metal-on-Metal, Polyethylene Wear\u0026rdquo; highlights keywords with exceptionally high mean association to both endpoints within the Wear/Materials tier, presented separately to underscore their translational pivot role.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eKeyword Count:\u0026nbsp;\u003c/strong\u003eRefers to the count of high-frequency keywords (total occurrences \u0026ge;50) classified into each tier.\u003cstrong\u003e\u003cbr /\u003e \u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eKnowledge Base and Interdisciplinary Knowledge Flow\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eDocument co-citation analysis delineated three phases in the knowledge evolution of PPO research: mechanical wear mechanism research represented by Gruen et al. [34] (laying the foundation for implant design) \u0026rarr; immune-inflammatory axis research on particle-induced osteolysis represented by Green et al. [35] and Urban et al. [36] \u0026rarr; standardized revision technology research represented by Kurtz et al. [37] (directly guiding clinical practice).\u003c/p\u003e\n\u003cp\u003eDual-map overlay analysis revealed three major interdisciplinary citation trajectories in PPO research (Figure 9)\u0026nbsp;: the penetration of physics/materials/chemistry into biomechanics and molecular biology, providing a foundation for prosthetic material and interface design; high internal specialization of knowledge in molecular biology/immunology, which, while taking genetics as the core theoretical basis, has limited citation flow to application fields; clinical medicine, as the ultimate integrator, converges knowledge from applied clinical fields such as neurology/sports medicine/ophtalmology, integrating molecular biology (disease mechanisms), materials science (biomaterials), and sports rehabilitation (rehabilitation programs) to solve specific clinical problems.\u003c/p\u003e\n\u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003ch2\u003e\u003cstrong\u003eQuantitative Roadmap for Clinical Translation: The \"Clinical Translational Funnel\"\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe core innovation is the novel keyword correlation analysis, complementing traditional bibliometrics’ deficiency in translational evaluation\u0026nbsp;[24]. It quantifies theme-clinical endpoint association, enabling objective judgment of clinically valuable research directions.\u003c/p\u003e\n\u003cp\u003eOur results identified a major translational bottleneck: basic mechanism research has weak clinical relevance, while clinical engineering and wear-resistant material research strongly correlate with prosthesis survival\u0026nbsp;[33]. This provides clear guidance for resource allocation.\u003c/p\u003e\n\u003cp\u003eNotably, this method is based on existing bibliometric tool data, highly replicable and promotable. It can be applied to other medical fields, addressing the common “basic-clinical translation inefficiency” problem\u0026nbsp;[38].\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eResearch Paradigm Evolution: A Systematic Response to Translational Attenuation\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThe 25-year paradigm shift in PPO research (basic pathology → engineering optimization → clinical management) represents a collective response to translational attenuation. The establishment of the early pathological framework laid the foundation for subsequent research, but the limitations of downstream drug intervention drove research to shift toward wear source control. The recent focus on clinical outcomes and risk assessment highlights the comprehensive alignment of research with clinical needs. This evolution indicates that the synergy between advanced materials and precise surgical techniques is key to PPO prevention and control, and the impact of the biomechanical environment on long-term implant survival emphasizes the importance of individualized engineering.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eInterdisciplinary Translational Gaps and Global Collaboration Imbalances\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003e\"Silos\" between disciplines are important sources of translational bottlenecks. Insufficient knowledge diffusion between materials science and clinical orthopaedics hinders the translation of emerging concepts such as immunomodulatory biomaterials into clinical applications. The core-periphery structure of global collaboration further exacerbates this problem: Western core institutions dominate the research agenda, potentially neglecting the specific clinical needs of regions such as Asia. Future efforts should establish interdisciplinary collaboration platforms and equitable global research alliances, integrating diverse clinical data to enhance the generalizability of research.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003ePotential Limitations\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eThis study has certain limitations. First, the literature was only retrieved from the Web of Science Core Collection, which may have missed relevant research from other databases; second, keyword co-occurrence analysis relies on keywords annotated in the database, which may have subjective biases; finally, translational association strength is based on keyword co-occurrence and does not include the impact of factors such as research quality and sample size. These limitations provide directions for future research improvements.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed a PPO research paradigm shift from reactive pathological research to proactive engineering prevention (2000–2025). Key bottlenecks include basic-clinical translational gaps and imbalanced global collaboration. Future efforts need to break disciplinary and geographical silos. The path forward lies in advanced wear-resistant biomaterials combined with precise surgical fixation. We propose a three-pillar framework: two-way translational pipelines for intelligent biomaterials, equitable global research alliances, and preventive design in prosthetic systems. This transforms PPO research into a field proactively building lifelong joint health via materials science and surgical excellence.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis bibliometric study used publicly available data and did not involve human participants or animal subjects. Ethical approval was therefore not required.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe datasets analyzed during this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (Grant No. 81971322). The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch3\u003e\u003cstrong\u003eTrial registration number\u003c/strong\u003e\u003c/h3\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSingh JA, Yu S, Chen L, Cleveland JD (2019) Rates of total joint replacement in the United States: future projections to 2020\u0026ndash;2040 using the National Inpatient Sample. J Rheumatol 46:1134\u0026ndash;1140. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3899/jrheum.170990\u003c/span\u003e\u003cspan address=\"10.3899/jrheum.170990\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlug A, Gramlich Y, Rudert M, Drees P, Hoffmann R, Weissenberger M et al (2021) The projected volume of primary and revision total knee arthroplasty will place an immense burden on future health care systems over the next 30 years. 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Lancet 393:550\u0026ndash;559. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(18)32995-7\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(18)32995-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Periprosthetic osteolysis, Bibliometric analysis, Translational analytics, Implant performance","lastPublishedDoi":"10.21203/rs.3.rs-8617314/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8617314/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003ePeriprosthetic osteolysis (PPO) remains the leading cause of late-term failure in total joint arthroplasty. While bibliometric studies have mapped research trends, they have not systematically quantified the translational efficiency of different research themes toward reducing revision rates and prolonging implant survival. This study aimed to map the evolving research trends and identify translational bottlenecks in PPO research (2000\u0026ndash;2025) by constructing a novel \u0026ldquo;clinical translational funnel\u0026rdquo; model, which quantifies the association strength between research themes and key clinical endpoints via an innovative keyword correlation analysis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe retrieved 3,858 publications from the Web of Science Core Collection. VOSviewer and CiteSpace were used for co-occurrence, burst detection, timeline, and collaboration analyses. A novel keyword correlation strength calculation method was developed to categorize keywords into four translational tiers and quantify their associative strength with \u0026ldquo;revision\u0026rdquo; and \u0026ldquo;implant survival.\u0026rdquo;\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe analysis revealed a clear paradigm shift from basic pathology (2000\u0026ndash;2010) to clinical risk management (2018\u0026ndash;2025). Associative strength with \u0026ldquo;implant survival\u0026rdquo; attenuated sharply from the clinical/technical tier (e.g., \u0026ldquo;fixation\u0026rdquo;: strength\u0026thinsp;=\u0026thinsp;35) to near-zero in molecular tiers. Key translational bottlenecks were identified, including the \u0026ldquo;titanium particle paradox\u0026rdquo; (high experimental use but low clinical relevance) and Western-centric collaboration patterns.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003ePPO management has transitioned toward a preventive, engineering-driven paradigm. Optimizing prosthetic fixation and wear-resistant materials represents the most efficient pathway to prolong implant survival. The proposed \u0026ldquo;translational funnel\u0026rdquo; model and keyword correlation method offer a data-driven framework for prioritizing clinically impactful research and reallocating resources to overcome identified bottlenecks.\u003c/p\u003e","manuscriptTitle":"Mapping Translational Bottlenecks in Periprosthetic Osteolysis Research: A Bibliometric Correlation Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 11:28:00","doi":"10.21203/rs.3.rs-8617314/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6ab7a86f-166b-4728-ac97-b76059a43c5f","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-06T12:12:53+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 11:28:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8617314","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8617314","identity":"rs-8617314","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}